RNA-binding proteins (RBPs) are intimately involved in all aspects of RNA processing and regulation and are linked to neurodegenerative diseases and cancer. Therefore, investigating the relationship between RBPs and their RNA targets is critical for a broader understanding of post-transcriptional regulation in normal and disease processes. The majority of approaches to study RNA–protein interactions interrogate only individual RBPs. However, there are hundreds of these proteins encoded in the human genome, and each cell type expresses a different repertoire, greatly limiting the ability of current methods to capture the global landscape of RNA–protein interactions. To address this gap, we and others have recently developed methods to globally identify regions of RNAs that are bound by proteins in an unbiased manner. Here, we describe a detailed protocol for performing our ribonuclease-mediated protein footprint sequencing approach, termed protein interaction profile sequencing (PIP-seq). In this protocol, RNA–protein interactions are stabilized by cross-linking, and unbound regions are digested with ribonucleases (RNases), leaving only the protein-bound regions intact. To control for RNase insensitive regions, proteins are first denatured and degraded, then protein-depleted RNAs are subjected to RNase treatment. After high-throughput sequencing of the remaining fragments, peak calling is performed to identify protein-protected sites (PPSs). We describe the application of this protocol to a human embryonic kidney cell line (HEK293T) and perform basic quality control, reproducibility, and benchmarking analyses. Finally, we delineate the landscape of protein-interactions in HEK293T cells, underscoring the value of this approach. Future applications of this method to study the dynamics of RNA–protein interactions in developmental and disease processes will help to further uncover the role of RBPs in post-transcriptional regulation.