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Candidaemia is a bloodstream infection caused by Candida species that primarily affects specific groups of at-risk patients. Because only small candidaemia patient cohorts are available, classical genome wide association cannot be used to identify Candida susceptibility genes. Therefore, we have applied an integrative genomics approach to identify novel susceptibility genes and pathways for candidaemia. Candida-induced transcriptome changes in human primary leukocytes were assessed by RNA sequencing. Genetic susceptibility to candidaemia was assessed using the Illumina immunochip platform for genotyping of a cohort of 217 patients. We then integrated genetics data with gene-expression profiles, Candida-induced cytokine production capacity, and circulating concentrations of cytokines. Based on the intersection of transcriptome pathways and genomic data, we prioritized 31 candidate genes for candidaemia susceptibility. This group of genes was enriched with genes involved in inflammation, innate immunity, complement, and hemostasis. We then validated the role of MAP3K8 in cytokine regulation in response to Candida stimulation. Here, we present a new framework for the identification of susceptibility genes for infectious diseases that uses an unbiased, hypothesis-free, systems genetics approach. By applying this approach to candidaemia, we identified novel susceptibility genes and pathways for candidaemia, and future studies should assess their potential as therapeutic targets. [ABSTRACT FROM AUTHOR]

Recently it has become clear that only a small percentage (7%) of disease-associated single nucleotide polymorphisms (SNPs) are located in protein-coding regions, while the remaining 93% are located in gene regulatory regions or in intergenic regions. Thus, the understanding of how genetic variations control the expression of non-coding RNAs (in a tissue-dependent manner) has far-reaching implications. We tested the association of SNPs with expression levels (eQTLs) of large intergenic non-coding RNAs (lincRNAs), using genome-wide gene expression and genotype data from five different tissues. We identified 112 cis-regulated lincRNAs, of which 45% could be replicated in an independent dataset. We observed that 75% of the SNPs affecting lincRNA expression (lincRNA cis-eQTLs) were specific to lincRNA alone and did not affect the expression of neighboring protein-coding genes. We show that this specific genotype-lincRNA expression correlation is tissue-dependent and that many of these lincRNA cis-eQTL SNPs are also associated with complex traits and diseases. [ABSTRACT FROM AUTHOR]