Biology subjects

Jann, J.-C.

Publications and source records attributed to Jann, J.-C..

4 recordsLinked to original sources

bioRxiv2023

Cell type-specific consequences of mosaic structural variants in hematopoietic stem and progenitor cells

The functional impact and cellular context of mosaic structural variants (mSVs) in normal tissues is understudied. Utilizing Strand-seq, we sequenced 1,133 single cell genomes from 19 human donors of increasing age, revealing a heterogeneous mSV landscape in hematopoietic stem and progenitor cells (HSPCs). While mSV clonal expansions are confined to individuals over 60, de novo mSV formation occurs consistently across age, frequently leading to megabase-scale segmental aneuploidies. Cells harboring subclonal mosaicism show evidence for increased mSV formation. To enable high-resolution cell-typing of each Strand-seq library, we generated single-cell MNase-seq reference datasets for eight distinct HSPCs. Subclonal mSVs frequently exhibit enrichment in myeloid progenitors, and single-cell multiomic analysis suggests that these mSVs result in recurrent dysregulation of pathways related to proliferation and metabolism, including Ras signaling and lipid metabolism. The comprehensive mSV landscape identified in this study implicates mSVs in cell type-specific molecular phenotypes, establishing a foundation for deciphering links between mSVs, aging, and disease risk.

genomics↗

bioRxiv2021

Haplotype-aware single-cell multiomics uncovers functional effects of somatic structural variation

Somatic structural variants (SVs) are widespread in cancer genomes, however, their impact on tumorigenesis and intra-tumour heterogeneity is incompletely understood, since methods to functionally characterize the broad spectrum of SVs arising in cancerous single-cells are lacking. We present a computational method, scNOVA, that couples SV discovery with nucleosome occupancy analysis by haplotype-resolved single-cell sequencing, to systematically uncover SV effects on cis-regulatory elements and gene activity. Application to leukemias and cell lines uncovered SV outcomes at several loci, including dysregulated cancer-related pathways and mono-allelic oncogene expression near SV breakpoints. At the intra-patient level, we identified different yet overlapping subclonal SVs that converge on aberrant Wnt signaling. We also deconvoluted the effects of catastrophic chromosomal rearrangements resulting in oncogenic transcription factor dysregulation. scNOVA directly links SVs to their functional consequences, opening the door for single-cell multiomics of SVs in heterogeneous cell populations.

genomics↗

bioRxiv2021

Single-cell proteo-genomic reference maps of the hematopoietic system enable the purification and massive profiling of precisely defined cell states

Single-cell genomics has transformed our understanding of complex cellular systems. However, excessive costs and a lack of strategies for the purification of newly identified cell types impede their functional characterization and large-scale profiling. Here, we have generated high content single-cell proteo-genomic reference maps of human blood and bone marrow that quantitatively link the expression of up to 197 surface markers to cellular identities and biological processes across all major hematopoietic cell types in healthy aging and leukemia. These reference maps enable the automatic design of cost-effective high-throughput cytometry schemes that outperform state-of-the-art approaches, accurately reflect complex topologies of cellular systems, and permit the purification of precisely defined cell states. The systematic integration of cytometry and proteo-genomic data enables measuring the functional capacities of precisely mapped cell states at the single-cell level. Our study serves as an accessible resource and paves the way for a data-driven era in cytometry.

immunology↗

bioRxiv2018

MutaSeq reveals the transcriptomic consequences of clonal evolution in acute myeloid leukemia

Cancer stem cells drive disease progression and relapse in many types of cancer. Despite this, a thorough characterization of these cells remains elusive and with i the ability to eradicate cancer at its source. In acute myeloid leukemia (AML), leukemic stem cells (LSCs) underlie mortality but are difficult to isolate due to their low abundance and high similarity to healthy hematopoietic stem cells (HSCs). Here, we demonstrate that LSCs, HSCs, and pre-leukemic stem cells can be identified and molecularly profiled by combining single-cell transcriptomics with lineage tracing using both nuclear and mitochondrial somatic variants. While mutational status discriminates between healthy and cancerous cells, gene expression distinguishes stem cells and progenitor cell populations. Our approach enables the identification of LSC-specific gene expression programs and the characterization of differentiation blocks induced by leukemic mutations. Taken together, we demonstrate the power of single-cell multi-omic approaches in characterizing cancer stem cells.

genomics↗