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Zaurin, R.

Publications and source records attributed to Zaurin, R..

2 recordsLinked to original sources

Translocations can drive expression changes of multiple genes in regulons covering entire chromosome arms

Translocations have largely been implicated in tumor development. However, beyond the consequences of aberrant gene expression near the breakpoint, their effects remain unexplored. In this work, we characterize the interplay between translocations, chromatin organization and gene expression using mantle cell lymphoma (MCL) as a model. We show that in vitro induced MCL-associated translocations can drive transcriptional changes at entire chromosome arms affecting multiple genes in a regulon-like fashion. Additionally, overexpressed genes in MCL patients are enriched in the exact same genomic regions, further underlining its potential relevance for lymphomagenesis. Moreover, we demonstrate a clear link between the translocation-induced transcriptional alterations and genome organization, with genes most susceptible to change expression residing in pre-existing long-range interacting loops spanning 50 megabases. The translocation places the strong immunoglobulin enhancer into this loop, allowing the spread of its regulatory potential over the entire affected chromosome arm. Finally, we show that translocation-induced effects mainly represent expression enhancement of genes already active prior to translocation formation, highlighting the importance of the epigenetic state of the cell in which this initial hit occurs. In summary, we show that translocations can induce ample, simultaneous gene expression changes affecting entire chromosome arms, representing an important new mechanism for tumorigenesis.

cancer biology↗

scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells

Single-cell DNA methylation profiling currently suffers from excessive noise and/or limited cellular throughput. We developed scTAM-seq, a targeted bisulfite-free method for profiling up to 650 CpGs in up to 10,000 cells per experiment, with a dropout rate of less than seven percent. scTAM-seq focuses sequencing coverage on informative, variably methylated CpGs that in many tissues and cell types make up a minor fraction of all CpGs. By applying scTAM-seq to B cells from blood and bone marrow, we demonstrate that it can resolve DNA methylation dynamics across B-cell differentiation at unprecedented resolution, identifying intermediate differentiation states that were previously masked. scTAM-seq additionally queries surface protein expression and somatic mutations, thus enabling integration of single-cell DNA methylation information with cell atlas data, and opening applications in tumor profiling. In summary, scTAM-seq is the first high-throughput, high-confidence method for analyzing DNA methylation at single-CpG resolution across thousands of single cells.

genomics↗