Michael Hagemann-Jensen

Dr. Michael Hagemann-Jensen

orcid

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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4 May 2020 in Nature Biotechnology
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Journal Article
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MHMichael Hagemann-Jensen
Michael Hagemann-Jensen
CZChristoph Ziegenhain
Christoph Ziegenhain
PCPing Chen
Ping Chen
DRDaniel Ramsköld
Daniel Ramsköld
GHGert-Jan Hendriks
Gert-Jan Hendriks
RSRickard Sandberg
Rickard Sandberg

2 January 2019 in Nature
Verified
Journal Article
Closed access
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ALAnton J. M. Larsson
Anton J. M. Larsson
PJPer Johnsson
Per Johnsson
MHMichael Hagemann-Jensen
Michael Hagemann-Jensen
LHLeonard Hartmanis
Leonard Hartmanis
OFOmid R. Faridani
Omid R. Faridani
RSRickard Sandberg
Rickard Sandberg

31 October 2016 in Nature Biotechnology
Verified
Journal Article
Closed access
OFOmid R Faridani
Omid R Faridani
IAIlgar Abdullayev
Ilgar Abdullayev
MHMichael Hagemann-Jensen
Michael Hagemann-Jensen
JSJohn P Schell
John P Schell
FLFredrik Lanner
Fredrik Lanner
RSRickard Sandberg
Rickard Sandberg

30 May 2022 in Nature Biotechnology
Verified
Journal Article
Open access
PDF file
MHMichael Hagemann-Jensen
Michael Hagemann-Jensen
CZChristoph Ziegenhain
Christoph Ziegenhain
RSRickard Sandberg
Rickard Sandberg
Current single-cell RNA sequencing (scRNA-seq) methods with high cellular throughputs sacrifice full-transcript coverage and often sensitivity. Here we describe Smart-seq3xpress, which miniaturizes and streamlines the Smart-seq3 protocol to substantially reduce reagent use and increase cellular throughput. Smart-seq3xpress analysis of peripheral blood mononuclear cells resulted in a granular atlas complete with common and rare cell types. Compared with droplet-based single-cell RNA sequencing that sequences RNA ends, the additional full-transcript coverage revealed cell-type-associated isoform variation.

8 December 2023 in Science
Verified
Journal Article
Closed access
CECamilla Engblom
Camilla Engblom
KTKim Thrane
Kim Thrane
QLQirong Lin
Qirong Lin
AAAlma Andersson
Alma Andersson
HTHosein Toosi
Hosein Toosi
JFJonas Frisén
Jonas Frisén
The spatial distribution of lymphocyte clones within tissues is critical to their development, selection, and expansion. We have developed spatial transcriptomics of variable, diversity, and joining (VDJ) sequences (Spatial VDJ), a method that maps B cell and T cell receptor sequences in human tissue sections. Spatial VDJ captures lymphocyte clones that match canonical B and T cell distributions and amplifies clonal sequences confirmed by orthogonal methods. We found spatial congruency between paired receptor chains, developed a computational framework to predict receptor pairs, and linked the expansion of distinct B cell clones to different tumor-associated gene expression programs. Spatial VDJ delineates B cell clonal diversity and lineage trajectories within their anatomical niche. Thus, Spatial VDJ captures lymphocyte spatial clonal architecture across tissues, providing a platform to harness clonal sequences for therapy.

24 September 2018 in Nature Protocols
Verified
Journal Article
Closed access
PDF file
MHMichael Hagemann-Jensen
Michael Hagemann-Jensen
IAIlgar Abdullayev
Ilgar Abdullayev
RSRickard Sandberg
Rickard Sandberg
OFOmid R Faridani
Omid R Faridani