فراواکاوی داده های RNA-seq گیاه دارویی پروانش (Catharanthus roseus) تحت برخی تنش های زیستی و غیر زیستی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری بیوتکنولوژی کشاورزی، گروه ا صلاح نباتات و بیوتکنولوژی، دانشکده کشاورزی، دانشگاه شهرکرد، شهرکرد، ایران

2 استاد، گروه بیوتکنولوژی و اصلاح‌نباتات، دانشکده کشاورزی، دانشگاه شهرکرد، شهرکرد ، ایران

3 استادیار ، گروه اصلاح نباتات و بیوتکنولوژی کشاورزی ، دانشکده کشاورزی ، دانشگاه شهرکرد ، شهرکرد ، ایران.

4 استاد، گروه بیوتکنولوژی، دانشکده کشاورزی، دانشگاه شیراز، شیراز ، ایران.

5 دانشیار، آزمایشگاه تحقیقات سرطان، دانشکده پزشکی آدلاید، دانشگاه آدلاید، آدلاید، استرالیای جنوبی، استرالیا.

10.22103/jab.2024.22497.1523

چکیده

هدف: اهداف مهندسی ژنتیک و متابولیک را می‏توان با درک فرآیندهای مولکولی پاسخ به تنش به میزان زیادی محقق کرد. پژوهشگران می‏توانند از طریق مطالعات ترنسکریپتوم به داده‏های فراوانی در این خصوص دسترسی پیدا کنند. استفاده از روش‌های آماری پیشرفته مانند فراواکاوی برای ادغام داده‌های بسیاری از منابع، روش جدیدی برای یافتن ژن‌های با بیان متفاوت (DEG) ، برای غلبه بر پیچیدگی زیستی و ارائه نتایج دقیق‌تر ارائه می‌دهد. مطالعه فعلی از فراواکاوی داده‌های بیانی RNA-seq گیاه پروانش برای کشف DEGهای غنی‏سازی شده در پاسخ به عوامل تنش‌زا و تولید متابولیت‌های ثانویه مهم استفاده کرد.
مواد و روش‏ها: داده‏های RNA-seq از پایگاه داده EMBL-EBIدریافت و پس از پیش پردازش، نقشه‏یابی خوانش‏های با کیفیت بر روی ژنوم مرجع پروانش صورت گرفت. تغییرات بیان ژن‏ها برای هر مجموعه داده، بررسی و سپس برای فراواکاوی استفاده شد. ژن‎های با بیان متفاوت و معنی‏دار در پاسخ به تنش‏های زیستی و غیرزیستی ، از نظر عمکرد زیستی و مسیرهای زیستی درگیر بررسی شدند و تجزیه و تحلیل هم‏بیانی انجام شد و در نهایت ژن‏های کلیدی و هاب در پاسخ به تنش و مسیر بیوسنتزی تولید متابولیت‏های مهم ترپنوئید ایندول آلکالوئیدها ((TIAs)Terpenoid Indole Alkaloids ) تعیین گردید.
نتایج: یافته‌های فراواکاوی، 772 ژن با بیان متفاوت دارای Log2FC≥|1 (Log2 Fold Change) و FDR≤0.05 (FalseDiscovery Rate) را شناسایی کرد که 305 و 467 ژن از این ژن‌ها به ترتیب دارای بیان بالا و پایین تحت تنش بودند. در این میان، فراواکاوی امکان شناسایی 27 ژن را فراهم نمود که در آنالیزهای انفرادی به عنوان DEG شناسایی نشده بودند. نتایج غنی‌سازی عملکردی DEGها اهمیت حیاتی آنها را در فرآیندهای متابولیک، پاسخ به محرک‌ها و فرآیندهای سلولی نشان داد. آنها همچنین در مسیرهای متعددی مانند مسیر سیگنالینگ ، پروتئین کینازهای فعال شده با میتوژن ((MAPK)Mitogen activated protein kinases)، بیوسنتز متابولیت‏های ثانویه، انتقال هورمون‏های گیاهی و مسیرهای متابولیک تحت تنش اهمیت معنی‏داری داشتند. از طریق تجزیه و تحلیل شبکه هم‌بیانی، ژن‌های هاب پاسخ‌دهنده به تنش و مرتبط با مسیرهای بیوسنتز ترپنوئید ایندول آلکالوئیدها (TIA) یافت شدند که می‏توانند ژن‌های بالقوه‌ای در سنتز ترکیبات دارویی منحصر به فرد گیاه باشند.
نتیجه‏گیری:
در این تحقیق، با بررسی پاسخ‌های مولکولی گیاه پروانش تحت تنش‌های مختلف با استفاده از رویکردهای فراواکاوی و زیست‌شناسی سامانه‌ای ، ژن‌های کلیدی و جدید شناسایی شدند. این ژن‌ها دارای توانایی بالقوه جهت استفاده به عنوان ژن‌های کاندید در پروژه‌های مهندسی ژنتیک و متابولیک بوده که به منظور افزایش توانایی گیاه در تولید متابولیت‌های درمانی در آینده به کار گرفته شوند.

