Reads were trimmed using Cutadapt and then clustered into unique sequences using vsearch (Rognes et al., 2016 (link)). Each unique read was then aligned to the matched sgRNA sequence, allowing up to two mismatches. Finally, we stored all sgRNA types and their frequency in each sample.
Amplification and Sequencing of sgRNAs
Reads were trimmed using Cutadapt and then clustered into unique sequences using vsearch (Rognes et al., 2016 (link)). Each unique read was then aligned to the matched sgRNA sequence, allowing up to two mismatches. Finally, we stored all sgRNA types and their frequency in each sample.
Variable analysis
- From each sorted population, as well as ancestor sample, genomic DNA was extract using PureLink genomic DNA mini kit and used as templates for PCR to amplify specifically the sgRNAs in the population.
- PCR reaction was conducted using 2X KAPA HiFi HotStart ReadyMix, 10 µM of each primer and 20 ng of genomic DNA extracted from the samples in a 50 µl total volume reaction, for 20 cycles, Tm = 58°C.
- We used shifted primers to increase library complexity.
- PCR products were purified with SPRI-beads using left-side size selection protocol in which the PCR product and beads were mixed at 1:1.5 ratio.
- The barcoding PCR and final PCR clean-up was done as described for the genomic tRNA library preparation.
- Samples were pooled and sequenced using a 75 bp single read output run using MiniSeq high output reagent kit (Ilumina; FC-420–1001).
- Reads were trimmed using Cutadapt and then clustered into unique sequences using vsearch (Rognes et al., 2016 (link)).
- Each unique read was then aligned to the matched sgRNA sequence, allowing up to two mismatches.
- Finally, we stored all sgRNA types and their frequency in each sample.
- Control variables not explicitly mentioned.
- Positive control: Not mentioned.
- Negative control: Not mentioned.
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