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Identification and integrated analysis of mRNAs, lncRNAs, and microRNAs of developing seeds in high oleic acid sunflower (Helianthus annuus L.)

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Abstract

High unsaturated fatty acid content of sunflower seed is desirable for human-healthy high oleic acid oil production. Knowledge of lipid metabolic regulatory mechanisms is key to improving oil content and quality. This study is expected to explore regulatory mechanisms of lipid metabolism in high oleic acid seeds. First, we analyzed the oil contents and detected the fatty acid compositions in developing sunflower seeds with high oleic acid content. Next, high-throughput sequencing (HTS) of seed RNA samples from three key seed developmental stages relevant to oil content and quality was performed. Pairwise comparisons of differentially expressed mRNAs, long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) yielded respective differentially expressed transcripts as follows: 52293, 120625, 95 (L7d vs L22d); 57398, 123485, 127 (L7 vs L37d); 15417, 9554, 77 (L22d vs L37d). 15652 novel mRNAs, 123888 novel lncRNAs, and 98 novel miRNAs were identified, which enriched the RNA library of sunflower. Furthermore, gene functions were predicted using GO and KEGG analyses. These prediction analysis revealed that differentially expressed ncRNAs and mRNAs were mainly included in fatty acid metabolism and oil accumulation. Moreover, 9072 pairs of competing endogenous RNA (ceRNA) relationships comprised of interacting lncRNAs, miRNAs, and mRNAs. Pathway network analysis of differentially expressed lipid metabolism-associated ceRNAs revealed several important enzymes including glycerol-3-phosphate O-acyltransferase, linoleate 9S-lipoxygenase, acyl-CoA oxidase, and others that were enriched in fatty acid synthesis and oil accumulation, which highlighted competitive interactions in lipid metabolism. This study will elucidate potential regulatory mechanisms of lipid metabolism in sunflower seeds.

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Data availability

The datasets supporting the conclusions of this article have been deposited in the NCBI GEO database under accession numbers GSE151779 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE151779) and GSE151552 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE151552).

References

  • Abdi H (2007) The Bonferonni and Šidák corrections for multiple comparisons. Encycl Meas Stat 1:1–9

    Google Scholar 

  • Agarwal V, Bell GW, Nam J, Bartel DP (2015) Predicting effective microRNA target sites in mammalian mRNAs. Elife 4:1

    Article  Google Scholar 

  • Benelli M, Pescucci C, Marseglia G, Severgnini M, Torricelli F, Magi A (2012) Discovering chimeric transcripts in paired-end RNA-seq data by using EricScript. Bioinformatics 28:3232–3239

    Article  CAS  PubMed  Google Scholar 

  • Bera SK, Kamdar JH, Kasundra SV, Dash P, Maurya AK, Jasani MD, Chandrashekar AB, Manivannan N, Vasanthi RP, Dobariya KL, Pandey MK, Janila P, Radhakrishnan T, Varshney RK (2018) Improving oil quality by altering levels of fatty acids through marker-assisted selection of ahfad2 alleles in peanut (Arachis hypogaea L.). Euphytica 214:162

    Article  Google Scholar 

  • Bonnet E, He Y, Billiau K, Van de Peer Y (2010) TAPIR, a web server for the prediction of plant microRNA targets, including target mimics. Bioinformatics 26:1566–1568

    Article  CAS  PubMed  Google Scholar 

  • Chen XT, Xu YZ, Zhao D, Chen T, Gu CX, Yu GX, Chen K, Zhong Y, He J, Liu SM, Nie YQ, Yang H (2018) LncRNA-AK012226 Is involved in fat accumulation in db/db mice fatty liver and non-alcoholic fatty liver disease cell model. Front Pharmacol 9:888

    Article  PubMed  PubMed Central  Google Scholar 

  • Connor WE (2000) Importance of n-3 fatty acids in health and disease. Am J Clin Nutr 71:171S-175S

