OSCR

A human-specific microRNA controls the timing of excitatory synaptogenesis.

Code ↔ Paper

27 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 27 matches
  1. [1] § Methods › SNP analysis ↔ 03_pLNA_GRCh38.p13_Ens107/pLNA_experiment/SNP_analysis/star_align.sh, lines 1–40 · score 1.00 · ConcordantPair, SeparateSAMold, alignEndsProtrude, alignIntronMax, alignMatesGapMax, alignSJDBoverhangMin
  2. [2] § Methods › Ribosomal depletion sequencing of the time course dataset ↔ 03_pLNA_GRCh38.p13_Ens107/pLNA_experiment/SNP_analysis/star_align.sh, lines 1–40 · score 1.00 · ConcordantPair, SeparateSAMold, alignEndsProtrude, alignIntronMax, alignMatesGapMax, alignSJDBoverhangMin
  3. [3] § Methods › Proteomics analysis of the time course dataset ↔ 01_TimeCourse_MultiOmics/Proteomics/Proteomics_R/proteomics.reference.datagen.DEA.SE.Rmd, lines 199–237 · score 0.80 · eBayes, lmFit, topTable, limma, imputed, Protein
  4. [4] § Results › miR-1229-3p targets a network of genes involved in mitochondrial – ER homeostasis ↔ 07_Sy5y_GRCh38.p13_Ens107/Figures/Targets/Plot_Targets.Rmd, lines 233–295 · score 0.71 · ARL6IP1, EIF4G2, SYNJ2BP, Dlgap4, Hipk2, genes
  5. [5] § Methods › Ribosomal Depletion sequencing analysis of the mouse dataset from Whipple et al. ↔ 01_TimeCourse_MultiOmics/RNA_GRCm38.p6_Genc/Long_RNA_Mouse/generateSE_salmon_Whipple.Rmd, lines 18–26 · score 0.67 · GRCm38.p6, release M20, Gencode, salmon, mouse, Genes
  6. [6] § Methods › GO-Term analysis ↔ 03_pLNA_GRCh38.p13_Ens107/pLNA_experiment/longRNA_R/GO_Terms/GO_1229_symbol.Rmd, lines 39–49 · score 0.60 · nodeSize, TopGO, hs, db, symbol, Ontology
  7. [7] § Methods › GO-Term analysis ↔ 03_pLNA_GRCh38.p13_Ens107/pLNA_experiment/longRNA_R/GO_Terms/GO_1229_symbol_down.Rmd, lines 41–51 · score 0.60 · nodeSize, TopGO, hs, db, symbol, Ontology
  8. [8] § Methods › enrichMiR analyses ↔ 03_pLNA_GRCh38.p13_Ens107/pLNA_experiment/longRNA_R/enrichMiR.Rmd, lines 89–122 · score 0.60 · scanMiR, enrichMiR, EnrichPlots, areamir, Siteoverlap
  9. [9] § Methods › enrichMiR analyses ↔ 07_Sy5y_GRCh38.p13_Ens107/longRNA_R/EnrichMiR/enrichMiR.Rmd, lines 77–107 · score 0.60 · scanMiR, enrichMiR, EnrichPlots, areamir, Siteoverlap
  10. [10] § Results › The ncRNAome during human excitatory synaptogenesis ↔ 09_Conservation_analyses/miRNA_conservation/Figures/structural_conservation.Rmd, lines 135–210 · score 0.59 · seed mutation, structural conservation, intercept, slope, miRNA, Pairwise
  11. [11] § Methods › Plots ↔ 07_Sy5y_GRCh38.p13_Ens107/longRNA_R/DataPrep/generateDEA_salmon.Rmd, lines 31–46 · score 0.58 · SEtools, log2FC, logFC, sechm, RNA
  12. [12] § Methods › Plots ↔ 07_Sy5y_GRCh38.p13_Ens107/longRNA_R/DataPrep/generateDEA_salmonTX.Rmd, lines 35–50 · score 0.58 · SEtools, log2FC, logFC, sechm, RNA
  13. [13] § Results › miR-1229-3p targets a network of genes involved in mitochondrial – ER homeostasis ↔ 07_Sy5y_GRCh38.p13_Ens107/Figures/GO_GSEA/GO_1229_10nM_FDR005_symbol_figures_general.Rmd, lines 165–196 · score 0.58 · Cellular Component, fold enrichment, GO Term, Bars, DEA, position
