A comprehensive platform for analyzing longitudinal multi-omics data

We profiled four healthy individuals with age between 25 to 38 years old over 10-week period longitudinally using high throughput analysis. We measured blood count, flow-based cell populations, plasma proteome, transcriptome at single cell level, and genomic region accessibility using single cell ATAC to infer immune variations in healthy individuals. Peripheral blood mononuclear cells from 4 healthy individuals were profiled using multi-modal single cell RNAseq and scATACseq using the 10x Genomics Chromium system. Single-cell RNA-seq libraries were generated using the 10x Genomics Chromium 3’ Single Cell Gene Expression assay and Chromium Controller Instrument according to the manufacturer’s published protocol with modifications for cell hashing. Final libraries were quantified using Picogreen and their quality was assessed via capillary electrophoresis using the Agilent Fragment Analyzer HS DNA fragment kit and/or Agilent Bioanalyzer High Sensitivity chips. Libraries were sequenced on the Illumina NovaSeq platform using S4 flow cells. Read lengths were 28bp read1, 8bp i7 index read, 91bp read2. For scATACseq PBMC samples were sorted by fluorescence activated cell sorting (FACS) prior to cell permeabilization. Permeabilized-cell scATAC-seq was performed as described previously (Swanson et al. 2021). scATAC-seq libraries were prepared according to the Chromium Single Cell ATAC v1.1 Reagent Kits. Final libraries were quantified using a Quant-iT PicoGreen dsDNA Assay Kit (Thermo Fisher Scientific) on a SpectraMax iD3 (Molecular Devices). Library quality and average fragment size was assessed using a Bioanalyzer (Agilent, G2939A) High Sensitivity DNA chip (Agilent, 5067-4626). Libraries were sequenced on the Illumina NovaSeq platform with the following read lengths: 51nt read 1, 8nt i7 index, 16nt i5 index, 51nt read 2. scATAC based fragments were submitted to ArchR package to create ArchR object. The QC analysis shows FRiP score (the fraction of reads that fall into a peak) >0.25. ----------------------------------- Authors state "Raw files from human subjects will be submitted to dbGaP."