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2000
Volume 26, Issue 3
  • ISSN: 1389-2029
  • E-ISSN: 1875-5488

Abstract

Introduction

Microtia, a prevalent congenital maxillofacial deformity, significantly impacts the physical and psychological health of children. Its etiology, especially in non-syndromic cases, remains a complex and partially understood domain, complicating etiological treatment. Recent studies pointed to a genetic predisposition in non-syndromic microtia, yet research on susceptible or pathogenic genes is limited.

Objectives

This study focused on identifying key biomarker genes in microtia cartilage to elucidate pathogenesis and assist in prenatal diagnosis.

Methods

We first collated two bulk transcriptome datasets from the GEO database, followed by functional enrichment analysis and Weighted Gene Co-expression Network Analysis (WGCNA) to pinpoint differentially expressed genes (DEGs) and gene modules. The subsequent intersection of DEGs with WGCNA modules, aided by support vector machine-recursive feature elimination (SVM-RFE) and protein-protein interaction (PPI) networks, predicted potential susceptibility genes for microtia. Finally, we integrated bulk RNA sequencing with single-cell data the “scissor” R package and further validated it with Real-time PCR and immunofluorescence.

Results

We identified as a prominent biomarker for microtia, evidenced by its significant upregulation in microtia cartilage.

Conclusion

Our findings implicate in microtia development and suggest its role in chondrocyte maturation and differentiation through Notch signaling pathway activation, shedding light on the potential pathogenesis of microtia.

© 2025 Bentham Science Publishers
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2025-12-08

