Ribozymes and deoxyribozymes are catalytic RNA and DNA, respectively, that catalyze chemical reactions such as self-cleavage or ligation reactions. While some ribozymes are found in nature, a larger variety of ribozymes and deoxyribozymes have been discovered by in vitro selection from random sequences. These catalytic nucleic acids, especially ribozymes, are of fundamental interest because they are crucial for the RNA world hypothesis, which suggests that RNA played a central role in both the propagation of genetic information and catalyzing metabolic reactions in primordial life prior to the emergence of proteins and DNA. On the practical side, catalytic nucleic acids have been extensively engineered for various applications, such as biosensors and genetic devices for synthetic biology. Therefore, it is important to gain a deeper understanding of the sequence-function relationships of ribozymes and deoxyribozymes.Mutational analysis, or measurements of activities of catalytic nucleic acid mutants, is one of the most fundamental approaches for that purpose. Mutations that abolish, reduce, retain, or even increase activity provide useful information about nucleic acid catalysts for engineering and other purposes. However, methods for mutational analysis of ribozymes and deoxyribozymes have not evolved much for decades, requiring tedious and low-throughput assays (e.g., gel electrophoresis) of individually prepared mutants. This has prevented researchers from performing quantitative mutational analysis of ribozymes and deoxyribozymes on a large scale.To address this limitation, we developed a massively parallel ribozyme and deoxyribozyme assay strategy that allows >104 assays using high-throughput sequencing (HTS). We used HTS to literally count the number of cleaved (or ligated) and uncleaved (or unligated) ribozyme (or deoxyribozyme) sequences and calculated the activities of each mutant in a reaction mixture. This simple yet powerful strategy was applied to analyze the mutational effects of various natural and synthetic ribozymes and deoxyribozymes at scales impossible for conventional mutational analysis. These large-scale sequence-function data sets were used to better understand the functional consequences of mutations and to engineer ribozymes for practical applications. Furthermore, these newly available data are motivating researchers to employ more rigorous computational methods to extract additional insights such as structural information and nonlinear effects of multiple mutations. The new HTS-based assay strategy is distinct from and complementary to a related strategy that uses HTS to analyze ribozyme and deoxyribozyme populations subjected to in vitro selection. Postselection sequencing can cover a larger sequence space, although it does not directly quantify the activities of ribozyme and deoxyribozyme mutants. With further advances in DNA sequencing technologies and computational methods, there should be more opportunities to harness the power of HTS to deepen our understanding of catalytic nucleic acids and enhance our ability to engineer them for even more applications.