OSCR

MeCP2 gene dosage-dependent neurodevelopmentally restricted defects arise by aberrant activation of cell fate-determining bivalent genes.

Code ↔ Paper

18 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 18 matches · 2 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
  1. [1] § Methods › Computational analysis › RNA-seq data analysis and integration ↔ 03_RNAseq_analysis/02_star_alignment.sh, lines 46–99 · score 0.98 · GeneCounts, SortedByCoordinate, alignIntronMax, alignSJoverhangMin, outFilterMismatchNoverReadLmax, outSAMtype
  2. [2] § Methods › Computational analysis › SAMMY-seq bioinformatics analysis ↔ 06_SAMMY_seq/01_process_fastq.sh, lines 193–275 · score 0.97 · MarkDuplicates, PCR duplicates, extendReads, normalizeUsing, mapping quality, binSize
  3. [3] § Methods › Computational analysis › SAMMY-seq bioinformatics analysis ↔ 06_SAMMY_seq/02b_sammy_analysis_blacklisted.py, lines 150–202 · score 0.89 · extendReads, binSize, bamCoverage, RPKM normalization, BigWig, SAMMY seq
  4. [4] § Methods › Computational analysis › CUT&Tag data processing and analysis ↔ 06_SAMMY_seq/01_process_fastq.sh, lines 193–275 · score 0.85 · PCR duplicates, mapping quality, bamCoverage, bigWig, Alignments, Trim
  5. [5] § Methods › Computational analysis › CUT&Tag data processing and analysis ↔ 02_CpG_enrichment/integrate_rnaseq.R, lines 41–97 · score 0.83 · transcript database, TxDb.Mmusculus.UCSC.mm10.knownGene, nearest genes, TSS regions, mapping, Peak
  6. [6] § Methods › Computational analysis › RNA-seq data analysis and integration ↔ 03_RNAseq_analysis/04_deseq2_analysis.R, lines 149–215 · score 0.82 · variance stabilizing transformation, DESeq2, log2FC, log2 fold change, VST, padj
  7. [7] § Methods › Computational analysis › CUT&Tag data processing and analysis ↔ 04_binding_expression_integration/integrate_genebody_rnaseq.py, lines 177–237 · score 0.80 · binding expression correlation, exogenous signal, endogenous signal, log2 fold changes, gene expression, MeCP2
  8. [8] § Methods › Computational analysis › CUT&Tag data processing and analysis ↔ 04_binding_expression_integration/peak_expression_correlation.py, lines 225–289 · score 0.79 · peak enrichment ratios, binding expression correlation, log2 fold changes, MeCP2 enrichment, aggregated, DEA
  9. [9] § Methods › Computational analysis › Smarcb1 binding analysis and integration ↔ 07_visualization/01_metaprofiles.sh, lines 47–124 · score 0.79 · plotHeatmap, computeMatrix, plotProfile, Metaprofiles, width, bp
  10. [10] § Methods › Computational analysis › CUT&Tag data processing and analysis ↔ 02_CpG_enrichment/cpg_enrichment_analysis.py, lines 1–24 · score 0.73 · pyBigWig, signal intensities, RPKM normalized, quantification, island, enrichment
  11. [11] § Methods › Computational analysis › CUT&Tag data processing and analysis ↔ 04_binding_expression_integration/integrate_rnaseq_base.py, lines 61–113 · score 0.70 · nearest genes, log2 fold change, endo signal, closest, RNA seq, padj
  12. [12] § Results › Mecp2 localization into CpG islands in both NPCs and Ns ↔ 06_SAMMY_seq/07_target_comparison_heatmap.py, lines 210–339 · score 0.57 · transcriptional end site, transcriptional start sites, located, heatmaps, upstream, genomic
  13. [13] § Results › Differential gene deregulation and phenotypic changes induced by Mecp2 overexpression in primary neuronal progenitor cells and neurons ↔ 03_RNAseq_analysis/05_functional_enrichment.R, lines 43–92 · score 0.57 · Gene Ontology, upregulated genes, downregulated genes, fold change, GO, enriched
  14. [14] § Results › Differential occupancy of CpG islands by Mecp2-endo and -exo in NPCs and Ns ↔ 03_RNAseq_analysis/05_functional_enrichment.R, lines 43–92 · score 0.55 · Gene Ontology, upregulated genes, downregulated genes, GO, enriched, enrichment
  15. [15] § Results › Differential gene deregulation and phenotypic changes induced by Mecp2 overexpression in primary neuronal progenitor cells and neurons ↔ 03_RNAseq_analysis/generate_de_table.R, lines 150–188 · score 0.54 · Benjamini Hochberg, detected genes, log2FC, log2 fold changes, protein, downregulated
  16. [16] § Results › Exogenous Mecp2 upregulated bivalent genes in NPCs by interacting with the SWI/SNF complex ↔ 04_binding_expression_integration/integrate_rnaseq_base.py, lines 268–322 · score 0.54 · Mecp2 enriched genes, Mecp2 enrichment, RNA seq, fold change, endo, CpG
  17. [17] § Results › Exogenous Mecp2 exerted a more pronounced effect on the chromatin state in NPCs than in Ns ↔ 06_SAMMY_seq/02_run_sammy_analysis.sh, the whole file · a weak match · score 0.53 · chromatin fraction, SAMMY seq, chromatin state, accessibility, S2S, S3
  18. [18] § Methods › Computational analysis › SAMMY-seq bioinformatics analysis ↔ 06_SAMMY_seq/02_run_sammy_analysis.sh, the whole file · a weak match · score 0.51 · chromatin fractions, SAMMY seq, S2S, S3

