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Acta Agronomica Sinica ›› 2023, Vol. 49 ›› Issue (7): 1785-1798.doi: 10.3724/SP.J.1006.2023.24137

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

Integrated analysis of transcriptome and metabolome reveals the metabolic response pathways of sweetpotato under shade stress

WANG Yan-Nan1(), CHEN Jin-Jin1, BIAN Qian-Qian1, HU Lin-Lin2, ZHANG Li3, YIN Yu-Meng1, QIAO Shou-Chen1, CAO Guo-Zheng1, KANG Zhi-He1, ZHAO Guo-Rui1, YANG Guo-Hong1, YANG Yu-Feng1,*()   

  1. 1Cereal Crops Research Institute, Henan Academy of Agricultural Sciences, Zhengzhou 450002, Henan, China
    2School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450001, Henan, China
    3Institute of Agricultural Economics and Information, Henan Academy of Agricultural Sciences, Zhengzhou 450002, Henan, China
  • Received:2022-06-08 Accepted:2022-11-25 Online:2023-07-12 Published:2022-12-28
  • Contact: *E-mail: yyfyyf5@163.com E-mail:alman001@qq.com;yyfyyf5@163.com
  • Supported by:
    The Natural Science Foundation of Henan Province(212300410170);The Science and Technology Research Program of Henan Province(212102110251);The Henan Joint Research Program for Improved Agricultural Varieties(2022010401-2);The Special Fund for Henan Agriculture Research System(HARS-22-04-G1);The China Agriculture Research System of MOF and MARA(甘薯);The China Agriculture Research System of MOF and MARA(CARS-10-C14)

Abstract:

Sweetpotato is a heliophile crop. However, it is usually shaded in the lower position in the interplanting cultivation mode. During the middle and late field growing period, it often faces rainy weather with little illumination, which affects the dry matter accumulation in tuberous roots. Thus, analyzing the metabolic response pathways of sweetpotato under shade stress will provide the theoretical basis for the varieties’ genetic improvement of shade tolerance. In this study, the sweetpotato variety Zhenghong 23 was exposed to shade stress with 50% light transmittance for 15 days. Results showed that chlorophyll b and the total chlorophyll contents of Zhenghong 23 under shade stress were significantly increased compared with those under natural light. The maximum photochemical efficiency (Fv/Fm), the potential activity (Fv/Fo), and the comprehensive index of photosynthetic performance (PIABS) of the chlorophyll photosystem PSII decreased significantly under shade stress. The net photosynthetic rate and water use efficiency decreased significantly, while SOD and POD enzyme activities increased significantly. In addition, shade stress increased significantly the vine length and specific leaf area of Zhenghong 23, but reduced significantly the fresh weight of roots. Transcriptome and metabolome analysis of leaf tissues under shade stress and natural light conditions showed that the DEGs and DMs were mainly enriched in phenylpropanoid biosynthesis, sugar metabolism, sphinolipid metabolism, and arginine biosynthesis pathways. Most of the up-regulated DEGs enriched in the phenylpropanoid biosynthesis pathway were POD enzyme family genes, indicating that the shade stress triggered the ROS scavenging system in sweetpotato. Meanwhile, shade stress reduced sugar metabolism level of sweetpotato, decreased the soluble sugar content of leaves, inhibited both the synthesis and degradation of starch, and blocked the expansion of tuberous roots. In addition, the sphinolipid and arginine metabolism pathways may better adapt sweetptoato plants to shade stress through improving the stability of biomembranes and increase the synthetic substrates of polyamine anti-stress factors. These results provide new theoretical basis for understanding the metabolic response pathways of sweetpotato under shade stress.

Key words: sweetpotato, shade stress, transciptome, metabolome, the response pathways

Fig. 1

Comparison of plant morphology of Zhenghong 23 under natural light and shade stress"

Table 1

Effects of shade stress on plant morphological indexes and leaf enzymatic activity of Zhenghong 23"

光处理
Light
treatment
蔓长
Vine length
(cm)
茎节数
Stem internode number
比叶面积
Specific leaf area
(cm2 g-1)
根鲜重
Root fresh weight (g)
SOD活性
SOD activity
(U g-1 FW)
POD活性
POD activity
(U g-1 FW)
光照Light 43.5 (6.9) 13.3 (0.5) 211.9 (28.3) 17.9 (9.9) 339.7 (80.2) 1096.1 (230.0)
遮阴Shade 65.7 (9.3)** 14.8 (2.1) 457.6 (39.2)*** 1.2 (0.5)* 547.2 (72.8)** 2366.9 (398.0)**

Table 2

Effects of shade stress on chlorophyll content (mg g-1 FW) and fluorescence characteristics of Zhenghong 23"

光处理
Light treatment
叶绿素a
Chlorophyll a
叶绿素b
Chlorophyll b
叶绿素a/b
Chlorophyll a/b
总叶绿素
Total chlorophyll
Fv/Fm Fv/Fo PIABS
光照Light 1.08 (0.11) 0.45 (0.12) 2.44 (0.34) 1.53 (0.23) 0.749 (0.022) 2.838 (0.210) 0.570 (0.055)
遮阴Shade 1.21 (0.04) 0.73 (0.05)** 1.66 (0.15)** 1.94 (0.05)* 0.670 (0.033)** 2.107 (0.364)* 0.398 (0.046)**