    Article  CAS  PubMed  Google Scholar 

  • Costa FF (2005) Non-coding RNAs: new players in eukaryotic biology. Gene 357:83–94

    Article  CAS  PubMed  Google Scholar 

  • Dar AA, Choudhury AR, Kancharla PK, Arumugam N (2017) The FAD2 gene in plants: occurrence, regulation, and role. Front Plant Sci 8:1789

    Article  PubMed  PubMed Central  Google Scholar 

  • Debat HJ, Ducasse DA (2014) Plant microRNAs: recent advances and future challenges. Plant Mol Biol Rep 32:1257–1269

    Article  CAS  Google Scholar 

  • Derrien T, Johnson R, Bussotti G, Tanzer A, Djebali S, Tilgner H, Guernec G, Martin D, Merkel A, Knowles DG, Lagarde J, Veeravalli L, Ruan XA, Ruan YJ, Lassmann T, Carninci P, Brown JB, Lipovich L, Gonzalez JM, Thomas M, Davis CA, Shiekhattar R, Gingeras TR, Hubbard TJ, Notredame C, Harrow J, Guigó R (2012) The GENCODE v7 catalog of human long noncoding RNAs: analysis of their gene structure, evolution, and expression. Genome Res 22:1775–1789

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Dou C, Cao Z, Yang B, Ding N, Hou TY, Luo F, Kang F, Li JM, Yang XC, Jiang H, Xiang JY, Quan HY, Xu JZ, Dong SW (2016) Changing expression profiles of lncRNAs, mRNAs, circRNAs and miRNAs during osteoclastogenesis. Sci Rep 6:21499

  • Elahi N, Duncan RW, Stasolla C (2015) Decreased seed oil production in FUSCA3 Brassica napus mutant plants. Plant Physiol Biochem 96:222–230

    Article  CAS  PubMed  Google Scholar 

  • Elahi N, Duncan RW, Stasolla C (2016) Modification of oil and glucosinolate content in canola seeds with altered expression of Brassica napus LEAFY COTYLEDON1. Plant Physiol Biochem 100:52–63

    Article  CAS  PubMed  Google Scholar 

  • Evers M, Huttner M, Dueck A, Meister G, Engelmann JC (2015) miRA: adaptable novel miRNA identification in plants using small RNA sequencing data. BMC Bioinform 16:370

    Article  Google Scholar 

  • Fahlgren N, Carrington JC (2010) MiRNA target prediction in plants. Methods Mol Biol 592:51–57

    Article  CAS  PubMed  Google Scholar 

  • Feshani AM, Mohammadi S, Frazier TP, Abbasi A, Abedini R, Farsad LK, Ehya F, Salekdeh GH, Mardi M (2012) Identification and validation of Asteraceae miRNAs by the expressed sequence tag analysis. Gene 493:253–259

    Article  CAS  Google Scholar 

  • Finn RD, Coggill P, Eberhardt RY, Eddy SR, Mistry J, Mitchell AL, Potter SC, Punta M, Qureshi M, Sangrador-Vegas A, Salazar GA, Tate J, Bateman A (2016) The Pfam protein families database: towards a more sustainable future. Nucl Acids Res 44:D279–D285

    Article  CAS  PubMed  Google Scholar 

  • Flórez-Zapata NM, Reyes-Valdés MH, Martínez O (2016) Long non-coding RNAs are major contributors to transcriptome changes in sunflower meiocytes with different recombination rates. BMC Genomics 17:490

    Article  PubMed  PubMed Central  Google Scholar 

  • Gang HX, Li RH, Zhao YM, Liu GF, Chen S, Jiang J (2019) Loss of GLK1 transcription factor function reveals new insights in chlorophyll biosynthesis and chloroplast development. J Exp Bot 70:3125–3138

    Article  CAS  PubMed  Google Scholar 

  • Ge W, Zhang Y, Cheng Z, Hou D, Li X, Gao J (2017) Main regulatory pathways, key genes and microRNAs involved in flower formation and development of moso bamboo (Phyllostachys edulis). Plant Biotechnol J 15:82–96