  14. [14] § Methods › miRNA conservation analysis ↔ 09_Conservation_analyses/miRNA_conservation/src/miRNA_conservation.Rmd, lines 370–428 · score 0.57 · pairwise alignments, sequence identity, conservation, Precursors, miRNA, human
  15. [15] § Methods › Clustering of the ribosomal depletion time course dataset ↔ 00_functions/clustering.R, lines 94–113 · score 0.57 · silhouette width, Medoids, dissimilarity, pam, matrix, Clustering
  16. [16] § Methods › Target conservation analysis ↔ 09_Conservation_analyses/target_conservation/CompareChimpHuman_BindingSites.Rmd, lines 271–286 · score 0.56 · scanMiR, binding sites, chimp, scanned, hsa, conservation
  17. [17] § Results › The ncRNAome during human excitatory synaptogenesis ↔ 09_Conservation_analyses/miRNA_conservation/src/miRNA_conservation.R, lines 32–73 · score 0.56 · panTro6, miRNAs, gorilla, orangutan, marmoset, blast
  18. [18] § Methods › Clustering of the small RNA time course dataset ↔ 01_TimeCourse_MultiOmics/smallRNA/SmallRNA_R/smallRNA_Clustering.Rmd, lines 162–172 · score 0.55 · walktrap, graph, small RNAs, distance, loess, numeric
  19. [19] § Results › miR-1229-3p controls mitochondrial function during human excitatory synaptogenesis ↔ 06_Ca-Imaging/Mitochondrial_activation/R/Ca-Figures_MCMA.Rmd, lines 350–385 · score 0.54 · peak duration, Ca imaging, pLNA, activation, mitochondria
  20. [20] § Results › The ncRNAome during human excitatory synaptogenesis ↔ 09_Conservation_analyses/miRNA_conservation/src/miRNA_conservation.Rmd, lines 80–211 · score 0.54 · seed region, miRNAS, mature, orthologs, alignment, mismatches
  21. [21] § Methods › Clustering of the small RNA time course dataset ↔ 01_TimeCourse_MultiOmics/Figures_Omics/SmallRNA_Mouse/Whipple_2020_SmallRNA_Figures.Rmd, lines 285–302 · score 0.54 · walktrap, graph, small RNAs, distance, loess, numeric
  22. [22] § Methods › miRNA conservation analysis ↔ 09_Conservation_analyses/miRNA_conservation/src/miRNA_conservation.R, lines 75–114 · score 0.53 · Reciprocal blast, hit, orthologs, mismatches, Genome, miRNA
  23. [23] § Methods › Calcium imaging ↔ 06_Ca-Imaging/Mitochondrial_activation/R/Analysis Spike It_MCMA.Rmd, lines 26–64 · score 0.52 · SpikeIt, baseline, video, spiked, peaks, amplitude
  24. [24] § Methods › Calcium imaging ↔ 06_Ca-Imaging/Time_Course/R/Analysis Spike It TimeCourse.Rmd, lines 26–45 · score 0.52 · SpikeIt, baseline, video, spiked, peaks, amplitude
  25. [25] § Results › The ncRNAome during human excitatory synaptogenesis ↔ 09_Conservation_analyses/miRNA_conservation/Figures/structural_conservation.Rmd, lines 112–130 · score 0.52 · structural conservation, miRNAs, mature, alignment, mismatches, primates
  26. [26] § Methods › Image analysis ↔ 02_Image_Analysis/NeuronMorphology/TimeCourse/Synapse_Quantification/R/Synapse_Figures.rmd, lines 29–62 · score 0.52 · dendritic area, co cluster, masked, synapse
  27. [27] § Methods › Label-free proteomics › Protein search and quantification ↔ 01_TimeCourse_MultiOmics/Proteomics/Proteomics_R/proteomics.reference.datagen.DEA.SE.Rmd, lines 120–166 · score 0.52 · stripped sequence, proteome, SpectronautTM, protein, ID, filtering

