Scientia Agricultura Sinica ›› 2023, Vol. 56 ›› Issue (21): 4288-4303.doi: 10.3864/j.issn.0578-1752.2023.21.012

• HORTICULTURE • Previous Articles     Next Articles

Sequencing and Functional Analysis of Tomato circRNA During Flowering Stage

YIN ZiHe(), YANG ChengCheng, ZHAO YuHui, ZHAO Li, LÜ XiuRong, YANG ZhenChao, WU YongJun()   

  1. College of Life Sciences/College of Horticulture, Northwest A&F University, Yangling 712100, Shaanxi
  • Received:2023-04-03 Accepted:2023-06-09 Online:2023-11-01 Published:2023-11-06
  • Contact: WU YongJun

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Abstract:

【Background】As one of the most important periods in plant growth and development, the flowering period directly affects fruit ripening and seed development. circRNAs are a class of covalent closed-loop RNA molecules that are ubiquitous in eukaryotic cells and play an important role in the regulation of tomato development and stress response. However, the current circRNA studies on tomato mainly focus on fruit and leaves, and there is a lack of systematic studies on tomato circRNA at flowering stage.【Objective】Identification and analysis of circRNs in flowering tomato could be of great significance for the functional study of miRNA and circRNA in tomato, and also layed a foundation for the study of tomato growth, development and stress response mechanism.【Method】circRNA sequencing was performed on 3 tissue samples of flowers, roots and leaves of flowering tomato plants, with 3 replicates for each sample. circRNAs were identified and their basic characteristics were analyzed. The cycle-forming ability of tissue-specific circRNAs was screened, and the host genes of identified circRNAs were analyzed by GO analysis and KEGG analysis. The mode and site of action of circRNAs were predicted and analyzed by bioinformatics methods to construct a potential circRNA-miRNA-mRNA interaction regulatory network in response to tomato growth and development.【Result】A total of 532 circRNAs were obtained by high-throughput sequencing, 83% of which were exon types. The distribution of circRNA in each chromosome of flowering tomato was uneven, among which chromosome 1 produced the most circRNAs and chromosome 5 produced the least. circRNAs differentially expressed in flower, leaf and root tissues of flowering tomato showed that 79 circRNAs were differentially expressed in flower and leaf, 133 circRNAs were differentially expressed in flower and root, and 132 circRNAs were differentially expressed in leaf and root tissues. Among them, 14 circRNAs were differentially expressed in flower, leaf and root tissues. The cyclization ability of 8 circRNAs randomly selected from 14 differentially expressed circRNAs was tested, and the results showed that all 8 circRNAs had cyclization ability. GO analysis and KEGG analysis showed that circRNAs in flowering tomato were mainly related to the binding of nucleic acids, proteins and other small molecules, as well as the synthesis and metabolism of various biological macromolecules. Finally, the tomato circRNA-miRNA-mRNA interaction regulatory network composed of 14 circRNAs, 10 miRNAs and 136 mRNAs was constructed.【Conclusion】A total of 342 tissue-specific circRNAs were identified, among which 14 were significantly expressed, and 8 were successfully identified. A circRNA-miRNA-mRNA interaction regulatory network was constructed for tomato at flowering stage. This study laid a foundation for the subsequent research of circRNA in flowering period.

Key words: circRNA, tomato, flowering stages, miRNA, ceRNA

Table 1

Primer sequences"