    Article  CAS  PubMed  Google Scholar 

  • Ghildiyal M, Zamore PD (2009) Small silencing RNAs: an expanding universe. Nat Rev Genet 10:94–108

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Giacomelli JI, Weigel D, Chan RL, Manavella PA (2012) Role of recently evolved miRNA regulation of sunflower HaWRKY6 in response to temperature damage. New Phytol 195:766–773

    Article  CAS  PubMed  Google Scholar 

  • Gil M, Vega T, Felitti S, Picardi L, Balzergue S, Nestares G (2018) Characterization of non-target-site mechanisms in imidazolinone-resistant sunflower by RNA-seq. Helia 41(69):267–278

    Article  Google Scholar 

  • Gomes AQ, Nolasco S, Soares H (2013) Non-coding RNAs: multi-tasking molecules in the cell. Int J Mol Sci 14:16010–16039

    Article  PubMed  PubMed Central  Google Scholar 

  • Guo SC, Zuo YC, Zhang YF, Wu CY, Su WX, Jin W, Yu HF, An YL, Li QZ (2017) Large-scale transcriptome comparison of sunflower genes responsive to Verticillium dahliae. BMC Genomics 18:42

    Article  PubMed  PubMed Central  Google Scholar 

  • Guttman M, Garber M, Levin JZ, Donaghey J, Robinson J, Adiconis X, Fan L, Koziol MJ, Gnirke A, Nusbaum C, Rinn JL, Lander ES, Regev A (2010) Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Nat Biotechnol 28:503–510

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Huang JQ, Zhang T, Zhang QX, Chen M, Wang ZJ, Zheng BS, Xia GH, Yang XY, Huang CY, Huang YJ (2016) The mechanism of high contents of oil and oleic acid revealed by transcriptomic and lipidomic analysis during embryogenesis in Carya cathayensis Sarg. BMC Genomics 17:113

    Article  PubMed  PubMed Central  Google Scholar 

  • Ibáñez-Salazar A, Rosales-Mendoza S, Rocha-Uribe A, Ramírez-Alonso JI, Lara-Hernández I, Hernández-Torres A, Paz-Maldonado LM, Silva-Ramírez AS, Bañuelos-Hernández B, Martínez-Salgado JL, Soria-Guerra RE (2014) Over-expression of DOF-type transcription factor increases lipid production in Chlamydomonas reinhardtii. J Biotechnol 184:27–38

    Article  PubMed  Google Scholar 

  • Irene GT, Mónica VC, Rafael G, Penny WK, Enrique MF (2015) Sunflower (Helianthus annuus) fatty acid synthase complex: enoyl-[acyl carrier protein]-reductase genes. Planta 241:43–56

    Article  Google Scholar 

  • Irene GT, Mónica VC, Rosario S, Rafael G, Penny WK, Enrique MF (2016) Sunflower (Helianthus annuus) fatty acid synthase complex: β-hydroxyacyl-[acyl carrier protein] dehydratase genes. Planta 243:397–410

    Article  Google Scholar 

  • Islam N, Bates PD, Maria John KM, Krishnan HB, Zhang ZJ, Luthria DL, Natarajan SS (2019) Quantitative proteomic analysis of low linolenic acid transgenic soybean reveals perturbations of fatty acid metabolic pathways. Proteomics 19:1800379

    Article  Google Scholar 

  • Jessen D, Roth C, Wiermer M, Fulda M (2015) Two activities of long-chain acyl-coenzyme a synthetase are involved in lipid trafficking between the endoplasmic reticulum and the plastid in arabidopsis. Plant Physiol 167:351–366

    Article  CAS  PubMed  Google Scholar 

  • Jha JK, Sinha S, Maiti MK, Basu A, Mukhopadhyay UK, Sen SK (2007) Functional expression of an acyl carrier protein (ACP) from Azospirillum brasilense alters fatty acid profiles in Escherichia coli and Brassica juncea. Plant Physiol Biochem 45:490–500

