Biology subjects

Levy, A. A.

Publications and source records attributed to Levy, A. A..

8 recordsLinked to original sources

bioRxiv2026

Features affecting Cas9-Induced Editing Efficiency and Patterns in Tomato: Evidence from a Large CRISPR Dataset

CRISPR/Cas9 is a cornerstone of genome editing, yet the determinants of editing efficiency and DNA Double Strand Break (DSB) repair outcomes remain poorly understood, particularly in plants. To address this gap, we generated a dataset of 420 sgRNAs targeting promoters, exons, and introns of 137 genes in tomato protoplasts and quantified editing efficiencies together with ATAC-seq-derived chromatin accessibility and transcriptional states in the same cellular system. Editing efficiency was consistently higher at open chromatin sites and modestly elevated in promoters and introns relative to exons, whereas transcriptional activity did not measurably influence editing outcomes. Additionally, we identified a local genomic effect resulting in less variable editing between sgRNAs targeting the same compared to different genes. A distinct subset of sgRNAs achieved nearly complete editing, producing long deletions with extended microhomology tracts. These repair footprints closely parallel those observed for high-efficiency guides in human datasets, implicating conserved sequence-driven biases and a predominant role for microhomology-mediated end joining at these sites. Yet, widely used human-trained prediction models failed to rank sgRNA performance in plants, underscoring the limits of cross-species generalization. This dataset defines how chromatin accessibility, genomic context, and intrinsic sequence characteristics shape Cas9 activity in plants, and provides a resource for improving guide design and advancing mechanistic understanding of plant DNA repair.

plant biology↗

bioRxiv2024

A multi-omics approach to identify deleterious mutations in plants

Crops lose genetic variation due to strong founder effects during domestication, accumulating and potentially exposing recessive deleterious alleles. Therefore, identifying those deleterious variants in domesticated varieties and their functional orthologs in wild relatives is key for plant breeding, food security and in rescuing the biodiversity of cultivated crops. We explored a machine learning strategy to estimate the impact of new and existing mutations in plant genomes, leveraging multi-omics data, encompassing genomic, epigenomic and transcriptomic information. Specifically, we applied a support-vector-machine framework, previously applied to animal datasets, to published omics data of two important crops of the genus Solanum - tomato and potato - and for the model plant Arabidopsis thaliana. We show that our approach provides biologically plausible inferences on the role of mutations occurring in different genomic regions and predictions that correlate with natural genetic variation for the three species, supporting the validity of our estimates. Finally, we show that our estimates outperform existing methods relying exclusively on phylogenetic conservation and not leveraging the availability of omics data for crop species. This approach provides a simple score for researchers to prioritize variants for gene editing and breeding purposes.

bioinformatics↗

bioRxiv2023

A CRISPR-induced DNA break can trigger crossover, chromosomal loss and chromothripsis-like rearrangements

The fate of DNA double-strand breaks (DSBs) generated by the Cas9 nuclease has been thoroughly studied. Repair via non-homologous end-joining (NHEJ) or homologous recombination (HR) is the common outcome. However, little is known about unrepaired DSBs and the type of damage they can trigger in plants. In this work, we designed a new assay that detects loss of heterozygosity (LOH) in somatic cells, enabling the study of a broad range of DSB-induced genomic events. The system relies on a mapped phenotypic marker which produces a light purple color (Betalain pigment) in all plant tissues. Plants with sectors lacking the Betalain marker upon DSB induction between the marker and the centromere were tested for LOH events. Using this assay we detected a flower with a twin yellow and dark purple sector, corresponding to a germinally transmitted somatic crossover event. We also identified instances of small deletions of genomic regions spanning the T-DNA and whole chromosome loss. In addition, we show that major chromosomal rearrangements including loss of large fragments, inversions, and translocations were clearly associated with the CRISPR-induced DSB. Detailed characterization of complex rearrangements by whole genome sequencing, molecular, and cytological analyses, supports a model in which breakage-fusion-bridge cycle followed by chromothripsis-like rearrangements had been induced. Our LOH assay provides a new tool for precise breeding via targeted crossover detection. It also uncovers CRISPR mediated chromothripsis-lke events that had not been previously identified in plants.

genetics↗

bioRxiv2023

Uncovering the Dynamics of Precise Repair at CRISPR/Cas9-induced Double-Strand Breaks

