Crops ›› 2022, Vol. 38 ›› Issue (6): 42-53.doi: 10.16035/j.issn.1001-7283.2022.06.006

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Transcriptome Analysis of OsWD40 Overexpression Rice Roots in Response to Salt Stress

Wen Danni(), Bao Lingran, Liu Mengmeng, Shen Bo()   

  1. College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou 311121, Zhejiang, China
  • Received:2021-05-26 Revised:2021-07-13 Online:2022-12-15 Published:2022-12-21
  • Contact: Shen Bo E-mail:txchwdn@163.com;bshen65@163.com

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Abstract:

Salt stress is a major factor affecting rice yield. Therefore, it is necessary to investigate salt tolerance mechanisms in rice. In order to reveal the molecular mechanism of OsWD40 gene involved in salt tolerance, comparative transcriptome analysis was performed on roots of Nipponbare and OsWD40 overexpression rice line treated with 200mmol/L NaCl for 0, 12, 24 and 48h, respectively. The results showed that a total of 1950, 1646, 3499 and 1522 differentially expressed genes were identified between Nipponbare and OsWD40 overexpression line at the same time of salt stress (ST0 vs NT0, ST12 vs NT12, ST24 vs NT24 and ST48 vs NT48). Among them, the number of differentially expressed genes of 24h was more than those of 0, 12 and 48h treatment. GO functional enrichment analysis and KEGG metabolic pathway analysis were performed on differentially expressed genes in four comparison groups, which found that the differentially expressed genes were mainly enriched in salt stress response, abscisic acid response, transcriptional regulation, and so on. The important metabolic pathways also were enriched, including plant hormone signal transduction, plant MAPK signal transduction pathway, phenylpropane biosynthesis, and secondary metabolic pathways related to flavonoid biosynthesis. Meanwhile, the transcription factors, such as WRKY, MYB and bHLH, were differentially expressed in each comparison group. We speculated that phenylpropane biosynthesis, flavonoid biosynthesis and other plant secondary metabolic pathways play an important role in roots of OsWD40 overexpression rice in response to salt stress, and OsWD40 may mediate the regulation of gene transcription in response to abscisic acid and activate the expression of downstream salt stress related genes.

Key words: Rice, Salt stress, Transgene, Transcriptome analysis

Table 1

The primer and sequences of qRT-PCR"

基因Gene 上游引物Forward primer (5′-3′) 下游引物Reverse primer (5′-3′)
Actin TGGCATCTCTCAGCACATTCC TGCACAATGGATGGGTCAGA
LOC_Os11g03300 TTCTCCTCGACGGCTCATCC ATGGATGGCTCAGCAGATTG
LOC_Os05g39770 AGTGGAACTGGCACCAGGA CCGCCAGCTTTCCTTACC
LOC_Os07g47100 CATTGATCAGGCTGCTGCTA AGGAGAATGCAGGGACTTTG
LOC_Os06g10880 AGCAGGTGGAAATGATACAG GGTCCAAGTTGCTGAGTGATTC
LOC_Os03g44380 CCCCTCCCAAACCATCCAAACCGA TGTGAGCATATCCTGGCGTCGTGA
LOC_Os05g46480 CAACAGGCGAGTGAGCAGGT GGCAGAGGTGTCCTTGTTGG

Table 2

The number of sequencing obtained from each sample and the clean reads mapped to the reference genome"

