Abstract: The present disclosure provides a novel machine learning model capable of assisting those of ordinary skill in the art to conduct base editing by, inter alia, facilitating the selection of an appropriate guide RNA and base editor combination which are capable of conducting base editing at a certain level of efficiency and specificity on a given input target DNA sequence desired to be edited to produce an outcome genotype of interest. The disclosure also provides base editors (e.g., ABEs and CBEs), napDNAbps, cytidine deaminases, adenosine deaminases, nucleic acid sequences encoding base editors and components thereof, vectors, and cells. In addition, the disclosure provides methods of making biological or experimental training and/or validation data for training and/or validating the machine learning computational models, as well as, vectors, libraries, and nucleic acid sequences for use in obtaining said experimental training and/or validation data.

Abstract: The specification provides methods for introducing a desired genetic change in a nucleotide sequence using a double-strand break (DSB)-inducing genome editing system, the method comprising: identifying one or more available cut sites in a nucleotide sequence; analyzing the nucleotide sequence and available cut sites with a computational model to identify the optimal cut site for introducing the desired genetic change into the nucleotide sequence; and contacting the nucleotide sequence with a DSB-inducing genome editing system, thereby introducing the desired genetic change in the nucleotide sequence at the cut site.

Abstract: The specification provides a machine-learning model which predicts, based on input that can include a given target DNA sequence and a CRISPR/Cas cut site location, repair genotype outcomes associated with template-free repair processes (e.g., MMEJ or NHEJ) acting on Cas9-induced double-stranded DNA breaks. The specification further provides for the use of a machine-learning model for conducting genome editing based on a template-free CRISPR/Cas system, including the selection of an appropriate guide RNA (gRNA) to achieve a desired repaired genotype outcome.