Cell-type–specific eQTL of primary melanocytes facilitates identification of melanoma susceptibility genes

Most expression quantitative trait locus (eQTL) studies to date have been performed in heterogeneous tissues as opposed to specific cell types. To better understand the cell-type–specific regulatory landscape of human melanocytes, which give rise to melanoma but account for <5% of typical human skin biopsies, we performed an eQTL analysis in primary melanocyte cultures from 106 newborn males. We identified 597,335 cis-eQTL SNPs prior to linkage disequilibrium (LD) pruning and 4997 eGenes (FDR < 0.05). Melanocyte eQTLs differed considerably from those identified in the 44 GTEx tissue types, including skin. Over a third of melanocyte eGenes, including key genes in melanin synthesis pathways, were unique to melanocytes compared to those of GTEx skin tissues or TCGA melanomas. The melanocyte data set also identified trans-eQTLs, including those connecting a pigmentation-associated functional SNP with four genes, likely through cis-regulation of IRF4. Melanocyte eQTLs are enriched in cis-regulatory signatures found in melanocytes as well as in melanoma-associated variants identified through genome-wide association studies. Melanocyte eQTLs also colocalized with melanoma GWAS variants in five known loci. Finally, a transcriptome-wide association study using melanocyte eQTLs uncovered four novel susceptibility loci, where imputed expression levels of five genes (ZFP90, HEBP1, MSC, CBWD1, and RP11-383H13.1) were associated with melanoma at genome-wide significant P-values. Our data highlight the utility of lineage-specific eQTL resources for annotating GWAS findings, and present a robust database for genomic research of melanoma risk and melanocyte biology

Evaluation of Recipients of Positive and Negative Secondary Findings Evaluations in a Hybrid CLIA-Research Sequencing Pilot

© 2018 While consensus regarding the return of secondary genomic findings in the clinical setting has been reached, debate about such findings in the research setting remains. We developed a hybrid, research-clinical translational genomics process for research exome data coupled with a CLIA-validated secondary findings analysis. Eleven intramural investigators from ten institutes at the National Institutes of Health piloted this process. Nearly 1,200 individuals were sequenced and 14 secondary findings were identified in 18 participants. Positive secondary findings were returned by a genetic counselor following a standardized protocol, including referrals for specialty follow-up care for the secondary finding local to the participants. Interviews were undertaken with 13 participants 4 months after receipt of a positive report. These participants reported minimal psychologic distress within a process to assimilate their results. Of the 13, 9 reported accessing the recommended health care services. A sample of 107 participants who received a negative findings report were surveyed 4 months after receiving it. They demonstrated good understanding of the negative secondary findings result and most expressed reassurance (64%) from that report. However, a notable minority (up to 17%) expressed confusion regarding the distinction of primary from secondary findings. This pilot shows it is feasible to couple CLIA-compliant secondary findings to research sequencing with minimal harms. Participants managed the surprise of a secondary finding with most following recommended follow up, yet some with negative findings conflated secondary and primary findings. Additional work is needed to understand barriers to follow-up care and help participants distinguish secondary from primary findings

Comparative analyses of multi-species sequences from targeted genomic regions

The systematic comparison of genomic sequences from different organisms represents a central focus of contemporary genome analysis. Comparative analyses of vertebrate sequences can identify coding and conserved non-coding regions, including regulatory elements, and provide insight into the forces that have rendered modern-day genomes. As a complement to whole-genome sequencing efforts, we are sequencing and comparing targeted genomic regions in multiple, evolutionarily diverse vertebrates. Here we report the generation and analysis of over 12 megabases (Mb) of sequence from 12 species, all derived from the genomic region orthologous to a segment of about 1.8 Mb on human chromosome 7 containing ten genes, including the gene mutated in cystic fibrosis. These sequences show conservation reflecting both functional constraints and the neutral mutational events that shaped this genomic region. In particular, we identify substantial numbers of conserved non-coding segments beyond those previously identified experimentally, most of which are not detectable by pair-wise sequence comparisons alone. Analysis of transposable element insertions highlights the variation in genome dynamics among these species and confirms the placement of rodents as a sister group to the primates

Longitudinal shift in diabetic wound microbiota correlates with prolonged skin defense response

Diabetics frequently suffer from chronic, nonhealing wounds. Although bacterial colonization and/or infection are generally acknowledged to negatively impact wound healing, the precise relationship between the microbial community and impaired wound healing remains unclear. Because the host cutaneous defense response is proposed to play a key role in modulating microbial colonization, we longitudinally examined the diabetic wound microbiome in tandem with host tissue gene expression. By sequencing 16S ribosomal RNA genes, we show that a longitudinal selective shift in wound microbiota coincides with impaired healing in diabetic mice (Leprdb/db; db/db). We demonstrate a parallel shift in longitudinal gene expression that occurs in a cluster of genes related to the immune response. Further, we establish a correlation between relative abundance of Staphylococcus spp. and the expression of cutaneous defense response genes. Our data demonstrate that integrating two types of global datasets lends a better understanding to the dynamics governing host–microbe interactions