Recent breakthroughs in spatial transcriptomics technologies have enhanced our understanding of diverse cellular identities, spatial organizations, and functions. Yet existing spatial transcriptomics tools are still limited in either transcriptomic coverage or spatial resolution, hindering unbiased, hypothesis-free transcriptomic analyses at high spatial resolution. Here, we develop reverse-padlock amplicon-encoding fluorescence in situ hybridization (RAEFISH), an image-based spatial transcriptomics method with whole-genome coverage and single-molecule resolution in intact tissues. We demonstrate the spatial profiling of transcripts from 23,000 human or 22,000 mouse genes in single cells and tissue sections. Our analyses reveal transcript-specific subcellular localization, cell-type-specific and cell-type-invariant zonation-dependent transcriptomes, and gene programs underlying preferential cell-cell interactions. Finally, we further develop our technology for the direct spatial readout of guide RNAs (gRNAs) in an image-based, high-content CRISPR screen. Overall, these developments offer a broadly applicable technology that enables high-coverage, high-resolution spatial profiling of both long and short, native and engineered RNAs in many biomedical contexts.