The Transcriptomics to Proteomics of Hair Cell Regeneration: Looking for a Hair Cell in a Haystack
AbstractMature mammals exhibit very limited capacity for regeneration of auditory hair cells, while all non-mammalian vertebrates examined can regenerate them. In an effort to find therapeutic targets for deafness and balance disorders, scientists have examined gene expression patterns in auditory tissues under different developmental and experimental conditions. Microarray technology has allowed the large-scale study of gene expression profiles (transcriptomics) at whole-genome levels, but since mRNA expression does not necessarily correlate with protein expression, other methods, such as microRNA analysis and proteomics, are needed to better understand the process of hair cell regeneration. These technologies and some of the results of them are discussed in this review. Although there is a considerable amount of variability found between studies owing to different species, tissues and treatments, there is some concordance between cellular pathways important for hair cell regeneration. Since gene expression and proteomics data is now commonly submitted to centralized online databases, meta-analyses of these data may provide a better picture of pathways that are common to the process of hair cell regeneration and lead to potential therapeutics. Indeed, some of the proteins found to be regulated in the inner ear of animal models (e.g., IGF-1) have now gone through human clinical trials. View Full-Text
Share & Cite This Article
Smith, M.E.; Rajadinakaran, G. The Transcriptomics to Proteomics of Hair Cell Regeneration: Looking for a Hair Cell in a Haystack. Microarrays 2013, 2, 186-207.
Smith ME, Rajadinakaran G. The Transcriptomics to Proteomics of Hair Cell Regeneration: Looking for a Hair Cell in a Haystack. Microarrays. 2013; 2(3):186-207.Chicago/Turabian Style
Smith, Michael E.; Rajadinakaran, Gopinath. 2013. "The Transcriptomics to Proteomics of Hair Cell Regeneration: Looking for a Hair Cell in a Haystack." Microarrays 2, no. 3: 186-207.