Biology subjects

Yousefi, R.

Publications and source records attributed to Yousefi, R..

5 recordsLinked to original sources

bioRxiv2024

Computer simulations reveal mechanisms of spatio-temporal regulation of DNA replication

The dynamics of DNA replication, activation of replication origins and elongation rate, depend on dNTP in ways that remain poorly understood. Here, we present RepliSim, a probabilistic computer model of DNA replication simulation, which is capable of simulating DNA replication not only in normal conditions, but also during perturbations (e.g. HU treatment) and in mutant cells (here checkpoint deficient yeast cells). We show that different mutations in checkpoint genes, affect the origin activation differently by modulating the stochasticity of firing time and efficiency, regardless of the dNTP levels. The origin activation is less affected by increase in dNTP levels, however it declined drastically during the S phase when the dNTP levels decreased compared to G1 phase. Additionally, we show that the distribution of distances covered by replication forks is influenced not only by average fork progression speed, but also by firing time and fork progression speed stochasticity, while the latter has been neglected in most of the proposed models for DNA replication. These together, opens up new insight to the studies about the dynamics of replication and how it is coordinated during the S-phase.

bioinformatics↗

bioRxiv2020

Local translation in synaptic mitochondria influences synaptic transmission

Mitochondria possess a small genome that codes for core subunits of the oxidative phosphorylation system, and whose expression is essential for energy production. Information on the regulation and spatial organization of mitochondrial gene expression in the cellular context has been difficult to obtain. Here we addressed this by devising an imaging approach to analyze mitochondrial translation, by following the incorporation of clickable non-canonical amino acids. We applied this method to multiple cell types, including hippocampal neurons, where we found ample evidence for mitochondrial translation in both dendrites and axons. Translation levels were surprisingly heterogeneous, were typically stronger in axons, and were independent of their distance from the cell soma, where mitochondria presumably descent from. Presynaptic mitochondrial translation correlated with local synaptic activity, and blocking mitochondria translation reduced synaptic function. Overall, these findings demonstrate that mitochondrial gene expression in neurons is intimately linked to neuronal function.

biochemistry↗

bioRxiv2019

Stochasticity of replication fork speed plays a key role in the dynamics of DNA replication

Eukaryotic DNA replication is elaborately orchestrated to duplicate the genome timely and faithfully. Replication initiates at multiple origins from which replication forks emanate and travel bi-directionally. The complex spatio-temporal regulation of DNA replication remains incompletely understood. To study it, computational models of DNA replication have been developed in S. cerevisiae. However, in spite of the experimental evidence of replication speed stochasticity, all models assumed that replication fork speed is constant or varies only with genomic coordinates. Here, we present the first model of DNA replication assuming stochastic speed of the replication fork. Utilizing data from both wild-type and hydroxyurea-treated yeast cells, we show that our model is more accurate than models assuming constant fork speed and reconstructs dynamics of DNA replication faithfully starting both from population-wide data and data reflecting fork movement in individual cells. Completion of replication in a timely manner is a challenge due to its stochasticity; we propose an empirically derived modification to replication speed based on the distance to the approaching fork, which promotes timely completion of replication. In summary, our work discovers a key role that stochasticity of the fork speed plays in the dynamics of DNA replication. We show that without including stochasticity of fork speed it is not possible to accurately reconstruct movement of individual replication forks, measured by DNA combing.\n\nAuthor summaryDNA replication in eukaryotes starts from multiple sites termed replication origins. Replication timing at individual sites is stochastic, but reproducible population-wide. Complex and not yet completely understood mechanisms ensure that genome is replicated exactly once and that replication is finished in time. This complex spatio-temporal organization of DNA replication makes computational modeling a useful tool to study replication mechanisms. For simplicity, all previous models assumed constant replication fork speed. Here, we show that such models are incapable of accurately reconstructing distances travelled by individual replication forks. Therefore, we propose a model with a stochastic replication fork speed. We show that such model reproduces faithfully distances travelled by individual replication forks. Moreover, our model is simpler than previous model and thus avoids over-learning (fitting noise). We also discover how replication speed may be attuned to timely complete replication. We propose that fork speed exponentially increases with diminishing distance to the approaching fork, which we show promotes timely completion of replication. Such speed up can be e.g. explained by a synergy effect of chromatin unwinding by both forks. Our model can be used to simulate phenomena beyond replication, e.g. DNA double-strand breaks resulting from broken replication forks.

bioinformatics↗

bioRxiv2017

Integrated analysis of DSB patterns reveals precisely DSB formation mechanisms following replication fork collapse

DNA double-strand breaks (DSBs) can be detected by label-based sequencing or pulsed-field gel electrophoresis (PFGE). Sequencing yields population-average DSB frequencies genome-wide, while PFGE reveals percentages of broken chromosomes. We constructed a mathematical framework to combine advantages of both: high-resolution DSB locations and their population distribution. We also use sequencing read patterns to identify replication-induced DSBs and active replication origins. We describe changes in spatiotemporal replication program upon hydroxyurea-induced replication stress. We found that one-ended DSBs, resulting from collapsed replication forks, are population-representative, while majority of two-ended DSBs (79-100%) are not. To study replication fork collapse, we used strains lacking the checkpoint protein Mec1 and the endonuclease Mus81 and quantified that 19% and 13% of hydroxyurea-induced one-ended DSBs are Mec1-and Mus81-dependent, respectively. We also clarified that Mus81-induced one-ended DSBs are Mec1-dependent.

genomics↗

bioRxiv2017

Quantitative DSB sequencing (qDSB-Seq): a method for genome-wide accurate estimation of absolute DNA double-strand break frequencies per cell

Sequencing-based methods for mapping DNA double-strand breaks (DSBs) allow measurement only of relative frequencies of DSBs between loci, which limits our understanding of the physiological relevance of detected DSBs. We propose quantitative DSB sequencing (qDSB-Seq), a method providing both DSB frequencies per cell and their precise genomic coordinates. We induced spike-in DSBs by a site-specific endonuclease and used them to quantify labeled DSBs (e.g. using i-BLESS). Utilizing qDSB-Seq, we determined numbers of DSBs induced by a radiomimetic drug and various forms of replication stress, and revealed several orders of magnitude differences in DSB frequencies. We also measured for the first time Top1-dependent absolute DSB frequencies at replication fork barriers. qDSB-Seq is compatible with various DSB labeling methods in different organisms and allows accurate comparisons of absolute DSB frequencies across samples.

genomics↗