Home > Publications database > Spatial transcriptomics map of the embryonic mouse brain - a tool to explore neurogenesis. > print |
001 | 284831 | ||
005 | 20240303005600.0 | ||
024 | 7 | _ | |a 10.1242/bio.060151 |2 doi |
024 | 7 | _ | |a pmid:37855382 |2 pmid |
024 | 7 | _ | |a altmetric:156946960 |2 altmetric |
037 | _ | _ | |a DKFZ-2023-02127 |
041 | _ | _ | |a English |
082 | _ | _ | |a 570 |
100 | 1 | _ | |a Di Marco, Barbara |0 P:(DE-He78)3f238cb47096916308d99eabbce682e9 |b 0 |e First author |u dkfz |
245 | _ | _ | |a Spatial transcriptomics map of the embryonic mouse brain - a tool to explore neurogenesis. |
260 | _ | _ | |a Cambridge |c 2023 |b Company |
336 | 7 | _ | |a article |2 DRIVER |
336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1697807411_29650 |2 PUB:(DE-HGF) |
336 | 7 | _ | |a ARTICLE |2 BibTeX |
336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
500 | _ | _ | |a #EA:A231#LA:A231# |
520 | _ | _ | |a The developing brain has a well-organized anatomical structure comprising different types of neural and non-neural cells. Stem cells, progenitors and newborn neurons tightly interact with their neighbouring cells and tissue microenvironment, and this intricate interplay ultimately shapes the output of neurogenesis. Given the relevance of spatial cues during brain development, we acknowledge the necessity for a spatial transcriptomics map accessible to the neurodevelopmental community. To fulfil this need, we generated spatially resolved RNA sequencing (RNAseq) data from embryonic day 13.5 mouse brain sections immunostained for mitotic active neural and vascular cells. Unsupervised clustering defined specific cell type populations of diverse lineages and differentiation states. Differential expression analysis revealed unique transcriptional signatures across specific brain areas, uncovering novel features inherent to particular anatomical domains. Finally, we integrated existing single-cell RNAseq datasets into our spatial transcriptomics map, adding tissue context to single-cell RNAseq data. In summary, we provide a valuable tool that enables the exploration and discovery of unforeseen molecular players involved in neurogenesis, particularly in the crosstalk between different cell types. |
536 | _ | _ | |a 311 - Zellbiologie und Tumorbiologie (POF4-311) |0 G:(DE-HGF)POF4-311 |c POF4-311 |f POF IV |x 0 |
588 | _ | _ | |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de |
650 | _ | 7 | |a Gene expression atlas |2 Other |
650 | _ | 7 | |a Mouse telencephalon |2 Other |
650 | _ | 7 | |a Neurodevelopment |2 Other |
650 | _ | 7 | |a Single-cell and spatial transcriptomics data integration |2 Other |
700 | 1 | _ | |a Vázquez-Marín, Javier |b 1 |
700 | 1 | _ | |a Monyer, Hannah |0 P:(DE-HGF)0 |b 2 |
700 | 1 | _ | |a Centanin, Lázaro |0 0000-0003-3889-4524 |b 3 |
700 | 1 | _ | |a Alfonso, Julieta |0 P:(DE-He78)3f128e570b3a9009d7b52a0523af43dd |b 4 |e Last author |u dkfz |
773 | _ | _ | |a 10.1242/bio.060151 |g Vol. 12, no. 10, p. bio060151 |0 PERI:(DE-600)2632264-X |n 10 |p bio060151 |t Biology open |v 12 |y 2023 |x 2046-6390 |
909 | C | O | |o oai:inrepo02.dkfz.de:284831 |p VDB |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 0 |6 P:(DE-He78)3f238cb47096916308d99eabbce682e9 |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 2 |6 P:(DE-HGF)0 |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 4 |6 P:(DE-He78)3f128e570b3a9009d7b52a0523af43dd |
913 | 1 | _ | |a DE-HGF |b Gesundheit |l Krebsforschung |1 G:(DE-HGF)POF4-310 |0 G:(DE-HGF)POF4-311 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-300 |4 G:(DE-HGF)POF |v Zellbiologie und Tumorbiologie |x 0 |
914 | 1 | _ | |y 2023 |
915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b BIOL OPEN : 2022 |d 2023-08-22 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2023-08-22 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2023-08-22 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0320 |2 StatID |b PubMed Central |d 2023-08-22 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0501 |2 StatID |b DOAJ Seal |d 2021-10-20T13:41:03Z |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0500 |2 StatID |b DOAJ |d 2021-10-20T13:41:03Z |
915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b DOAJ : Anonymous peer review |d 2021-10-20T13:41:03Z |
915 | _ | _ | |a Creative Commons Attribution CC BY (No Version) |0 LIC:(DE-HGF)CCBYNV |2 V:(DE-HGF) |b DOAJ |d 2021-10-20T13:41:03Z |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2023-08-22 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |d 2023-08-22 |
915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2023-08-22 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2023-08-22 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1190 |2 StatID |b Biological Abstracts |d 2023-08-22 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2023-08-22 |
915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |d 2023-08-22 |
915 | _ | _ | |a Article Processing Charges |0 StatID:(DE-HGF)0561 |2 StatID |d 2023-08-22 |
915 | _ | _ | |a Fees |0 StatID:(DE-HGF)0700 |2 StatID |d 2023-08-22 |
920 | 2 | _ | |0 I:(DE-He78)A231-20160331 |k A231 |l A231 AG Alfonso |x 0 |
920 | 1 | _ | |0 I:(DE-He78)A231-20160331 |k A231 |l A231 AG Alfonso |x 0 |
920 | 0 | _ | |0 I:(DE-He78)A231-20160331 |k A231 |l A231 AG Alfonso |x 0 |
980 | _ | _ | |a journal |
980 | _ | _ | |a VDB |
980 | _ | _ | |a I:(DE-He78)A231-20160331 |
980 | _ | _ | |a UNRESTRICTED |
Library | Collection | CLSMajor | CLSMinor | Language | Author |
---|