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

The paper is loaded when this pane is shown.

The authors' code

Shell · 45 lines · 1.2 KB · no license · 2 matches

  1. #! /bin/bash
  3. ref=/mnt/reference/reference/Homo_sapiens/Ensembl/GRCh38.p13/Annotation/Release_107-2022/
  5. cd /mnt/schratt/internData/2022_soutschek_Ngn2pLNAs_polyARNA/11_2022/X204SC22021444-Z01-F010/01.RawData/
  7. for f in ./*_*/; do
  8. f2=`basename $f`
  9. echo $f2;
  11. STAR --genomeDir $ref/star_index \
  12. --genomeLoad NoSharedMemory \
  13. --readFilesIn "$f"*_1.fq.gz "$f"*_2.fq.gz \
  14. --readFilesCommand zcat \
  15. --runThreadN 12 \
  16. --alignIntronMax 1000000 \
  17. --alignMatesGapMax 1000000 \
  18. --alignSJDBoverhangMin 1 \
  19. --alignSJoverhangMin 8 \
  20. --outFilterMatchNmin 30 \
  21. --outFilterMismatchNmax 10 \
  22. --outFilterMismatchNoverLmax 0.05 \
  23. --outFilterMultimapNmax 50 \
  24. --twopassMode Basic \
  25. --chimSegmentMin 15 \
  26. --chimJunctionOverhangMin 15 \
  27. --chimScoreMin 15 \
  28. --chimScoreSeparation 10 \
  29. --chimOutType Junctions SeparateSAMold\
  30. --outFileNamePrefix ../../star/$f2. \
  31. --outSAMtype BAM Unsorted \
  32. --alignEndsProtrude 3 ConcordantPair \
  33. --outSAMattributes All \
  34. --outMultimapperOrder Random > ../../star/$f2.log
  36. samtools sort -l 9 -m 3500M -@ 12 ../../star/$f2.Aligned.out.bam -o ../../star/$f2.sorted.bam &&
  37. samtools index ../../star/$f2.sorted.bam &&
  38. rm ../../star/$f2.Aligned.out.bam
  40. done

