Bioinformatic analysis of Msx1 and Msx2 involved in craniofacial development

Jiewen Dai1, Zhifang Mou, Shunyao Shen

  • 1From the *Department of Oral & Cranio-maxillofacial Science, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine,Shanghai Key Laboratory of Stomatology, Shanghai; and †Emergency Department and ‡Department of Orthopaedics, the First People's Hospital of Lian Yun Gang, Lianyungang, China.

Insights

This study systematically analyzed MSX genes and their related factors in craniofacial deformities. It identified key genes involved in cleft lip/palate and craniosynostosis, revealing novel interactions for future research.

Area of Science:

  • Genetics and Developmental Biology
  • Bioinformatics
  • Craniofacial Research

Background:

  • Msx1 and Msx2 are candidate genes for craniofacial deformities like cleft lip/palate (CL/P) and craniosynostosis.
  • Numerous genes interact with MSX genes in causing these defects, but a systematic evaluation is lacking.

Purpose of the Study:

  • To conduct a systematic bioinformatic analysis of MSX genes and their related factors.
  • To identify genes and pathways involved in CL/P and craniosynostosis.
  • To explore novel gene interactions, such as SUMO with MSX1, for understanding genetic mutations.

Main Methods:

  • Utilized GeneDecks, DAVID, and STRING databases for systematic bioinformatic analysis.
  • Integrated gene interaction data with known craniofacial deformity associations.
  • Investigated protein-protein interactions for novel gene discoveries.

Main Results:

  • Identified numerous MSX gene-related factors, including IRF6, TP63, DLX2, DLX5, PAX3, PAX9, BMP4, TGF-β2, TGF-β3 for CL/P.
  • Highlighted FGFR1, FGFR2, FGFR3, and TWIST1 involvement in craniosynostosis.
  • Discovered a protein-protein interaction between SUMO and MSX1, relevant to nonsyndromic CL/P.

Conclusions:

  • MSX gene networks are crucial in craniofacial development and deformity.
  • Findings provide a basis for analyzing MSX gene functions within a broader network.
  • The identified SUMO-MSX1 interaction offers a new avenue for bioinformatic analysis of GWAS data and mutation impact prediction.