Sandberg Lab

Ludwig Institute for Cancer Research & Department of Cell and Molecular Biology, Karolinska Institutet

Research

We are interested in determining how gene expression patterns are regulated during development through global measurements of transcripts copy numbers (RNA-Seq), genome-wide locations of transcription factors (ChIP-Seq). Computational analyses of these data aim to tease out the gene regulatory networks acting in early embryonic development, and general patterns in the specification of cell types. To this end we have been developing global RNA-Seq from few or single cells that we are applying to studies on the first differentiation events taking place during mouse preimplantation development.

Ongoing Projects:

Determining the clonality of gene expression, with an emphasis on allelic resolution transcription.

Mapping of in vivo cell lineage decisions with sigle-cell resolution.

A long-term aim of the lab is to map gene regulatory events goveringing cell lineage decisions. To this end, we are focusing on preimplantation development and how the fertilized egg eventually gives rise to the three lineages of the blasocyst. Using single-cell transcriptomics and combining it with other genomic data sets on gene regulation, we will more precisely map the gene regulatory processes such as zygotic gene activation, X chromosome inactivation, and cell lineage decisions. For our recent work on the mouse, see Deng, Ramskold et al. Science 2014 and for our recent work on human preimplantation development see Petropopolous, Edsgard, Reinius et al. Cell 2016.

Improve single-cell transcriptomics methodolody.

Our lab is continuing the development of single-cell assays for quantifying RNAs from individual cells. We previously developed Smart-seq2 (see Picelli et al. Nature Methods 2013) and a single-cell assay for short RNAs (Faridani, Abdullayev et al. Nature Biotecthnology 2016). In collaboration with Andreas Tolias lab, we have also developed protocols for sequencing of single patched cells (see Patch-seq, Cadwell, Palasantza et al. Nature Biotechnology 2015).

Infer transcriptional kinetics from single-cell RNA-seq data, with allelic resolition.

Recent Projects:

Single-cell RNA-Seq using Smart-Seq

In a collaboration with Illumina Inc. (Hayward) and Louise Laurent's lab we have deloped Smart-Seq, a robust and sensitive RNA-Seq method applicable to single mammalian cells. Using Smart-Seq we generated genome-wide transcriptomes from circulating melanoma tumor cells.
Ramskold D. et al. Nature Biotechnology 2012.

Sequentially acting Sox transcription factors show coordinated binding patterns through development.

In a collaboration with Jonas Muhr's lab we have been studying the genome-wide binding patterns of Sox2, Sox3 and Sox11 in ES, NPC and post-mitotic neurons, respectively, and found that Sox factors often bind in proximity of genes that will be first activated at the subsequent developmental stage.
Bergsland,Ramskold et al. Genes & Development 2011.

 
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