star_align.sh at commit 8bffbcf, no license · at the source

Overview

Authors: Michael Soutschek1,2, Alessandra Lo Bianco1, Simon Galkin1, Tatjana Wüst1, Koen Wentinck2, David Colameo1, Tomas Germade1, Fridolin Gross1,3, Lukas von Ziegler4, Johannes Bohacek4, Betina Elfving5, Pierre-Luc Germain1,4,6, Jochen Winterer1, Tatjana Kleele2, Gerhard Schratt1
ORCID iDs: Michael Soutschek, Simon Galkin, David Colameo, Tomas Germade, Johannes Bohacek, Betina Elfving, Pierre-Luc Germain, Jochen Winterer, Tatjana Kleele, Gerhard Schratt
  1. Laboratory of Systems Neuroscience, Institute for Neuroscience, Department of Health Science and Technology, ETH Zurich,Zurich, Switzerland
  2. Department of Biology, Institute of Biochemistry, ETH Zurich,Zurich, Switzerland
  3. Present Address: CNRS UMR5164 ImmunoConcEpT, University of Bordeaux,Bordeaux, France
  4. Laboratory of Molecular and Behavioural Neuroscience, Institute for Neuroscience, Department of Health Science and Technology, ETH Zurich,Zurich, Switzerland
  5. Translational Neuropsychiatry Unit A601, Department of Clinical Medicine, Aarhus University,Aarhus, Denmark
  6. Lab of Statistical Bioinformatics, IMLS, University of Zurich,Zurich, Switzerland
Institutions: Institute for Neuroscience (Switzerland); ETH Zurich (Switzerland); Université de Bordeaux (France); Aarhus University (Denmark); University of Zurich (Switzerland)
Journal: Nature communications, volume 17, issue 1, article 8365
Dates: received 27 October 2023; accepted 10 June 2026; published online 6 July 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1038/s41467-026-74753-y · PMID 42409844 · PMCID PMC13473650 · OpenAlex W4387389556
Open access: gold, a free copy (OpenAlex)
Preprint: doi:10.1101/2023.10.04.560889
Status: code verified
Categories: human (organism), cellular / molecular (subfield)
Methods: Statistics, Smoothing, state filtering, decompositions, Preprocessing, Machine learning, Single-unit activity, calcium imaging
Keywords: Molecular neuroscience, Cellular neuroscience
MeSH: MicroRNAs*, Neurogenesis*, Synapses*, DNA, Mitochondrial, Humans, Induced Pluripotent Stem Cells, Mitochondria, Mitophagy, Neurodevelopment, Neurons, Synaptic Transmission (* major topic)
Topic: MicroRNA in disease regulation (Cancer Research, Biochemistry, Genetics and Molecular Biology), according to OpenAlex
Funding: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) (32NE30_189486)
Citations: not cited yet (Europe PMC); 90 references in the paper

Abstract

Neural circuit development in the human cortex is considerably prolonged in comparison to non-human primates, a trait that contributes to the remarkable cognitive capacity of modern humans. Here, we explore the regulatory role of non-coding RNAs, which dramatically expanded during brain evolution, in synapse development of human induced pluripotent stem-cell derived neurons. We found that inhibition of a human-specific microRNA, miR-1229-3p, alters the trajectory of human neuronal maturation and enhances excitatory synaptic transmission. Transcriptome analysis following miR-1229 knockdown revealed a downregulation of mitochondrial DNA (mtDNA) encoded genes. We further show that miR-1229 regulates mitochondrial morphology, mtDNA abundance as well as mitophagy, and that stimulation of mitochondrial metabolism rescues decreased calcium buffering in miR-1229-3p depleted neurons. Accordingly, miR-1229 directly targets an entire network of genes involved in mitochondrial function and ER-associated protein homeostasis. Our findings reveal an important function of human-specific miR-1229-3p in developmental timing of human synaptogenesis and generally implicate non-coding RNAs in the control of human connectivity and cognition.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repositories

Its files are read in the Code ↔ Paper reader above, with 27 matches between paragraphs and lines of code.

michasou/Soutschek_et_al.-2026

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 8bffbcf497b30d3c25e4ee71ada6d19da449e4f5, 10 May 2026
Languages: R (176), Shell (10)
Size: 877 files, 186 scripts
Software Heritage: not archived
Found in: “Data availability”
Holds: README, 165 notebooks
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: ggplot2 (82 files), tidyverse (81 files), cowplot (57 files), data.table (39 files), emmeans (36 files), rstatix (33 files), edgeR (24 files), ggpubr (23 files), lmerTest (18 files), Plotly (12 files), igraph (8 files), reshape2 (7 files), pheatmap (6 files), ComplexHeatmap (4 files), easystats (3 files), limma (3 files), lme4 (3 files), patchwork (2 files), SAMtools (2 files), STAR (2 files), BCFtools (1 file), circlize (1 file), reticulate (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
187 files
At the source: github.com/michasou/Soutschek_et_al.-2026

Zenodo 20109278

License: CC-BY-4.0
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: “Data availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
At the source:

Code availability

The app to perform calcium imaging analysis can be accessed at: https://ethz-ins.org/SpikeIt.