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References

  1. LuquettiD.V. HeikeC.L. HingA.V. CunninghamM.L. CoxT.C. Microtia: Epidemiology and genetics.Am. J. Med. Genet. A.2012158A112413910.1002/ajmg.a.3435222106030
     [Google Scholar]
  2. DengK. DaiL. YiL. DengC. LiX. ZhuJ. Epidemiologic characteristics and time trend in the prevalence of anotia and microtia in China.Birth Defects Res. A Clin. Mol. Teratol.20161062889410.1002/bdra.2346226681129
     [Google Scholar]
  3. LiD. ChinW. WuJ. ZhangQ. XuF. XuZ. ZhangR. Psychosocial outcomes among microtia patients of different ages and genders before ear reconstruction.Aesthetic Plast. Surg.201034557057610.1007/s00266‑010‑9502‑120397014
     [Google Scholar]
  4. CollettB.R. ChapmanK. WallaceE.R. KinterS.L. HeikeC.L. SpeltzM.L. WerlerM. Speech, language, and communication skills of adolescents with Craniofacial Microsomia.Am. J. Speech Lang. Pathol.20192841571158110.1044/2019_AJSLP‑19‑008931580699
     [Google Scholar]
  5. NuyenB.A. KandathilC.K. SaltychevM. FirminF. MostS.P. TruongM.T. The social perception of microtia and auricular reconstruction.Laryngoscope2021131119520010.1002/lary.2861932275329
     [Google Scholar]
  6. ZhangT. BulstrodeN. ChangK.W. ChoY.S. FrenzelH. JiangD. KesserB.W. SiegertR. TrigliaJ.M. International consensus recommendations on microtia, aural atresia and functional ear reconstruction.J. Int. Adv. Otol.201915220420810.5152/iao.2019.738331418720
     [Google Scholar]
  7. ZhaoR. DuP. SunH. YangL. LinP. Fetal microtia and FGFR2 polymorphism.Exp Ther Med201918138438810.3892/etm.2019.7568.
     [Google Scholar]
  8. MarkerP.C. SeungK. BlandA.E. RussellL.B. KingsleyD.M. Spectrum of Bmp5 mutations from germline mutagenesis experiments in mice.Genetics1997145243544310.1093/genetics/145.2.4359071596
     [Google Scholar]
  9. LiuW. WangQ. GuoY. LinL. YangQ. JiangH. Whole-genome sequencing identifies two novel rare mutations in BMP5 and BMP2 in monozygotic twins with microtia.J. Craniofac. Surg.2022332e212e21710.1097/SCS.000000000000768934183628
     [Google Scholar]
  10. PiceciF. MorlinoS. CastoriM. BuffoneE. De LucaA. GrammaticoP. GuidaV. Identification of a secondHOXA2 nonsense mutation in a family with autosomal dominant non‐syndromic microtia and distinctive ear morphology.Clin. Genet.201791577477910.1111/cge.1284527503514
     [Google Scholar]
  11. HaoS. JinL. LiC. WangH. ZhengF. MaD. ZhangT. Mutational analysis of GSC, HOXA2 and PRKRA in 106 Chinese patients with microtia.Int. J. Pediatr. Otorhinolaryngol.201793788210.1016/j.ijporl.2016.12.02628109504
     [Google Scholar]
  12. MaJ. ZhangY. YanZ. WuP. LiC. YangR. LuX. ChenX. HeA. FuY. MaD. TianW. ZhangT. Single‐cell transcriptomics reveals pathogenic dysregulation of previously unrecognised chondral stem/progenitor cells in children with microtia.Clin. Transl. Med.2022122e70210.1002/ctm2.70235184397
     [Google Scholar]
  13. HuminieckiŁ. Bulk and single-cell RNA sequencing elucidate the etiology of severe COVID-19.Int. J. Mol. Sci.2024256328010.3390/ijms2506328038542251
     [Google Scholar]
  14. RenY. WuR. LiC. LiuL. LiL. WengS. XuH. XingZ. ZhangY. WangL. LiuZ. HanX. Single-cell RNA sequencing integrated with bulk RNA sequencing analysis identifies a tumor immune microenvironment-related lncRNA signature in lung adenocarcinoma.BMC Biol.20242216910.1186/s12915‑024‑01866‑538519942
     [Google Scholar]
  15. ChenX. XuY. LiC. LuX. FuY. HuangQ. MaD. MaJ. ZhangT. Key genes identified in nonsyndromic microtia by the analysis of transcriptomics and proteomics.ACS Omega2022720169171692710.1021/acsomega.1c0705935647449
     [Google Scholar]
  16. WuT. HuE. XuS. ChenM. GuoP. DaiZ. FengT. ZhouL. TangW. ZhanL. FuX. LiuS. BoX. YuG. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data.Innovation20212310014110.1016/j.xinn.2021.10014134557778
     [Google Scholar]
  17. ZhangL. HeA. YinZ. YuZ. LuoX. LiuW. ZhangW. CaoY. LiuY. ZhouG. Regeneration of human-ear-shaped cartilage by co-culturing human microtia chondrocytes with BMSCs.Biomaterials201435184878488710.1016/j.biomaterials.2014.02.04324656731
     [Google Scholar]
  18. HeA. XiaH. XiaoK. WangT. LiuY. XueJ. LiD. TangS. LiuF. WangX. ZhangW. LiuW. CaoY. ZhouG. Cell yield, chondrogenic potential, and regenerated cartilage type of chondrocytes derived from ear, nasoseptal, and costal cartilage.J. Tissue Eng. Regen. Med.20181241123113210.1002/term.261329139602
