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Massively parallel reporter assays (MPRAs) test the capacity of putative gene regulatory elements to drive transcription on a genome-wide scale. Most gene regulatory activity occurs within accessible chromatin, and recently described methods have combined assays that capture these regions—such as assay for transposase-accessible chromatin using sequencing (ATAC-seq)—with self-transcribing active regulatory region sequencing (STARR-seq) to selectively assay the regulatory potential of accessible DNA (ATAC-STARR-seq). Here, we report an integrated approach that quantifies activating and silencing regulatory activity, chromatin accessibility, and transcription factor (TF) occupancy with one assay using ATAC-STARR-seq. Our strategy, including important updates to the ATAC-STARR-seq assay and workflow, enabled high-resolution testing of ∼50 million unique DNA fragments tiling ∼101,000 accessible chromatin regions in human lymphoblastoid cells. We discovered that 30% of all accessible regions contain an activator, a silencer, or both. Although few MPRA studies have explored silencing activity, we demonstrate that silencers occur at similar frequencies to activators, and they represent a distinct functional group enriched for unique TF motifs and repressive histone modifications. We further show that Tn5 cut-site frequencies are retained in the ATAC-STARR plasmid library compared to standard ATAC-seq, enabling TF occupancy to be ascertained from ATAC-STARR data. With this approach, we found that activators and silencers cluster by distinct TF footprint combinations, and these groups of activity represent different gene regulatory networks of immune cell function. Altogether, these data highlight the multilayered capabilities of ATAC-STARR-seq to comprehensively investigate the regulatory landscape of the human genome all from a single DNA fragment source.

Background Using a dextrose-containing solution, instead of normal saline, to maintain the patency of an arterial cannula results in the admixture of glucose in line samples. This can misguide the clinician down an inappropriate treatment pathway for hyperglycaemia.Methods Following a near-miss and subsequent educational and training efforts at our institution, we conducted two simulations: (1) to observe whether 20 staff would identify a 5% dextrose/0.9% saline flush solution as the cause for a patient’s refractory hyperglycaemia, and (2) to compare different arterial line sampling techniques for glucose contamination.Results (1) Only 2/20 participants identified the incorrect dextrose-containing flush solution, with the remainder choosing to escalate insulin therapy to levels likely to risk fatality, and (2) glucose contamination occurred regardless of sampling technique.Conclusion Despite national guidance and local educational efforts, this is still an under-recognised error. Operator-focussed preventative strategies have not been effective and an engineered solution is needed.

The epigenome is multidimensional, with individual molecular components operating on different levels to control transcriptional output. Techniques that combine measurements of these features can reveal their precise correspondence in genomic space, or temporal connectivity, to better understand how they jointly regulate genes. ATAC-Me is an integrated method to probe DNA methylation and chromatin accessibility from a single DNA fragment library. Intact nuclei undergo Tn5 transposition to isolate DNA fragments within nucleosome-free regions. Isolated fragments are exposed to sodium bisulfite before library amplification and sequencing. A typical ATAC-Me experiment detects ~60,000–75,000 peak regions (P< 0.05), covering ~3–4 million CpG sites with at least 5× coverage. These sites display a range of methylation values depending on the cellular and genomic context. The approach is well suited for time course studies that aim to capture chromatin and DNA methylation dynamics in tandem during cellular differentiation. The protocol is completed in 2 d with standard molecular biology equipment and expertise. Analysis of resulting data uses publicly available software requiring basic bioinformatics skills to interpret results.

Higher-order genome structure influences the transcriptional regulation of cellular genes through the juxtaposition of regulatory elements, such as enhancers, close to promoters of target genes. While enhancer activation has emerged as an important facet of Kaposi sarcoma-associated herpesvirus (KSHV) biology, the mechanisms controlling enhancer-target gene expression remain obscure. Here, we discover that the KSHV genome tethering protein latency-associated nuclear antigen (LANA) potentiates enhancer-target gene expression in primary effusion lymphoma (PEL), a highly aggressive B cell lymphoma causally associated with KSHV. Genome-wide analyses demonstrate increased levels of enhancer RNA transcription as well as activating chromatin marks at LANA-bound enhancers. 3D genome conformation analyses identified genes critical for latency and tumorigenesis as targets of LANA-occupied enhancers, and LANA depletion results in their downregulation. These findings reveal a mechanism in enhancer-gene coordination and describe a role through which the main KSHV tethering protein regulates essential gene expression in PEL.

The investigation of the small RNA pathways of monotremes by deep sequencing of six platypus and echidna tissues is described. It is observed that the highly conserved microRNA species exhibit their signature tissue-specific expression patterns and also large quickly evolving cluster of microRNAs on platypus chromosomes XI, which is distinct to monotremes are seen.