circRNA ID 正向引物 Forward primer (5′-3′) 反向引物 Reverse primer (5′-3′)
Circ_97/NC_015441.2：3422764-3423369 S97 TGTTGACATTGAGAGTGTGGGGTGT TTGAAAAGATGAAAGGGCTTTTGCT
F97 TCAAAATCATCACCTCCAGAAACCAG TATCCAGCATCAGCACCGCCACTAC
Circ_473/NC_015444.2:
64279949-64300043		 S473 AAAGGGAGAAGAGCAGGAGGCAGGT CTTATGTTTCCGATGATTGAGTGTA
F473 ATCATCATCTCTTCATCCTCAAACA TGGCGGTCGTGCTCCTATT
Circ_136/NC_015444.2:
211739-220422		 S136 ATTATCCATTACAGTAACACCCACC TTAAATTAAACACATTGAAAGCCTC
F136 GCCCATCATTGGAATAGCAAAAGAGC CAGCTAGGAGCAGGAGGGAAGAAGC
Circ_240/NC_015441.2:
2372079-2376972		 S240 CATGCTGTACGTGCTGCTGTTATAT TCCTCTTCATCGTGTTTTGCTTTTG
F240 TCACAAACCTACACCAACTCTAAACA GGACTTCCGTACTGAAAGAAATGAG
Circ_19/NC_015447.2:
1328362-1329697		 S19 TAAGAAGAAGAGGACTCACCAAAGG AAGATCAGCATCATCCACAACCCGA
F19 TGATGAGTTGATCGGTGTTCTG TGTGCTGATCTGAAGAGGTCTCC
Circ_105/NC_015439.2:
4011485-40114693		 S105 ACTTGATTCCTACTTCCTTTTTCGT TAGTTTTAGTTGATCGTTTGCCTTG
F105 CTGAAAGATTAGTTGGATGGAGGAGG GTTGCCCTCTGTTCCGAAAATGACTC
Circ_77/NC_015438.2:
89916310-89921994		 S77 CTTTACTTTCCATTTCATTTGTTGT ATCTTTTTCTCTCCCATTTTCTTTC
F77 ATGTAGTCCTGGATTGAAGGAGAC GAACTTGTGACGATATGCCTCTC
Circ_228/NC_015449.2:
64101116-64102065		 S228 ATCAAGGAGGACCAATGCTTCAGTA CGGAGAATGTGTATGCGATTTATGT
F228 TATCTCTTGTTTGTTCAACCCCACTG ATGGAACAGATTGGTGAAAATGCCCT

Table 2

Statistic of evaluating the circRNA-seq data"

样本 ID
Sample ID		 总读数的数量
No. of total reads		 清洁读数对比率
Percentage of mapped reads (%)		 可映射到基因组上的读数率
Percentage of unique mapped reads (%)
F1 81824486 0.9999 0.9037
F2 81760358 0.9999 0.8673
F3 80496996 0.9998 0.9237
L1 80618686 0.9998 0.7741
L2 81111640 0.9998 0.7384
L3 84395574 0.9999 0.7272
R1 80571720 0.9999 0.8953
R2 80841312 0.9998 0.8781
R3 80087212 0.9999 0.7404

Fig. 1

Identification of tomato circRNA A: Tomato circRNA identified by CIRI and find _circ; B: Total circRNAs Venn diagram analysis of all tomato tissues"

Fig. 2

Classification and characterization of circRNA of tomato A: Classification diagram of circRNA identified in tomato; B: Analysis of circRNA number and type proportion of each chromosome in tomato; C: Distribution and type of circRNA of different lengths in tomato; D: Number of circRNA with different expressions (RPM) in flowers, leaves and roots of tomato"

Fig. 3

Differential expression analysis of tomato circRNA A: Overall distribution of tomato circRNA in flower, leaf and root. B: Differential expression statistics and up/down regulation levels of circRNA in flower, leaf and root. C, D and E show volcano plots of DE circRNA genes (Degs) in tomato leaf (L), flower (F) and root (R). C: The DEGS_Volcano of F-vs-L; D: The DEGS_Volcano of L-vs-R. E: The DEGS_Volcano of F-vs-R. Red, green and grey indicate up-regulated, down-regulated and non-DEG. F: Intersection analysis of circRNA differentially expressed in flower, leaf and root tissues. G: Results of hierarchical clustering of 14 circRNA significantly differentially expressed in flower, leaf and root tissues"

Fig. 4

Validation of ring forming ability and differential expression of tomato circRNA A: Principle of circRNA ring forming ability; B: Detection of ring forming ability of tomato circRNA; C: Validation of differential expression circRNA in tomato"

Fig. 5

GO/KEGG pathway analysis Gene ontology enrichment analysis (GO) of circRNA cis-target genes in circRNA-hosting gene A: The vertical axis represents the number of genes in tomato, the horizontal axis represents the enrichment items listing the top 10 biological process (BP), cellular component (CC) Top 10 bars, Top 16 of molecular function (MF); B: KEGG pathway enrichment of circRNA cis-target genes in tomato (top 24), items / paths on the vertical axis are drawn by the classification of paths (different colors represent different categories), the horizontal axis represents the enrichment coefficient"