Paper

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The authors' code

Shell · 275 lines · 9.2 KB · no license · 2 matches

  1. #!/bin/bash
  2. #SBATCH --job-name=process_samples
  3. #SBATCH --output=logs/process_samples_%a.out
  4. #SBATCH --error=logs/process_samples_%a.err
  5. #SBATCH --nodes=1
  6. #SBATCH --ntasks=1
  7. #SBATCH --cpus-per-task=16
  8. #SBATCH --mem=64G
  9. #SBATCH --time=24:00:00
  10. #SBATCH --partition=workq
  11. #SBATCH --array=1-34%10 # Update based on the number of files
  13. # Error handling
  14. set -e # Exit on error
  15. set -u # Exit on undefined variable
  17. # Activate conda environment with required tools (BWA, samtools, picard, bamCoverage)
  18. conda activate snakemake # Adjust to your environment name
  20. # Set WORKDIR to your working directory
  21. WORKDIR="" # e.g., "/path/to/sammy_seq/analysis"
  22. cd $WORKDIR
  24. # Directory setup
  25. FASTQ_DIR="${WORKDIR}/../DATA/Sammy_Seq_fastq"
  26. OUTPUT_DIR="${WORKDIR}/results"
  27. # Need to set up BWA index for mm10 genome
  28. BWA_GENOME_DIR="${WORKDIR}/mm10"
  29. BLACKLIST_FILE="${WORKDIR}/mm10-blacklist.v2.bed"
  30. THREADS=16 # Using all CPUs allocated to the job
  32. # Create a directory for trimmed reads
  33. mkdir -p $OUTPUT_DIR/trimmed
  34. mkdir -p $OUTPUT_DIR/bam/temp
  35. mkdir -p logs
  37. # Download blacklist file if it doesn't exist
  38. if [ ! -f "$BLACKLIST_FILE" ]; then
  39. echo "Downloading mm10 blacklist file..."
  40. mkdir -p $(dirname $BLACKLIST_FILE)
  41. wget -O $BLACKLIST_FILE https://www.encodeproject.org/files/ENCFF547MET/@@download/ENCFF547MET.bed.gz
  42. gunzip -f $BLACKLIST_FILE.gz
  43. fi
  45. # Check if the FASTQ directory exists
  46. if [ ! -d "$FASTQ_DIR" ]; then
  47. echo "Error: FASTQ directory $FASTQ_DIR does not exist"
  48. exit 1
  49. fi
  50. echo "Using FASTQ directory: $FASTQ_DIR"
  52. # Create output directories
  53. mkdir -p $OUTPUT_DIR/bam
  54. mkdir -p logs
  56. # Check if the filtered_sample_list.txt exists
  57. if [ ! -f "filtered_sample_list.txt" ]; then
  58. echo "Error: filtered_sample_list.txt not found"
  59. echo "Please run check_number_of_files.sh first to generate the file list"
  60. exit 1
  61. fi
  63. # Count how many files we have
  64. FILE_COUNT=$(wc -l < filtered_sample_list.txt)
  65. echo "Found $FILE_COUNT files in the filtered sample list"
  67. # Display the first few files to verify
  68. echo -e "\nFirst 10 files to process:"
  69. head -n 10 filtered_sample_list.txt
  71. # Check if the array size matches the number of files
  72. if [[ "$SLURM_ARRAY_TASK_MAX" ]]; then
  73. ARRAY_SIZE=$((SLURM_ARRAY_TASK_MAX))
