<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter>Xiaoyun Hu</submitter><organism>Panthera tigris altaica</organism><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-15936</full_dataset_link><description>Inbreeding leads to a reduction in genetic diversity and an elevated likelihood of expressing recessive defective genes, which adversely affect the development of the immune system and render individuals and populations more susceptible to carcinogenic factors, consequently heightening the risk of cancer. Through investigating the function and extent of immune cell interaction in peripheral blood mononuclear cells (PBMCs) of inbred individuals, one can gain a comprehensive understanding of the impact of inbreeding on various aspects of the immune system, including diversity, self-tolerance, immune responsiveness, susceptibility to diseases, and other related areas. Currently, the wild Amur tiger population in China exhibits a moderate degree of inbreeding, with a probability exceeding 90% that it will be deemed extinct within the forthcoming century. However, the impact of inbreeding on the immune system remains ambiguous, presenting numerous challenges for the development and implementation of conservation strategies. The present study presents, for the first time, a detailed single-cell sequencing atlas of peripheral blood samples obtained from Amur tigers, delineating eight distinct cell types. Research findings show that inbred individuals have a lower percentage of lymphocytes and cDC2 cells, as well as diminished intercellular interactions compared to non-inbred individuals. Meanwhile, inbred individuals exhibited significantly increased expression of signaling pathways such as TGFb, APRIL, BAG, GRN, and VISFATIN, which are closely associated with inflammation and cancer. Moreover, the WGCNA analysis unveiled the core gene regulatory network specific to inbred individuals, highlighting a robust correlation between inbreeding and the cancer-related gene YTHDC2. Our study presents a comprehensive analysis of PBMC characteristics in the Amur tigers and reveals the possibility of increased susceptibility to cancer and inflammation associated with inbreeding. These findings provide novel insights into the immune heterogeneity in the inbred Amur tiger and furnish valuable data supporting timely treatment for affected individuals.</description><repository>biostudies-arrayexpress</repository><sample_protocol>Sample Collection - All samples were collected with the informed consent of the owners, and the collection process was approved by the Laboratory Animal Welfare and Ethics Committee of Jilin Agricultural University.</sample_protocol><sample_protocol>Sequencing - Subsequently, high-throughput sequencing was conducted on the Illumina NovaSeq platform.</sample_protocol><sample_protocol>Library Construction - Firstly, the cell suspension was placed into Chromium microfluidic chips with 3' chemistry, and a 10x Chromium Controller (10X Genomics) was employed to barcode the chips. Afterward, the RNA from barcoded cells was reverse-transcribed, and sequencing libraries were constructed using the Chromium Single Cell 3' reagent kit (10X Genomics) according to the manufacturer's instructions.</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 - The 10XGenomics Cell Ranger pipeline was utilized with default parameters to demultiplex raw data and align it to the reference genome of the Amur tiger. Subsequently, each gene's unique molecule identifiers (UMIs) were quantified. Then, the star software of Cell Ranger 7.0.0 [26] was used for alignment. After the reads were aligned to the reference genome, the GTF annotation file was used for correction, and the exon region, intron region, and intergenic region were distinguished. The discrimination rule is: at least 50% of the reads aligned to the exon are recorded as the exon region, and the reads aligned to the non-exon region and intersected with the intron region are recorded as the intron region, and the remaining sequences are non-coding regions. Next, Cell Ranger is used to distinguish each cell's reads by the input data's barcode, and the number of cells in the sample, the number of reads of cell, and the number of detected genes are counted by filtering and screening. The specific steps are as follows: First, a desired number of cells (N, default 3000) is specified, and then the barcodes are sorted from high to low according to their respective UMI totals. The 99% quantile of the first N UMI values is taken as the maximum estimated UMI total (m), and the barcodes with a UMI number exceeding m/10 are used as the final captured cells. Finally, further filtration was performed using Seurat 3.1.0 [27] to remove multiple cells from the dataset to ensure the reliability and accuracy of the subsequent analysis results; the filtration criterion involved removing genes detected in fewer than three cells, as well as cells with gene expression below 200, and filtering out some of the foreign cells.</data_protocol><omics_type>Unknown</omics_type><omics_type>Transcriptomics</omics_type><omics_type>Genomics</omics_type><omics_type>Proteomics</omics_type><instrument_platform>Illumina NovaSeq X</instrument_platform><study_type>RNA-seq of coding RNA from single cells</study_type><species>Panthera tigris altaica</species><pubmed_authors>Xiaoyun Hu</pubmed_authors></additional><is_claimable>false</is_claimable><name>Gene expression and immune cell heterogeneity in inbred Amur tiger</name><description>Inbreeding leads to a reduction in genetic diversity and an elevated likelihood of expressing recessive defective genes, which adversely affect the development of the immune system and render individuals and populations more susceptible to carcinogenic factors, consequently heightening the risk of cancer. Through investigating the function and extent of immune cell interaction in peripheral blood mononuclear cells (PBMCs) of inbred individuals, one can gain a comprehensive understanding of the impact of inbreeding on various aspects of the immune system, including diversity, self-tolerance, immune responsiveness, susceptibility to diseases, and other related areas. Currently, the wild Amur tiger population in China exhibits a moderate degree of inbreeding, with a probability exceeding 90% that it will be deemed extinct within the forthcoming century. However, the impact of inbreeding on the immune system remains ambiguous, presenting numerous challenges for the development and implementation of conservation strategies. The present study presents, for the first time, a detailed single-cell sequencing atlas of peripheral blood samples obtained from Amur tigers, delineating eight distinct cell types. Research findings show that inbred individuals have a lower percentage of lymphocytes and cDC2 cells, as well as diminished intercellular interactions compared to non-inbred individuals. Meanwhile, inbred individuals exhibited significantly increased expression of signaling pathways such as TGFb, APRIL, BAG, GRN, and VISFATIN, which are closely associated with inflammation and cancer. Moreover, the WGCNA analysis unveiled the core gene regulatory network specific to inbred individuals, highlighting a robust correlation between inbreeding and the cancer-related gene YTHDC2. Our study presents a comprehensive analysis of PBMC characteristics in the Amur tigers and reveals the possibility of increased susceptibility to cancer and inflammation associated with inbreeding. These findings provide novel insights into the immune heterogeneity in the inbred Amur tiger and furnish valuable data supporting timely treatment for affected individuals.</description><dates><release>2025-10-30T00:00:00Z</release><modification>2026-05-27T15:25:47.727Z</modification><creation>2025-10-30T12:28:14.91Z</creation></dates><accession>E-MTAB-15936</accession><cross_references><ENA>ERP183379</ENA><EFO>EFO_0004170</EFO><EFO>EFO_0005684</EFO><EFO>EFO_0005518</EFO><EFO>EFO_0003816</EFO><EFO>EFO_0004184</EFO></cross_references></HashMap>