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Microarray-based characterization of differential gene expression during vocal fold wound healing in rats

机译:大鼠声带伤口愈合过程中差异基因表达的基于微阵列的表征

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The vocal fold (VF) mucosa confers elegant biomechanical function for voice production but is susceptible to scar formation following injury. Current understanding of VF wound healing is hindered by a paucity of data and is therefore often generalized from research conducted in skin and other mucosal systems. Here, using a previously validated rat injury model, expression microarray technology and an empirical Bayes analysis approach, we generated a VF-specific transcriptome dataset to better capture the system-level complexity of wound healing in this specialized tissue. We measured differential gene expression at 3, 14 and 60 days post-injury compared to experimentally na?ve controls, pursued functional enrichment analyses to refine and add greater biological definition to the previously proposed temporal phases of VF wound healing, and validated the expression and localization of a subset of previously unidentified repair- and regeneration-related genes at the protein level. Our microarray dataset is a resource for the wider research community and has the potential to stimulate new hypotheses and avenues of investigation, improve biological and mechanistic insight, and accelerate the identification of novel therapeutic targets.
机译:声带(VF)粘膜具有优雅的生物力学功能,可产生声音,但易于受伤后形成疤痕。缺乏数据阻碍了对VF伤口愈合的当前了解,因此通常从皮肤和其他粘膜系统的研究中得到概括。在这里,使用先前验证的大鼠损伤模型,表达微阵列技术和经验贝叶斯分析方法,我们生成了VF特异性转录组数据集,以更好地捕获该专业组织中伤口愈合的系统级复杂性。与实验中的原始对照组相比,我们在损伤后第3、14和60天测量了差异基因表达,进行了功能富集分析,以完善和增加更大的生物学定义到先前提出的VF伤口愈合的临时阶段,并验证了表达和在蛋白质水平上定位先前未知的修复和再生相关基因的子集。我们的微阵列数据集是更广泛的研究社区的资源,并且有可能激发新的研究假设和途径,提高生物学和机制的见解,并加快新治疗靶标的识别。

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