  74. if [ "$ARRAY_SIZE" != "$FILE_COUNT" ]; then
  75. echo "Warning: Array size ($ARRAY_SIZE) does not match the number of files ($FILE_COUNT)"
  76. echo "For optimal processing, you should cancel this job and resubmit with:"
  77. echo "sbatch --array=1-${FILE_COUNT}%10 $0"
  78. fi
  79. else
  80. echo "Note: Running in non-array mode or array information not available"
  81. fi
  83. # Get the FASTQ file for this array job
  84. FASTQ=$(sed -n "${SLURM_ARRAY_TASK_ID}p" filtered_sample_list.txt)
  85. if [ -z "$FASTQ" ]; then
  86. echo "Error: No file found for task ID ${SLURM_ARRAY_TASK_ID}"
  87. exit 1
  88. fi
  89. FASTQ="$FASTQ_DIR/$FASTQ"
  91. if [ ! -f "$FASTQ" ]; then
  92. echo "Error: FASTQ file $FASTQ not found"
  93. exit 1
  94. fi
  96. # Get base name for output files
  97. BASE=$(basename $FASTQ _R1_001.fastq.gz)
  98. echo "Processing $BASE..."
  100. # Create a directory to store trimmed adapter files if it doesn't exist
  101. ADAPTER_DIR="$WORKDIR/adapters"
  102. mkdir -p $ADAPTER_DIR
  103. ADAPTER_FILE="$ADAPTER_DIR/TruSeq3-SE-2.fa"
  105. # Create adapter file if it doesn't exist
  106. if [ ! -f "$ADAPTER_FILE" ]; then
  107. echo "Creating TruSeq3-SE-2.fa adapter file..."
  108. cat > "$ADAPTER_FILE" << 'EOL'
  109. >TruSeq3_IndexedAdapter
  110. AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC
  111. >TruSeq3_UniversalAdapter
  112. AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTA
  113. EOL
  114. fi
  116. # Step 1: Trim reads using Trimmomatic as specified in the paper
  117. TRIMMED_FASTQ="$OUTPUT_DIR/trimmed/${BASE}.trimmed.fastq.gz"
  118. if [ -f "$TRIMMED_FASTQ" ]; then
  119. echo "Trimmed file already exists, skipping trimming step..."
  120. else
  121. echo "Trimming reads with Trimmomatic..."
  122. trimmomatic SE $FASTQ $TRIMMED_FASTQ \
  123. ILLUMINACLIP:$ADAPTER_FILE:2:30:10 \
  124. SLIDINGWINDOW:4:15 \
  125. MINLEN:36
  126. fi
  128. # Step 2: Align with BWA as specified in the paper
  129. echo "Aligning with BWA..."
  130. # Check if BWA index exists and is valid, if not create it
  131. BWA_INDEX_FILES=("$BWA_GENOME_DIR/mm10.amb" "$BWA_GENOME_DIR/mm10.ann" "$BWA_GENOME_DIR/mm10.bwt" "$BWA_GENOME_DIR/mm10.pac" "$BWA_GENOME_DIR/mm10.sa")
  132. INDEX_VALID=true
  134. # Check if all index files exist and have non-zero size
  135. for index_file in "${BWA_INDEX_FILES[@]}"; do
  136. if [ ! -s "$index_file" ]; then
  137. INDEX_VALID=false
  138. echo "BWA index file $index_file is missing or empty."
  139. break
  140. fi
  141. done
  143. # Even if all files exist, perform a more thorough validation by attempting to use the index
  144. if [ "$INDEX_VALID" = true ]; then
