International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci.

The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5-20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson's disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations

FLASH: ultra-fast protocol to identify RNA-protein interactions in cells

Determination of the in vivo binding sites of RNA-binding proteins (RBPs) is paramount to understanding their function and how they affect different aspects of gene regulation. With hundreds of RNA-binding proteins identified in human cells, a flexible, high-resolution, high-throughput, highly multiplexible and radioactivity-free method to determine their binding sites has not been described to date. Here we report FLASH (Fast Ligation of RNA after some sort of Affinity Purification for High-throughput Sequencing), which uses a special adapter design and an optimized protocol to determine protein-RNA interactions in living cells. The entire FLASH protocol, starting from cells on plates to a sequencing library, takes 1.5 days. We demonstrate the flexibility, speed and versatility of FLASH by using it to determine RNA targets of both tagged and endogenously expressed proteins under diverse conditions in vivo

Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens:a transcriptomic model

Sporulation is a survival strategy, adapted by bacterial cells in response to harsh environmental adversities. The adaptation potential differs between strains and the variations may arise from differences in gene regulation. Gene networks are a valuable way of studying such regulation processes and establishing associations between genes. We reconstructed and compared sporulation gene co-expression networks (GCNs) of the model laboratory strain Bacillus subtilis 168 and the food-borne industrial isolate Bacillus amyloliquefaciens. Transcriptome data obtained from samples of six stages during the sporulation process were used for network inference. Subsequently, a gene set enrichment analysis was performed to compare the reconstructed GCNs of B. subtilis 168 and B. amyloliquefaciens with respect to biological functions, which showed the enriched modules with coherent functional groups associated with sporulation. On basis of the GCNs and time-evolution of differentially expressed genes, we could identify novel candidate genes strongly associated with sporulation in B. subtilis 168 and B. amyloliquefaciens. The GCNs offer a framework for exploring transcription factors, their targets, and co-expressed genes during sporulation. Furthermore, the methodology described here can conveniently be applied to other species or biological processes

Computational Approaches for the Analysis of Chromosome Conformation Capture Data and Their Application to Study Long-Range Gene Regulation: A Dissertation

Over the last decade, development and application of a set of molecular genomic approaches based on the chromosome conformation capture method (3C), combined with increasingly powerful imaging approaches have enabled high resolution and genome-wide analysis of the spatial organization of chromosomes. The aim of this thesis is two-fold; 1), to provide guidelines for analyzing and interpreting data obtained from genome-wide 3C methods such as Hi-C and 3C-seq and 2), to leverage the 3C technology to solve genome function, structure, assembly, development and dosage problems across a broad range of organisms and disease models. First, through the introduction of cWorld, a toolkit for manipulating genome structure data, I accelerate the pace at which *C experiments can be performed, analyzed and biological insights inferred. Next I discuss a set of practical guidelines one should consider while planning an experiment to study the structure of the genome, a simple workflow for data processing unique to *C data and a set of considerations one should be aware of while attempting to gain insights from the data. Next, I apply these guidelines and leverage the cWorld toolkit in the context of two dosage compensation systems. The first is a worm condensin mutant which shows a reduction in dosage compensation in the hermaphrodite X chromosomes. The second is an allele-specific study consisting of genome wide Hi-C, RNA-Seq and ATAC-Seq which can measure the state of the active (Xa) and inactive (Xi) X chromosome. Finally I turn to studying specific gene – enhancer looping interactions across a panel of ENCODE cell-lines. These studies, when taken together, further our understanding of how genome structure relates to genome function

Computational strategies for dissecting the high-dimensional complexity of adaptive immune repertoires

The adaptive immune system recognizes antigens via an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in disease and infection (e.g., autoimmunity, cancer, HIV). Adaptive immune receptor repertoire sequencing (AIRR-seq) has driven the quantitative and molecular-level profiling of immune repertoires thereby revealing the high-dimensional complexity of the immune receptor sequence landscape. Several methods for the computational and statistical analysis of large-scale AIRR-seq data have been developed to resolve immune repertoire complexity in order to understand the dynamics of adaptive immunity. Here, we review the current research on (i) diversity, (ii) clustering and network, (iii) phylogenetic and (iv) machine learning methods applied to dissect, quantify and compare the architecture, evolution, and specificity of immune repertoires. We summarize outstanding questions in computational immunology and propose future directions for systems immunology towards coupling AIRR-seq with the computational discovery of immunotherapeutics, vaccines, and immunodiagnostics.Comment: 27 pages, 2 figure