     [Google Scholar]
  19. WuX. FuY. MaJ. LiC. HeA. ZhangT. LGR5 modulates differentiated phenotypes of chondrocytes through PI3K/AKT signaling pathway.Tissue Eng Regen Med202421579180710.1007/s13770‑024‑00645‑1.
     [Google Scholar]
  20. JiangT. LiuW. LvX. SunH. ZhangL. LiuY. ZhangW.J. CaoY. ZhouG. Potent in vitro chondrogenesis of CD105 enriched human adipose-derived stem cells.Biomaterials201031133564357110.1016/j.biomaterials.2010.01.05020153525
     [Google Scholar]
  21. HaoY. HaoS. Andersen-NissenE. MauckW.M.III ZhengS. ButlerA. LeeM.J. WilkA.J. DarbyC. ZagerM. HoffmanP. StoeckiusM. PapalexiE. MimitouE.P. JainJ. SrivastavaA. StuartT. FlemingL.M. YeungB. RogersA.J. McElrathJ.M. BlishC.A. GottardoR. SmibertP. SatijaR. Integrated analysis of multimodal single-cell data.Cell20211841335733587.e2910.1016/j.cell.2021.04.04834062119
     [Google Scholar]
  22. KorsunskyI. MillardN. FanJ. SlowikowskiK. ZhangF. WeiK. BaglaenkoY. BrennerM. LohP. RaychaudhuriS. Fast, sensitive and accurate integration of single-cell data with Harmony.Nat. Methods201916121289129610.1038/s41592‑019‑0619‑031740819
     [Google Scholar]
  23. SunD. GuanX. MoranA.E. WuL.Y. QianD.Z. SchedinP. DaiM.S. DanilovA.V. AlumkalJ.J. AdeyA.C. SpellmanP.T. XiaZ. Identifying phenotype-associated subpopulations by integrating bulk and single-cell sequencing data.Nat. Biotechnol.202240452753810.1038/s41587‑021‑01091‑334764492
     [Google Scholar]
  24. McNultyAL. VailTP. KrausVB. Chondrocyte transport and concentration of ascorbic acid is mediated by SVCT2.Biochim Biophys Acta2005171222122110.1016/j.bbamem.2005.04.009.
     [Google Scholar]
  25. SimpkinVL. MurrayDH. HallAP. HallAC. Bicarbonate-dependent pH(i) regulation by chondrocytes within the superficial zone of bovine articular cartilage.J Cell Physiol20072123600910.1002/jcp.21054.
     [Google Scholar]
  26. LiangS. ZhangJM. LvZT. ChengP. ZhuWT. ChenAM. Identification of Skt11-regulated genes in chondrocytes by integrated bioinformatics analysis.Gene201867734034810.1016/j.gene.2018.08.013.
     [Google Scholar]
  27. MaoD. JiangH. ZhangF. YangH. FangX. ZhangQ. ZhaoG. HDAC2 exacerbates rheumatoid arthritis progression via the IL-17-CCL7 signaling pathway.Environ Toxicol20233871743175510.1002/tox.23802.
     [Google Scholar]
  28. GanjiwaleA. KarthikK.V. RajalingamA. ShivashankarM. Recursive feature elimination-based biomarker identification for open neural tube defects.Curr. Genomics202223319520610.2174/138920292366622051116203836777008
     [Google Scholar]
  29. YangM. WuY. YangX. LiuT. ZhangY. ZhuoY. LuoY. ZhangN. Establishing a prediction model of severe acute mountain sickness using machine learning of support vector machine recursive feature elimination.Sci. Rep.2023131463310.1038/s41598‑023‑31797‑036944699
     [Google Scholar]
  30. SahranS. AlbashishD. AbdullahA. ShukorN.A. Hayati Md PauziS. Absolute cosine-based SVM-RFE feature selection method for prostate histopathological grading.Artif. Intell. Med.201887789010.1016/j.artmed.2018.04.00229680688
     [Google Scholar]
  31. TangD. ChenW. ZhangF. XuH. HouX. Prospective analysis of proteins carried in extracellular vesicles with clinical outcome in hepatocellular carcinoma.Curr. Genomics202223210911710.2174/138920292366622030412545836778976
     [Google Scholar]
  32. JinW. BrannanK.W. KapeliK. ParkS.S. TanH.Q. GosztylaM.L. MujumdarM. AhdoutJ. HenroidB. RothamelK. XiangJ.S. WongL. YeoG.W. HydR.A. HydRA: Deep-learning models for predicting RNA-binding capacity from protein interaction association context and protein sequence.Mol. Cell2023831425952611.e1110.1016/j.molcel.2023.06.01937421941
     [Google Scholar]
  33. PaikD.T. ChoS. TianL. ChangH.Y. WuJ.C. Single-cell RNA sequencing in cardiovascular development, disease and medicine.Nat. Rev. Cardiol.202017845747310.1038/s41569‑020‑0359‑y32231331
     [Google Scholar]
  34. WangT. WangL. ZhangL. LongY. ZhangY. HouZ. Single-cell RNA sequencing in orthopedic research.Bone Res.20231111010.1038/s41413‑023‑00245‑036828839
     [Google Scholar]
  35. CuiX. QinF. YuX. XiaoF. CaiG. SCISSOR™: A single-cell inferred site-specific omics resource for tumor microenvironment association study.NAR Cancer202133zcab03710.1093/narcan/zcab037.
     [Google Scholar]