کلیدواژه‌ها


عنوان مقاله [English]

Meta-analysis of RNA-seq data of the medicinal plant Catharanthus roseus under some biotic and abiotic stresses

نویسندگان [English]

  • Seyede Nasim Tabatabeipour 1
  • Behrouz Shiran 2
  • Rudabeh Ravash 3
  • Ali Niazi 4
  • Esmaeil Ebrahimie 5
1 Department of Plant Breeding and Biotechnology, Faculty of Agriculture, Shahrekord University
2 Professor, Department of Plant Breeding and Biotechnology, Faculty of Agriculture, Shahrekord University, Shahrekord, Iran
3 Assistant Professor, Department of Plant Breeding and Biotechnology, Faculty of Agriculture, Shahrekord University, Shahrekod, Iran.
4 Professor, Department of Biotechnology, Faculty of Agriculture, University of Shiraz, Shiraz, Iran
5 Associate Professor, Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia.
چکیده [English]

Objective
The objectives of genetic and metabolic engineering can be greatly advanced through comprehending the molecular processes of the stress response. Researchers may access an abundance of data through transcriptome studies. Using advanced statistical methods such as meta-analysis to integrate data from many sources offers a new way to find differentially expressed genes (DEGs), get beyond biological complexity, and provide more accurate results. The current work used transcriptome data from RNA-seq meta-analysis to uncover Catharanthus roseus DEGs in response to stressors and the production of important secondary metabolites.
Materials and methods
The EMBL-EBI database provided the RNA-seq data, which was then pre-processed and mapped quality reads using STAR software to the reference genome of C. roseus. Each data set's changes in gene expression were examined independently using the edgeR package, and the output from these analyses was then utilized for a meta-analysis with the use of the metaRNAseq program. Key genes in reaction to stress and pathways were finally examined, along with the biological function and biological pathways involved in the different and significant expression of these genes in response to stress. Co-expression analysis was carried out using the WGCNA software and hub genes associated with stress response and the production of important plant-related metabolites were found.
Results
The findings of the meta-analysis show that 772 genes with average expression log2FC≥|1 and FDR≤0.05 were found, and that 305 and 467 of these genes, respectively, had up- and downregulated expression under stress. Of these, only a meta-analysis enables the identification of 27 genes that were not identified as DEGs in individual analyses. The functional enrichment results of DEGs demonstrate their crucial importance in metabolic processes, response to stimuli, and cellular processes. They also lead multiple pathways, such as the MAPK signaling pathway, the biosynthesis of secondary metabolites, the transduction of plant hormones, and metabolic pathways under stress. Through co-expression network analysis, stress-responsive hubs genes and associated with the TIA biosynthesis pathways were found that may be potential genes involved in the synthesis of therapeutic compounds exclusive to plants.
Conclusions
In this study, we identified key and novel genes by investigating the molecular responses of C. roseus plant under various stresses using meta-analysis and systems biology approaches. These genes have the potential to be employed as candidate genes in genetic and metabolic engineering projects aimed at enhancing the plant's capability to produce therapeutic metabolites in the future.

