Biology subjects

Suryawanshi, G. W.

Publications and source records attributed to Suryawanshi, G. W..

2 recordsLinked to original sources

bioRxiv2025

Single cell Edit Detection and Identification Tool (scEDIT): computational workflow for efficient and economical single cell analysis of CRISPR edited cells

Advances in CRISPR technology are revolutionizing gene therapy and drug discovery. The advent of single-cell DNA sequencing (scDNA-seq) is generating granular level insight into CRISPR induced genomic changes both intended and unintended. However, analysis of single cell data necessitates expensive high-performance computing (HPC) clusters or large data servers. Analysis of the single cell data is currently limited unaffordable computational cost and the lack of open-source software tools. To address this, we present scEDIT, a fast, lightweight, portable, and standalone software for pre- and post-processing CRISPR editing data from the Tapestri single-cell DNA-seq platform. scEDIT is memory-efficient, multithreaded, and compatible with most UNIX based systems. Tests using a low-cost desktop and public single cell CRISPR data demonstrate that the tool can efficiently process raw sequences, identify cell barcodes, count unedited and edited amplicons per cell, and outputs detailed filtered reads. Analysis of the single cell CRISPR data reveals indel patterns shared between in vitro experiments and unique indel profiles detected for in vivo study. Results further demonstrate the ability of single cell analysis in providing quantitative insights into the true zygosity of edited cell population. Although data shows a linear relation between indel frequencies by read count and cell count details of indel share between difference cells can only be truly explored with single cell data. Furthermore, scEDIT can analyze massively parallel base editing in human hematopoietic stem cells providing insights into the base editing patterns for hundreds of gRNAs targeting GATA1 and HbF gene. Importantly, scEDIT detected low frequency unintended and potentially harmful deletions introduced during the base editing. The reanalysis of two independent studies demonstrated the efficiency, stability, and portability of scEDIT making it an invaluable tool for uncovering new insights into the single cell data with limited and inexpensive computational resources. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/634562v2_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@1cfc5b2org.highwire.dtl.DTLVardef@1bc47cborg.highwire.dtl.DTLVardef@d8431org.highwire.dtl.DTLVardef@161d3f9_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2020

LoVIS-Seq reveals clonal dynamics of human-HSPC in humanized mice and vector integration bias

BackgroundCurrent understanding of hematopoiesis is largely derived from mouse models that are physiologically distant from humans. Humanized mice provide the most physiologically relevant small animal model to study human diseases, most notably preclinical gene-therapy studies. However, the clonal repopulation dynamics of human hematopoietic stem and progenitor cells (HSPC) in these animal models is only partially understood. Using a new clonal tracking methodology designed for small sample volumes, we aim to reveal the underlying clonal dynamics of human cell repopulation in a mouse environment. MethodsHumanized BLT (bone marrow-liver-thymus) mice were generated by transplanting lentiviral vector transduced human fetal liver HSPC (FL-HSPC) in NOD.Cg-PrkdcscidIl2rgtm1Wjl/SzJ (NSG) mice implanted with a piece of human fetal thymus. We developed a methodology to track vector integration sites (VIS) in a mere 25{micro}l of mouse blood for longitudinal and quantitative clonal analysis of human HSPC repopulation in mouse environment. We explored transcriptional and epigenetic features of human HSPC for possible VIS bias. Results897 HSPC clones were longitudinally tracked in BLT mice--providing a first-ever demonstration of clonal dynamics and competitive expansion of therapeutic and control vector-modified human cell populations simultaneously repopulating in the same humanized mice. The polyclonal repopulation stabilized at 19 weeks post-transplant and the contribution of the largest clone doubled within 4 weeks. Moreover, 550 ([~]60%) clones persisted over 6 weeks and were highly shared between different organs. The normal clonal profiles confirmed the safety of our gene therapy vectors. Multi-omics analysis of human FL-HSPC revealed that 54% of vector integrations in repopulating clones occurred within {+/-}1kb of H3K36me3-enriched regions. ConclusionsHuman repopulation in mice is polyclonal and stabilizes more rapidly than that previously observed in humans. VIS preference for H3K36me3 has no apparent negative effects on HSPC repopulation. Our study provides a methodology to longitudinally track clonal repopulation in small animal models extensively used for stem cell and gene-therapy research and with lentiviral vectors designed for clinical applications. Results of this study provide a framework for understanding the clonal behavior of human HPSC repopulating in a mouse environment, critical for translating results from humanized mice models to the human settings.

molecular biology↗