Biology subjects

Peets, E. M.

Publications and source records attributed to Peets, E. M..

7 recordsLinked to original sources

bioRxiv2025

Generating long deletions across the genome with pooled paired prime editing screens

Engineered deletions are a powerful probe for studying genome architecture, function, and regulation. Yet, the lack of effective methods to create them in large numbers and at multi-kilobase scale has rendered interrogating all the gigabases of human DNA elusive. Prime editing based approaches are promising contenders to fill this gap, but have not been adopted for large-scale pooled screening so far. Here, we performed the first high-throughput paired prime editing deletion screens. To establish the technology, we generated 3,802 deletions of up to 1.2 Mb in a reporter locus in two human cell lines, and identified key determinants of paired prime editing efficiency to be deletion length, predicted pegRNA efficacy, and contact frequency. We used these learnings to generate therapeutically important deletions at rates that are expected to give clinical benefits for retinitis pigmentosa and Duchenne muscular dystrophy. Combining several technological advances, we then performed the first pooled paired prime editing screen to delete over 10,471 sequences of median length 1.1 kb that target 149 genes across the genome. Our screens were high quality, recovering 75% of positive controls. We discovered 462 non-coding regions with fitness effects, and validated deletions with impact as well as tolerated ones in regions with functional annotations. Our screens are the largest pooled characterization of precise deletions to date, demonstrating that prime deletion screens can perturb the genome at scale, and highlighting that most non-coding DNA around essential genes is dispensable for cell growth in one condition.

genomics↗

bioRxiv2025

Resolution of a human super-enhancer by targeted genome randomisation

Human gene expression is controlled from distance via enhancers, which can form longer super-enhancer-regions of intense regulatory activity. Whether super-enhancers constitute a separate regulatory paradigm remains unclear, largely due to the difficulty of dissecting the contributions and interactions of individual elements within their natural chromosomal context. To address this challenge, we developed enhancer scrambling, a high-throughput strategy to generate stochastic inversions and deletions of targeted enhancer regions by combining CRISPR prime editing insertion of symmetrical loxP sites with Cre recombinase-induced rearrangements. We applied our approach to dissect a distal super-enhancer of the OTX2 gene, generating up to 134 alternative regulatory configurations in a single experiment, and establishing how they drive gene expression and chromatin accessibility, as well as the individual contributions of its elements to this activity. Surprisingly, the presence of the sequence containing a single DNase I hypersensitive site predominantly controls OTX2 expression. Our findings highlight that enhancer-driven regulation of some highly expressed, cell-type-specific genes can rely on an individual element within a cluster of non-interacting, dispensable components, and suggest a simple functional core to a subset of super-enhancers. The targeted randomisation method to scramble enhancers can scale to resolve many super-enhancers and human gene regulatory landscapes.

synthetic biology↗

bioRxiv2024

Randomizing the human genome by engineering recombination between repeat elements

While protein-coding genes are characterized increasingly well, 99% of the human genome is non-coding and poorly understood. This gap is due to a lack of tools for engineering variants that affect sequence to the necessary extent. To bridge this gap, we have developed a toolbox to create deletions, inversions, translocations, and extrachromosomal circular DNA at scale by highly multiplexed insertion of recombinase recognition sites into repetitive sequences with CRISPR prime editing. Using this strategy, we derived stable human cell lines with several thousand clonal insertions, the highest number of novel sequences inserted into single human genomes. Subsequent recombinase induction generated an average of more than one hundred megabase-sized rearrangements per cell, and thousands across the whole population. The ability to detect rearrangements as they are generated and to track their abundance over time allowed us to measure the selection pressures acting on different types of structural changes. We observed a consolidation towards shorter variants that preferentially delete growth-inhibiting genes and a depletion of translocations. We isolated and characterized 21 clones with multiple recombinase-induced rearrangements. These included viable haploid clones with deletions that span hundreds of kilobases as well as triploid HEK293T clones with aneuploidies and fold back chromosomes. We mapped the impact of these genetic changes on gene expression to decipher how structural variants affect gene regulation. The genome scrambling strategy developed here makes it possible to delete megabases of sequence, move sequences between and within chromosomes, and implant regulatory elements into new contexts which will shed light on the genome organization principles of humans and other species.

genomics↗

bioRxiv2023

The interplay of DNA repair context with target sequence predictably biasses Cas9-generated mutations