  145. echo "Testing BWA index validity..."
  146. # Create a small test FASTQ with a few reads
  147. TEST_FASTQ="${BWA_GENOME_DIR}/test_reads.fastq"
  148. echo -e "@test_read\nACGTACGTACGTACGTACGT\n+\nIIIIIIIIIIIIIIIIIIII" > "$TEST_FASTQ"
  150. # Try to align the test read - redirect stderr to capture any errors
  151. TEST_OUTPUT=$(bwa mem "$BWA_GENOME_DIR/mm10" "$TEST_FASTQ" 2>&1 || true)
  153. # Check if the output contains error messages related to index files
  154. if echo "$TEST_OUTPUT" | grep -q -E "(Can't|Cannot|failed|error|Unexpected end of file)"; then
  155. INDEX_VALID=false
  156. echo "BWA index validation failed with error:"
  157. echo "$TEST_OUTPUT" | grep -E "(Can't|Cannot|failed|error|Unexpected end of file)"
  158. else
  159. echo "BWA index validation successful."
  160. fi
  162. # Clean up test file
  163. rm -f "$TEST_FASTQ"
  164. fi
  166. if [ "$INDEX_VALID" = false ]; then
  167. echo "BWA index is invalid or incomplete. Removing old index files and recreating..."
  168. # Remove any existing index files that might be corrupted
  169. rm -f ${BWA_INDEX_FILES[@]}
  170. # Also remove any potential temporary files that might have been created during a failed indexing
  171. rm -f "$BWA_GENOME_DIR/mm10."*
  172. mkdir -p $BWA_GENOME_DIR
  174. # Check if reference genome exists
  175. if [ ! -f "$WORKDIR/references/mm10.fa" ]; then
  176. echo "Error: Reference genome file $WORKDIR/references/mm10.fa not found"
  177. exit 1
  178. fi
  180. # Check available disk space before indexing
  181. GENOME_SIZE=$(du -b "$WORKDIR/references/mm10.fa" | cut -f1)
  182. REQUIRED_SPACE=$((GENOME_SIZE * 5)) # BWA index typically requires ~5x the genome size
  183. AVAILABLE_SPACE=$(df -B1 "$BWA_GENOME_DIR" | awk 'NR==2 {print $4}')
  185. if [ "$AVAILABLE_SPACE" -lt "$REQUIRED_SPACE" ]; then
  186. echo "Error: Not enough disk space for BWA indexing. Need at least $((REQUIRED_SPACE/1024/1024/1024)) GB, but only $((AVAILABLE_SPACE/1024/1024/1024)) GB available."
  187. exit 1
  188. fi
  190. echo "Creating BWA index. This may take a while..."
  191. bwa index -p $BWA_GENOME_DIR/mm10 "$WORKDIR/references/mm10.fa"
  193. # Verify index was created successfully
  194. for index_file in "${BWA_INDEX_FILES[@]}"; do
  195. if [ ! -s "$index_file" ]; then
  196. echo "Error: Failed to create BWA index file $index_file"
  197. exit 1
  198. fi
  199. done
  200. else
  201. echo "BWA index is valid and complete."
  202. fi
  204. # Check if BAM file already exists
  205. if [ -f "$OUTPUT_DIR/bam/${BASE}.bam" ]; then
  206. echo "BAM file already exists, skipping alignment step..."
  207. else
  208. # Align with BWA using parameters from the paper
