<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter>Xuefei Yuan</submitter><organism>Pan paniscus</organism><software>cell ranger (version 5.0.1), STARsolo (version 2.7.9a)</software><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-15548</full_dataset_link><description>Single-nucleus RNA-seq was performed on the liver samples from adult chimpanzees and bonobos. Two individuals were included for both species. The single-nucleus libraries were generated using the 10X Chromium Next GEM Single Cell 3ʹ platform and sequenced on Illumina NextSeq 550. This dataset is part of a larger evolutionary study of mammalian livers across 17 species.</description><repository>biostudies-arrayexpress</repository><sample_protocol>Nucleic Acid Extraction - Each sample was homogenized with a micropestle in 400 μl ice-cold homogenization buffer (250 mM sucrose, 25 mM KCl, 5 mM MgCl2, 10 mM Tris-HCl (pH 8), 0.1% IGEPAL, 1 μM DTT, 0.4 U/μl Murine RNase Inhibitor (New England BioLabs, cat# M0314L), 0.2 U/μl SUPERas-In (Ambion, cat# AM2694), and cOmplete Protease Inhibitor Coctail (Roche, cat# 11 836 145 001)). The homogenates were triturated gently by a P1000 tip for 10 times, incubated on ice for 5-10 minutes, and then centrifuged at 100g for 1 minute at 4 °C to pellet any unlysed tissue chunks. The supernatant was transferred into another 1.5 mL Eppendorf tube and centrifuged at 400g for 4 minutes at 4 °C to collect nuclei. The nuclei were washed twice in 400 μl homogenization buffer and strained by a 40 μm Flowmi strainer (Sigma, BAH136800040) during the second wash step to remove nuclei aggregates. The final nuclei pellet was resuspended in 30-50 μl Nuclei buffer (10X Genomics, PN-2000207). To estimate the nuclei concentration, nuclei aliquots were diluted in PBS with Hoechst and PI DNA dyes and counted on Countess II FL Automated Cell Counter (Thermo Fisher Scientific).</sample_protocol><sample_protocol>Library Construction - Around 15,000 -20,000 nuclei were used as input for the single-nuclei RNA-seq experiment. The Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 were used for generating the single-nuclei RNA-seq libraries following the manufacturer’s instructions. Libraries were quantified on a Qubit Fluorometer (Thermo Fisher Scientific) and the profiles were assessed on a Fragment Analyzer (Agilent) for quality control.</sample_protocol><sample_protocol>Sequencing - Libraries were sequenced on NextSeq 550 (Illumina, 28 cycles for Read 1, 56 cycles for Read 2, 8 cycles for i7 index). Each library has been sequenced multiple times for spiking-in quality control and for achieving a comparable number of reads per nucleus for all samples. Each sequencing run was carried out in four lanes.</sample_protocol><sample_protocol>Sample Collection - Livers were dissected from adult animals after euthanasia, cut into small pieces, and flash-frozen in a 1.5 or 2 mL Eppendorf tube in liquid nitrogen. RNA was extracted from tissue pieces for quality control. About 5-10 mg of liver tissue was used for each nuclei extraction.</sample_protocol><figure_sub>Organization</figure_sub><figure_sub>MINSEQE Score</figure_sub><figure_sub>Assays and Data</figure_sub><figure_sub>Processed Data</figure_sub><figure_sub>MAGE-TAB Files</figure_sub><data_protocol>Data Transformation - For each sample, we counted the UMI that mapped to the mature mRNA annotation (exons) and mapped to the pre-mature RNA annotation (exon + intron) separately. We then leveraged the high proportion of intronic UMI counts and total UMI counts that valid barcodes contained to distinguish them from the empty droplets. We used the total UMI counts (exon + intron) for the downstream analyses and provided the gene count matrices of the valid barcodes as processed data.</data_protocol><data_protocol>Sequence Alignment - Raw sequencing data were demultiplexed using cellranger mkfastq (v 5.0.1). Then STARsolo (v 2.7.9a) was used for the initial alignment and Unique Molecular Identifier (UMI) counting with the following parameters (--soloType CB_UMI_Simple –soloUMIlen 12 –readFilesCommand zcat –soloCBwhitelist 3M-february-2018.txt –clipAdapterType CellRanger4 –outFilterScoreMin 20 –soloCBmatchWLtype 1MM_multi_Nbase_pseudocounts –soloUMIfiltering MultiGeneUMI_CR –soloUMIdedup 1MM_CR –soloFeatures Gene GeneFull –soloMultiMappers Unique EM –outSJtype Standard). We enabled counting of multiple-mapping reads using the Expectation-Maximization (EM) algorithm implemented in STARsolo. Reads were aligned to the respective genomes (chimpanzee: Pan_tro_3.0, GCA_000001515.5; bonobo: panpan1.1, GCA_000258655.2) and Ensembl transcriptomes re-annotated with bulk liver RNA-seq data (release 104).</data_protocol><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><instrument_platform>10x Chromium</instrument_platform><instrument_platform>NextSeq 550</instrument_platform><study_type>single nucleus RNA sequencing</study_type><species>Pan paniscus</species><pubmed_authors>Henrik Kaessmann</pubmed_authors><pubmed_authors>Xuefei Yuan</pubmed_authors><pubmed_authors>Leticia Rodríguez-Montes</pubmed_authors></additional><is_claimable>false</is_claimable><name>Single-nucleus RNA-seq of adult chimpanzee and bonobo livers</name><description>Single-nucleus RNA-seq was performed on the liver samples from adult chimpanzees and bonobos. Two individuals were included for both species. The single-nucleus libraries were generated using the 10X Chromium Next GEM Single Cell 3ʹ platform and sequenced on Illumina NextSeq 550. This dataset is part of a larger evolutionary study of mammalian livers across 17 species.</description><dates><release>2026-07-13T00:00:00Z</release><modification>2026-07-13T01:00:40.007Z</modification><creation>2025-09-04T16:13:31.27Z</creation></dates><accession>E-MTAB-15548</accession><cross_references><ENA>ERP179655</ENA><Biostudies>E-MTAB-15550</Biostudies><Biostudies>E-MTAB-15549</Biostudies><Biostudies>E-MTAB-15545</Biostudies><Biostudies>E-MTAB-15544</Biostudies><Biostudies>E-MTAB-15547</Biostudies><Biostudies>E-MTAB-15546</Biostudies><Biostudies>E-MTAB-15541</Biostudies><Biostudies>E-MTAB-15552</Biostudies><Biostudies>E-MTAB-15551</Biostudies><Biostudies>E-MTAB-15553</Biostudies><EFO>EFO_0002944</EFO><EFO>EFO_0004170</EFO><EFO>EFO_0004917</EFO><EFO>EFO_0009809</EFO><EFO>EFO_0005518</EFO><EFO>EFO_0003816</EFO><EFO>EFO_0004184</EFO></cross_references></HashMap>