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Human immunity exhibits remarkable heterogeneity among individuals, which engenders variable responses to immune perturbations in human populations. Population studies reveal that, in addition to interindividual heterogeneity, systemic immune signatures display longitudinal stability within individuals, and these signatures may reliably dictate how given individuals respond to immune perturbations. We hypothesize that analyzing relationships among these signatures at the population level may uncover baseline immune phenotypes that correspond with response outcomes to immune stimuli. To test this, we quantified global gene expression in peripheral blood CD4 + cells from healthy individuals at baseline and following CD3/CD28 stimulation at two time points 1 mo apart. Systemic CD4 + cell baseline and poststimulation molecular immune response signatures (MIRS) were defined by identifying genes expressed at levels that were stable between time points within individuals and differential among individuals in each state. Iterative differential gene expression analyses between all possible phenotypic groupings of at least three individuals using the baseline and stimulated MIRS gene sets revealed shared baseline and response phenotypic groupings, indicating the baseline MIRS contained determinants of immune responsiveness. Furthermore, significant numbers of shared phenotype-defining sets of determinants were identified in baseline data across independent healthy cohorts. Combining the cohorts and repeating the analyses resulted in identification of over 6000 baseline immune phenotypic groups, implying that the MIRS concept may be useful in many immune perturbation contexts. These findings demonstrate that patterns in complex gene expression variability can be used to define immune phenotypes and discover determinants of immune responsiveness., (Copyright © 2018 by The American Association of Immunologists, Inc.)

The identification of cis-acting regulatory variation in primary tissues has the potential to elucidate the genetic basis of complex traits and further our understanding of transcriptomic diversity across cell types. Expression quantitative trait locus (eQTL) association analysis using RNA sequencing (RNA-seq) data can improve upon the detection of cis-acting regulatory variation by leveraging allele-specific expression (ASE) patterns in association analysis. Here, we present a comprehensive evaluation of cis-acting eQTLs by analyzing RNA-seq gene-expression data and genome-wide high-density genotypes from 471 samples of normal primary prostate tissue. Using statistical models that integrate ASE information, we identified extensive cis-eQTLs across the prostate transcriptome and found that approximately 70% of expressed genes corresponded to a significant eQTL at a gene-level false-discovery rate of 0.05. Overall, cis-eQTLs were heavily concentrated near the transcription start and stop sites of affected genes, and effects were negatively correlated with distance. We identified multiple instances of cis-acting co-regulation by using phased genotype data and discovered 233 SNPs as the most strongly associated eQTLs for more than one gene. We also noted significant enrichment (25/50, p = 2E-5) of previously reported prostate cancer risk SNPs in prostate eQTLs. Our results illustrate the benefit of assessing ASE data in cis-eQTL analyses by showing better reproducibility of prior eQTL findings than of eQTL mapping based on total expression alone. Altogether, our analysis provides extensive functional context of thousands of SNPs in prostate tissue, and these results will be of critical value in guiding studies examining disease of the human prostate., (Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Our aim was to conduct a pilot case-control study of RNA expression profile using RNA sequencing of rectosigmoid mucosa of nine females with -diarrhea-predominant irritable bowel syndrome (IBS-D) with accelerated colonic transit and nine female healthy controls. Mucosal total RNA was isolated and purified, and next-generation pair-end sequencing was performed using Illumina TruSeq. Analysis was carried out using a targeted approach toward 12 genes previously associated with IBS and a hypothesis-generating approach. Of the 12 targeted genes tested, patients with IBS-D had decreased mRNA expression of TNFSF15 (fold change controls to IBS-D: 1.53, P = 0.01). Overall, up- and downregulated mRNA expressions of 21 genes (P = 10(-5) to 10(-8); P values with false detection rates are shown) were potentially relevant to IBS-D including the following: neurotransmitters [P2RY4 (P = 0.001), vasoactive intestinal peptide (VIP, P = 0.02)]; cytokines [CCL20 (P = 0.019)]; immune function [C4BPA complement cascade (P = 0.0187)]; interferon-related [IFIT3 (P = 0.016)]; mucosal repair and cell adhesion [trefoil protein (TFF1, P = 0.012)], retinol binding protein [RBP2 (P = 0.017)]; fibronectin (FN1, P = 0.009); and ion channel functions [guanylate cyclase (GUCA2B, P = 0.017), PDZ domain-containing protein 3 (PDZD3, P = 0.029)]. Ten genes associated with functions related to pathobiology of IBS-D were validated by RT-PCR. There was significant correlation in fold changes of the selected genes (Rs = 0.73, P = 0.013). Up- or downregulation of P2RY4, GUC2AB, RBP2, FNI, and C4BPA genes were confirmed on RT-PCR, which also revealed upregulation of farnesoid X receptor (FXR) and apical sodium-coupled bile acid transporter (IBAT/ASBT). RNA-Seq and RT-PCR analysis of rectosigmoid mucosa in IBS-D show transcriptome changes that provide the rationale for validation studies to explore the role of mucosal factors in the pathobiology of IBS-D., (Copyright © 2014 the American Physiological Society.)