Table 1_Uncovering codon usage patterns during murine embryogenesis and tissue-specific developmental diseases.xlsx

IntroductionMouse models share significant genetic similarities with humans and have expanded our understanding of how embryonic tissue-specific genes influence disease states. By improved analyses of temporal, transcriptional data from these models, we can capture unique tissue codon usage patterns and determine how deviations from these patterns can influence developmental disorders.
MethodsWe analyzed transcriptomic-weighted data from four mouse strains across three different germ layer tissues (liver, heart, and eye) and through embryonic stages. Applying a multifaceted approach, we calculated relative synonymous codon usage, reduced the dimensionality, and employed machine learning clustering techniques.
Results and discussionThese techniques identified relative synonymous codon usage differences/similarities among strains and deviations in codon usage patterns between healthy and disease-linked genes. Original transcriptomic mouse data and RefSeq gene sequences can be found at the associated Mouse Embryo CoCoPUTs (codon and codon pair usage tables) website. Future studies can leverage this resource to uncover further insights into the dynamics of embryonic development and the corresponding codon usage biases that are paramount to understanding disease processes of embryologic origin.

引言：小鼠模型与人类具有高度相似的遗传同源性，极大拓展了我们对胚胎组织特异性基因如何影响疾病状态的认知。通过对该类模型的时序转录组数据进行优化分析，我们能够捕捉到独特的组织特异性密码子使用模式，并明确此类模式的偏离如何影响发育障碍类疾病。
方法：本研究分析了来自4个小鼠品系、覆盖3种不同胚层组织（肝脏、心脏与眼球）及多个胚胎发育阶段的转录组加权数据。研究采用多维度分析策略，计算了相对同义密码子使用频率，进行了降维处理，并运用机器学习聚类技术。
结果与讨论：上述分析方法鉴定出不同小鼠品系间相对同义密码子使用模式的差异与相似性，以及健康基因与疾病关联基因之间密码子使用模式的偏离情况。原始小鼠转录组数据及RefSeq基因序列可从关联的小鼠胚胎CoCoPUTs（密码子与密码子对使用表）网站获取。未来研究可依托本数据集资源，进一步揭示胚胎发育的动态调控机制，以及破译胚胎起源疾病过程所必需的密码子使用偏好性。