Biology subjects

Graf, T.

Publications and source records attributed to Graf, T..

4 recordsLinked to original sources

bioRxiv2018

Single cell expression analysis uncouples transdifferentiation and reprogramming

Many somatic cell types are plastic, having the capacity to convert into other specialized cells (transdifferentiation)(1) or into induced pluripotent stem cells (iPSCs, reprogramming)(2) in response to transcription factor over-expression. To explore what makes a cell plastic and whether these different cell conversion processes are coupled, we exposed bone marrow derived pre-B cells to two different transcription factor overexpression protocols that efficiently convert them either into macrophages or iPSCs and monitored the two processes over time using single cell gene expression analysis. We found that even in these highly efficient cell fate conversion systems, cells differ in both their speed and path of transdifferentiation and reprogramming. This heterogeneity originatesin two starting pre-B cell subpopulations,large pre-BII and the small pre-BII cells they normally differentiate into. The large cells transdifferentiate slowly but exhibit a high efficiency of iPSC reprogramming. In contrast, the small cells transdifferentiate rapidly but are highly resistant to reprogramming. Moreover, the large B cells induce a stronger transient granulocyte/macrophage progenitor (GMP)-like state, while the small B cells undergo a more direct conversion to the macrophage fate. The large cells are cycling and exhibit high Myc activity whereas the small cells are Myc low and mostly quiescent. The observed heterogeneity of the two cell conversion processes can therefore be traced to two closely related cell types in the starting population that exhibit different types of plasticity. These data show that a somatic cells propensity for either transdifferentiation and reprogramming can be uncoupled.\n\nOne sentence summarySingle cell transcriptomics of cell conversions

developmental biology↗

bioRxiv2017

OneD: increasing reproducibility of Hi-C Samples with abnormal karyotypes

The three-dimensional conformation of genomes is an essential component of their biological activity. The advent of the Hi-C technology enabled an unprecedented progress in our understanding of genome structures. However, Hi-C is subject to systematic biases that can compromise downstream analyses. Several strategies have been proposed to remove those biases, but the issue of abnormal karyotypes received little attention. Many experiments are performed in cancer cell lines, which typically harbor large-scale copy number variations that create visible defects on the raw Hi-C maps. The consequences of these widespread artifacts on the normalized maps are mostly unexplored. We observed that current normalization methods are not robust to the presence of large-scale copy number variations, potentially obscuring biological differences and enhancing batch effects. To address this issue, we developed an alternative approach designed to take into account chromosomal abnormalities. The method, called OneD, increases reproducibility among replicates of Hi-C samples with abnormal karyotype, outperforming previous methods significantly. On normal karyotypes, OneD fared equally well as state-of-the-art methods, making it a safe choice for Hi-C normalization. OneD is fast and scales well in terms of computing resources for resolutions up to 1 kbp. OneD is implemented as an R package available at http://www.github.com/qenvio/dryhic.

bioinformatics↗

bioRxiv2017

Managing The Analysis Of High-Throughput Sequencing Data

T47D_rep2 and b1913e6c1_51720e9cf were two Hi-C samples. They were born and processed at the same time, yet their fates were very different. The life of b1913e6c1_51720e9cf was simple and fruitful, while that of T47D_rep2 was full of accidents and sorrow. At the heart of these differences lies the fact that b1913e6c1_51720e9cf was born under a lab culture of Documentation, Automation, Traceability, Autonomy and compliance with the FAIR Principles. Their lives are a lesson for those who wish to embark on the journey of managing high throughput sequencing data.

bioinformatics↗

bioRxiv2017

Transcription Factors Orchestrate Dynamic Interplay Between Genome Topology And Gene Regulation During Cell Reprogramming

Chromosomal architecture is known to influence gene expression, yet its role in controlling cell fate remains poorly understood. Reprogramming of somatic cells into pluripotent stem cells by the transcription factors (TFs) Oct4, Sox2, Klf4 and Myc offers an opportunity to address this question but is severely limited by the low proportion of responding cells. We recently developed a highly efficient reprogramming protocol that synchronously converts somatic into pluripotent stem cells. Here, we employ this system to integrate time-resolved changes in genome topology with gene expression, TF binding and chromatin state dynamics. This revealed that TFs drive topological genome reorganization at multiple architectural levels, which often precedes changes in gene expression. Removal of locus-specific topological barriers can explain why pluripotency genes are activated sequentially, instead of simultaneously, during reprogramming. Taken together, our study implicates genome topology as an instructive force for implementing transcriptional programs and cell fate in mammals.

molecular biology↗