Elucidating the spatiotemporal dynamics of gene expression is essential for understanding complex physiological and pathological processes. Current spatial transcriptomics (ST) techniques are hindered by low read depths and limited gene detection capabilities. To achieve more precise gene expression patterns, we introduce Palette, a pipeline that infers detailed spatial gene expression patterns from bulk RNA-seq data, utilizing existing ST data as the sole reference. We applied Palette to construct the zebrafish SpatioTemporal Expression Profiles (zSTEP) by integrating 53-slice serial bulk RNA-seq data with existing ST and image references. zSTEP provides a comprehensive cartographic resource for investigating developmental events within zebrafish embryos.