Ryan C. Thompson

Molecular classifiers for acute kidney transplant rejection in peripheral blood by whole genome gene expression profiling.

There are no minimally invasive diagnostic metrics for acute kidney transplant rejection (AR), especially in the setting of the common confounding diagnosis, acute dysfunction with no rejection (ADNR). Thus, though kidney transplant biopsies remain the gold standard, they are invasive, have substantial risks, sampling error issues and significant costs and are not suitable for serial monitoring. Global gene expression profiles of 148 peripheral blood samples from transplant patients with excellent function and normal histology (TX; n = 46), AR (n = 63) and ADNR (n = 39), from two independent cohorts were analyzed with DNA microarrays. We applied a new normalization tool, frozen robust multi‐array analysis, particularly suitable for clinical diagnostics, multiple prediction tools to discover, refine and validate robust molecular classifiers and we tested a novel one‐by‐one analysis strategy to model the real clinical application of this test. Multiple three‐way classifier tools identified 200 highest value probesets with sensitivity, specificity, positive predictive value, negative predictive value and area under the curve for the validation cohort ranging from 82% to 100%, 76% to 95%, 76% to 95%, 79% to 100%, 84% to 100% and 0.817 to 0.968, respectively. We conclude that peripheral blood gene expression profiling can be used as a minimally invasive tool to accurately reveal TX, AR and ADNR in the setting of acute kidney transplant dysfunction.

Illumina mate-paired DNA sequencing-library preparation using Cre-Lox recombination

Standard Illumina mate-paired libraries are constructed from 3- to 5-kb DNA fragments by a blunt-end circularization. Sequencing reads that pass through the junction of the two joined ends of a 3–5-kb DNA fragment are not easy to identify and pose problems during mapping and de novo assembly. Longer read lengths increase the possibility that a read will cross the junction. To solve this problem, we developed a mate-paired protocol for use with Illumina sequencing technology that uses Cre-Lox recombination instead of blunt end circularization. In this method, a LoxP sequence is incorporated at the junction site. This sequence allows screening reads for junctions without using a reference genome. Junction reads can be trimmed or split at the junction. Moreover, the location of the LoxP sequence in the reads distinguishes mate-paired reads from spurious paired-end reads. We tested this new method by preparing and sequencing a mate-paired library with an insert size of 3 kb from Saccharomyces cerevisiae. We present an analysis of the library quality statistics and a new bio-informatics tool called DeLoxer that can be used to analyze an IlluminaCre-Lox mate-paired data set. We also demonstrate how the resulting data significantly improves a de novo assembly of the S. cerevisiae genome.

Orthogonal Comparison of Molecular Signatures of Kidney Transplants With Subclinical and Clinical Acute Rejection: Equivalent Performance Is Agnostic to Both Technology and Platform

We performed orthogonal technology comparisons of concurrent peripheral blood and biopsy tissue samples from 69 kidney transplant recipients who underwent comprehensive algorithm‐driven clinical phenotyping. The sample cohort included patients with normal protocol biopsies and stable transplant (sTx) function (n = 25), subclinical acute rejection (subAR, n = 23), and clinical acute rejection (cAR, n = 21). Comparisons between microarray and RNA sequencing (RNA‐seq) signatures were performed and demonstrated a strong correlation between the blood and tissue compartments for both technology platforms. A number of shared differentially expressed genes and pathways between subAR and cAR in both platforms strongly suggest that these two clinical phenotypes form a continuum of alloimmune activation. SubAR is associated with fewer or less expressed genes than cAR in blood, whereas in biopsy tissues, this clinical phenotype demonstrates a more robust molecular signature for both platforms. The discovery work done in this study confirms a clear ability to detect gene expression profiles for sTx, subAR, and cAR in both blood and biopsy tissue, yielding equivalent predictive performance that is agnostic to both technology and platform. Our data also provide strong biological insights into the molecular mechanisms underlying these signatures, underscoring their logistical potential as molecular diagnostics to improve clinical outcomes following kidney transplantation.

