<HashMap><database>biostudies-arrayexpress</database><scores/><additional><omics_type>Metabolomics</omics_type><omics_type>Unknown</omics_type><omics_type>Transcriptomics</omics_type><omics_type>Genomics</omics_type><omics_type>Proteomics</omics_type><submitter>Luis Valor</submitter><instrument_platform>Illumina NovaSeq 6000</instrument_platform><instrument_platform>Chromium 10xGenomics</instrument_platform><study_type>RNA-seq of coding RNA from single cells</study_type><organism>Homo sapiens</organism><species>Homo sapiens</species><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-15129</full_dataset_link><description>Transcriptional dysregulation is among the most prominent molecular alterations in Huntington’s disease. It is not confined to brain but is also extended to peripheral tissues and cells, enabling minimally invasive screens aimed at identifying transcriptional surrogates of the health status in HD mutation carriers. In this study, we applied single-cell RNA-seq in peripheral blood mononuclear cells (PBMCs) to determine those cellular compartments that accumulate the most prominent gene expression changes as potential sources of reliable biomarkers.</description><repository>biostudies-arrayexpress</repository><sample_protocol>Sample Collection - Human volunteers were recruited through the Service of Neurology of the Hospital General Universitario Dr. Balmis (HGUDrB), and consisted on 4 controls (without the HD mutation) and 4 HD symptomatic patients, with equal representation of both sexes in each condition (2 women and 2 men) and balanced age. Human blood samples were collected in EDTA-K2 Vaccutainer tubes (BD) for isolation of peripheral blood mononuclear cells (PBMC) after a density gradient centrifugation using Pancoll human, 1.077 g/mL (PAN-Biotech) following this procedure: 1,300xg 15min, followed by a wash with 0.1M PBS 1,000xg 5min. Cells were immediately cryopreserved in two aliquotes per donor using the Demonstrated Protocol CG00039 RevD “Fresh Frozen Human PBMC for scRNA-seq” (10xGenomics).</sample_protocol><sample_protocol>Library Construction - We followed the Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 (Dual Index) protocol</sample_protocol><sample_protocol>Sequencing - The resulting libraries were sequenced in Illumina NovaSeq 6000 system to achieve 25,000 reads/cell (3’-GEX libraries) and 5,000 reads/cell (CMO libraries).</sample_protocol><sample_protocol>Nucleic Acid Extraction - For the first assay (SC1), we created two pools (CTRL and HD) from samples; briefly, an aliquot of each cryopreserved sample was thawed and washed following the Demonstrated Protocol CG00039 RevD “Fresh Frozen Human PBMC for scRNA-seq” (10xGenomics), and subsequently sorted in a FACSAria III (Becton Dickinson) to remove cell debris and platelets and to collect equal number of cellular events (~4,500). For the second assay (SC2), we repeated the same procedure with the same samples with the exception of including a prior labelling procedure for each individual sample using Cell Multiplexing Oligo (CMO) tags linked to cell-associated barcodes. Next, CTRL and HD pools were processed with the Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 (Dual Index) protocol to obtain single cell barcodes.</sample_protocol><figure_sub>Organization</figure_sub><figure_sub>MINSEQE Score</figure_sub><figure_sub>Assays and Data</figure_sub><figure_sub>MAGE-TAB Files</figure_sub><pubmed_authors>Luis Valor</pubmed_authors></additional><is_claimable>false</is_claimable><name>Single-cell RNA-seq of peripheral blood mononuclear cells from Huntington's disease patients and controls</name><description>Transcriptional dysregulation is among the most prominent molecular alterations in Huntington’s disease. It is not confined to brain but is also extended to peripheral tissues and cells, enabling minimally invasive screens aimed at identifying transcriptional surrogates of the health status in HD mutation carriers. In this study, we applied single-cell RNA-seq in peripheral blood mononuclear cells (PBMCs) to determine those cellular compartments that accumulate the most prominent gene expression changes as potential sources of reliable biomarkers.</description><dates><release>2025-12-31T00:00:00Z</release><modification>2025-12-31T02:02:51.289Z</modification><creation>2025-05-08T12:07:16.202Z</creation></dates><accession>E-MTAB-15129</accession><cross_references><ENA>ERP172412</ENA><EFO>EFO_0002944</EFO><EFO>EFO_0004170</EFO><EFO>EFO_0005684</EFO><EFO>EFO_0005518</EFO><EFO>EFO_0004184</EFO></cross_references></HashMap>