Spike-in RNA-seq and Ribo-seq of Budding Yeast under Differernt Nutrient Conditions

This project profiles transcription and translation in Saccharomyces cerevisiae across four defined growth conditions. We generated spike-in RNA-seq datasets to quantify absolute (per-cell) total mRNA concentration and to assess global transcriptome changes with internal standards. In parallel, ribosome profiling (Ribo-seq) was performed to map ribosome-protected footprints and estimate gene-specific translation efficiency by relating footprint density to mRNA abundance. Together, these paired datasets provide a resource to dissect how gene expression is allocated between transcription and translation under distinct conditions.本项目针对酿酒酵母（Saccharomyces cerevisiae）在四种明确设定的生长条件下的转录与翻译过程开展了表征分析。我们构建了spike-in RNA测序（spike-in RNA-seq）数据集，以定量获取每细胞总信使RNA（mRNA）的绝对浓度，并通过内参标准评估全局转录组（transcriptome）的变化情况。与此同时，我们开展了核糖体足迹测序（Ribo-seq）实验，以绘制核糖体保护足迹图谱，并通过将足迹密度与信使RNA（mRNA）丰度相关联，估算基因特异性翻译效率。上述配对数据集共同构成了一套研究资源，可用于解析不同生长条件下基因表达在转录与翻译过程之间的分配机制。