Mutagenic outcomes of CRISPR/Cas9-generated double-stranded breaks depend on both the sequence flanking the cut and cellular DNA damage repair. The interaction of these features has been largely unexplored, limiting our ability to understand and manipulate the outcomes. Here, we measured how the absence of 18 repair genes changed frequencies of 83,680 unique mutational outcomes generated by Cas9 double-stranded breaks at 2,838 synthetic target sequences in mouse embryonic stem cells. This large scale survey allowed us to classify the outcomes in an unbiased way, generating hypotheses about new modes of double-stranded break repair. Our data indicate a specialised role for Prkdc (DNA-PKcs protein) and Polm (Pol) in creating 1bp insertions that match the nucleotide on the proximal side of the Cas9 cut with respect to the protospacer-adjacent motif (PAM), a variable involvement of Nbn (NBN) and Polq (Pol{theta}) in the creation of different deletion outcomes, and a unique class of uni-directional deletion outcomes that are dependent on both end-protection gene Xrcc5 (Ku80) and the resection gene Nbn (NBN). We used the knowledge of the reproducible variation across repair milieus to build predictive models of the mutagenic outcomes of Cas9 scission that outperform the current standards. This work improves our understanding of DNA repair gene function, and provides avenues for more precise modulation of CRISPR/Cas9-generated mutations.

genetics↗

bioRxiv2021

Predicting efficiency of writing short sequences into the genome using prime editing

Short sequences can be precisely written into a selected genomic target using prime editing. This ability facilitates protein tagging, correction of pathogenic deletions, and many other exciting applications. However, it remains unclear what types of sequences prime editors can easily insert, and how to choose optimal reagents for a desired outcome. To characterize features that influence insertion efficiency, we designed a library of 2,666 sequences up to 69 nt in length and measured the frequency of their insertion into four genomic sites in three human cell lines, using different prime editor systems. We discover that insertion sequence length, nucleotide composition and secondary structure all affect insertion rates, and that mismatch repair proficiency is a strong determinant for the shortest insertions. Combining the sequence and repair features into a machine learning model, we can predict insertion frequency for new sequences with R = 0.69. The tools we provide allow users to choose optimal constructs for DNA insertion using prime editing.

molecular biology↗

bioRxiv2021

Predicting base editing outcomes using position-specific sequence determinants

Nucleotide-level control over DNA sequences is poised to power functional genomics studies and lead to new therapeutics. CRISPR/Cas base editors promise to achieve this ability, but the determinants of their activity remain incompletely understood. We measured base editing frequencies in two human cell lines for two cytosine and two adenine base editors at [~]14,000 target sequences. Base editing activity is sequence-biased, with largest effects from nucleotides flanking the target base, and is correlated with measures of Cas9 guide RNA efficiency. Whether a base is edited depends strongly on the combination of its position in the target and the preceding base, with a preceding thymine in both editor types leading to a wider editing window, while a preceding guanine in cytosine editors and preceding adenine in adenine editors to a narrower one. The impact of features on editing rate depends on the position, with guide RNA efficacy mainly influencing bases around the centre of the window, and sequence biases away from it. We use these observations to train a machine learning model to predict editing activity per position for both adenine and cytosine editors, with accuracy ranging from 0.49 to 0.72 between editors, and with better generalization performance across datasets than existing tools. We demonstrate the usefulness of our model by predicting the efficacy of potential disease mutation correcting guides, and find that most of them suffer from more unwanted editing than corrected outcomes. This work unravels the position-specificity of base editing biases, and provides a solution to account for them, thus allowing more efficient planning of base edits in experimental and therapeutic contexts.

genetics↗

bioRxiv2019

Minimized double guide RNA libraries enable scale-limited CRISPR/Cas9 screens

Genetic screens based on CRISPR/Cas technology are a powerful tool for understanding cellular phenotypes. However, the coverage and replicate requirements result in large experiment sizes, which are limiting when samples are scarce, or the protocols are expensive and laborious. Here, we present an approach to reduce the scale of genome-wide perturbation screens up to fivefold without sacrificing performance. To do so, we deliver two randomly paired gRNAs into each cell, and rely on recent advances in gRNA design, as well as availability of gRNA effect measurements, to reduce the number of gRNAs per gene. We designed a human genome-wide library that has effective size of 30,000 constructs, yet targets each gene with three gRNAs. Our minimized double guide RNA library gives similar results to a standard single gRNA one, but using substantially fewer cells. We demonstrate that genome-wide screens can be optimized in a demanding model of induced pluripotent stem cells, reducing reagent cost 70% per replicate compared to conventional approach, while retaining high performance. The screen design and the reduction in scale it provides will enable functional genomics experiments across many possible combinations of environments and genetic backgrounds, as well as in hard to obtain and culture primary cells.

genetics↗