Over 570,000 solid organ transplants have been performed in the United States since 1988. Despite significant improvements in transplant outcomes, chronic organ rejection affects up to 60% of patients and represents a major cause of mortality following transplantation. Sources of genetic variation underpinning rejection include homozygous deletion copy number variants (CNVs) spanning whole gene or exon regions and Loss of Function (LoF) variants ablating two copies of a given gene, resulting in incompatibility across the proteomes of donor and recipient (D-R). It has been shown through large-scale whole genome sequencing studies that the average human has 20 genes disrupted (i.e. with LoF) in two copies. To better understand how polymorphisms affect transplant outcomes we formed iGeneTrain, a large-scale international consortium, which ultimately aims to translate genetic data into clinical applications such as more optimal genomic compatibility matching of D-R pairs and IST dosing. We report and discuss the design and preliminary results from 23,400 of samples typed on a state-of-art transplantation-focused SNP array comprising nearly 780K markers with coverage of a number of genomic features of interest in particular to the transplant community: Exonic and LoF variants (274K) from a recently updated exome data across 40K individuals; Imputation panel (463K) with all available European ancestry data from the 1000 genome project and 90K African ancestry panels SNPs to boost coverage and improve fine-mapping. We added significant content (55K) for UTRs, pharmacogenomic markers (7.5K) and the candidate studies in the literature related to IST response; Expression QTL markers (17.4 K SNPs) from NCBI/NIH GTEx eQTL database; Dense coverage across the MHC and KIR regions; and Cardiovascular & metabolic disease related content for analysis of NODAT & CAV by collation of SNPs from 600 PubMed manuscripts. This genotyping array offers rich information for the transplant community utilizing state-of-the-art array design technology and data from large-scale resequencing projects and publicly available functional and gene expression datasets.

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