    Article  CAS  PubMed  Google Scholar 

  • John B, Enright AJ, Aravin A, Tuschl T, Sander C, Marks DS (2004) Human microRNA targets. PLoS Biol 2:1862–1879

    Article  CAS  Google Scholar 

  • Khaksefidi R, Mirlohi S, Khalaji F, Fakhari Z, Shiran B, Fallahi H, Rafiei F, Budak H, Ebrahimie E (2015) Differential expression of seven conserved microRNAs in response to abiotic stress and their regulatory network in Helianthus annuus. Front Plant Sci 6:741

    Google Scholar 

  • Kim D, Langmead B, Salzberg SL (2015) HISAT: a fast spliced aligner with low memory requirements. Nat Methods 12:357–360

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kivioja T, Vähärautio A, Karlsson K, Bonke M, Enge M, Linnarsson S, Taipale J (2011) Counting absolute numbers of molecules using unique molecular identifiers. Nat Methods 9:72–74

    Article  PubMed  Google Scholar 

  • Kong L, Zhang Y, Ye ZQ, Liu XQ, Zhao SQ, Wei L, Gao G (2007) CPC: assess the protein-coding potential of transcripts using sequence features and support vector machine. Nucleic Acids Res 35:W345–W349

    Article  PubMed  PubMed Central  Google Scholar 

  • Langmead B, Salzberg SL (2012) Fast gapped-read alignment with Bowtie 2. Nat Methods 9:357–359

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10:R25

    Article  PubMed  PubMed Central  Google Scholar 

  • Li B, Dewey CN (2011) RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinform 12:323

    Article  CAS  Google Scholar 

  • Li RQ, Li YR, Kristiansen K, Wang J (2008) SOAP: short oligonucleotide alignment program. Bioinformatics 24:713–714

    Article  CAS  PubMed  Google Scholar 

  • Li W, Cui X, Meng Z, Huang X, Xie Q, Wu H, Jin H, Zhang D, Liang W (2012) Transcriptional regulation of arabidopsis MIR168a and ARGONAUTE1 homeostasis in abscisic acid and abiotic stress responses. Plant Physiol 158:1279–1292

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Li XY, Ao JP, Wu J (2017) Systematic identification and comparison of expressed profiles of lncRNAs and circRNAs with associated co-expression and ceRNA networks in mouse germline stem cells. Oncotarget 8:26573–26590

    Article  PubMed  PubMed Central  Google Scholar 

  • Liang CB, Wang WJ, Wang J, Ma J, Li C, Zhou F, Zhang SQ, Yu Y, Zhang LG, Li WZ, Huang XT (2017) Identification of differentially expressed genes in sunflower (Helianthus annuus) leaves and roots under drought stress by RNA sequencing. Bot Stud 58:42

    Article  PubMed  PubMed Central  Google Scholar 

  • Liu TT, Zhu DM, Chen W, Deng W, He H, He GM, Bai BY, Qi YJ, Chen RS, Deng XW (2013) A global identification and analysis of small nucleolar RNAs and possible intermediate-sized non-coding RNAs in Oryza sativa. Mol Plant 6:830–846

    Article  CAS  PubMed  Google Scholar 

  • Liu X, Hao LL, Li DY, Zhu LH, Hu SN (2015) Long non-coding RNAs and their biological roles in plants. Genom Proteom Bioinform 13:137–147

    Article  CAS  Google Scholar 

  • Long WH, Hu ML, Gao JQ, Chen S, Zhang JF, Cheng L, Pu HM (2018) Identification and functional analysis of two new mutant BnFAD2 alleles that confer elevated oleic acid content in rapeseed. Front Genet 9:399–419

    Article  PubMed  PubMed Central  Google Scholar 

  • Ma LN, Bajic VB, Zhang Z (2013) On the classification of long non-coding RNAs. RNA Biol 10:924–933

