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Publication Highlights

bioRxiv 2023
Dimension Reduction by Spatial Components Analysis Improves Pattern Detection in Multivariate Spatial Data

In recent years, spatial transcriptomics has emerged as a powerful tool for studying gene expression in complex tissues. To analyze such data, we introduce a multivariate statistical approach for pattern recognition called SPACO. Our algorithm constructs a low-dimensional projection of the data that maximizes Moran’s I, which is a measure of spatial autocorrelation. This approach mitigates non-spatial variation and outperforms PCA for pre-processing. Furthermore, our method provides a calibrated, powerful test of spatial gene expression that excels in robustness and specificity. By identifying spatially expressed genes, we can gain insights into the spatial organization and functional relationships of genes within complex tissues.


Kleinenkuhnen N, Köhler D, Baar T, Nikopoulou C, Kondylis V, Schmid M, Tessarz P, Tresch A. (2023) Dimension Reduction by Spatial Components Analysis Improves Pattern Detection in Multivariate Spatial Data. bioRxiv.:2023.10.12.562016. doi:10.1101/2023.10.12.562016

Lab Animal 2023
Group size planning for breedings of gene-modified mice and other organisms following Mendelian inheritance

Colony management of gene-modified animals is time-consuming, costly and affected by random events related to Mendelian genetics, fertility and litter size. Careful planning is mandatory to ensure successful outcomes using the least number of animals, hence adhering to the 3R principles of animal welfare. Here we have developed an R package, accessible also through an interactive public website, that optimizes breeding design by providing information about the optimal number of breedings needed to obtain defined breeding outcomes, taking into account specific species, strain, or line properties and success probability. Our software also enables breeding planning for balanced male-to-female ratio or single-sex experiments. We show that, for single-sex designs, the necessary number of breedings is at least doubled compared to the use of all born animals. While the presented tool provides preset parameters for the laboratory mouse, it can be readily used for any other species.


Milchevskaya V, Bugnon P, Ten Buren EB, Vanhecke D, Brand F, Tresch A, Buch T. (2023) Group size planning for breedings of gene-modified mice and other organisms following Mendelian inheritance. Lab Animal. 2023 Jul 24:1-6. doi:10.1038/s41684-023-01213-1

Scientific Reports 2022
Pseudotime analysis reveals novel regulatory factors for multigenic onset and monogenic transition of odorant receptor expression

During their maturation from horizontal basal stem cells, olfactory sensory neurons (OSNs) are known to select exactly one out of hundreds of olfactory receptors (ORs) and express it on their surface, a process called monogenic selection. Monogenic expression is preceded by a multigenic phase during which several OR genes are expressed in a single OSN. Here, we perform pseudotime analysis of a single cell RNA-Seq dataset of murine olfactory epithelium to precisely align the multigenic and monogenic expression phases with the cell types occurring during OSN differentiation. In combination with motif analysis of OR gene cluster-associated enhancer regions, we identify known and novel transcription (co-)factors (Ebf1, Lhx2, Ldb1, Fos and Sspp2) and chromatin remodelers (Kdm1a, Eed and Zmynd8) associated with OR expression. The inferred temporal order of their activity suggests novel mechanisms contributing to multigenic OR expression and monogenic selection.


Hussainy M, Korsching S I, Tresch A. (2022) Pseudotime analysis reveals novel regulatory factors for multigenic onset and monogenic transition of odorant receptor expression. Scientific Reports 12, 16183 (2022). doi:110.1038/s41598-022-20106-w

Science 2016
TT-seq maps the human transient transcriptome

RNA expression is related to protein abundance and cellular function. However, the amounts of RNA generated at any one time-point have been difficult to determine. Schwalb et al. developed a method, transient transcriptome sequencing (TT-Seq), to collect and sequence all RNA segments synthesized over 5 minutes. Because 5 minutes is not long enough to fully degrade even the most transient RNA, this method can detect the synthesis of most RNA without bias. Applying this method to human K562 cells, TT-Seq detected thousands of noncoding transcripts, providing a snapshot of RNA synthesis rates and RNA half-lives, and full-length maps of short-lived RNAs such as enhancers and short intergenic noncoding RNAs.


