Biology subjects

Hard, J.

Publications and source records attributed to Hard, J..

7 recordsLinked to original sources

bioRxiv2025

Phylogenetic tree inference from single-cell RNA sequencing data

Single-cell RNA sequencing technologies enable the large-scale measurement of gene expression profiles at the individual cell level to assess cellular diversity and function. In oncology, leveraging these single-cell transcriptomic data to reconstruct the phylogenetic relationships among cancer cells can provide insights into tumor evolution, metastasis formation, and the development of treatment resistance. However, phylogenetic inference from single-cell RNA sequencing is challenging due to sparse and noisy data and large dataset sizes. We present a novel tree inference method designed for such data that takes reference and alternative read counts of single-nucleotide variants and reconstructs a phylogenetic tree of the sequenced cells via maximum likelihood using a random-scan greedy search. To overcome local optima in the search, our algorithm alternates between two different tree representations: cell lineage trees, where cells are represented by nodes and mutations are attached to edges, and mutation trees, where mutation nodes encode the mutational events and cells are attached to them. Because a local optimum in one tree space generally does not correspond to a local optimum in the other space, we maximize the likelihood by switching between the two tree spaces until convergence is achieved in both. We demonstrate superior performance of our approach on simulated data with complex clonal architectures compared to existing methods. Furthermore, we show its applicability to cancer single-cell RNA sequencing data, which allows us to link evolutionary trajectories of cells to their gene expression profiles.

genomics↗

bioRxiv2025

Cell lineage inference from mitochondrial mutations

Tracing genealogical relationships between cells and their molecular states is essential for understanding tissue development, maintenance and disease. We present mt-SCITE, a computational method that reconstructs cell division histories from mitochondrial mutations in single cells. On simulated and experimental benchmarks, mt-SCITE outperformed existing methods in terms of cell lineage reconstruction, and scaled to thousands of cells. Applied to expanded CD8+ T cells following vaccination, mt-SCITE resolved subclonal relationships and revealed clones with predominantly memory-like, effector-like, or mixed states. mt-SCITE robustly identifies clonally related populations and resolves substructure within them, providing a broadly applicable approach to study cell lineage development.

bioinformatics↗

bioRxiv2022

Clonally heritable gene expression imparts a layer of diversity within cell types

Cell types can be classified based on shared patterns of transcription. Variability in gene expression between individual cells of the same type has been ascribed to stochastic transcriptional bursting and transient cell states. We asked whether long-term, heritable differences in transcription can impart diversity within a cell type. Studying clonal human lymphocytes and mouse brain cells, we uncover a vast diversity of heritable transcriptional states among different clones of cells of the same type in vivo. In lymphocytes we show that this diversity is coupled to clone specific chromatin accessibility, resulting in distinct expression of genes by different clones. Our findings identify a source of cellular diversity, which may have important implications for how cellular populations are shaped by selective processes in development, aging and disease.

systems biology↗

bioRxiv2021

Long-read whole genome analysis of human single cells

With long-read sequencing, we have entered an era where individual genomes are routinely assembled to near completion and where complex genetic variation can efficiently be resolved. Here, we demonstrate that long reads can be applied to study the genomic architecture of individual human cells. Clonally expanded CD8+ T-cells from a human donor were used as starting material for a droplet-based multiple displacement amplification (dMDA) to generate long molecules with minimal amplification bias. PacBio HiFi sequencing generated up to 20 Gb data and 40% genome coverage per single cell. The data allowed for accurate detection and haplotype phasing of single nucleotide variants (SNVs), structural variants (SVs), and tandem repeats, including in genomic regions inaccessible by short reads. Somatic SNVs were detected in the nuclear genome and mitochondrial DNA. An average of 1278 high-confidence SVs per cell were discovered in the PacBio data, nearly four times as many compared to those found in Illumina dMDA data from clonally related cells. Single-cell de novo assembly resulted in a genome size of up to 598 Mb and 1762 (12.8%) complete gene models. In summary, the work presented here demonstrates the utility of whole genome amplification combined with long-read sequencing toward the characterization of the full spectrum of genetic variation at the single-cell level.

genomics↗

bioRxiv2019

High-dimensional analysis reveals a distinct population of adaptive-like tissue-resident NK cells in human lung

Human adaptive-like “memory” CD56dimCD16+ NK cells in peripheral blood from cytomegalovirus-seropositive individuals have been extensively investigated in recent years and are currently explored as a treatment strategy for hematological cancers. However, treatment of solid tumors remains limited due to insufficient NK cell tumor infiltration, and it is unknown whether large expansions of adaptive-like NK cells that are equipped for tissue-residency and tumor-homing exist in peripheral tissues. Here, we show that human lung and blood contains adaptive-like CD56brightCD16− NK cells with hallmarks of tissue-residency, including expression of CD49a. Expansions of adaptive-like lung tissue-resident (tr)NK cells were found to be present independently of adaptive-like CD56dimCD16+ NK cells and to be hyperresponsive towards target cells. Together, our data demonstrate that phenotypically, functionally, and developmentally distinct subsets of adaptive-like NK cells exist in human lung and blood. Given their tissue-related character and hyperresponsiveness, human lung adaptive-like trNK cells might represent a suitable alternative for therapies targeting solid tumors.Competing Interest StatementThe authors have declared no competing interest.Abbreviations:EomesEomesoderminFITCFluorescein isothiocyanateHCMVHuman cytomegalovirusILCInnate lymphoid cellKIRKiller cell immunoglobulin-like receptorNKNatural killerPEPhycoerythrinROSReactive oxygen speciesView Full Text

immunology↗

bioRxiv2019

Clonally distinct differentiation trajectories shape CD8+ memory T cell heterogeneity after acute viral infections in humans

CD8+ T cells play essential roles in immunity to viral and bacterial infections, and to guard against malignant cells. The CD8+ T cell response to an antigen is composed of many T cell clones with unique T cell receptors, together forming a heterogenous repertoire of phenotypically and functionally distinct effector and memory cells1, 2. How individual T cell clones contribute to this heterogeneity during an immune response is key to understand immunity but remains largely unknown. Here, we longitudinally tracked CD8+ T cell clones expanding in response to yellow fever virus vaccination at the single cell level in humans. We show that only a fraction of the clones detected in the acute response persists as circulating memory T cells, indicative of clonal selection. Clones persisting in the memory phase displayed biased differentiation trajectories along a gradient of stem cell memory (SCM) towards terminally differentiated effector memory (EMRA) fates. Reactivation of single memory CD8+ T cells revealed that they were poised to recapitulate skewed differentiation trajectories in secondary responses, and this was generalizable across individuals for both yellow fever and influenza virus. Together, we show that the sum of distinct clonal differentiation repertoires results in the multifaceted T cell response to acute viral infections in humans.

immunology↗

bioRxiv2018

Conbase: a software for discovery of clonal somatic mutations in single cells through read phasing

Here we report the development of Conbase, a software application for the identification of somatic mutations in single cell DNA sequencing data with high rates of allelic dropout and at low read depth. Conbase leverages data from multiple samples in a dataset and utilizes read phasing to call somatic single nucleotide variants and to accurately predict genotypes in whole genome amplified single cells in somatic variant loci. We demonstrate the accuracy of Conbase on simulated datasets, in vitro expanded fibroblasts and clonally in vivo expanded lymphocyte populations isolated directly from a healthy human donor.

bioinformatics↗