Table 3

Effects of shade stress on photosynthetic parameters of Zhenghong 23"

光处理
Light
treatment
净光合速率
Net photosynthetic rate
(μmol m-2 s-1)
蒸腾速率
Transpiration
rate
(mmol m-2 s-1)
胞间CO2浓度
Intercellular CO2 concentration
(μmol mol-1)
气孔导度
Stomatal
conductance
(mmol m-2 s-1)
水汽压亏缺
Vapor pressure deficit
(mb)
水分利用效率
Water use
efficiency
(%)
光照Light 9.13 (0.87) 2.29 (0.53) 241.8 (28.2) 103.5 (8.9) 2.07 (0.18) 4.07 (0.54)
遮阴Shade 2.45 (0.54)*** 1.93 (0.46) 341.0 (13.7)** 97.3 (10.1) 2.18 (0.23) 1.02 (0.37)***

Fig. 2

Heatmap of the Pearson correlation between RNA-seq samples (a) and principal component analysis plots of samples in metabolome (b) S: shade treatment; L: light treatment."

Table 4

RNA-seq quality of samples"

样品
Sample name
原始序列数
Raw
reads
过滤后序列及占比
Clean reads and
percentage (%)
比对到基因组上的reads数及占比
Number and proportion of reads
on the genome (%)
单一位置reads数及百分比
Unique mapped reads
and percentage (%)
Q30比例
Q30 ratio
(%)
S1 46,514,384 45,395,970 (97.60) 32,813,096 (72.28%) 31,148,789 (68.62%) 92.72
S2 45,595,318 44,524,818 (97.65) 32,073,379 (72.03%) 30,310,383 (68.08%) 93.15
S3 48,243,946 46,619,848 (96.63) 33,903,203 (72.72%) 32,580,570 (69.89%) 93.16
S4 45,242,868 43,886,694 (97.00) 31,090,577 (70.84%) 29,766,110 (67.82%) 92.72
L1 51,826,126 50,453,206 (97.35) 36,601,089 (72.54%) 35,349,491 (70.06%) 92.79
L2 52,046,026 50,516,688 (97.06) 35,620,398 (70.51%) 34,152,030 (67.61%) 93.27
L3 43,082,564 42,246,862 (98.06) 29,421,358 (69.64%) 28,373,138 (67.16%) 92.76
L4 45,214,902 43,699,856 (96.65) 30,949,611 (70.82%) 29,612,170 (67.76%) 93.30

Fig. 3

Number of total genes (a) and DEGs (b) identified under shade stress and natural light conditions S: shade treatment; L: light treatment."

Fig. 4

Top 30 function terms significantly enriched by GO (a) and the top 20 pathways significantly enriched by KEGG (b) BP: biological process; CC: cellular component; MF: molecular function. Numbers of DEGs enriched are marked above the bars. The higher the ordinate value is, the more significant the enrichment is."

Fig. 5

Correlation chart of the Top20 DMs (a) and the bubble chart of the KEGG enrichment of DMs (b) (a): the red shape indicates the positive correlation and blue indicates the negative correlation. The dot with no color means the correlation is not significant at P > 0.05. (b): the color and size of the bubble represent the enrichment reliability and the number of DMs enriched, respectively. The bigger the-log10 (P-value) is, the more reliable the enrichment is. S: shade treatment; L: light treatment."

Fig. 6

Correlation heatmap of the Top50 DMs (top) and Top100 DEGs (left) (a) and the bubble chart of the KEGG pathways jointly enriched from DEGs and DMs (b) (a): the red indicates the positive correlation and blue indicates the negative correlation. The flatter the ellipse, the higher the absolute value of the correlation. (*) means significant difference at P < 0.05. (b): triangles are DEGs and dots are DMs. The bigger the-log10(P-value) is, the more reliable the enrichment is. S: shade treatment; L: light treatment."

Fig. 7

Content heatmap of DMs enriched in the phenylpropanoid biosynthesis pathway (a) and correlation heatmap of the DMs and DEGs enriched in this pathway (b)"

Fig. 8

Content heatmap of DMs enriched in the sugar metabolism related pathways (a) and correlation heatmap of the DMs and DEGs enriched in these pathways (b)"