The results from studies of 12 Drosophila genomes, which provide insight into structural and evolutionary signatures of microRNA regulation and development, are presented.

In this review, Boothby et al. summarize some salient advances toward elucidation of the molecular programming of the fate choices and function of B cells in the periphery. They also note unanswered questions that pertain to differences among subsets of B lymphocytes and plasma cells.

Pregnancy is the major modulator of mammary gland activity. It induces a tremendous expansion of the mammary epithelium and the generation of alveolar structures for milk production. Anecdotal evidence from multiparous humans indicates that the mammary gland may react less strongly to the first pregnancy than it does to subsequent pregnancies. Here, we verify that the mouse mammary gland responds more robustly to a second pregnancy, indicating that the gland retains a long-term memory of pregnancy. A comparison of genome-wide profiles of DNA methylation in isolated mammary cell types reveals substantial and long-lasting alterations. Since these alterations are maintained in the absence of the signal that induced them, we term them epigenetic. The majority of alterations in DNA methylation affect sites occupied by the Stat5a transcription factor and mark specific genes that are upregulated during pregnancy. We postulate that the epigenetic memory of a first pregnancy primes the activation of gene expression networks that promote mammary gland function in subsequent reproductive cycles. More broadly, our data indicate that physiological experience can broadly alter epigenetic states, functionally modifying the capacity of the affected cells to respond to later stimulatory events.

In this paper we aim to create a reference data collection of Northern blot results and demonstrate how such a collection can enable a quantitative comparison of modern expression profiling techniques, a central component of functional genomics studies. Historically, Northern blots were the de facto standard for determining RNA transcript levels. However, driven by the demand for analysis of large sets of genes in parallel, high‐throughput methods, such as microarrays, dominate modern profiling efforts. To facilitate assessment of these methods, in comparison to Northern blots, we created a database of published Northern results obtained with a standardized commercial multiple tissue blot (dbMTN). In order to demonstrate the utility of the dbMTN collection for technology comparison, we also generated expression profiles for genes across a set of human tissues, using multiple profiling techniques. No method produced profiles that were strongly correlated with the Northern blot data. The highest correlations to the Northern blot data were determined with microarrays for the subset of genes observed to be specifically expressed in a single tissue in the Northern analyses. The database and expression profiling data are available via the project website (http://www.cisreg.ca). We believe that emphasis on multi‐technique validation of expression profiles is justified, as the correlation results between platforms are not encouraging on the whole. Supplementary material for this article can be found at: http://www.interscience.wiley.com/jpages/1531‐6912/suppmat Copyright © 2005 John Wiley & Sons, Ltd.

Coronary Artery Disease is a highly polygenic disorder and has increased comorbidity with Major Depressive Disorder (MDD). Our previous work demonstrated that the PRS for MDD was significantly associated with manifestations of CAD including ischemic heart disease (OR = 1.09, p=8.28x10-6) and coronary atherosclerosis (OR = 1.10, p=1.08x10-5) in a large hospital population. Furthermore, the association remained robust after adjusting for known CAD risk factors, suggesting that some proportion of genes that increase susceptibility to MDD act pleiotropically to increase CAD risk. Therefore, the aim of our study was to identify genes that increase risk for both CAD and MDD. We first performed an imputed TWAS using existing GWAS data on CAD from the CARDIoGRAMplusC4D consortium and UKBB and MDD from Psychiatric Genomics Consortium. TWAS uses the summary statistics from a GWAS and expression prediction models to infer the association between the genetically predicted expression of each gene and a phenotype of interest. We identified genes for which predicted expression was associated with increased risk of both MDD and CAD. We then further tested the relationship between those genes and quantitative biomarkers recorded in the Vanderbilt electronic health record (EHR). For this, we used Vanderbilt’s collection of de-identified biosamples (BioVU) which currently includes ~100k genotyped patient DNA samples linked with their EHRs. We used PredixVU, a gene-based association method to determine whether genes identified in the TWAS were associated with clinical biomarkers. We identified significant overlap in the genes associated with both MDD and CAD at an FDR of 0.01 (hypergeometric enrichment factor of 3.2; p = 0.002) and 0.05 (hypergeometric enrichment factor of 2.4; p = 8.35e-9). TMEM106B was significantly associated with both MDD and CAD after Bonferroni correction was applied. TMEM106B is involved in lysosomal activity and has been independently associated with both, CAD and MDD. The predicted expression of TMEM106B in the putamen is associated with decreased levels of hydroxyproline (OR = 0.830, P-Value = 7.5 e-5). For our future work, we aim to investigate the shared pathways of these genes across Asian, European and African ancestry using BioVU.