CRISPR/Cas9-mediated genome editing relies on error-prone repair of targeted DNA double-strand breaks (DSBs). Understanding CRISPR/Cas9-mediated DSB induction and subsequent repair dynamics requires measuring the rate of cutting and that of precise repair, a hidden-variable of the repair machinery. Here, we present a molecular and computational toolkit for multiplexed quantification of DSB intermediates and repairproducts by single-molecule sequencing. Using this approach, we characterized the dynamics of DSB induction, processing and repair at endogenous loci along a 72-hour time-course in tomato protoplasts. Combining this data with kinetic modeling reveals that indel accumulation is not an accurate reflection of DSB induction efficiency due to prominent precise re-ligation, accounting for 40-70% of all repair events. Altogether, this system exposes previously unseen flux in the DSB repair process, decoupling induction and repair dynamics, and suggesting an essential role of high-fidelity repair in limiting CRISPR editing efficiency in somatic cells.

molecular biology↗

bioRxiv2022

Machine learning reveals conserved chromatin patterns determining meiotic recombination sites in plants

Distribution of meiotic recombination events in plants has been associated with local chromatin and DNA characteristics, chromosome landmark proximity, and other features1-7. However, relative importance of these characteristics is unclear and it is unknown if they are sufficient to unambiguously determine recombination landscape8. Here, we analyzed over 40 DNA sequence, chromatin, and chromosome location features of maize and Arabidopsis recombination sites using machine learning9,10. We discovered that a combination of just three features, CG methylation, CHG methylation, and nucleosome occupancy, enabled identification of exact crossover site with 90% accuracy. These results imply redundancy of most recombination site characteristics. Recombination takes place in a small fraction of the genome with chromatin features distinct from those of genome at large. Surprisingly, crossover sites show elevated heterochromatin histone marks despite low DNA methylation. Crossover site features show broad evolutionary conservation, which will enable creating genetic maps in species where conventional mapping is unfeasible.

plant biology↗

bioRxiv2022

The genetic structure of a wild wheat population has remained associated with microhabitats over 36 years

Long-term genetic studies of wild populations are very scarce, but are essential for connecting ecological and population genetics models, and for understanding the dynamics of biodiversity. We present a study of a wild wheat population sampled over a 36-year period at high spatial resolution. We genotyped 832 individuals from regular sampling along transects during the course of the experiment. Genotypes were clustered into ecological microhabitats over scales of tens of metres, and this clustering was remarkably stable over the 36 generations of the study. Simulations show that it is difficult to explain this spatial and temporal stability using only limited dispersal, suggesting a role for fine-scale local adaptation to ecological parameters. Using a common-garden experiment, we showed that the genotypes found in distinct microhabitats differ phenotypically, further supporting the hypothesis of local adaptation. Our results provide a rare insight into the population genetics of a natural population over a long monitoring period.

evolutionary biology↗

bioRxiv2020

Independent evolution of transcript abundance and gene regulatory dynamics

Changes in gene expression drive novel phenotypes, raising interest in how gene expression evolves. In contrast to the static genome, cells regulate gene expression to accommodate changing conditions. Previous comparative studies focused on specific conditions, describing inter-species variation in expression levels, but providing limited information about variations in gene regulation. To close this gap, we profiled gene expression of related yeast species in hundreds of conditions, and used co-expression analysis to distinguish variations in transcription regulation from variations in expression levels or environmental perception. The majority of genes whose expression varied between the species maintained a conserved transcriptional regulation. Profiling the interspecific hybrid provided insights into the basis of variations, showed that trans-varying alleles interact dominantly, and revealed complementation of cis-variations by variations in trans. Our data suggests that gene expression diverges primarily through changes in promoter strength that do not alter gene positioning within the transcription network.

systems biology↗

bioRxiv2017

T-DNA integration is rapid and influenced by the chromatin state of the host genome.

Agrobacterium tumefaciens mediated T-DNA integration is a common tool for plant genome manipulation. However, there is controversy regarding whether T-DNA integration is biased towards genes or randomly distributed throughout the genome. In order to address this question, we performed high-throughput mapping of T-DNA-genome junctions obtained in the absence of selection at several time points after infection. T-DNA-genome junctions were detected as early as 6 hours post-infection. T-DNA distribution was apparently uniform throughout the chromosomes, yet local biases toward AT-rich motifs and T-DNA border sequence micro-homology were detected. Analysis of the epigenetic landscape of integration showed that selected events reported on previously were associated with extremely low methylation and nucleosome occupancy. Conversely, non-selected events from this study showed chromatin marks, such as high nucleosome occupancy and high H3K27me3 that correspond to 3D-interacting heterochromatin islands embedded within euchromatin. Such structures might play a role in capturing and silencing invading T-DNA.

plant biology↗