  209. echo "Performing BWA alignment..."
  210. bwa mem -t $THREADS $BWA_GENOME_DIR/mm10 $OUTPUT_DIR/trimmed/${BASE}.trimmed.fastq.gz > $OUTPUT_DIR/bam/${BASE}.sam
  212. # Convert SAM to BAM
  213. echo "Converting SAM to BAM..."
  214. samtools view -bS $OUTPUT_DIR/bam/${BASE}.sam > $OUTPUT_DIR/bam/${BASE}.bam
  215. rm $OUTPUT_DIR/bam/${BASE}.sam
  216. fi
  218. # Sort BAM if it exists but hasn't been sorted yet
  219. if [ -f "$OUTPUT_DIR/bam/${BASE}.bam" ]; then
  220. # Check if BAM is already sorted
  221. if ! samtools view -H "$OUTPUT_DIR/bam/${BASE}.bam" | grep -q 'SO:coordinate'; then
  222. echo "Sorting BAM..."
  223. samtools sort -@ $THREADS $OUTPUT_DIR/bam/${BASE}.bam -o $OUTPUT_DIR/bam/${BASE}.sorted.bam
  224. mv $OUTPUT_DIR/bam/${BASE}.sorted.bam $OUTPUT_DIR/bam/${BASE}.bam
  225. else
  226. echo "BAM file already sorted, skipping sorting step..."
  227. fi
  228. fi
  230. # Step 3: Mark and remove PCR duplicates using Picard
  231. if [ -f "$OUTPUT_DIR/bam/${BASE}.dedup.bam" ]; then
  232. echo "Deduplicated BAM already exists, skipping deduplication step..."
  233. else
  234. echo "Marking and removing PCR duplicates with Picard..."
  235. picard MarkDuplicates \
  236. I=$OUTPUT_DIR/bam/${BASE}.bam \
  237. O=$OUTPUT_DIR/bam/${BASE}.dedup.bam \
  238. M=$OUTPUT_DIR/bam/${BASE}.metrics.txt \
  239. REMOVE_DUPLICATES=true \
  240. TMP_DIR=$OUTPUT_DIR/bam/temp
  241. fi
  243. # Step 4: Filter by mapping quality (q>=1) as in the paper
  244. if [ -f "$OUTPUT_DIR/bam/${BASE}.filtered.bam" ]; then
  245. echo "Filtered BAM already exists, skipping filtering step..."
  246. else
  247. echo "Filtering by mapping quality..."
  248. samtools view -q 1 -b $OUTPUT_DIR/bam/${BASE}.dedup.bam > $OUTPUT_DIR/bam/${BASE}.filtered.bam
  249. fi
  251. # Index BAM if needed
  252. if [ ! -f "$OUTPUT_DIR/bam/${BASE}.filtered.bam.bai" ]; then
  253. echo "Indexing BAM..."
  254. samtools index $OUTPUT_DIR/bam/${BASE}.filtered.bam
  255. else
  256. echo "BAM index already exists, skipping indexing step..."
  257. fi
  259. # Step 5: Create bigWig file
  260. if [ -f "$OUTPUT_DIR/bigwig/${BASE}.bw" ]; then
  261. echo "BigWig file already exists, skipping bigWig creation step..."
  262. else
  263. echo "Creating bigWig for $BASE..."
  264. bamCoverage \
  265. --bam $OUTPUT_DIR/bam/${BASE}.filtered.bam \
  266. --outFileName $OUTPUT_DIR/bigwig/${BASE}.bw \
  267. --binSize 50 \
  268. --normalizeUsing RPKM \
  269. --effectiveGenomeSize 2652783500 \
  270. --blackListFileName $BLACKLIST_FILE \
  271. --extendReads 250 \
  272. --numberOfProcessors $THREADS
  273. fi
  275. echo "Processing complete for $BASE"

