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Workman, M. J.

Publications and source records attributed to Workman, M. J..

2 recordsLinked to original sources

Single-cell RNA-seq analysis of human iPSC-derived motor neurons resolves early and predictive ALS signatures

Induced pluripotent stem cell (iPSC) derived neural cultures from amyotrophic lateral sclerosis (ALS) patients can reflect disease phenotypes targetable by treatments. However, widely used differentiation protocols produce mixtures of progenitors, neurons, glia, and other cells at various developmental stages and rostrocaudal neural tube segments. Here we present a methodology using single-cell RNA sequencing analysis to distinguish cell type expression in C9orf72 ALS, sporadic ALS, control, and genome-edited cultures across multiple subjects, experiments, and commercial platforms. Combinations of HOX and developmental gene expression with global clustering classified rostrocaudal, progenitor, and mantle zone fates. This demonstrated that iPSC-differentiated cells recapitulate fetal hindbrain and spinal cord development and resolved early, reproducible, and motor neuron-specific signatures of familial and sporadic ALS. This includes downregulated ELAVL3 expression, which persists into disease endstages. Single-cell analysis thus yielded predictive ALS markers in other human and mouse models which were otherwise undiscovered through bulk omics assays.

neuroscience↗

HiCAGE: an R package for large-scale annotation and visualization of 3C-based genomic data

Chromatin interactions measured by the 3C-based family of next generation technologies are becoming increasingly important for measuring the physical basis for regulatory interactions between different classes of functional domains in the genome. Software is needed to streamline analyses of these data and integrate them with custom genome annotations, RNA-seq, and gene ontologies. We introduce a new R package compatible with Bioconductor--Hi-C Annotation and Graphics Ensemble (HiCAGE)--to perform these tasks with minimum effort. In addition, the package contains a shiny/R web app interface to provide ready access to its functions.\n\nAvailability and ImplementationThe software is implemented in R and is freely available under GPLv3. HiCAGE runs in R (version 3.4) and is freely available through github (https://github.com/mworkman13/HiCAGE) or on the web (https://junkdnalab.shinyapps.io/hicage).

bioinformatics↗