  36. ChengM. XiongJ. LiuQ. ZhangC. LiK. WangX. ChenS. Integrating bulk and single-cell sequencing data to construct a Scissor+ dendritic cells prognostic model for predicting prognosis and immune responses in ESCC.Cancer Immunol. Immunother.20247369710.1007/s00262‑024‑03683‑938619620
     [Google Scholar]
  37. AsterJ.C. PearW.S. BlacklowS.C. The varied roles of notch in cancer.Annu Rev Pathol20171224527510.1146/annurev‑pathol‑052016‑100127.
     [Google Scholar]
  38. GuruharshaK.G. KankelM.W. Artavanis-TsakonasS. The Notch signalling system: Recent insights into the complexity of a conserved pathway.Nat. Rev. Genet.201213965466610.1038/nrg327222868267
     [Google Scholar]
  39. KohnA. RutkowskiTP. LiuZ. MirandoAJ. ZuscikMJ. O'KeefeRJ. HiltonMJ. Notch signaling controls chondrocyte hypertrophy via indirect regulation of Sox9.Bone Res201531502110.1038/boneres.2015.21.
     [Google Scholar]
  40. ShangX. WangJ. LuoZ. WangY. MorandiMM. MarymontJV. HiltonMJ. DongY. Notch signaling indirectly promotes chondrocyte hypertrophy via regulation of BMP signaling and cell cycle arrest.Sci Rep201662559410.1038/srep25594.
     [Google Scholar]
  41. ChenS. TaoJ. BaeY. JiangMM. BertinT. ChenY. YangT. LeeB. Notch gain of function inhibits chondrocyte differentiation via Rbpj-dependent suppression of Sox9.J Bone Miner Res20132836495910.1002/jbmr.1770.
     [Google Scholar]
  42. CaoH. YangP. LiuJ. ShaoY. LiH. LaiP. WangH. LiuA. GuoB. TangB. BaiX. LiK. MYL3 protects chondrocytes from senescence by inhibiting clathrin-mediated endocytosis and activating of Notch signaling.Nat Commun2023141619010.1038/s41467‑023‑41858‑7.
     [Google Scholar]
  43. LefebvreV. AngelozziM. HaseebA. SOX9 in cartilage development and disease.Curr. Opin. Cell Biol.201961394710.1016/j.ceb.2019.07.00831382142
     [Google Scholar]
  44. HaseebA. KcR. AngelozziM. de CharleroyC. RuxD. TowerR.J. YaoL. Pellegrino da SilvaR. PacificiM. QinL. LefebvreV. SOX9 keeps growth plates and articular cartilage healthy by inhibiting chondrocyte dedifferentiation/osteoblastic redifferentiation.Proc. Natl. Acad. Sci. USA20211188e201915211810.1073/pnas.201915211833597301
     [Google Scholar]
  45. SongH. ParkK.H. Regulation and function of SOX9 during cartilage development and regeneration.Semin. Cancer Biol.202067Pt 1122310.1016/j.semcancer.2020.04.00832380234
     [Google Scholar]
  46. ZhaoC. MatalongaJ. LancmanJ.J. LiuL. XiaoC. KumarS. GatesK.P. HeJ. GravesA. HuiskenJ. AzumaM. LuZ. ChenC. DingB.S. DongP.D.S. Regenerative failure of intrahepatic biliary cells in Alagille syndrome rescued by elevated Jagged/Notch/Sox9 signaling.Proc. Natl. Acad. Sci. USA202211950e220109711910.1073/pnas.220109711936469766
     [Google Scholar]
  47. WangW. FengY. AimaitiY. JinX. MaoX. LiD. TGFβ signaling controls intrahepatic bile duct development may through regulating the Jagged1‐Notch‐Sox9 signaling axis.J. Cell. Physiol.201823385780579110.1002/jcp.2630429194611
     [Google Scholar]
  48. GroganS.P. OleeT. HiraokaK. LotzM.K. Repression of chondrogenesis through binding of notch signaling proteins HES‐1 and HEY‐1 to N‐box domains in the COL2A1 enhancer site.Arthritis Rheum.20085892754276310.1002/art.2373018759300
     [Google Scholar]
  49. CooperF. SouilholC. HastonS. GrayS. BoswellK. GogolouA. FrithT.J.R. StavishD. JamesB.M. BoseD. DaleJ.K. TsakiridisA. Notch signalling influences cell fate decisions and HOX gene induction in axial progenitors.Development20241513dev.20209810.1242/dev.20209838223992
     [Google Scholar]
  50. ZhangY. AodengG. LiuP. SuW. ZhaoH. Effects of HOX transcript antisense intergenic RNA on the metastasis, epithelial-mesenchymal transition, and Notch signaling pathway in tongue cancer.Transl. Cancer Res.202110152052810.21037/tcr‑20‑345235116281
     [Google Scholar]
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JAG2: A Potential Biomarker for Microtia Identified by Integrated RNA Transcriptome Analysis
Curr. Genomics 26, 210 (2025); https://doi.org/10.2174/0113892029311725240911065539
/content/journals/cg/10.2174/0113892029311725240911065539
/content/journals/cg/10.2174/0113892029311725240911065539
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  • Article Type:     Research Article
Keyword(s): bioinformatics; Chondrocyte; JAG2; maxillofacial deformity; microtia; RNA transcriptome

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