Biology subjects

Diermeier, S.

Publications and source records attributed to Diermeier, S..

3 recordsLinked to original sources

bioRxiv2024

Filtering for highly variable genes and high quality spots improves phylogenetic analysis of cancer spatial transcriptomics Visium data

Phylogenetic relationship of cells within tumours can help us to understand how cancer develops in space and time, iden-tify driver mutations and other evolutionary events that enable can-cer growth and spread. Numerous studies have reconstructed phylo-genies from single-cell DNA-seq data. Here we are looking into the problem of phylogenetic analysis of spatially resolved near single-cell RNA-seq data, which is a cost-efficient alternative (or complemen-tary) data source that integrates multiple sources of evolutionary information including point mutations, copy-number changes, and epimutations. Recent attempts to use such data, although promis-ing, raised many methodological challenges. Here, we explored data-preprocessing and modelling approaches for evolutionary analyses of Visium spatial transcriptomics data. We conclude that using only highly variable genes and accounting for heterogeneous RNA capture across tissue-covered spots improves the reconstructed topological relationships and influences estimated branch lengths.

cancer biology↗

bioRxiv2021

Cancer phylogenetics using single-cell RNA-seq data

Phylogenetic methods are emerging as a useful tool to understand cancer evolutionary dynamics, including tumor structure, heterogeneity, and progression. Most currently used approaches utilize either bulk whole genome sequencing (WGS) or single-cell DNA sequencing (scDNA-seq) and are based on calling copy number alterations and single nucleotide variants (SNVs). scRNA-seq is commonly applied to explore differential gene expression of cancer cells throughout tumor progression. The method exacerbates the single-cell sequencing problem of low yield per cell with uneven expression levels. This accounts for low and uneven sequencing coverage and makes SNV detection and phylogenetic analysis challenging. In this paper, we demonstrate for the first time that scRNA-seq data contains sufficient evolutionary signal and can also be utilized in phylogenetic analyses. We explore and compare results of such analyses based on both expression levels and SNVs called from scRNA-seq data. Both techniques are shown to be useful for reconstructing phylogenetic relationships between cells, reflecting the clonal composition of a tumor. Both standardized expression values and SNVs appear to be equally capable of reconstructing a similar pattern of phylogenetic relationship. This pattern is stable even when phylogenetic uncertainty is taken in account. Our results open up a new direction of somatic phylogenetics based on scRNA-seq data. Further research is required to refine and improve these approaches to capture the full picture of somatic evolutionary dynamics in cancer.

cancer biology↗

bioRxiv2018

Characterizing higher order structures of chromatin in human cells

Packaging of DNA into chromatin regulates DNA accessibility and, consequently, all DNA-dependent processes, such as transcription, recombination, repair, and replication. The nucleosome is the basic packaging unit of DNA forming arrays that are suggested, by biochemical studies, to fold hierarchically into ordered higher-order structures of chromatin. This defined organization of chromatin has been recently questioned using microscopy techniques, proposing a rather irregular structure. To gain more insight into the principles of chromatin organization, we applied an in situ differential MNase-seq strategy and analyzed in silico the results of complete and partial digestions of human chromatin. We investigated whether different levels of chromatin packaging exist in the cell. Thus, we assessed the accessibility of chromatin within distinct domains of kb to Mb genomic regions by utilizing statistical data analyses and computer modelling. We found no difference in the degree of compaction between domains of euchromatin and heterochromatin or between other sequence and epigenomic features of chromatin. Thus, our data suggests the absence of differentially compacted domains of higher-order structures of chromatin. Moreover, we identified only local structural changes, with individual hyper-accessible nucleosomes surrounding regulatory elements, such as enhancers and transcription start sites. The regulatory sites per se are occupied with structurally altered nucleosomes, exhibiting increased MNase sensitivity. Our findings provide biochemical evidence that supports an irregular model of large-scale chromatin organization.

genomics↗