01_process_fastq.sh at commit a378313, no license · at the source

Overview

Authors: Mirko Luoni1,2, Michal Kubacki2, Serena Gea Giannelli2, Francesca Morosi1,2, Claudia Di Berardino2, Angelo Iannielli1,2, Alessandro Sessa3, Gaia Colasante2, Emanuele Di Patrizio Soldateschi4, Chiara Lanzuolo4,5, Vania Broccoli1,2
ORCID iDs: Mirko Luoni, Serena Gea Giannelli, Claudia Di Berardino, Alessandro Sessa, Gaia Colasante, Chiara Lanzuolo, Vania Broccoli
  1. Institute of Neuroscience, National Research Council (CNR),Milan, Italy
  2. Stem Cell and Neurogenesis Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute,Milan, Italy
  3. Neuroepigenetics Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute,Milan, Italy
  4. INGM Istituto Nazionale Genetica Molecolare Romeo ed Enrica Invernizzi,Milan, Italy
  5. Institute of Biomedical Technologies, National Research Council (CNR),Milan, Italy
Institutions: National Research Council (Italy); IRCCS Ospedale San Raffaele (Italy); Istituto Nazionale Genetica Molecolare (Italy)
Journal: Nature communications, volume 17, issue 1, article 3225
Dates: received 2 June 2025; accepted 4 March 2026; published online 23 April 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s41467-026-71432-w · PMID 42026056 · PMCID PMC13106735 · OpenAlex W7155387614
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), mouse (organism), other condition (population), cellular / molecular (subfield)
Methods: Spectral & time-frequency, Statistics, Smoothing, state filtering, decompositions, Preprocessing, Connectivity
Keywords: Epigenetics, Molecular neuroscience, Gene expression, Gene regulation
MeSH: Gene Dosage*, Methyl-CpG-Binding Protein 2*, Animals, CpG Islands, Humans, Mice, Neural Stem Cells, Neurodevelopment, Neurons, Rett Syndrome, Transcriptional Activation (* major topic)
Topic: Genetics and Neurodevelopmental Disorders (Genetics, Biochemistry, Genetics and Molecular Biology), according to OpenAlex
Funding: International Rett Syndrome Foundation (IRSF) (4002)
Citations: cited by 1 paper (Europe PMC); 89 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repositories

Its files are read in the Code ↔ Paper reader above, with 18 matches between paragraphs and lines of code.

Zenodo 18257503

License: CC-BY-4.0
State: the link answers, verified on 29 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: the text, “CUT&Tag data processing and analysis”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: pandas (23 files), Matplotlib (21 files), NumPy (21 files), seaborn (18 files), SciPy (14 files), tidyverse (8 files), BEDTools (5 files), deepTools (5 files), SAMtools (5 files), clusterProfiler (3 files), DESeq2 (2 files), ggplot2 (2 files), pheatmap (2 files), FastQC (1 file), scikit-learn (1 file), STAR (1 file), statsmodels (1 file), Subread (featureCounts) (1 file)
Availability: 1 check, the latest on 29 September 2026: the link answers (HTTP 200)
  • 29 September 2026: the link answers (HTTP 200)
51 files
At the source:

u9856112956-prog/mecp2_analysis

License: none: the authors keep all their rights
State: the link answers, verified on 29 September 2026
Evidence: files inventoried
Commit: a378313b060fefaa5e141b10bffedc0a6e2f36bd, 15 January 2026
Languages: Python (23), R (14), Shell (13)
Size: 51 files, 50 scripts
Software Heritage: not archived
Found in: the Zenodo archive record
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: pandas (23 files), Matplotlib (21 files), NumPy (21 files), seaborn (18 files), SciPy (14 files), tidyverse (8 files), BEDTools (5 files), deepTools (5 files), SAMtools (5 files), clusterProfiler (3 files), DESeq2 (2 files), ggplot2 (2 files), pheatmap (2 files), FastQC (1 file), scikit-learn (1 file), STAR (1 file), statsmodels (1 file), Subread (featureCounts) (1 file)
Availability: 1 check, the latest on 29 September 2026: the link answers
  • 29 September 2026: the link answers
51 files
At the source: github.com/u9856112956-prog/MeCP2_analysis/tree/v0.1

The paper's code and data availability statement is in the Data section.