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doi: 10.1111/ppa.2016.65.issue-9
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[2] CHEN Yi-Hang, TANG Chao-Chen, ZHANG Xiong-Jian, YAO Zhu-Fang, JIANG Bing-Zhi, WANG Zhang-Ying. Construction of core collection of sweetpotato based on phenotypic traits and SSR markers [J]. Acta Agronomica Sinica, 2023, 49(5): 1249-1261.
[3] WU Shi-Yu, CHEN Kuang-Ji, LYU Zun-Fu, XU Xi-Ming, PANG Lin-Jiang, LU Guo-Quan. Effects of nitrogen fertilizer application rate on starch contents and properties during storage root expansion in sweetpotato [J]. Acta Agronomica Sinica, 2023, 49(4): 1090-1101.
[4] LIU Ming, FAN Wen-Jing, ZHAO Peng, JIN Rong, ZHANG Qiang-Qiang, ZHU Xiao-Ya, WANG Jing, LI Qiang. Genotypes screening and comprehensive evaluation of sweetpotato tolerant to low potassium stress at seedling stage [J]. Acta Agronomica Sinica, 2023, 49(4): 926-937.
[5] YAO Zhu-Fang, ZHANG Xiong-Jian, YANG Yi-Ling, HUANG Li-Fei, CHEN Xin-Liang, YAO Xiao-Jian, LUO Zhong-Xia, CHEN Jing-Yi, WANG Zhang-Ying, FANG Bo-Ping. Genetic diversity of phenotypic traits in 177 sweetpotato landrace [J]. Acta Agronomica Sinica, 2022, 48(9): 2228-2241.
[6] CHEN Lu, ZHOU Shu-Qian, LI Yong-Xin, CHEN Gang, LU Guo-Quan, YANG Hu-Qing. Identification and expression analysis of uncoupling protein gene family in sweetpotato [J]. Acta Agronomica Sinica, 2022, 48(7): 1683-1696.
[7] JIN Rong, JIANG Wei, LIU Ming, ZHAO Peng, ZHANG Qiang-Qiang, LI Tie-Xin, WANG Dan-Feng, FAN Wen-Jing, ZHANG Ai-Jun, TANG Zhong-Hou. Genome-wide characterization and expression analysis of Dof family genes in sweetpotato [J]. Acta Agronomica Sinica, 2022, 48(3): 608-623.
[8] ZHANG Hai-Yan, XIE Bei-Tao, JIANG Chang-Song, FENG Xiang-Yang, ZHANG Qiao, DONG Shun-Xu, WANG Bao-Qing, ZHANG Li-Ming, QIN Zhen, DUAN Wen-Xue. Screening of leaf physiological characteristics and drought-tolerant indexes of sweetpotato cultivars with drought resistance [J]. Acta Agronomica Sinica, 2022, 48(2): 518-528.
[9] CAO Liang, DU Xin, YU Gao-Bo, JIN Xi-Jun, ZHANG Ming-Cong, REN Chun-Yuan, WANG Meng-Xue, ZHANG Yu-Xian. Regulation of carbon and nitrogen metabolism in leaf of soybean cultivar Suinong 26 at seed-filling stage under drought stress by exogenous melatonin [J]. Acta Agronomica Sinica, 2021, 47(9): 1779-1790.
[10] ZHANG Si-Meng, NI Wen-Rong, LYU Zun-Fu, LIN Yan, LIN Li-Zhuo, ZHONG Zi-Yu, CUI Peng, LU Guo-Quan. Identification and index screening of soft rot resistance at harvest stage in sweetpotato [J]. Acta Agronomica Sinica, 2021, 47(8): 1450-1459.
[11] NIU Li, BAI Wen-Bo, LI Xia, DUAN Feng-Ying, HOU Peng, ZHAO Ru-Lang, WANG Yong-Hong, ZHAO Ming, LI Shao-Kun, SONG Ji-Qing, ZHOU Wen-Bin. Effects of plastic film mulching on leaf metabolic profiles of maize in the Loess Plateau with two planting densities [J]. Acta Agronomica Sinica, 2021, 47(8): 1551-1562.
[12] MA Meng, YAN Hui, GAO Run-Fei, KOU Meng, TANG Wei, WANG Xin, ZHANG Yun-Gang, LI Qiang. Construction linkage maps and identification of quantitative trait loci associated with important agronomic traits in purple-fleshed sweetpotato [J]. Acta Agronomica Sinica, 2021, 47(11): 2147-2162.
[13] Shan-Bin CHEN, Si-Fan SUN, Nan NIE, Bing DU, Shao-Zhen HE, Qing-Chang LIU, Hong ZHAI. Cloning of IbCAF1 and identification on tolerance to salt and drought stress in sweetpotato [J]. Acta Agronomica Sinica, 2020, 46(12): 1862-1869.
[14] Hai-Yan ZHANG,Bei-Tao XIE,Bao-Qing WANG,Shun-Xu DONG,Wen-Xue DUAN,Li-Ming ZHANG. Evaluation of drought tolerance and screening for drought-tolerant indicators in sweetpotato cultivars [J]. Acta Agronomica Sinica, 2019, 45(3): 419-430.
[15] ZHANG Hai-Yan,DUAN Wen-Xue,XIE Bei-Tao,DONG Shun-Xu,WANG Bao-Qing,SHI Chun-Yu,ZHANG Li-Ming. Effects of Drought Stress at Different Growth Stages on Endogenous Hormones and Its Relationship with Storage Root Yield in Sweetpotato [J]. Acta Agron Sin, 2018, 44(01): 126-136.
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