Table 3

GO annotations of the host genes with differentially expressed circRNA"

GO类别 GO category GO名称 GO name GO ID 宿主基因数量 No. of host genes
生物过程
Biological process		 生物调节 Biological regulation GO: 0065007 41
基因表达调控 Regulation of gene expression GO: 0010468 17
细胞分解代谢过程 Cellular catabolic process GO: 0044248 17
细胞组分
Cellular component		 细胞质 Cytoplasm GO: 0005737 70
胞质部分 Cytoplasmic part GO: 0044444 51
质膜 Plasma membrane GO: 0005886 21
分子功能
Molecular function		 核苷酸结合 Nucleotide binding GO: 0000166 49
离子结合 Ion binding GO: 0043167 45
碳水化合物衍生物结合 Carbohydrate derivative binding GO: 0097367 42

Table 4

KEGG annotations of the host genes with differentially expressed circRNA"

KEGG通路名称 Name of the KEGG pathway KEGG编号 KEGG number 宿主基因数量 No. of host genes
丙氨酸，天冬氨酸和谷氨酸的代谢 Alanine, aspartate and glutamate metabolism sly00250 30
精氨酸的生物合成 Arginine biosynthesis sly00220 12
磷酸戊糖途径 Pentose phosphate pathway sly00030 10
脂肪酸的降解 Fatty acid degradation sly00071 6
脂肪酸的生物合成 Fatty acid biosynthesis sly00061 5
脂肪酸代谢 Fatty acid metabolism sly01212 3
花生四烯酸代谢 Arachidonic acid metabolism sly00590 2

Table 5

miRNA target genes and binding sites of tomato circRNAs during flowering"

Trans ID miR ID 结合位点 Binding sites 靶向基因数量 No. of target genes
circ_1420/NC_015447.2:
2008132-2031198		 sly-miR5303
 38
circ_547/NC_015449.2:
53700671-53711562		 38
circ_459/NC_015444.2:
21380917-21381396		 sly-miR9476-5p 5
circ_1112/NC_015444.2:
64279962-64300043		 sly-miR396b 30
circ_473/NC_015444.2:
64279949-64300043
circ_10/NC_015444.2:
208457-238616		 sly-miR9478-3p 4
circ_1079/NC_015444.2:
230400-238546
circ_176/NC_015444.2:
210427-211962		 4
circ_437/NC_015438.2:
97435162-97451603		 sly-miR156e-3p 4
circ_704/NC_015438.2:
95819397-95828905		 sly-miR482d-5p 1
circ_733/NC_015438.2:
95819397-95825691
circ_739/NC_015438.2:
90765535-90770648		 sly-miR1916 6
circ_309/NC_015445.2:
2493994-2498871		 sly-miR1918 3
circ_1403/NC_015439.2:
47259582-47353207		 sly-miR9479-3p 1
sly-miR167b-3p 2

Table 6

GO annotation of target genes in the circRNA-miRNA-mRNA module"

GO类别
GO category		 GO名称
GO name		 GO ID 宿主基因数量
No. of target genes
生物过程
Biological process		 谷氨酸代谢 Glutamate metabolic process GO: 0006536 4
胞外多糖的生物合成 Extracellular polysaccharide biosynthetic process GO: 0045226 4
DNA模板化转录调控 Regulation of transcription, DNA-templated GO: 0006355 3
细胞组分
Cellular component		 细胞核 Nucleus GO: 0005634 10
线粒体基质 Mitochondrial matrix GO: 0005759 2
分子功能
Molecular function		 ATP结合 ATP binding GO: 0005524 12
蛋白结合 Protein binding GO: 0005515 12
辅酶结合 Coenzyme binding GO: 0050662 4

Fig. 6

Visualization plot of the circRNA-miRNA-mRNA co-expression network in flowering tomato"

[1]
FORNARA F, DE MONTAIGU A, COUPLAND G. SnapShot: Control of flowering in Arabidopsis. Cell, 2010, 141(3): 550-550.e2.