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Data

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Code and data availability statement

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Read it in the paper: doi.org/10.1038/s41467-026-71432-w.

Versions

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Version 1, 29 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 11 authors, 4 keywords, 11 MeSH terms, 1 funder, 88 references.

Cite

This paper

Luoni, M., Kubacki, M., Giannelli, S. G., Morosi, F., Di Berardino, C., Iannielli, A., Sessa, A., Colasante, G., Di Patrizio Soldateschi, E., Lanzuolo, C., & Broccoli, V. (2026). MeCP2 gene dosage-dependent neurodevelopmentally restricted defects arise by aberrant activation of cell fate-determining bivalent genes. Nature communications, 17(1), 3225. https://doi.org/10.1038/s41467-026-71432-w

BibTeX

@article{luoni2026mecp2,
author = {Luoni, Mirko and Kubacki, Michal and Giannelli, Serena Gea and Morosi, Francesca and Di Berardino, Claudia and Iannielli, Angelo and Sessa, Alessandro and Colasante, Gaia and Di Patrizio Soldateschi, Emanuele and Lanzuolo, Chiara and Broccoli, Vania},
title = {{MeCP2 gene dosage-dependent neurodevelopmentally restricted defects arise by aberrant activation of cell fate-determining bivalent genes}},
journal = {Nature communications},
year = {2026},
month = apr,
volume = {17},
number = {1},
pages = {3225},
publisher = {Nature Publishing Group},
issn = {2041-1723},
doi = {10.1038/s41467-026-71432-w},
url = {https://doi.org/10.1038/s41467-026-71432-w},
pmid = {42026056},
pmcid = {PMC13106735}
}

RIS

TY - JOUR
AU - Luoni, Mirko
AU - Kubacki, Michal
AU - Giannelli, Serena Gea
AU - Morosi, Francesca
AU - Di Berardino, Claudia
AU - Iannielli, Angelo
AU - Sessa, Alessandro
AU - Colasante, Gaia
AU - Di Patrizio Soldateschi, Emanuele
AU - Lanzuolo, Chiara
AU - Broccoli, Vania
TI - MeCP2 gene dosage-dependent neurodevelopmentally restricted defects arise by aberrant activation of cell fate-determining bivalent genes
T2 - Nature communications
J2 - Nat Commun
PY - 2026
DA - 2026/04/23
VL - 17
IS - 1
SP - 3225
SN - 2041-1723
PB - Nature Publishing Group
DO - 10.1038/s41467-026-71432-w
UR - https://doi.org/10.1038/s41467-026-71432-w
LA - en
ER -

CSL-JSON

{
"id": "10.1038/s41467-026-71432-w",
"type": "article-journal",
"title": "MeCP2 gene dosage-dependent neurodevelopmentally restricted defects arise by aberrant activation of cell fate-determining bivalent genes",
"container-title": "Nature communications",
"author": [
{
"family": "Luoni",
"given": "Mirko"
},
{
"family": "Kubacki",
"given": "Michal"
},
{
"family": "Giannelli",
"given": "Serena Gea"
},
{
"family": "Morosi",
"given": "Francesca"
},
{
"family": "Di Berardino",
"given": "Claudia"
},
{
"family": "Iannielli",
"given": "Angelo"
},
{
"family": "Sessa",
"given": "Alessandro"
},
{
"family": "Colasante",
"given": "Gaia"
},
{
"family": "Di Patrizio Soldateschi",
"given": "Emanuele"
},
{
"family": "Lanzuolo",
"given": "Chiara"
},
{
"family": "Broccoli",
"given": "Vania"
}
],
"container-title-short": "Nat Commun",
"volume": "17",
"issue": "1",
"page": "3225",
"DOI": "10.1038/s41467-026-71432-w",
"PMID": "42026056",
"PMCID": "PMC13106735",
"ISSN": "2041-1723",
"publisher": "Nature Publishing Group",
"URL": "https://doi.org/10.1038/s41467-026-71432-w",
"language": "en",
"issued": {
"date-parts": [
[
2026,
4,
23
]
]
}
}

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