Biology subjects

Lederer, A. R.

Publications and source records attributed to Lederer, A. R..

5 recordsLinked to original sources

bioRxiv2024

Evolutionarily recent transcription factors partake in human cell cycle regulation

The cell cycle is a fundamental process in eukaryotic biology and is accordingly controlled by a highly conserved core signaling cascade. However, whether recently evolved proteins also influence this process is unclear. Here, we systematically map the influence of evolutionarily recent transcription factors (TFs) on human cell cycle progression. We find that the genomic targets of select young TFs, many of which belong to the rapidly evolving Kruppel-associated box (KRAB) zinc-finger proteins (KZFP) family, exhibit synchronized cell cycle expression. Systematic perturbation studies reveal that silencing recent TFs disrupts normal cell cycle progression, which we experimentally confirm for ZNF519, a simian-restricted KZFP. Further, we show that the therian-specific KZFP ZNF274 sets the cell cycle expression and replication timing of hundreds of clustered genes. These findings highlight an underappreciated level of lineage specificity in cell cycle regulation.

cell biology↗

bioRxiv2024

Single-nuclei histone modification profiling of the adult human central nervous system unveils epigenetic memory of developmental programs

The adult human central nervous system (CNS) is remarkably complex, with neural cells displaying extensive transcriptional heterogeneity. However, how different layers of epigenetic regulation underpin this heterogeneity is poorly understood. Here, we profile the adult human CNS from distinct regions, for chromatin accessibility at the single-nuclei level. In addition, we simultaneously co-profiled the histone modifications H3K27me3 and H3K27ac at the single nuclei-level, providing their first map in all major human CNS cell types. We unveil primed chromatin signatures at HOX loci in spinal cord-derived human oligodendroglia (OLG) but not microglia. These signatures were reminiscent of developmental OLG but were decoupled from robust gene expression. Moreover, using high-resolution Micro-C, we show that induced pluripotent stem cell (iPS) derived human OLGs exhibit a HOX chromatin architecture compatible with the primed chromatin in adult OLGs, and bears a strong resemblance not only to OLG developmental architecture, but also high-grade pontine gliomas. Thus, adult OLG retain epigenetic memory from developmental states, which might enable them to promptly transcribe Hox genes, in contexts of regeneration, but also make them susceptible to gliomagenesis.

neuroscience↗

bioRxiv2024

Statistical inference with a manifold-constrained RNA velocity model uncovers cell cycle speed modulations

Across a range of biological processes, cells undergo coordinated changes in gene expression, resulting in transcriptome dynamics that unfold within a low-dimensional manifold. Single-cell RNA-sequencing (scRNA-seq) only measures temporal snapshots of gene expression. However, information on the underlying low-dimensional dynamics can be extracted using RNA velocity, which models unspliced and spliced RNA abundances to estimate the rate of change of gene expression. Available RNA velocity algorithms can be fragile and rely on heuristics that lack statistical control. Moreover, the estimated vector field is not dynamically consistent with the traversed gene expression manifold. Here, we develop a generative model of RNA velocity and a Bayesian inference approach that solves these problems. Our model couples velocity field and manifold estimation in a reformulated, unified framework, so as to coherently identify the parameters of an autonomous dynamical system. Focusing on the cell cycle, we implemented VeloCycle to study gene regulation dynamics on one-dimensional periodic manifolds and validated using live-imaging its ability to infer actual cell cycle periods. We benchmarked RNA velocity inference with sensitivity analyses and demonstrated one- and multiple-sample testing. We also conducted Markov chain Monte Carlo inference on the model, uncovering key relationships between gene-specific kinetics and our gene-independent velocity estimate. Finally, we applied VeloCycle to in vivo samples and in vitro genome-wide Perturb-seq, revealing regionally-defined proliferation modes in neural progenitors and the effect of gene knockdowns on cell cycle speed. Ultimately, VeloCycle expands the scRNA-seq analysis toolkit with a modular and statistically rigorous RNA velocity inference framework.

systems biology↗

bioRxiv2021

Molecular profiling of retinal pigment epithelial cell differentiation for therapeutic use

Human embryonic stem cell-derived retinal pigment epithelial cells (hESC-RPE) are a promising cell source to treat age-related macular degeneration (AMD). Despite several ongoing clinical studies, detailed single cell mapping of the transient cellular and molecular dynamics from the pluripotent state to mature RPE has not been performed. Here we conduct single-cell transcriptomic analyses of 25,718 cells during differentiation as well as in embryonic and adult retina references, revealing differentiation progression through an un-expected initial cell diversification recapitulating early embryonic development before converging towards an RPE lineage. We also identified NCAM1 to track and capture an intermediate retinal progenitor with the potential to give rise to multiple neuroepithelial lineages. Finally, we profiled hESC-RPE cells after subretinal transplantation into the rabbit eye, uncovering robust in vivo maturation towards an adult state. Our detailed evaluation of hESC-RPE differentiation supports the development of safe and efficient pluripotent stem cell-based therapies for AMD.

developmental biology↗

bioRxiv2019

The Paf1 complex broadly impacts the transcriptome of Saccharomyces cerevisiae

The Polymerase Associated Factor 1 complex (Paf1C) is a multifunctional regulator of eukaryotic gene expression important for the coordination of transcription with chromatin modification and post-transcriptional processes. In this study, we investigated the extent to which the functions of Paf1C combine to regulate the Saccharomyces cerevisiae transcriptome. While previous studies focused on the roles of Paf1C in controlling mRNA levels, here we took advantage of a genetic background that enriches for unstable transcripts and demonstrate that deletion of PAF1 affects all classes of Pol II transcripts including multiple classes of noncoding RNAs. By conducting a de novo differential expression analysis independent of gene annotations, we found that Paf1 positively and negatively regulates antisense transcription at multiple loci. Comparisons with nascent transcript data revealed that many, but not all, changes in RNA levels detected by our analysis are due to changes in transcription instead of post-transcriptional events. To investigate the mechanisms by which Paf1 regulates protein-coding genes, we focused on genes involved in iron and phosphate homeostasis, which were differentially affected by PAF1 deletion. Our results indicate that Paf1 stimulates phosphate gene expression through a mechanism that is independent of any individual Paf1C-dependent histone modification. In contrast, the inhibition of iron gene expression by Paf1 correlates with a defect in H3 K36 tri-methylation. Finally, we showed that one iron regulon gene, FET4, is coordinately controlled by Paf1 and transcription of upstream noncoding DNA. Together these data identify roles for Paf1C in controlling both coding and noncoding regions of the yeast genome.

genomics↗