In a very productive collaboration, led by Maria Kasper, we find that cellular identity in the hair follicle and epidermis is shaped by overlapping differentiation and spatial signatures.

Using the power of single-cell RNA-seq, we discover the neurons that control goosebumps and nipple erection. A great collaboration with Patrik Ernfors’ group at KI, with fantastic mouse work by Alessandro Furlan and single-cell RNA-seq analysis by Gioele La Manno.

A new method for spatially resolved transcriptomics, based on capturing RNA from tissue sections onto barcoded microarrays. Great work by the groups of Jonas Frisén and Joakim Lundeberg, with contributions from Simone Codeluppi in my group.

In collaboration with Goncalo Castelo-Branco, we describe unexpected heterogeneity of oligodendrocytes in the mouse brain.

In collaboration with professor Marco Prinz (Univeristy of Freiburg), we demonstrate that brain perivascular macrophages, like micoglia, originate from the yolk sac.

Kasper Karlsson defends his thesis “Counting molecules in cell-free DNA and single-cell RNA” on March 29, 9.00 in Samuelssonsalen (Tomtebodavägen 6).

In collaboration with professor Tibor Harkany, we present a new method that combines electrophysiology with single-cell RNA sequencing. This new strategy makes it possible to simultaneously obtain electrical, morphological and molecular properties of single cells, and should help improve our understanding of the functional properties of neurons that underlie computation in the brain.

As previously announced, I have been selected to receive the 2015 Erik K. Fernström prize. Today, I’ve decided to give it away.

Sten Linnarsson has been appointed Professor of Molecular Systems Biology, effective July 1, 2015.

From ki.se: “Sten Linnarsson (…) has been awarded the Eric K Fernström Prize for 2015. He is receiving the prize for establishing himself as an internationally leading researcher within the area single cell analysis, where he contributed with both publicized work focusing on methods and with studies where this technology has been used for investigations which have resulted in breakthrough biological findings.”

We applied single-cell analysis to the mouse cortex and hippocampus - to our knowledge the most complex tissues analyzed in this way by single-cell methods. We describe 47 distinct subclasses of cells, and find that transcription factors form a complex, layered regulatory code.

We describe an amplification-free method for sequencing of cell-free DNA, even from low levels of starting material.

We performed a comprehensive molecular census of the dorsal root ganglion by analyzing 622 single neurons. We found 11 distinct types of sensory neurons, and were able to map them back to the tissue using combinatorial immunohistochemistry.

Single-cell RNA-seq has one major drawback: since cells are isolated as a single-cell suspension from the source tissue, spatial context is lost. Recently, several solutions have been proposed, collectively called ‘spatial transcriptomics’. Here, we show that a standard single-cell RNA seq protocol can be applied to laser capture microdissected material. By sampling a tissue slice systematically (in a grid), a spatial transcriptome image can be built. In contrast to other recently proposed methods (e.g. FISSEQ), our approach requires only standard generally-available instruments.

Una Kjällquist defends her thesis Sequencing Cancer on May 28, 9.30 in Samuelssonsalen (Tomtebodavägen 6).

Myelodysplastic syndrome is a leukemic syndrome that often progresses to life-threatening AML. In a new study, we show that mutations found in the bulk of the tumor originate in individual hematopoietic stem cells, demonstrating clearly that this disease is driven by the stem cells.

Nature Methods has declared Single-cell sequencing its Method of the Year for 2013, which obviously I think is a great choice. The January 2014 issue comes with news features by Tal Nawy and Kelly Rae Chi, and reviews by Paul Blainey and Steve Quake on single-cell genomics, good friend Rickard Sandberg on single-cell transcriptomics, and James Eberwine and colleagues on multimodal single-cell measurement technologies.

One of the major challenges in single-cell transcriptomics is the distortion introduced by the unavoidable amplification step. In this new paper, we show that nearly all this distortion can be removed by labeling individual cDNA molecules with short, random sequences.