Reproduced under the paper's license (CC BY), from the paper cited above.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 186 scripts, each with its path and the digest of its content;
  • 27 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data availability

RNA sequencing data have been deposited to the GEO database and are available under the accession GSE244444 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE244444).

The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE90 partner repository with the dataset identifier PXD045809.

The igNeurons time course data can be additionally accessed via:

https://ethz-ins.org/igNeuronsTimeCourse

Scripts used for data analysis and figure generation (including source and further raw data) can be found at:https://github.com/michasou/Soutschek_et_al.-2026

We generated a stable version of this repository at:

10.5281/zenodo.20109278

RNA sequencing data from other publicly available datasets can be accessed from:

Ribosomal depletion and small RNA sequencing data of mouse neuronal differentiations with NGN2 (GSE140838) [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE140838]; Single-Cell sequencing data of human NGN2-neurons cultured together with astrocytes (E-MTAB-10632) [https://www.ebi.ac.uk/biostudies/ArrayExpress/studies/E-MTAB-10632?query=E-MTAB-10632]; Single-cell sequencing data of the developing human cortex obtained by Trevino et al. (GSE162170) [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE162170] and Single-cell sequencing data of the developing human cortex obtained by Mayer et al. (dbGaP: phs000989) [https://dbgap.ncbi.nlm.nih.gov/beta/study/phs000989.v6.p1/#study]. Source data for the main figures are provided in this paper.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 15 authors, 2 keywords, 11 MeSH terms, 1 funder, 90 references.

Cite

This paper

Soutschek, M., Lo Bianco, A., Galkin, S., Wüst, T., Wentinck, K., Colameo, D., Germade, T., Gross, F., von Ziegler, L., Bohacek, J., Elfving, B., Germain, P.-L., Winterer, J., Kleele, T., & Schratt, G. (2026). A human-specific microRNA controls the timing of excitatory synaptogenesis. Nature communications, 17(1), 8365. https://doi.org/10.1038/s41467-026-74753-y

BibTeX

@article{soutschek2026human,
author = {Soutschek, Michael and Lo Bianco, Alessandra and Galkin, Simon and Wüst, Tatjana and Wentinck, Koen and Colameo, David and Germade, Tomas and Gross, Fridolin and von Ziegler, Lukas and Bohacek, Johannes and Elfving, Betina and Germain, Pierre-Luc and Winterer, Jochen and Kleele, Tatjana and Schratt, Gerhard},
title = {{A human-specific microRNA controls the timing of excitatory synaptogenesis}},
journal = {Nature communications},
year = {2026},
month = jul,
volume = {17},
number = {1},
pages = {8365},
publisher = {Nature Publishing Group},
issn = {2041-1723},
doi = {10.1038/s41467-026-74753-y},
url = {https://doi.org/10.1038/s41467-026-74753-y},
pmid = {42409844},
pmcid = {PMC13473650}
}

RIS

TY - JOUR
AU - Soutschek, Michael
AU - Lo Bianco, Alessandra
AU - Galkin, Simon
AU - Wüst, Tatjana
AU - Wentinck, Koen
AU - Colameo, David
AU - Germade, Tomas
AU - Gross, Fridolin
AU - von Ziegler, Lukas
AU - Bohacek, Johannes
AU - Elfving, Betina
AU - Germain, Pierre-Luc
AU - Winterer, Jochen
AU - Kleele, Tatjana
AU - Schratt, Gerhard
TI - A human-specific microRNA controls the timing of excitatory synaptogenesis
T2 - Nature communications
J2 - Nat Commun
PY - 2026
DA - 2026/07/06
VL - 17
IS - 1
SP - 8365
SN - 2041-1723
PB - Nature Publishing Group
DO - 10.1038/s41467-026-74753-y
UR - https://doi.org/10.1038/s41467-026-74753-y
LA - en
ER -

CSL-JSON

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