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Biology subjects

Lindenhofer, D.

Publications and source records attributed to Lindenhofer, D..

2 recordsLinked to original sources

Functional phenotyping of genomic variants using multiomic scDNA-scRNA-seq

Genomic variation ranging from single nucleotide polymorphisms to structural variants can impact gene function and expression, contributing to disease mechanisms such as cancer progression. The systematic study of this variation is hindered by inefficient precision editing tools making it challenging to confidently link genotype and gene expression in pooled screens. Additionally, assessing heterogenous variants in primary tumor samples at scale is difficult with current single-cell technologies. We developed droplet-based multiomic targeted scDNA-scRNAseq (SDR-seq) to precisely link genotypes with gene expression profiles in high-throughput. SDR-seq simultaneously assesses up to 480 RNA and gDNA targets with high coverage and sensitivity across thousands of cells. Using SDR-seq, we associate coding and non-coding variants with distinct gene expression profiles in human iPSCs. Furthermore, we demonstrate that in primary B-cell lymphoma samples, cells with a higher mutational burden exhibit elevated B-cell receptor signaling and tumorigenic gene expression. SDR-seq has broad potential for gaining functional insights into regulatory mechanisms encoded by genetic variants at diverse loci, advancing our ability to study gene expression regulation and its implications for disease.

molecular biology↗

Neutral competition within a long-lived population of symmetrically dividing cells shapes the clonal composition of cerebral organoids

Cerebral organoids model the development of the human brain and are an indispensable tool for studying neurodevelopment. Whole-organoid lineage tracing has revealed the number of progeny arising from each initial stem cell to be highly diverse, with lineage sizes ranging from one to more than 20,000 cells. This exceeds what can be explained by existing stochastic models of corticogenesis, indicating the existence of an additional source of stochasticity. We propose an explanation in terms of the SAN model in which this additional source of stochasticity is the survival time of a lineage within a long-lived population of symmetrically dividing cells under neutral competition. We demonstrate that this model explains the experimentally observed variability of lineage sizes and we derive a formula that captures the quantitative relationship between survival time and lineage size. Finally, we show that our model implies the existence of a regulatory mechanism to keeps the size of the symmetrically dividing cell population constant.

developmental biology↗