Extended Data Fig. 1: Generating sequence tags with silent mutations for non-coding genomic regions. | Nature Biotechnology

Extended Data Fig. 1: Generating sequence tags with silent mutations for non-coding genomic regions.

From: A competitive precision CRISPR method to identify the fitness effects of transcription factor binding sites

Extended Data Fig. 1: Generating sequence tags with silent mutations for non-coding genomic regions.The alternative text for this image may have been generated using AI.

a, Frequency of the flanking mutations in the HDR templates. For creating sequence tags with silent or near-silent mutations, each of the ten positions flanking the MYC binding motif (E-box) was mutated with probability of 24% (each of the three non-consensus nucleotides introduced with a probability of 8%). This results in a library of sequences with most of the flanking sequence intact; oligoes synthesized using this approach typically harbor one, two, or three flanking mutations with probability of 20.3, 28.8 and 24.3%, respectively. b, All variations for sequence tags harboring one mutation (indicated in red) within ten nucleotides flanking the original E-box sequence (CACGTG) or mutated sequence (TATTTA) in HDR oligoes targeting the MYC binding motif at the RPL23 promoter. c, Examples of full length HDR oligos targeting the RPL23 promoter. The constant regions serving as homology arms and the two types of mutations are shown: (1) the experimental variants targeting the sequence of interest (E-box) in the middle of the oligo with either original E-box sequence (blue) or mutated non-functional sequence (orange); (2) flanking mutations that generate variable sequence tags (mutated nucleotide indicated in red, consensus sequence in black). Examples of sequence tags with one, two, and three flanking mutations are shown; the total number of potential tags with these mutations is also indicated.

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