doi: 10.1016/j.cell.2010.04.024
[2]
JECK W R, SHARPLESS N E. Detecting and characterizing circular RNAs. Nature Biotechnology, 2014, 32(5): 453-461.

doi: 10.1038/nbt.2890 pmid: 24811520
[3]
JECK W R, SORRENTINO J A, WANG K, SLEVIN M K, BURD C E, LIU J Z, MARZLUFF W F, SHARPLESS N E. Circular RNAs are abundant, conserved, and associated with ALU repeats. RNA, 2013, 19(2): 141-157.

doi: 10.1261/rna.035667.112 pmid: 23249747
[4]
CONN V M, HUGOUVIEUX V, NAYAK A, CONOS S A, CAPOVILLA G, CILDIR G, JOURDAIN A, TERGAONKAR V, SCHMID M, ZUBIETA C, CONN S J. A circRNA from SEPALLATA3 regulates splicing of its cognate mRNA through R-loop formation. Nature Plants, 2017, 3(5): 17053.

doi: 10.1038/nplants.2017.53
[5]
CHENG J P, ZHANG Y, LI Z W, WANG T Y, ZHANG X T, ZHENG B L. A lariat-derived circular RNA is required for plant development in Arabidopsis. Science China Life Sciences, 2018, 61(2): 204-213.

doi: 10.1007/s11427-017-9182-3
[6]
ZENG R F, ZHOU J J, HU C G, ZHANG J Z. Transcriptome-wide identification and functional prediction of novel and flowering-related circular RNAs from trifoliate orange (Poncirus trifoliata L. Raf.). PLANTA, 2018, 247(5): 1191-1202.

doi: 10.1007/s00425-018-2857-2
[7]
ZUO J H, WANG Q, ZHU B Z, LUO Y B, GAO L P. Deciphering the roles of circRNAs on chilling injury in tomato. Biochemical and Biophysical Research Communications, 2016, 479(2): 132-138.

doi: S0006-291X(16)31147-0 pmid: 27402275
[8]
TAN J J, ZHOU Z J, NIU Y J, SUN X Y, DENG Z P. Identification and functional characterization of tomato circRNAs derived from genes involved in fruit pigment accumulation. Scientific Reports, 2017, 7(1): 8594.

doi: 10.1038/s41598-017-08806-0 pmid: 28819222
[9]
WANG Y X, WANG Q, GAO L P, ZHU B Z, LUO Y B, DENG Z P, ZUO J H. Integrative analysis of circrNAs acting as ceRNAs involved in ethylene pathway in tomato. Physiologia Plantarum, 2017, 161(3): 311-321.

doi: 10.1111/ppl.2017.161.issue-3
[10]
YANG Z C, YANG C C, WANG Z Y, YANG Z, CHEN D Y, WU Y J. LncRNA expression profile and ceRNA analysis in tomato during flowering. PLoS ONE, 2019, 14(1): e0210650.
[11]
ZUO J H, GRIERSON D, COURTNEY L T, WANG Y X, GAO L P, ZHAO X Y, ZHU B Z, LUO Y B, WANG Q, GIOVANNONI J J. Relationships between genome methylation, levels of non-coding RNAs, mRNAs and metabolites in ripening tomato fruit. The Plant Journal, 2020, 103(3): 980-994.

doi: 10.1111/tpj.14778 pmid: 32314448
[12]
YANG X D, LIU Y H, ZHANG H, WANG J Y, ZINTA G, XIE S B, ZHU W M, NIE W F. Genome-wide identification of circular RNAs in response to low-temperature stress in tomato leaves. Frontiers in Genetics, 2020, 11: 591806.

doi: 10.3389/fgene.2020.591806
[13]
YANG Z C, YANG Z, XIE Y G, LIU Q, MEI Y H, WU Y J. Systematic identification and analysis of light-responsive circular RNA and co-expression networks in lettuce (Lactuca sativa). G3 (Bethesda, Md), 2020, 10(7): 2397-2410.
[14]
PRENSNER J R, IYER M K, BALBIN O A, DHANASEKARAN S M, CAO Q, BRENNER J C, LAXMAN B, ASANGANI I A, GRASSO C S, KOMINSKY H D, CAO X H, JING X J, WANG X J, SIDDIQUI J, WEI J T, ROBINSON D, IYER H K, PALANISAMY N, MAHER C A, CHINNAIYAN A M. Transcriptome sequencing across a prostate cancer cohort identifies PCAT-1, an unannotated lincRNA implicated in disease progression. Nature Biotechnology, 2011, 29(8): 742-749.