H3K27 Methylation Dynamics during CD4 T Cell Activation: Regulation of JAK/STAT and IL12RB2 Expression by JMJD3

The changes to the epigenetic landscape in response to Ag during CD4 T cell activation have not been well characterized. Although CD4 T cell subsets have been mapped globally for numerous epigenetic marks, little has been done to study their dynamics early after activation. We have studied changes to promoter H3K27me3 during activation of human naive and memory CD4 T cells. Our results show that these changes occur relatively early (1 d) after activation of naive and memory cells and that demethylation is the predominant change to H3K27me3 at this time point, reinforcing high expression of target genes. Additionally, inhibition of the H3K27 demethylase JMJD3 in naive CD4 T cells demonstrates how critically important molecules required for T cell differentiation, such as JAK2 and IL12RB2, are regulated by H3K27me3. Our results show that H3K27me3 is a dynamic and important epigenetic modification during CD4 T cell activation and that JMJD3-driven H3K27 demethylation is critical for CD4 T cell function.

Promoter H3K4 methylation dynamically reinforces activation-induced pathways in human CD4 T cells

The epigenetic determinants driving the responses of CD4 T cells to antigen are currently an area of active research. Much has been done to characterize helper T-cell subsets and their associated genome-wide epigenetic patterns. In contrast, little is known about the dynamics of histone modifications during CD4 T-cell activation and the differential kinetics of these epigenetic marks between naive and memory T cells. In this study, we have detailed the dynamics of genome-wide promoter H3K4me2 and H3K4me3 over a time course during activation of human naive and memory CD4 T cells. Our results demonstrate that changes to H3K4 methylation occur relatively late after activation (5 days) and reinforce activation-induced upregulation of gene expression, affecting multiple pathways important to T-cell activation, differentiation and function. The dynamics and mapped pathways of H3K4 methylation are distinctly different in memory cells, which have substantially more promoters marked by H3K4me3 alone, reinforcing their more differentiated state. Our study provides the first data examining genome-wide histone modification dynamics during CD4 T-cell activation, providing insight into the cross talk between H3K4 methylation and gene expression, and underscoring the impact of these marks upon key pathways integral to CD4 T-cell activation and function.

Differential brain mechanisms of selection and maintenance of information during working memory

Working memory is our ability to temporarily hold information as needed for complex cognitive operations. Models of working memory distinguish two separate processes: (i) a selection rule that identifies the content to be recalled and (ii) the maintenance of the content. We aimed to characterize the spatiotemporal neural dynamics underlying these two components. Healthy participants performed a visual working memory task during magnetoencephalography (MEG) recording. Multivariate Pattern Analysis (MVPA) and source analyses identified two distinct types of working memory neural processes underlying selection and maintenance of the content. The selection rule is specifically decoded from sustained low-frequency (<20Hz) neural activity within a cortical network that includes the ventrolateral prefrontal cortex. By contrast, working memory content is transiently reactivated over a distributed and occipito-temporal network that differs from that encoding the sensory stimulus. These results reveal different neural mechanisms that select and maintain information in memory and could account for previous paradoxical reports of persistent and dynamic neural correlates of working memory.

Investigate Global Chromosomal Interaction by Hi-C in Human Naive CD4 T Cells

Hi-C is a methodology developed to reveal chromosomal interactions from a genome-wide perspective. Here, we described a protocol for generating Hi-C sequencing libraries in resting and activated human naive CD4 T cells to investigate activation-induced chromatin structure re-arrangement in T cell activation followed by a section reviewing the general concepts of Hi-C data analysis.

RASLseqTools: open-source methods for designing and analyzing RNA-mediated oligonucleotide Annealing, Selection, and, Ligation sequencing (RASL-seq) experiments

RNA-mediated oligonucleotide Annealing, Selection, and Ligation (RASL-seq) is a method to measure the expression of hundreds of genes in thousands of samples for a fraction of the cost of competing methods. However, enzymatic inefficiencies of the original protocol and the lack of open source software to design and analyze RASL-seq experiments have limited its widespread adoption. We recently reported an Rnl2-based RASL-seq protocol (RRASL-seq) that offers improved ligation efficiency and a probe decoy strategy to optimize sequencing usage. Here, we describe an open source software package, RASLseqTools, that provides computational methods to design and analyze RASL-seq experiments. Furthermore, using data from a large RRASL-seq experiment, we demonstrate how normalization methods can be used for characterizing and correcting experimental, sequencing, and alignment error. We provide evidence that the three principal predictors of RRASL-seq reproducibility are barcode/probe sequence dissimilarity, sequencing read depth, and normalization strategy. Using dozens of technical and biological replicates across multiple 384-well plates, we find simple normalization strategies yield similar results to more statistically complex methods.