Biology subjects

Aparicio, S.

Publications and source records attributed to Aparicio, S..

5 recordsLinked to original sources

bioRxiv2018

Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data

We present Epiclomal, a probabilistic clustering method arising from a hierarchical mixture model to simultaneously cluster sparse single-cell DNA methylation data and impute missing values. Using synthetic and published single-cell CpG datasets we show that Epiclomal outperforms non-probabilistic methods and is able to handle the inherent missing data feature which dominates single-cell CpG genome sequences. Using a recently published single-cell 5mCpG sequencing method (PBAL), we show that Epiclomal discovers sub-clonal patterns of methylation in aneuploid tumour genomes, thus defining epiclones. We show that epiclones may transcend copy number determined clonal lineages, thus opening this important form of clonal analysis in cancer. Epiclomal is written in R and Python and is available at https://github.com/shahcompbio/Epiclomal.

genomics↗

bioRxiv2018

Resource: Scalable whole genome sequencing of 40,000 single cells identifies stochastic aneuploidies, genome replication states and clonal repertoires

Essential features of cancer tissue cellular heterogeneity such as negatively selected genome topologies, sub-clonal mutation patterns and genome replication states can only effectively be studied by sequencing single-cell genomes at scale and high fidelity. Using an amplification-free single-cell genome sequencing approach implemented on commodity hardware (DLP+) coupled with a cloud-based computational platform, we define a resource of 40,000 single-cell genomes characterized by their genome states, across a wide range of tissue types and conditions. We show that shallow sequencing across thousands of genomes permits reconstruction of clonal genomes to single nucleotide resolution through aggregation analysis of cells sharing higher order genome structure. From large-scale population analysis over thousands of cells, we identify rare cells exhibiting mitotic mis-segregation of whole chromosomes. We observe that tissue derived scWGS libraries exhibit lower rates of whole chromosome anueploidy than cell lines, and loss of p53 results in a shift in event type, but not overall prevalence in breast epithelium. Finally, we demonstrate that the replication states of genomes can be identified, allowing the number and proportion of replicating cells, as well as the chromosomal pattern of replication to be unambiguously identified in single-cell genome sequencing experiments. The combined annotated resource and approach provide a re-implementable large scale platform for studying lineages and tissue heterogeneity.

genomics↗

bioRxiv2018

clonealign: statistical integration of independent single-cell RNA & DNA-seq from human cancers

Measuring gene expression of genomically defined tumour clones at single cell resolution would associate functional consequences to somatic alterations, as a prelude to elucidating pathways driving cell population growth, resistance and relapse. In the absence of scalable methods to simultaneously assay DNA and RNA from the same single cell, independent sampling of cell populations for parallel measurement of single cell DNA and single cell RNA must be computationally mapped for genome-transcriptome association. Here we present clonealign, a robust statistical framework to assign gene expression states to cancer clones using single-cell RNA-seq and DNA-seq independently sampled from an heterogeneous cancer cell population. We apply clonealign to triple-negative breast cancer patient derived xenografts and high-grade serous ovarian cancer cell lines and discover clone-specific dysregulated biological pathways not visible using either DNA-Seq or RNA-Seq alone.

bioinformatics↗

bioRxiv2017

The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

High-grade serous ovarian cancer exhibits extensive intratumoral heterogeneity coupled with widespread intraperitoneal disease. Despite this, metastatic spread of tumor clones is non-random, implying the existence of local microenvironmental factors that shape tumor progression. We interrogated the molecular interface between tumor-infiltrating lymphocytes (TIL) and cancer cells in 143 samples from 21 patients using whole-genome sequencing, immunohistochemistry, histologic image analysis, gene expression profiling, and T- and B-cell receptor sequencing. We identify 3 immunologic response categories, which frequently co-exist within individual patients. Furthermore, epithelial CD8+ TIL were inversely associated with malignant cell diversity, evidenced by subclonal neoepitope elimination and spatial tracking between tumor and T-cell clones. Intersecting mutational signatures and immune analysis showed that foldback inversion genomic aberrations lead to worse outcomes even in the presence of cytotoxic TIL (n=433). Thus, regional variation in immune contexture mirrors the pattern of intraperitoneal malignant spread, provoking new perspectives for treatment of this challenging disease.

cancer biology↗

bioRxiv2017

EIF4A3 associated splicing and nonsense mediated decay defined by a systems analysis with novel small molecule inhibitors

Chemical biology approaches to the global functions of splicing reactions are gaining momentum, with an increasing repertoire of small molecule probes becoming available. Here we map the association of eIF4A3 with transcript expression, NMD and alternative splicing using a set of selective novel small molecule allosteric helicase inhibitors whose synthesis and chemical properties we have recently described. We show through analysis of dose monotonic transcriptional responses to increasing inhibition that both full length and NMD prone transcripts link eIF4A3 to normal functioning of cell division including chromosome segregation and cell cycle checkpoints, pointing to a conserved role of splicing and transcript quality processing in cell cycle functions. Cell cycle analysis and microscopy of inhibitor treated cells demonstrates chromosome mis-segregation and spindle defects, associated with a G2/M arrest, validating this observation. Through analysis of conserved alternative splicing patterns exhibiting monotonic responses, we find that eIF4A3 dependent alternative splicing involves exons that are longer and introns that are shorter than transcripts not modulated by eIF4A3. Moreover we observe conservation of over/under representation of RBP binding motif density over introns and exons implicated eIF4A3 modulated skipped exon and retained introns. The distribution of motif densities over 5 and branch intron sites and 5 exons is consistent with function of the exon-junction complex. Taken together we have defined a fraction of the transcrip-tome dependent on eIF4A3 functions and revealed a link between eIF4A3 and cell cycle regulation. The systems approach described here suggests additional avenues for therapeutic exploitation of eIF4A3 functions in cancer and related diseases.

genomics↗