کلیدواژه‌ها [English]

  • Catharanthus roseus
  • RNA-seq
  • Meta-analysis
  • Stress
  • Terpenoid Indole Alkaloids
عرب پور رق آبادی زهرا، محمدآبادی محمدرضا، خضری امین (1400) الگوی بیانی ژن  p32در بافت‏های ران، دست، راسته و چربی پشت بره کرمانی. مجله بیوتکنولوژی کشاورزی 13(4)، 200-183.
محمدآبادی محمدرضا، کرد محبوبه، نظری محمود (1397) مطالعه بیان ژن لپتین در بافت‏های مختلف گوسفند کرمانی با استفاده از.real time PCR  مجله بیوتکنولوژی کشاورزی 10(3)، 122-111.
References
Al-Khayri JM, Rashmi R, Toppo V, et al (2023) Plant secondary metabolites: the weapons for biotic stress management. Metabolites 13, 716-753.
Andrews S (2010) Fastqc - a quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/. Babraham Bioinforma http://www.bioinformatics.babraham.ac.uk/projects.
Arabpoor Raghabadi Z, Mohammadabadi M, Khezri A (2022) The expression pattern of p32 gene in femur, humeral muscle, back muscle and back fat tissues of Kermani lambs. Agric Biotech J 13, 183-200 (in Persian).
Araújo WL, Martins AO, Fernie AR, Tohge T (2014) 2-oxoglutarate: linking TCA cycle function with amino acid, glucosinolate, flavonoid, alkaloid, and gibberellin biosynthesis. Front Plant Sci 5, 552-558.
Bah SY, Forster T, Dickinson P, et al (2018) Meta-analysis identification of highly robust and differential immune-metabolic signatures of systemic host response to acute and latent tuberculosis in children and adults. Front Genet 9, 457-473.
Bairakdar MD, Tewari A, Truttmann MC (2023) A meta-analysis of RNA-seq studies to identify novel genes that regulate aging. Exp Gerontol 173, 1-34.
Balan B, Marra FP, Caruso T, Martinelli F (2018) Transcriptomic responses to biotic stresses in Malus x domestica: a meta-analysis study. Sci Rep 8, 1-12.
Bandehagh A, Taylor NL (2020) Can alternative metabolic pathways and shunts overcome salinity induced inhibition of central carbon metabolism in crops?. Front Plant Sci 11, 1072-1090.
Banothu V, Uma A (2022) Effect of Biotic and Abiotic Stresses on Plant Metabolic Pathways. In: Phenolic Compounds - Chemistry, Synthesis, Diversity, Non-Conventional Industrial, Pharmaceutical and Therapeutic Applications. Badria FA (ed). IntechOpen, London, UK, pp. 1-11.
Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for illumina sequence data. Bioinform 30, 2114-2120.
Buga AM, Docea AO, Albu C, et al (2019) Molecular and cellular stratagem of brain metastases associated with melanoma (review). Oncol Lett 17, 4170-4175.
Cavrak VV, Lettner N, Jamge S, et al (2014) How a retrotransposon exploits the plant’s heat stress response for its activation. PLoS Genet 10, 1-12.
Chen Y, Jiang Y, Chen Y, et al (2020) Uncovering candidate genes responsive to salt stress in Salix matsudana (Koidz) by transcriptomic analysis. PLoS One 15, 8-31.
Chin CH, Chen SH, Wu HH, et al (2014) Cytohubba: identifying hub objects and sub-networks from complex interactome. BMC Syst Biol 8, 4-11.
Conesa A, Götz S, García-Gómez JM, et al (2005) Blast2go: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinform 21, 3674-3676.
De Abreu Neto JB, Frei M (2016) Microarray meta-analysis focused on the response of genes involved in redox homeostasis to diverse abiotic stresses in rice. Front Plant Sci 6, 1-14.
De Planell-Saguer M, Schroeder DG, Rodicio MC, et al. (2009) Biochemical and genetic evidence for a role of IGHMBP2 in the translational machinery. Hum Mol Genet 18, 2115-2126.
Deelen J, Evans DS, Arking DE, et al. (2021) Publisher correction: a meta-analysis of genome-wide association studies identifies multiple longevity genes. Nat Commun 12, 1-2. 
