The incidence, prevalence, and often the severity of lupus in ethnic minorities is substantially higher than in European-Americans. Current evidence also indicates that these populations may have different risk alleles. Despite existing SNP databases and haplotype resources, our group and others have demonstrated the importance and value of re-sequencing in the identification of new variants that may contribute to disease susceptibility or severity. To facilitate the identification of novel SNPs and new haplotypic variants among populations of different ancestries, the Sequencing Core of this Program Project will re-sequence high priority candidate gene/genetic regions identified through the Genome Wide Association Studies (GWASs) and the first large replication study outlined in this Program Project. We anticipate a strategy in two phases in synergy with Projects 1-4. First, in Phase I to inform the first replication and early fine mapping studies, a focused subset of top candidate genes will be re-sequenced using standard 3730 series technology in a moderate through-put capacity. This stage will focus on coding and regulatory regions and splice junctions, anticipating ~10 kb per gene in 150 SLE affected among African-American, Ameridian admixed Hispanics, and Asians. Second, in Phase II and based on results of both the GWAS and the first large replication study, the 50 strongest candidate genes/gene regions will be re-sequenced from ~150 SLE patients drawn from Projects 2, 3, and 4 based on disease status and SNP genotypes at selected SLE susceptibility loci. Genomic regions of interest will be enriched via hybridization and elution from NimbleGen custom slide arrays and sequenced using the lllumina GS II genome analyzer using the Paired-End methodology. Sequence data will be organized in a database cataloguing genetic variations at SLE susceptibility loci available to SLEGEN investigators as an essential resource for investigations of the functional variations that predispose to SLE. Data will be deposited in dbSNP and GenBank for public access in keeping with the NIH data sharing recommendations.