doi: 10.1038/nbt.1914 pmid: 21804560
[15]
MURRAY M G, THOMPSON W F. Rapid isolation of high molecular weight plant DNA. Nucleic Acids Research, 1980, 8(19): 4321-4326.

doi: 10.1093/nar/8.19.4321 pmid: 7433111
[16]
TRIPATHI A, GOSWAMI K, TIWARI M, MUKHERJEE S K, SANAN-MISHRA N. Identification and comparative analysis of microRNAs from tomato varieties showing contrasting response to ToLCV infections. Physiology and Molecular Biology of Plants, 2018, 24(2): 185-202.

doi: 10.1007/s12298-017-0482-3 pmid: 29515314
[17]
LIU M M, YU H Y, ZHAO G J, HUANG Q F, LU Y E, OUYANG B. Profiling of drought-responsive microRNA and mRNA in tomato using high-throughput sequencing. BMC Genomics, 2017, 18(1): 481.

doi: 10.1186/s12864-017-3869-1 pmid: 28651543
[18]
ZHOU R, YU X Q, OTTOSEN C O, ZHANG T L, WU Z, ZHAO T M. Unique miRNAs and their targets in tomato leaf responding to combined drought and heat stress. BMC Plant Biology, 2020, 20(1): 107.

doi: 10.1186/s12870-020-2313-x pmid: 32143575
[19]
LIU Y, SU W J, WANG L J, LEI J, CHAI S S, ZHANG W Y, YANG X S. Integrated transcriptome, small RNA and degradome sequencing approaches proffer insights into chlorogenic acid biosynthesis in leafy sweet potato. PLoS ONE, 2021, 16(1): e0245266.
[20]
MIOZZI L, NAPOLI C, SARDO L, ACCOTTO G P. Transcriptomics of the interaction between the monopartite phloem-limited geminivirus tomato yellow leaf curl Sardinia virus and Solanum lycopersicum highlights a role for plant hormones, autophagy and plant immune system fine tuning during infection. PLoS ONE, 2014, 9(2): e89951.
[21]
ZHAO M, JI H M, GAO Y, CAO X X, MAO H Y, OUYANG S Q, LIU P. An integrated analysis of mRNA and sRNA transcriptional profiles in tomato root: Insights on tomato wilt disease. PLoS ONE, 2018, 13(11): e0206765.
[22]
HONG Y H, MENG J, HE X L, ZHANG Y Y, LUAN Y S. Overexpression of MiR482c in tomato induces enhanced susceptibility to late blight. Cells, 2019, 8(8): 822.

doi: 10.3390/cells8080822
[23]
LÓPEZ-GALIANO M J, SENTANDREU V, MARTÍNEZ-RAMÍREZ A D, RAUSELL C, REAL M D, CAMAÑES G, RUIZ-RIVERO O, CRESPO-SALVADOR O, GARCÍA-ROBLES I. Identification of stress associated microRNAs in Solanum lycopersicum by high-throughput sequencing. Genes, 2019, 10(6): 475.

doi: 10.3390/genes10060475
[24]
MENG X W, ZHANG P J, CHEN Q, WANG J J, CHEN M. Identification and characterization of ncRNA-associated ceRNA networks in Arabidopsis leaf development. BMC Genomics, 2018, 19(1): 607.

doi: 10.1186/s12864-018-4993-2
[25]
LIANG Y W, ZHANG Y Z, XU L A, ZHOU D, JIN Z M, ZHOU H Y, LIN S E, CAO J S, HUANG L. CircRNA expression pattern and ceRNA and miRNA-mRNA networks involved in anther development in the CMS line of Brassica campestris. International Journal of Molecular Sciences, 2019, 20(19): 4808.

