Automating multimodal microscopy with NanoJ-Fluidics, bioRxiv, 2018-05-14
AbstractFluorescence microscopy can reveal all aspects of cellular mechanisms, from molecular details to dynamics, thanks to approaches such as super-resolution and live-cell imaging. Each of its modalities requires specific sample preparation and imaging conditions to obtain high-quality, artefact-free images, ultimately providing complementary information. Combining and multiplexing microscopy approaches is crucial to understand cellular events, but requires elaborate workflows involving multiple sample preparation steps. We present a robust fluidics approach to automate complex sequences of treatment, labelling and imaging of live and fixed cells. Our open-source NanoJ-Fluidics system is based on low-cost LEGO hardware controlled by ImageJ-based software and can be directly adapted to any microscope, providing easy-to-implement high-content, multimodal imaging with high reproducibility. We demonstrate its capacity to carry out complex sequences of experiments such as super-resolved live-to-fixed imaging to study actin dynamics; highly-multiplexed STORM and DNA-PAINT acquisitions of multiple targets; and event-driven fixation microscopy to study the role of adhesion contacts in mitosis.
biorxiv cell-biology 200-500-users 2018Whole-genome deep learning analysis reveals causal role of noncoding mutations in autism, bioRxiv, 2018-05-11
AbstractWe address the challenge of detecting the contribution of noncoding mutations to disease with a deep-learning-based framework that predicts specific regulatory effects and deleterious disease impact of genetic variants. Applying this framework to 1,790 Autism Spectrum Disorder (ASD) simplex families reveals autism disease causality of noncoding mutations by demonstrating that ASD probands harbor transcriptional (TRDs) and post-transcriptional (RRDs) regulation-disrupting mutations of significantly higher functional impact than unaffected siblings. Importantly, we detect this significant noncoding contribution at each level, transcriptional and post-transcriptional, independently and after multiple hypothesis correction. Further analysis suggests involvement of noncoding mutations in synaptic transmission and neuronal development, and reveals a convergent genetic landscape of coding and noncoding (TRD and RRD) de novo mutations in ASD. We demonstrate that sequences carrying prioritized proband de novo mutations possess transcriptional regulatory activity and drive expression differentially, and highlight a link between noncoding mutations and IQ heterogeneity in ASD probands. Our predictive genomics framework illuminates the role of noncoding mutations in ASD, prioritizes high impact transcriptional and post-transcriptional regulatory mutations for further study, and is broadly applicable to complex human diseases.
biorxiv genomics 100-200-users 2018Massive single-cell RNA-seq analysis and imputation via deep learning, bioRxiv, 2018-05-06
Recent advances in large-scale single cell RNA-seq enable fine-grained characterization of phenotypically distinct cellular states within heterogeneous tissues. We present scScope, a scalable deep-learning based approach that can accurately and rapidly identify cell-type composition from millions of noisy single-cell gene-expression profiles.
biorxiv bioinformatics 0-100-users 2018Highly Multiplexed Single-Cell RNA-seq for Defining Cell Population and Transcriptional Spaces, bioRxiv, 2018-05-05
AbstractWe describe a universal sample multiplexing method for single-cell RNA-seq in which cells are chemically labeled with identifying DNA oligonucleotides. Analysis of a 96-plex perturbation experiment revealed changes in cell population structure and transcriptional states that cannot be discerned from bulk measurements, establishing a cost effective means to survey cell populations from large experiments and clinical samples with the depth and resolution of single-cell RNA-seq.
biorxiv genomics 200-500-users 2018Portraits of genetic intra-tumour heterogeneity and subclonal selection across cancer types, bioRxiv, 2018-05-05
SummaryOngoing cancer evolution gives rise to intra-tumour heterogeneity (ITH), which is a major mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin and drivers of ITH across cancer types are poorly understood. Here, we extensively characterise ITH across 2,778 cancer whole genome sequences from 36 cancer types. We demonstrate that nearly all tumours (94.7%) with sufficient sequencing depth contain evidence of recent subclonal expansions, and that most cancer types show clear signs of positive selection in both clonal and subclonal protein coding variants. We find distinctive subclonal patterns of driver gene mutations, fusions, structural variation and copy-number alterations across cancer types. Dynamic, tumour type-specific changes of mutational processes between subclonal expansions shape differences between clonal and subclonal events. Our results underline the importance of ITH and its drivers in tumour evolution, and provide an unprecedented pan-cancer resource of extensively annotated subclonal events, laying a foundation for future cancer genomic studies.
biorxiv cancer-biology 100-200-users 2018CRISPR-Cas9 interference in cassava linked to the evolution of editing-resistant geminiviruses, bioRxiv, 2018-05-04
ABSTRACTWe used CRISPR-Cas9 in the staple food crop cassava with the aim of engineering resistance to African cassava mosaic virus, a member of a widespread and important family of plant-pathogenic DNA viruses. We found that between 33 and 48% of edited virus genomes evolved a conserved single-nucleotide mutation that confers resistance to CRISPR-Cas9 cleavage. Our study highlights the potential for virus escape from this technology. Care should be taken to design CRISPR-Cas9 experiments that minimize the risk of virus escape.
biorxiv plant-biology 100-200-users 2018