Peripheral blood gene expression: it all boils down to the RNA collection tubes

Background: Gene expression profiling from peripheral blood is a valuable tool for biomarker discovery in clinical studies. Different whole blood RNA collection and processing methods are highly variable and might confound comparisons of results across studies. The main aim of the study was to compare genome-wide gene expression profiles obtained from the two widely used commercially available whole blood RNA collection systems - PAXgene and Tempus tubes. Comparisons of present call rates, variances, correlations and influence of globin reduction across the two collection systems was performed using in vivo glucocorticoid stimulation in 24 peripheral blood samples from three individuals. Results: RNA quality, yield and numbers of detected transcripts from the two RNA collection systems was comparable, with no significant differences between the tube types. Globin reduction resulted in a significant increase in present call rates (p = 8.17 × 10 -5 and p = 1.95 × 10 -3 in PAXgene and Tempus tubes respectively) and significant decrease in gene expression variance in both RNA collection tubes (p = 0.0025 and p = 0.041 in PAXgene and Tempus tubes respectively). Comparisons of glucocorticoid receptor-stimulated gene expression profiles between the two collection tube systems revealed an overlap of only 17 to 54%, depending on the stringency level of the statistical thresholds. This overlap increased by 1-8% when the RNA samples were processed to remove the globin mRNA. Conclusion: RNA obtained from PAXgene and Tempus tubes was comparable in terms of quality and yield, however, detectable gene expression changes after glucocorticoid receptor stimulation were distinct, with an overlap of only up to 46% between the two collection systems. This overlap increased to 54% when the samples were depleted of globin mRNA and drastically reduced to 17-18% when only gene expression differences with a fold change greater than 2.0 were assessed. These results indicate that gene expression profiles obtained from PAXgene and Tempus differ drastically and should not be analyzed together. These data suggest that researchers must exert caution while interpreting expression profiles obtained through different RNA collection tubes.</p

Differentiation of murine embryonic cells towards the haematopoietic cell lineage using the HepG2 conditioned medium and encapsulation in a rotating wall vessel bioreactor

Embryonic stem cells (ESCs) are known for their unique property to be maintained almost indefinitely in an undifferentiated, proliferating state with the potential to give rise to all types of cells. Current established protocols for the culture and differentiation of ESCs are cumbersome and inefficient involving three stages: a) maintenance or expansion of undifferentiated ESCs, b) spontaneous differentiation through formation of embryoid bodies (EBs), and c) dissociation of the EBs and replating leading to the terminal differentiation to the desired lineages. One of the major challenges in the use of ESCs for cell therapy is controlling their differentiation pathways. Optimal culture conditions and requirement as well as precise differentiation mechanisms and cellular interactions within EBs are still not well characterised resulting in sub-optimal control of homogenous differentiation especially due to the formation of all three germ layers. Attempts on developing an efficient culture protocol have been widely reported in order to overcome the limitations. Recent research approaches have shown that treatment with conditioned medium derived from HepG2, a human hepatocarcinoma cell line enhances the formation of multipotent mesodermal progenitors from ESCs. This promotes a greater control of ESC differentiation in a lineage-specific fashion possibly resulting in efficient haematopoietic differentiation. In this study, we have developed an integrated, single step bioprocess for ESCs hematopoietic differentiation that: a) uses HepG2-conditioned medium (HepG2-CM), that stimulates mesoderm formation, b) facilitates three dimensional (3D) culture through encapsulation of undifferentiated ESCs in hydrogels, c) bypasses EB formation, and d) involves culture in a rotating wall vessel bioreactor that does not require passaging of the cells and is scalable and automatable. In conclusion, this thesis reports the development of a novel culture system for the efficient single-step haematopoietic differentiation of ESC resulting in a reproducible, scalable, high-intensity culture system of mESCs for ex-vivo blood manufacture