Dhyani P, Quispe C, Sharma E, et al. (2022) Anticancer potential of alkaloids: a key emphasis to colchicine, vinblastine, vincristine, vindesine, vinorelbine and vincamine. Cancer Cell Int 22, 1-20.
Distéfano AM, Valiñas MA, Scuffi D, et al. (2015) Phospholipase D δ knock-out mutants re tolerant to severe drought stress. Plant Signal Behav 10, 1-7.
Dobin A, Davis CA, Schlesinger F, et al. (2013) Star: ultrafast universal RNA-seq aligner. Bioinform 29, 15-21.
Gao C, Yang B, Zhang D, et al. (2016) Enhanced metabolic process to indole alkaloids in Clematis terniflora DC. after exposure to high level of UV-B irradiation followed by the dark. BMC Plant Biol 16, 1-15.
Guo J, Huang Z, Sun J, et al. (2021) Research progress and future development trends in medicinal plant transcriptomics. Front Plant Sci 12, 1-10.
Han G, Qiao Z, Li Y, et al. (2021) The roles of CCCH zinc-finger proteins in plant abiotic stress tolerance. Int J Mol Sci 22, 15-35.
Jia Y, Li X, Liu Q, et al. (2020) Physiological and transcriptomic analyses reveal the roles of secondary metabolism in the adaptive responses of stylosanthes to manganese toxicity. BMC Genom 21, 1-17.
Kanehisa M, Goto S (2000) Kegg: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28, 27-30.
Langfelder P, Horvath S (2008) Wgcna: an R package for weighted correlation network analysis. BMC Bioinform 9, 1-13.
Li S, Liu Z, Jia Y, et al. (2019) Analysis of metabolic pathways related to fertility restoration and identification of fertility candidate genes associated with Aegilops kotschyi cytoplasm in wheat (Triticum aestivum L.). BMC Plant Biol 19, 1-17.
Li Y, Yang Z, Zhang Y, et al. (2022) The roles of HD-ZIP proteins in plant abiotic stress tolerance. Front Plant Sci 13, 1-19.
Liang SC, Hartwig B, Perera P, et al. (2015) Kicking against the PRCs – a domesticated transposase antagonises silencing mediated by Polycomb group proteins and is an accessory component of Polycomb repressive complex 2. PLoS Genet 11, 1-26.
Liu H, Shi J, Wu M, Xu D (2021) The application and future prospect of RNA-seq technology in chinese medicinal plants. J Appl Res Med Aromat Plants 24, 1-17.
Liu J, Gao F, Ren J, et al. (2017) A novel AP2/ERF transcription factor CR1 regulates the accumulation of vindoline and serpentine in Catharanthus roseus. Front Plant Sci 8, 1-11.
Lv DW, Zhen S, Zhu GR, et al. (2016) High-throughput sequencing reveals H2O2 stress-associated micro RNAs and a potential regulatory network in Brachypodium distachyon seedlings. Front Plant Sci 7, 1567-1587.
Mohammadabadi M, Masoudzadeh SH, Khezri A, et al. (2021) Fennel (Foeniculum vulgare) seed powder increases delta-like non-canonical notch ligand 1 gene expression in testis, liver, and humeral muscle tissues of growing lambs. Heliyon 7(12), e08542.
Mohammadabadi MR, Kord M, Nazari M (2018) Studying expression of leptin gene in different tissues of Kermani sheep using Real Time PCR. Agric Biotech J 10, 111-122 (in Persian).
Molina-Hidalgo FJ, Medina-Puche L, Cañete-Gómez C, et al. (2017) The fruit-specific transcription factor FaDOF2 regulates the production of eugenol in ripe fruit receptacles. J Exp Bot 68, 4529-4543.
Murray SL, Ingle RA, Petersen LN, Denby KJ (2007) Basal resistance against Pseudomonas syringae in arabidopsis involves WRKY53 and a protein with homology to a nematode resistance protein. Mol Plant-Microbe Interact 20, 1431-1438.