    Article  CAS  PubMed Central  Google Scholar 

  • Maeo K, Tokuda T, Ayame A, Mitsui N, Kawai T, Tsukagoshi H, Ishiguro S, Nakamura K (2009) An AP2-type transcription factor, WRINKLED1, of Arabidopsis thaliana binds to the AW-box sequence conserved among proximal upstream regions of genes involved in fatty acid synthesis. Plant J 60:476–487

    Article  CAS  PubMed  Google Scholar 

  • Mattick JS, Makunin IV (2006) Non-coding RNA. Hum Mol Genet 15:R17–R29

    Article  CAS  PubMed  Google Scholar 

  • Meng XW, Zhang PJ, Chen Q, Wang JJ, Chen M (2018) Identification and characterization of ncRNA-associated ceRNA networks in Arabidopsis leaf development. BMC Genomics 19:607

    Article  PubMed  PubMed Central  Google Scholar 

  • Mounts TL, Warner K, List GR, Kleiman R, Fehr WR, Hammond EG, Wilcox JR (1988) Effect of altered fatty acid composition on soybean oil stability. J Am Oil Chem Soc 65:624–628

    Article  CAS  Google Scholar 

  • Nawrocki EP, Eddy SR (2013) Infernal 1.1: 100-fold faster RNA homology searches. Bioinformatics 29:2933–2935

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ozseyhan ME, Li PC, Na GN, Li ZJ, Wang CL, Lu CF (2018) Improved fatty acid profiles in seeds of Camelina sativa by artificial microRNA mediated FATB gene suppression. Biochem Biophys Res Commun 503:621–624

    Article  CAS  PubMed  Google Scholar 

  • Pop LA, Puscas E, Pileczki V, Cojocneanu-Petric R, Braicu C, Achimas-Cadariu P, Berindan-Neagoe I (2014) Quality control of Ion Torrent sequencing library. Cancer Biomark 14:93–101

    Article  PubMed  Google Scholar 

  • Salmena L, Poliseno L, Tay Y, Kats L, Pandolfi PP (2011) A ceRNA hypothesis: the rosetta stone of a hidden RNA language. Cell 146:353–358

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Shen SH, Park JW, Lu ZX, Lin L, Henry MD, Wu YN, Zhou Q, Xing Y (2014) rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data. Proc Natl Acad Sci USA 111:E5593–E5601

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sood A, Chauhan RS (2015) Regulation of FA and TAG biosynthesis pathway genes in endosperms and embryos of high and low oil content genotypes of Jatropha curcas L. Plant Physiol Biochem 94:253–267

    Article  CAS  PubMed  Google Scholar 

  • Sujatha M, Ulaganathan K, Bhanu BD, Soni PK (2018) RNA-seq data of control and powdery mildew pathogen (Golovinomyces orontii) treated transcriptomes of Helianthus niveus. Data Brief 7:210–217

    Article  Google Scholar 

  • Sun L, Luo H, Bu D, Zhao G, Yu K, Zhang C, Liu Y, Chen R, Zhao Y (2013) Utilizing sequence intrinsic composition to classify protein-coding and long non-coding transcripts. Nucl Acids Res 41:e166

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Tu CF, Wu MH, Li GY (2013) The interaction between lncRNA and microRNA contributes to tumor. Chin J Biochem Mol Biol 29:1029–1034

    CAS  Google Scholar 

  • Wang LK, Feng ZX, Wang X, Wang XW, Zhang XG (2010) DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics 26:136–138

    Article  PubMed  Google Scholar 

  • Wang P, Ma LL, Li Y, Wang SA, Li LF, Yang RT (2017) Transcriptome analysis reveals sunflower cytochrome P450 CYP93A1 responses to high salinity treatment at the seedling stage. Genes Genomics 39:581–591

    Article  CAS  Google Scholar 

  • Wu HJ, Ma YK, Chen T, Wang M, Wang XJ (2012) PsRobot: a web-based plant small RNA meta-analysis toolbox. Nucleic Acids Res 40:W22–W28