样本
Sample		 下机
数据
Raw
data		 有效
数据
Valid data		 有效数
据占比
Valid
data ratio		 质量值
≥20的
碱基占比
Q20 (%)		 质量值
≥30的
碱基占比
Q30 (%)		 GC
含量
GC
content (%)		 比对上的数据
Mapped reads		 双端测序
比对的数据
PE mapped data		 比对到正义链
上的数据
Data map to
sense strand		 比对到负义链
上的数据
Data map to
antisense strand
NT0_1 55594226 53496550 96.23 99.97 98.30 51.50 51985392(97.18%) 43488358(81.29%) 25163319(47.04%) 25178904(47.07%)
NT0_2 52817870 50682622 95.96 99.97 98.13 51.50 49223859(97.12%) 40134484(79.19%) 23950832(47.26%) 23967765(47.29%)
NT0_3 52755478 50891124 96.47 99.98 98.37 51.50 49511211(97.29%) 41207684(80.97%) 24069909(47.30%) 24084911(47.33%)
NT12_1 54235522 50625828 93.34 99.97 98.29 52.00 49080156(96.95%) 37145844(73.37%) 23879823(47.17%) 23906904(47.22%)
NT12_2 46064242 44429636 96.45 99.97 97.97 51.50 42938113(96.64%) 36195478(81.47%) 20852098(46.93%) 20874021(46.98%)
NT12_3 44894412 43276734 96.40 99.97 97.99 52.00 41835537(96.67%) 35446854(81.91%) 20307875(46.93%) 20329368(46.98%)
NT24_1 41972552 40658514 96.87 99.98 98.09 51.00 39562402(97.30%) 33397190(82.14%) 19284864(47.43%) 19297600(47.46%)
NT24_2 41892832 40463424 96.59 99.97 97.98 51.50 39274992(97.06%) 32803824(81.07%) 19153423(47.34%) 19164127(47.36%)
NT24_3 47414386 45591086 96.15 99.97 98.20 51.50 44336074(97.25%) 36632882(80.35%) 21620685(47.42%) 21636406(47.46%)
NT48_1 42666604 39894332 93.50 99.97 97.99 51.00 36320644(91.04%) 28940110(72.54%) 17704975(44.38%) 17720169(44.42%)
NT48_2 40013330 37621550 94.02 99.98 98.27 51.00 34311261(91.20%) 27795630(73.88%) 16746205(44.51%) 16757258(44.54%)
NT48_3 48718112 45762610 93.93 99.98 98.22 50.50 41673375(91.06%) 33931226(74.15%) 20316666(44.40%) 20330708(44.43%)
ST0_1 54969298 53044704 96.50 99.97 97.98 52.00 51155862(96.44%) 43702296(82.39%) 24492741(46.17%) 24508398(46.20%)
ST0_2 51300678 49722622 96.92 99.97 98.08 51.00 48221641(96.98%) 41955702(84.38%) 23210529(46.68%) 23222965(46.71%)
ST0_3 38687294 37517004 96.98 99.97 98.07 51.50 36283839(96.71%) 30916570(82.41%) 17411611(46.41%) 17424467(46.44%)
ST12_1 44194388 42703814 96.63 99.97 97.97 52.50 41455059(97.08%) 35235574(82.51%) 20126507(47.13%) 20142756(47.17%)
ST12_2 51295308 49567818 96.63 99.97 98.21 51.50 48275090(97.39%) 41264814(83.25%) 23393716(47.20%) 23411185(47.23%)
ST12_3 43138696 41425600 96.03 99.97 98.01 52.00 40245905(97.15%) 34333534(82.88%) 19478261(47.02%) 19492528(47.05%)
ST24_1 47350468 45852822 96.84 99.97 98.31 51.50 44419860(96.87%) 38347230(83.63%) 21507933(46.91%) 21522388(46.94%)
ST24_2 45333810 43588952 96.15 99.97 98.23 52.00 42226091(96.87%) 35694034(81.89%) 20473666(46.97%) 20491512(47.01%)
ST24_3 55477336 53491042 96.42 99.97 98.09 51.50 51737530(96.72%) 43486768(81.30%) 25140157(47.00%) 25161755(47.04%)
ST48_1 50828748 48746228 95.90 99.98 98.16 50.50 44616047(91.53%) 37997692(77.95%) 21704972(44.53%) 21724068(44.57%)
ST48_2 51300532 49086028 95.68 99.98 98.17 51.00 45067807(91.81%) 37483712(76.36%) 21957557(44.73%) 21980721(44.78%)
ST48_3 52646234 50270482 95.49 99.98 98.05 51.00 44595442(88.71%) 37928460(75.45%) 20264052(40.31%) 20279655(40.34%)

Fig.1

The relationship of all surveyed samples"

Fig.2

Number of differently expressed genes in each comparison group"

Fig.3

Venn diagram of differently expressed genes between different comparison groups"

Table 3

The number of DEGs of important GO terms in each comparison groups"

GO条目
GO term		 比较组Group
ST0 vs NT0 ST12 vs NT12 ST24 vs NT24 ST48 vs NT48
生物进程Biological process
防御响应 97 70 113 67
蛋白质磷酸化 88 64 152 66
以DNA为模板的转录调控 76 71 140 79
氧化还原过程 62 46 102 39
信号转导 38 34 47 19
次生代谢产物的生物合成过程 33 34 41 27
细胞表面受体信号通路 23 26 42 18
跨膜受体蛋白酪氨酸激酶信号通路 16 16 46 10
对盐胁迫的响应 22 6 41 14
对ABA的响应 19 20 33 19
细胞组分Cellular component
核 276 256 573 250
质膜 281 221 501 219
膜的组成部分 172 151 327 141
细胞外区域 150 106 213 79
细胞质 162 133 315 128
分子功能Molecular function
蛋白结合 132 120 252 126
蛋白质丝氨酸/苏氨酸激酶活性 107 89 186 83
ATP结合 105 86 210 65
DNA结合转录因子活性 76 69 138 74
DNA结合 57 67 134 64