Pan Y jie, Lin Y chao, Yu B fan, et al. (2018) Transcriptomics comparison reveals the diversity of ethylene and methyl-jasmonate in roles of TIA metabolism in Catharanthus roseus. BMC Genom 19, 1-14.
Pathania S, Bagler G, Ahuja PS (2016) Differential network analysis reveals evolutionary complexity in secondary metabolism of Rauvolfia serpentina over Catharanthus roseus. Front Plant Sci 7, 1-17.
Paul I, Poddar Sarkar M, Bhadoria PBS (2022) Floral secondary metabolites in context of biotic and abiotic stress factors. Chemoecology 32, 49-68.
Rau A, Marot G, Jaffrézic F (2014) Differential meta-analysis of RNA-seq data from multiple studies. BMC Bioinf 15, 1-14.
Robinson M, McCarth D (2010) Edger: differential expression analysis of digital gene expression data. Bioconductor Fhcrc Org 1-76.
Shahsavari M, Mohammadabadi M, Khezri A, et al. (2021) Correlation between insulin-like growth factor 1 gene expression and fennel (Foeniculum vulgare) seed powder consumption in muscle of sheep. Anim Biotechnol 34(4), 882-892.
Skirycz A, Jozefczuk S, Stobiecki M, et al. (2007) Transcription factor AtDOF4;2 affects phenylpropanoid metabolism in Arabidopsis thaliana. New Phytol 175, 425-438.
Soltani N, Firouzabadi FN, Shafeinia A, et al. (2022) De novo transcriptome assembly and differential expression analysis of Catharanthus roseus in response to salicylic acid. Sci Rep 12, 1-13.
Tahmasebi A, Ashrafi-Dehkordi E, Shahriari AG, et al. (2019) Integrative meta-analysis of transcriptomic responses to abiotic stress in cotton. Prog Biophys Mol Biol 146, 112-122.
Thalmann M, Santelia D (2017) Starch as a determinant of plant fitness under abiotic stress. New Phytol 214, 943-951.
Verma M, Ghangal R, Sharma R, et al. (2014) Transcriptome analysis of Catharanthus roseus for gene discovery and expression profiling. PLoS One 9, 7-18.
Wang D, Guo Y, Wu C, et al. (2008) Genome-wide analysis of CCCH zinc finger family in Arabidopsis and rice. BMC Genom 9, 44-64.
Wang H, Liu C, Ma P, et al. (2018) Functional characterization of cytosolic pyruvate phosphate dikinase gene (MecyPPDK) and promoter (MecyPPDKP) of cassava in response to abiotic stress in transgenic tobacco. Crop Sci 58, 2002-2009.
Wu W, Howard D, Sibille E, French L (2021) Differential and spatial expression meta-analysis of genes identified in genome-wide association studies of depression. Transl Psychiatry 11, 1-12.
Xia C, Hong L, Yang Y, et al. (2019) Protein changes in response to lead stress of lead-tolerant and lead-sensitive industrial hemp using swath technology. Genes 10, 1-16.
Yadav S, Rathore MS, Mishra A (2020) The pyruvate-phosphate dikinase (C4-smppdk) gene from suaeda monoica enhances photosynthesis, carbon assimilation, and abiotic stress tolerance in a C3 plant under elevated CO2 conditions. Front Plant Sci 11, 345-367.
Yeshi K, Crayn D, Ritmejerytė E, Wangchuk P (2022) Plant secondary metabolites produced in response to abiotic stresses has potential application in pharmaceutical product development. Mol 27, 750-757.
Zhang Y, Lin Z, Wang M, Lin H (2018) Selective usage of isozymes for stress response. ACS Chem Biol 13, 3059-3064.
Zhang Y, Parmigiani G, Johnson WE (2020) Combat-seq: batch effect adjustment for RNA-seq count data. NAR Genom Bioinform 2, 1-21.
Zhu Y, Liu Q, Xu W, et al. (2019) De novo assembly and discovery of genes that involved in drought tolerance in the common vetch. Int J Mol Sci 20, 1-17.
Zou X, Sun H (2023) Dof transcription factors: specific regulators of plant biological processes. Front Plant Sci 14, 1-13.