in conclusion, this dataset, along with the models and analyses presented, can serve as a valuable and actionable resource, informing targeted immune modulation by site and age in future treatments for infectious, neoplastic and inflammatory diseases. this study uses samples obtained from deceased organ donors and does not qualify as human subjects research in the usa, given that the donors are deceased and not living, as confirmed by the columbia university institutional review board. in the uk, samples were collected and analysed under an ethically approved research protocol ( rec 15 / ee / 0152 ). the study analyzed immune cells from multiple tissue samples obtained from 24 organ donors. no statistical method was used to predetermine sample size. no data were excluded from the analysis. investigators were not blinded to allocation during experiments and outcome assessment, as this is a profiling study. tissues were obtained from deceased organ donors ( supplementary table 1 ) at the time of organ acquisition for clinical transplantation. in the usa, this was done through an approved protocol and material transfer agreement via liveonny, the organ procurement organization for the new york metropolitan area. in the uk, tissues were obtained through the cambridge biorepository for translational medicine ( cbtm ), rec 15 / ee / 0152, as previously described. owing to the different amounts of tissues and some distinc t samples ( for example, skin, liver and colon ) obtained at each location, protocols for processing may differ, as described below. each tissue was subjected to a tissue - specific protocol to maximize mnc recovery and viability across a diversity of sites. detailed, step - by - step protocols for immune cell isolation from blood, bm, spleen, lns, lungs ( parenchyma and airway or bal ) and jej ( jlp and jel ) are presented elsewhere. all single - cell suspensions from each site were centrifuged ( 400 g, 10 min at 4 °c ) and washed twice with pbs containing 5 % ( v / v ) fbs and 2 mm edta. cells were counted using the nc - 2000 cell counter ( chemometec ), and 50 million viable cells from each site were treated with trustain fcx ( biolegend ) and fcr blocking reagent ( miltenyi ). cells were subsequently labeled for 30 min at 4 °c with biotinylated anti - cd66b, anti - cd235ab and anti - cd326 to remove granulocytes, red blood cells and epithelial cells, respectively, by streptavidin - coated magnetic particles and negative selection ( bangs laboratories ). all single - cell suspensions were subjected to dead cell removal using a dead cell removal kit ( miltenyi ). each single - cell suspension was hashtagged to allow pooling of samples for loading on the 10× genomics chromium instrument. mncs from each site ( 10 per site ) were transferred into 4 ml flow cytometry tubes, pelleted by centrifugation as above and resuspended in pbs containing 5 % ( v / v ) fbs and 2 mm edta and then incubated with trustain fcx ( biolegend ) and fcr blocking reagent ( miltenyi ) at 4 °c for 10 min to reduce background labeling. each hashtag was spun at 14, 000 g for 10 min, added to each sample ( 1 µl hashtag per tube ), incubated at 4 °c for 30 min, pelleted and washed 3 times with pbs containing 5 % ( v / v ) fbs and 2 mm edta. for cite - seq antibod y staining, 200, 000 cells from each sample were resuspended in reconstituted totalseq - a universal cocktail ( biolegend ) ( donors 496 and 503 ) and totalseq - c universal cocktail ( biolegend ) ( remaining 10 donors ) in pbs containing 5 % ( v / v ) fbs and 2 mm edta, incubated at 4 °c for 30 min and washed 3 times with pbs containing 5 % ( v / v ) fbs and 2 mm edta before resuspension in a final volume of 1 ml. cite - seq antibod y panels are listed in supplementary table 1. each tissue was subjected to a tissue - specific protocol to generate a single - cell suspension of immune cells that has been published in detail elsewhere. immune cells were isolated from blood, bm aspirate s ( sternum ), spleen, lns, lungs, liver, jej ( jel and jlp ) and skin. each single - cell suspension was hashtagged to allow pooling of samples for loading on the 10× genomics chromium instrument. approximately 500, 000 mncs per tissue were transferred into 1. 5 ml lo - bind dna tubes. cells were centrifuged at 400 g for 5 min, the supernatant removed and resuspended in 50 μl pbs containing 0. 04 % bsa. cells were treated with 5 μl trustain fcx ( biolegend ) to reduce background labeling and incubated at 4 °c for 10 min, then each hashtag was added to the sample ( 1 µl hashtag per tube ). samples were incubated at 4 °c for 30 min, washed three times with pbs containing 0. 04 % bsa and equal numbers of cells from each tissue were pooled based on the number processed per donor. cells were incubated with totalseq - c human universal cocktail ( biolegend ) ( supplementary table 2 ) for 30 min at 4 °c and subsequently washed 3 times with pbs containing 0. 04 % bsa. cells were resuspended in 500 µl pbs containing 0. 04 % bsa and passed through a 40 µm flowmi pipette tip filter to remove any clumps of cells. for scrna - seq experiments, single cells were loaded onto the channels of a chromium chip ( 10× genomics ). cdna synthesis, amplification and sequencing libraries were generated using either the single cell 5 ′ reagent ( v1 and v2 ) or 3 ′ reagent ( v3 ) kits. tcrαβ and bcr paired vdj libraries were prepared from samples made with the 5 ′ reagent kit. all libraries were sequenced on either an illumina hiseq 4000, nextseq or novaseq 6000 instrument. alignment was performed using cell ranger ( v6. 0. 0 ) from 10× genomics with the appropriate chemistry option ( fiveprime or sc3pv3 ). we added the cell hashing antibod y and the protein antibod y fastqs to a single call of cellranger count. immune receptors ( tcr and bcr ) were aligned using cellranger vdj. tcr and bcr alignment results from cell ranger were used for quality control and filtering of low - quality cells ( individual cells with both tcr and bcr detected ). in cases where a single cell had both tcr and bcr reads, the immune receptor data were discarded, and the cell was labeled as a multiplet. for all alignments, we used reference genome refdata - gex - grch38 - 2020 - a and immune receptor reference refdata - cellranger - vdj - grch38 - alts - ensembl - 5. 0. 0. samples were demultiplexed by hashtag expression using hashsolo with default parameters. cells that were not uniquely assigned to an individual sample were removed from downstream analysis. filtering was performed to remove cells with fewer than 50 unique genes detected. mitochondrial counts were quantified, summing all genes starting with ‘ mt - ’, and ribosomal counts were quantified using all genes starting with ‘ rps ’ and ‘ rpl ’. for erythrocyte - related counts, all genes starting with ‘ hb ’ as well as alas2 and epor ( to detect erythrocyte precursors ) were quantified. cells with more than 20 % mitochondrial counts were flagged as potentially low - quality for later filtering. counts for mitochondrial genes and malat1 were subsequently removed from the gene expression object and downstream analysis. to exclude contamination from ambient rna, we processed the data using decontx. two samples ( one from liver and one from skin ) with abnormally high ambient counts were removed, as decontx could not correct the ambient counts ( for example, plasma cell genes like alb in all immune cells ). all downstream analysis was performed on uncorrected counts, as we found few ambient counts in other samples. we used a celltypist model ( at https: / / cog. sanger. ac. uk / celltypist / models / red _ blood _ czi / v1 / red _ blood _ czi. pkl ) to detect erythrocytes. doublets were additionally detected using scrublet with a sim _ doublet _ ratio of ten.