Schwalb B, Michel M, Zacher B, Hauf KF, Demel C, Tresch A, Gagneur J, Cramer P. (2016) TT-seq maps the human transient transcriptome. Science (80-83). 352(6290):1225–1228. doi:10.1126/science.aad9841

All Publications

since 2017

Von Stein P, Seitz L, Wienemann H, Hohmann C, Baar T, Baldus S, Halbach M. (2023) Early in-hospital discontinuation of aspirin following coronary stent implantation in patients with indication for direct oral anticoagulation. Frontiers in Cardiovascular Medicine 10: 1265452. doi:10.3389/fcvm.2023.1265452

Nikopoulou C, Kleinenkuhnen N, Parekh S, Sandoval T, Ziegenhain C, Schneider F, Giavalisco P, Donahue KF, Vesting AJ, Kirchner M, Bozukova M, Vossen C, Altmüller J, Wunderlich T, Sandberg R, Kondylis V, Tresch A, Tessarz P. (2023) Spatial and Single-Cell Profiling of the Metabolome, Transcriptome and Epigenome of the Aging Mouse Liver. Nat Aging 2662-8465. doi:10.1038/s43587-023-00513-y

Kleinenkuhnen N, Köhler D, Baar T, Nikopoulou C, Kondylis V, Schmid M, Tessarz P, Tresch A. (2023) Dimension Reduction by Spatial Components Analysis Improves Pattern Detection in Multivariate Spatial Data. bioRxiv.:2023.10.12.562016. doi:10.1101/2023.10.12.562016

Rubio K, Müller JM, Mehta A, Watermann I, Olchers T, Koch I, Wessels S, Schneider MA, Araujo-Ramos T, Singh I, Kugler C, Stoleriu MG, Kriegsmann M, Eichhorn M, Muley T, Merkel OM, Braun T, Ammerpohl O, Reck M, Tresch A, Barreto G. (2023) Preliminary Results from the EMoLung Clinical Study Showing Early Lung Cancer Detection by the LC Score. Discov Onc 14, 181. doi:10.1007/s12672-023-00799-9

Milchevskaya V, Bugnon P, Ten Buren EB, Vanhecke D, Brand F, Tresch A, Buch T. (2023) Group size planning for breedings of gene-modified mice and other organisms following Mendelian inheritance. Lab Animal. 2023 Jul 24:1-6. doi:10.1038/s41684-023-01213-1

Rubio K, Romero-Olmedo AJ, Sarvari P, Swaminathan G, Ranvir VP, Rogel-Ayala DG, Cordero J, Günther S, Mehta A, Bassaly B, Braubach P, Wygrecka M, Gattenlöhner S, Tresch A, Braun T, Dobreva G, Rivera MN, Singh I, Graumann J, Barreto G. (2023) Non-canonical integrin signaling activates EGFR and RAS-MAPK-ERK signaling in small cell lung cancer. Theranostics. 2023;13(8):2384. doi:10.7150/thno.79493

Müller JM, Moos K, Baar T, Zumer K, Tresch A. (2023) Nuclear export is a limiting factor in eukaryotic mRNA metabolism. bioRxiv. doi:10.1101/2023.05.04.539375


▾ 2022

Rosendahl AS, Schonborn K, Baar T, Kleinenkuhnen N, Tresch A, Eckes B, Moinzadeh P, Krieg T. (2023) Single cell RNA sequencing reveals specific subsets in Systemic Sclerosis fibroblast cultures. Journal of Investigative Dermatology, 142.12 (2022): S182. doi:10.26226/m.62fa008e5b695e001a542055

Campos-Martin R, Schmickler S, Goel M, Schneeberger K, Tresch A. (2023) Reliable genotyping of recombinant genomes using a robust hidden Markov model. Plant Physiology, 2023 Mar 22:kiad191. doi:10.1093/plphys/kiad191

Möllenhoff K, Tresch A. (2023) Investigating non-inferiority or equivalence in time-to-event data under non-proportional hazards. Lifetime Data Analysis, 1-25. doi:10.1007/s10985-023-09589-5

Werner DJ, Wenzel N, Abusalim N, Kiesslich R, Baar T, Tresch A, Rey JW. (2022) Unmasking lower gastrointestinal bleeding under administration of norepinephrine. World Journal of Radiology 14 (12), 375. doi:10.4329/wjr.v14.i12.375

Locatelli G, Marques‐Ferreira F, Katsoulas A, Kalaitzaki V, Krueger M, Ingold‐Heppner B, Walthert S, Sankowski R, Prazeres da Costa O, Dolga A, Huber M. (2022) IGF1R expression by adult oligodendrocytes is not required in the steady‐state but supports neuroinflammation. Glia. 2022 Nov 17. doi:10.1002/glia.24299

Von Stein P, Seitz L, Wienemann H, Hohmann C, Baar T, Baldus S, Halbach M. (2022) Early in-hospital discontinuation of aspirin following coronary stent implantation in patients with indication for direct oral anticoagulation. European Heart Journal, 2022 Oct, 43 (Supplement 2) ehac544-2035. doi:10.1093/eurheartj/ehac544.2035

Hussainy M, Korsching S I, Tresch A. (2022) Pseudotime analysis reveals novel regulatory factors for multigenic onset and monogenic transition of odorant receptor expression. Scientific Reports 12, 16183 (2022). doi:110.1038/s41598-022-20106-w

