Biology subjects

Binan, L.

Publications and source records attributed to Binan, L..

3 recordsLinked to original sources

bioRxiv2023

Compressed Perturb-seq: highly efficient screens for regulatory circuits using random composite perturbations

Pooled CRISPR screens with single-cell RNA-seq readout (Perturb-seq) have emerged as a key technique in functional genomics, but are limited in scale by cost and combinatorial complexity. Here, we reimagine Perturb-seqs design through the lens of algorithms applied to random, low-dimensional observations. We present compressed Perturb-seq, which measures multiple random perturbations per cell or multiple cells per droplet and computationally decompresses these measurements by leveraging the sparse structure of regulatory circuits. Applied to 598 genes in the immune response to bacterial lipopolysaccharide, compressed Perturb-seq achieves the same accuracy as conventional Perturb-seq at 4 to 20-fold reduced cost, with greater power to learn genetic interactions. We identify known and novel regulators of immune responses and uncover evolutionarily constrained genes with downstream targets enriched for immune disease heritability, including many missed by existing GWAS or trans-eQTL studies. Our framework enables new scales of interrogation for a foundational method in functional genomics.

systems biology↗

bioRxiv2022

Optimization-Based Decoding of Imaging Spatial Transcriptomics Data

MotivationImaging Spatial Transcriptomics (iST) techniques characterize gene expression in cells in their native context by imaging barcoded probes for mRNA with single molecule resolution. However, the need to acquire many rounds of high-magnification imaging data limits the throughput and impact of existing methods. ResultsWe describe the Joint Sparse method for Imaging Transcriptomics (JSIT), an algorithm for decoding lower magnification IT data than that used in standard experimental workflows. JSIT incorporates codebook knowledge and sparsity assumptions into an optimization problem which is less reliant on well separated optical signals than current pipelines. Using experimental data obtained by performing Multiplexed Error-Robust Fluorescence in situ Hybridization (MERFISH) on tissue from mouse motor cortex, we demonstrate that JSIT enables improved throughput and recovery performance over standard decoding methods. Contactyonina.eldar@weizmann.ac.il, sfarhi@broadinstitute.org, bcleary@bu.edu Availability and ImplementationSoftware implementation of JSIT, together with example files, are available at https://github.com/jpbryan13/JSIT. Supplementary InformationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2022

Robust induction of functional astrocytes using NGN2 expression in human pluripotent stem cells

Astrocytes play essential roles in normal brain function, with dysfunction implicated in diverse developmental and degenerative disease processes. Emerging evidence of profound species divergent features of astrocytes coupled with the relative inaccessibility of human brain tissue underscore the utility of human pluripotent stem cell (hPSC) technologies for the generation and study of human astrocytes. However, existing approaches for hPSC-astrocyte generation are typically lengthy, incompletely characterized, or require intermediate purification steps, limiting their utility for multi-cell line, adequately powered functional studies. Here, we establish a rapid and highly scalable method for generating functional human induced astrocytes (hiAs) based upon transient Neurogenin 2 (NGN2) induction of neural progenitor-like cells followed by maturation in astrocyte media, which demonstrate remarkable homogeneity within the population and across 11 independent cell lines in the absence of additional purification steps. These hiAs express canonical astrocyte markers, respond to pro-inflammatory stimuli, exhibit ATP-induced calcium transients and support neuronal maturation in vitro. Moreover, single-cell transcriptomic analyses reveal the generation of highly reproducible cell populations across individual donors, most closely resembling human fetal astrocytes, and highly similar to hPSC-derived astrocytes generated using more complex approaches. Finally, the hiAs capture key molecular hallmarks in a trisomy 21 disease model. Thus, hiAs provide a valuable and practical resource well-suited for study of basic human astrocyte function and dysfunction in disease.

neuroscience↗