Fig.4

Bubble chart of GO enrichment analysis of differently expressed genes"

Table 4

Important KEGG metabolic pathway with a large number of differently expressed genes"

比较组Group 通路ID Pathway ID KEGG代谢通路KEGG pathway 差异表达基因数目Number of differently expressed genes
ST0 vs NT0 ko04626 植物与病原体互作 93
ko00940 苯丙烷生物合成 63
ko04075 植物激素信号转导 53
ko04016 植物MAPK信号传导途径 41
ko03013 RNA转运 30
ko00500 淀粉和蔗糖代谢 30
ko00520 氨基糖和核苷酸糖代谢 22
ko00564 甘油磷脂代谢 20
ko00941 黄酮类生物合成 19
ko00270 内质网中的蛋白质加工 18
ST12 vs NT12 ko04626 植物与病原体互作 61
ko00940 苯丙烷生物合成 39
ko00500 淀粉和蔗糖代谢 28
ko04075 植物激素信号转导 28
ko04016 植物MAPK信号传导途径 25
ko00520 氨基糖和核苷酸糖代谢 24
ko03013 RNA转运 22
ko00904 二萜类生物合成 20
ko00941 黄酮类生物合成 18
ko04141 内质网中的蛋白质加工 18
ST24 vs NT24 ko03010 核糖体 208
ko04626 植物与病原体互作 86
ko00500 淀粉和蔗糖代谢 69
ko00940 苯丙烷生物合成 67
ko04075 植物激素信号转导 67
比较组Group 通路ID Pathway ID KEGG代谢通路KEGG pathway 差异表达基因数目Number of differently expressed genes
ko04016 植物MAPK信号传导途径 51
ko03013 RNA转运 47
ko00520 氨基糖和核苷酸糖代谢 42
ko03008 真核生物的核糖体生物发生 39
ko00941 黄酮类生物合成 30
ST48 vs NT48 ko04626 植物与病原体互作 57
ko00500 淀粉和蔗糖代谢 36
ko04075 植物激素信号转导 33
ko00940 苯丙烷生物合成 30
ko04016 植物MAPK信号传导途径 25
ko04141 内质网中的蛋白质加工 22
ko00520 氨基糖和核苷酸糖代谢 20
ko03013 RNA转运 15
ko00904 二萜类生物合成 14
ko00941 黄酮类生物合成 14

Table 5

Number of differently expressed genes related to transcription factors between Nipponbare and OsWD40 overexpression line"

转录因子
Transcription
factor		 ST0 vs NT0 ST12 vs NT12 ST24 vs NT24 ST48 vs NT48
上调
Up-regulated		 下调
Down-regulated		 上调
Up-regulated		 下调
Down-regulated		 上调
Up-regulated		 下调
Down-regulated		 上调
Up-regulated		 下调
Down-regulated
WRKY 11 2 3 1 6 0 1 4
MYB 2 6 4 3 13 7 1 7
bHLH 5 9 4 0 13 1 1 4
AP2/ERF 5 2 4 4 6 1 2 3
bZIP 1 1 0 1 2 1 0 1
MADS-box 1 0 1 1 3 2 2 2
其他Others 2 6 2 2 12 1 1 4
总数Total 27 27 18 12 55 13 8 25

Table 6

Transcriptome sequencing data of each differentially expressed genes"

基因Gene NT12/NT0 NT24/NT0 NT48/NT0 ST12/ST0 ST24/ST0 ST48/ST0
LOC_Os11g03300 8.10 16.45 7.29 5.93 4.84 3.57
LOC_Os05g39770 2.57 5.17 3.18 1.92 2.60 3.83
LOC_Os07g47100 2.13 3.89 2.98 1.58 5.20 6.38
LOC_Os06g10880 4.22 4.86 3.50 4.22 4.86 3.50
LOC_Os03g44380 13.09 47.01 9.59 10.64 19.41 3.84
LOC_Os05g46480 85.80 415.22 220.93 34.75 587.20 470.53

Fig.5

qRT-PCR analysis of differently expressed genes at different hours after salt treatment Different lowercase letters indicate significant difference among treatments at 0.05 level"

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