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Xu J, Li YS, Lu JP, Pan T, Ding N, Wang ZS, Shao TT, Zhang JW, Wang LH, Li X (2015) The mRNA related ceRNA-ceRNA landscape and significance across 20 major cancer types. Nucleic Acids Res 43:8169–8182

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Xu J, Feng L, Han ZJ, Li YS, Wu AW, Shao TT, Ding N, Li LL, Deng W, Di XB, Wang J, Zhang LF, Li X, Zhang KT, Cheng SJ (2016) Extensive ceRNA-ceRNA interaction networks mediated by miRNAs regulate development in multiple rhesus tissues. Nucleic Acids Res 44:9438–9451

    CAS  PubMed  PubMed Central  Google Scholar 

  • Yu HF, Han PA, Li MN, Chen F, Guo SC, Li SP, Zhang YF, Zhao JJ, Yan MX (2018) Transcriptome analysis of oleic acid formation of sunflower via RNA-seq technology. Chin J Oil Crop Sci 40:769–776

    Google Scholar 

  • Yuan CH, Meng XW, Li X, Illing N, Ingle RA, Wang JJ, Chen M (2017) PceRBase: a database of plant competing endogenous RNA. Nucleic Acids Res 45:D1009–D1014

    Article  CAS  PubMed  Google Scholar 

  • Zhou R, Wang Q, Jiang F, Cao X, Sun M, Liu M, Wu Z (2016) Identification of miRNAs and their targets in wild tomato at moderately and acutely elevated temperatures by high-throughput sequencing and degradome analysis. Sci Rep 6:33777

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhou F, Liu Y, Liang CB, Wang WJ, Li C, Guo YL, Ma J, Yu Y, Fan LJ, Yao YB, Zhao DS, Liu XM, Huang XT (2018) Construction of a high-density genetic linkage map and QTL mapping of oleic acid content and three agronomic traits in sunflower (Helianthus annuus L.) using specific-locus amplified fragment sequencing (SLAF-seq). Breed Sci 68:596–605

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhu L, Cheng JL, Luo B, Feng SX, Lin JS, Wang SB, Cronan JE, Wang HH (2009) Functions of the clostridium acetobutylicium FabF and FabZ proteins in unsaturated fatty acid biosynthesis. BMC Microbiol 9:119

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This research was funded by Heilongjiang Academy of Agricultural Sciences Innovation Fund of China, grant number 2020FJZX005, 2019YYYF012, and National Characteristic Oil Plants Industry Technology System, grant number CARS-14. We thank Institute of Field and Vegetable Crops (Novi Sad, Serbia) for providing high oleic acid sunflower materials “L-1-OL-1”.

Funding

This research was funded by Heilongjiang Academy of Agricultural Sciences Innovation Fund of China, grant number 2020FJZX005, 2019YYYF012, and National Characteristic Oil Plants Industry Technology System, grant number CARS-14.

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11738_2021_3259_MOESM1_ESM.rar

Supplementary file1 Fig. S1 The length distribution of sRNAs in each sample. Table S1 The mRNAs, lncRNAs and miRNAs found. Table S2 The differentially expressed mRNAs, lncRNAs and miRNAs. Table S3 The GO analysis of mRNAs. Table S4 The KEGG analysis of mRNAs. Table S5 DEGs riched in fatty acid metabolism. Table S6 Transcription factors related to lipid metabolism. Table S7 The GO analysis of lncRNAs and miRNAs. Table S8 The KEGG analysis of lncRNAs and miRNAs. Table S9 The ceRNA network related lncRNAs and mRNAs. Table S10 The lipid metabolism related KEGG network (RAR 50434 kb)

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Liu, Y., Zhou, F., Huang, X. et al. Identification and integrated analysis of mRNAs, lncRNAs, and microRNAs of developing seeds in high oleic acid sunflower (Helianthus annuus L.). Acta Physiol Plant 43, 85 (2021). https://doi.org/10.1007/s11738-021-03259-5

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