Biology subjects

Salehi, S.

Publications and source records attributed to Salehi, S..

22 records · Page 2Linked to original sources

bioRxiv2021

Evolutionary tracking of cancer haplotypes at single-cell resolution

Cancer genomes exhibit extensive chromosomal copy number changes and structural variation, yet how allele specific alterations drive cancer genome evolution remains unclear. Here, through application of a new computational approach we report allele specific copy number alterations in 11,097 single cell whole genomes from genetically engineered mammary epithelial cells and 21,852 cells from high grade serous ovarian and triple negative breast cancers. Resolving single cell copy number profiles to individual alleles uncovered genomic background distributions of gains, losses and loss of heterozygosity, yielding evidence of positive selection of specific chromosomal alterations. In addition specific genomic loci in maternal and paternal alleles were commonly found to be altered in parallel with convergent phenotypic transcriptional effects. Finally we show that haplotype specific alterations trace the cyclical etiology of high level amplifications and reveal clonal haplotype decomposition of complex structures. Together, our results illuminate how allele and haplotype specific alterations, here determined across thousands of single cell cancer genomes, impact the etiology and evolution of structural variations in human tumours.

cancer biology↗

bioRxiv2020

Single cell fitness landscapes induced by genetic and pharmacologic perturbations in cancer

Tumour fitness landscapes underpin selection in cancer, impacting etiology, evolution and response to treatment. Progress in defining fitness landscapes has been impeded by a lack of timeseries perturbation experiments over realistic intervals at single cell resolution. We studied the nature of clonal dynamics induced by genetic and pharmacologic perturbation with a quantitative fitness model developed to ascribe quantitative selective coefficients to individual cancer clones, enable prediction of clone-specific growth potential, and forecast competitive clonal dynamics over time. We applied the model to serial single cell genome (>60,000 cells) and transcriptome (>58,000 cells) experiments ranging from 10 months to 2.5 years in duration. We found that genetic perturbation of TP53 in epithelial cell lines induces multiple forms of copy number alteration that confer increased fitness to clonal populations with measurable consequences on gene expression. In patient derived xenografts, predicted selective coefficients accurately forecasted clonal competition dynamics, that were validated with timeseries sampling of experimentally engineered mixtures of low and high fitness clones. In cisplatin-treated patient derived xenografts, the fitness landscape was inverted in a time-dependent manner, whereby a drug resistant clone emerged from a phylogenetic lineage of low fitness clones, and high fitness clones were eradicated. Moreover, clonal selection mediated reversible drug response early in the selection process, whereas late dynamics in genomically fixed clones were associated with transcriptional plasticity on a fixed clonal genotype. Together, our findings outline causal mechanisms with implication for interpreting how mutations and multi-faceted drug resistance mechanisms shape the etiology and cellular fitness of human cancers.

cancer biology↗

bioRxiv2020

Efficient Bayesian inference of phylogenetic trees from large scale, low-depth genome-wide single-cell data

A new generation of scalable single cell whole genome sequencing (scWGS) methods allows unprecedented high resolution measurement of the evolutionary dynamics of cancer cell populations. Phylogenetic reconstruction is central to identifying sub-populations and distinguishing the mutational processes that gave rise to them. Existing phylogenetic tree building models do not scale to the tens of thousands of high resolution genomes achievable with current scWGS methods. We constructed a phylogenetic model and associated Bayesian inference procedure, sitka, specifically for scWGS data. The method is based on a novel phylogenetic encoding of copy number (CN) data, the sitka transformation, that simplifies the site dependencies induced by rearrangements while still forming a sound foundation to phylogenetic inference. The sitka transformation allows us to design novel scalable Markov chain Monte Carlo (MCMC) algorithms. Moreover, we introduce a novel point mutation calling method that incorporates the CN data and the underlying phylogenetic tree to overcome the low per-cell coverage of scWGS. We demonstrate our method on three single cell datasets, including a novel PDX series, and analyse the topological properties of the inferred trees. Sitka is freely available at https://github.com/UBC-Stat-ML/sitkatree.git.

bioinformatics↗

bioRxiv2018

Fast temporal dynamics and causal relevance of face processing in the human temporal cortex

Recordings with a large number of intracranial electrodes in eight neurosurgical subjects offered a unique opportunity to examine the fast temporal dynamics of face processing simultaneously across a relatively large extent of the human temporal cortex (TC). Measuring the power of slow oscillatory bands of activity ({theta}, , {beta}, and {gamma}) as well as High-Frequency Broadband (HFB, 70-177 Hz) signal, we found that the HFB showed the strongest univariate and multivariate changes in response to face compared to non-face stimuli. Using the HFB signal as a surrogate marker for local cortical engagement, we identified recording sites with selective responses to faces that were anatomically consistent across subjects and responded with graded strength to human, mammal, bird, and marine animal faces. Importantly, the most face selective sites were located more posteriorly and responded earlier than those with less selective responses to faces. Using machine learning based methods, we demonstrated that a sparse model focusing on information from the human face selective sites performed as well as, or better than, anatomically distributed models of face processing when discriminating faces from non-faces stimuli. Lastly, we identified the posterior fusiform (pFUS) site as causally the most relevant node for inducing distortion of face perception by direct electrical stimulation. Our findings support the notion of face information being processed first in the most selective sites - that are anatomically discrete and localizable within individual brains and anatomically consistent across subjects - which is then distributed in time to less selective anterior temporal sites within a time window that is too fast to be detected by current neuroimaging methods. The new information about the fast spatio-temporal dynamics of face processing across multiple sites of the human brain provides a new common ground for unifying the seemingly contradictory modular and distributed models of face processing in the human brain.

neuroscience↗