Baar T, Dümcke S, Gressel S, Schwalb B, Dilthey A, Cramer P, Tresch A. (2022) RNA transcription and degradation of Alu retrotransposons depends on sequence features and evolutionary history. G3 Genes|Genomes|Genetics. 12(5) doi:10.1093/G3JOURNAL/JKAC054


▾ 2021

Wienemann H, Meyer A, Mauri V, Baar T, Adam M, Baldus S, Halbach M. (2021) Comparison of Resting Full-cycle Ratio (RFR) and Fractional Flow Reserve (FFR) in a German real-world cohort. Frontiers in Cardiovascular Medicine, 2021:1973. doi:10.3389/fcvm.2021.744181

Failmezger H, Zwing N, Tresch A, Korski K, Schmich F. (2021) Computational Tumor Infiltration Phenotypes Enable the Spatial and Genomic Analysis of Immune Infiltration in Colorectal Cancer. Front Oncol. 11:567 doi:10.3389/FONC.2021.552331

Werner DJ, Baar T, Kiesslich R, Wenzel N, Abusalim N, Tresch A, Rey JW. (2021) Endoscopic hemostasis makes the difference: Angiographic treatment in patients with lower gastrointestinal bleeding. World J Gastrointest Endosc. 13(7):221–232 doi:10.4253/wjge.v13.i7.221

Schlusche AK, Vay SU, Kleinenkuhnen N, Sandke S, Campos-Martín R, Florio M, Huttner W, Tresch A, Roeper J, Rueger MA, et al. (2021) Developmental HCN channelopathy results in decreased neural progenitor proliferation and microcephaly in mice. Proc Natl Acad Sci U S A 118(35):e2009393118 doi:10.1073/pnas.2009393118


▾ Earlier

  See also the Google Scholar profile of Achim Tresch.

Schwarzer R, Jiao H, Wachsmuth L, Tresch A, Pasparakis M. (2020) FADD and Caspase-8 Regulate Gut Homeostasis and Inflammation by Controlling MLKL- and GSDMD-Mediated Death of Intestinal Epithelial Cells. Immunity. 52(6):978-993.e6 doi:10.1016/j.immuni.2020.04.002

Buch T, Moos K, Ferreira FM, Fröhlich H, Gebhard C, Tresch A. (2019) Benefits of a factorial design focusing on inclusion of female and male animals in one experiment. J Mol Med. 97(6):871–877 doi:10.1007/s00109-019-01774-0

Failmezger H, Dursun E, Dümcke S, Endele M, Poron D, Schroeder T, Krug A, Tresch A. (2019) Clustering of samples with a tree-shaped dependence structure, with an application to microscopic time lapse imaging. Murphy R, editor. Bioinformatics. 35(13):2291–2299 doi:10.1093/bioinformatics/bty939

Failmezger H, Lempe J, Khadem N, Cartolano M, Tsiantis M, Tresch A. (2018) MowJoe: A method for automated-high throughput dissected leaf phenotyping. Plant Methods. 14(1):1–9 doi:10.1186/s13007-018-0290-y

Rey JW, Dümcke S, Haschemi J, Tresch A, Borger D, Kirchner AC, Teubner D, Kiesslich R, Hoffman A. (2018) G-EYE advanced colonoscopy for improved polyp detection rates - A randomized tandem pilot study with different endoscopists. Z Gastroenterol. 56(5):488–494 doi:10.1055/s-0043-124089

Nguyen-Tat M, Cornelius C, Hoffman A, Tresch A, Krey J, Kiesslich R, Galle PR, Rey JW. (2018) The Manchester Triage System (MTS): A score for emergency management of patients with acute gastrointestinal bleeding. Z Gastroenterol. 56(5):479–487 doi:10.1055/s-0043-124194

Kiefer C, Severing E, Karl R, Bergonzi S, Koch M, Tresch A, Coupland G. (2017) Divergence of annual and perennial species in the Brassicaceae and the contribution of cis-acting variation at FLC orthologues. Mol Ecol. 26(13):3437–3457 doi:10.1111/mec.14084

Zacher B, Michel M, Schwalb B, Cramer P, Tresch A, Gagneur J. (2017) Accurate promoter and enhancer identification in 127 ENCODE and roadmap epigenomics cell types and tissues by GenoSTAN. PLoS One 12(1):e0169249 doi:10.1371/journal.pone.0169249

Stricker G, Engelhardt A, Schulz D, Schmid M, Tresch A, Gagneur J. (2017) GenoGAM: Genome-wide generalized additive models for ChIP-Seq analysis. Kelso J, editor. Bioinformatics. 33(15):2258–2265 doi:10.1093/bioinformatics/btx150