doi: 10.3390/ijms20194808
[26]
ZHAO W, CHENG Y H, ZHANG C, YOU Q B, SHEN X J, GUO W, JIAO Y Q. Genome-wide identification and characterization of circular RNAs by high throughput sequencing in soybean. Scientific Reports, 2017, 7(1): 5636.

doi: 10.1038/s41598-017-05922-9 pmid: 28717203
[27]
CHEN G, CUI J W, WANG L, ZHU Y F, LU Z G, JIN B. Genome-wide identification of circular RNAs in Arabidopsis thaliana. Frontiers in Plant Science, 2017, 8: 1678.

doi: 10.3389/fpls.2017.01678
[28]
WANG W H, WANG J L, WEI Q Z, LI B Y, ZHONG X M, HU T H, HU H J, BAO C L. Transcriptome-wide identification and characterization of circular RNAs in leaves of Chinese cabbage (Brassica rapa L. ssp. Pekinensis) in response to calcium deficiency- induced tip-burn. Scientific Reports, 2019, 9: 14544.

doi: 10.1038/s41598-019-51190-0
[29]
BABAEI S, SINGH M B, BHALLA P L. Circular RNAs repertoire and expression profile during Brassica rapa pollen development. International Journal of Molecular Sciences, 2021, 22(19): 10297.

doi: 10.3390/ijms221910297
[30]
ZHOU R, XU L P, ZHAO L P, WANG Y L, ZHAO T M. Genome-wide identification of circRNAs involved in tomato fruit coloration. Biochemical and Biophysical Research Communications, 2018, 499(3): 466-469.

doi: S0006-291X(18)30685-5 pmid: 29580993
[31]
HANSEN T B, JENSEN T I, CLAUSEN B H, BRAMSEN J B, FINSEN B, DAMGAARD C K, KJEMS J. Natural RNA circles function as efficient microRNA sponges. Nature, 2013, 495(7441): 384-388.

doi: 10.1038/nature11993
[32]
MEMCZAK S, JENS M, ELEFSINIOTI A, TORTI F, KRUEGER J, RYBAK A, MAIER L, MACKOWIAK S D, GREGERSEN L H, MUNSCHAUER M, LOEWER A, ZIEBOLD U, LANDTHALER M, KOCKS C, LE NOBLE F, RAJEWSKY N. Circular RNAs are a large class of animal RNAs with regulatory potency. Nature, 2013, 495(7441): 333-338.

doi: 10.1038/nature11928
[33]
ARORA S, PANDEY D K, CHAUDHARY B. Target-mimicry based diminution of miRNA167 reinforced flowering-time phenotypes in tobacco via spatial-transcriptional biases of flowering-associated miRNAs. Gene, 2019, 682: 67-80.

doi: 10.1016/j.gene.2018.10.008
[34]
MA L L, MU J L, GRIERSON D, WANG Y X, GAO L P, ZHAO X Y, ZHU B Z, LUO Y B, SHI K, WANG Q, ZUO J H. Noncoding RNAs: functional regulatory factors in tomato fruit ripening. Theoretical and Applied Genetics, 2020, 133(5): 1753-1762.

doi: 10.1007/s00122-020-03582-4 pmid: 32211918
[35]
CANDAR-CAKIR B, ARICAN E, ZHANG B H. Small RNA and degradome deep sequencing reveals drought-and tissue-specific micrornas and their important roles in drought-sensitive and drought- tolerant tomato genotypes. Plant Biotechnology Journal, 2016, 14(8): 1727-1746.

doi: 10.1111/pbi.2016.14.issue-8
[36]
KAUR P, SHUKLA N, JOSHI G, VIJAYAKUMAR C, JAGANNATH A, AGARWAL M, GOEL S, KUMAR A. Genome-wide identification and characterization of miRNAome from tomato (Solanum lycopersicum) roots and root-knot nematode (Meloidogyne incognita) during susceptible interaction. PLoS ONE, 2017, 12(4): e0175178.
[37]
CHEN L, MENG J, HE X L, ZHANG M, LUAN Y S. Solanum lycopersicum microRNA1916 targets multiple target genes and negatively regulates the immune response in tomato. Plant, Cell & Environment, 2019, 42(4): 1393-1407.
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