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Abstract Background Increasing evidence suggests that a substantial proportion of disease-associated mutations occur in enhancers, regions of non-coding DNA essential to gene regulation. Understanding the structures and mechanisms of the regulatory programs this variation affects can shed light on the apparatuses of human diseases. Results We collect epigenetic and gene expression datasets from seven early time points during neural differentiation. Focusing on this model system, we construct networks of enhancer-promoter interactions, each at an individual stage of neural induction. These networks serve as the base for a rich series of analyses, through which we demonstrate their temporal dynamics and enrichment for various disease-associated variants. We apply the Girvan-Newman clustering algorithm to these networks to reveal biologically relevant substructures of regulation. Additionally, we demonstrate methods to validate predicted enhancer-promoter interactions using transcription factor overexpression and massively parallel reporter assays. Conclusions Our findings suggest a generalizable framework for exploring gene regulatory programs and their dynamics across developmental processes; this includes a comprehensive approach to studying the effects of disease-associated variation on transcriptional networks. The techniques applied to our networks have been published alongside our findings as a computational tool, E-P-INAnalyzer. Our procedure can be utilized across different cellular contexts and disorders.

Abstract Regulation of gene expression through enhancers is one of the major processes shaping the structure and function of the human brain during development. High-throughput assays have predicted thousands of enhancers involved in neurodevelopment, and confirming their activity through orthogonal functional assays is crucial. Here, we utilized Massively Parallel Reporter Assays (MPRAs) in stem cells and forebrain organoids to evaluate the activity of ~ 7000 gene-linked enhancers previously identified in human fetal tissues and brain organoids. We used a Gaussian mixture model to evaluate the contribution of background noise in the measured activity signal to confirm the activity of ~ 35% of the tested enhancers, with most showing temporal-specific activity, suggesting their evolving role in neurodevelopment. The temporal specificity was further supported by the correlation of activity with gene expression. Our findings provide a valuable gene regulatory resource to the scientific community.

Abstract The gene regulatory code and grammar remain largely unknown, precluding our ability to link phenotype to genotype in regulatory sequences. Here, using a massively parallel reporter assay (MPRA) of 209,440 sequences, we examine all possible pair and triplet combinations, permutations and orientations of eighteen liver-associated transcription factor binding sites (TFBS). We find that TFBS orientation and order have a major effect on gene regulatory activity. Corroborating these results with genomic analyses, we find clear human promoter TFBS orientation biases and similar TFBS orientation and order transcriptional effects in an MPRA that tested 164,307 liver candidate regulatory elements. Additionally, by adding TFBS orientation to a model that predicts expression from sequence we improve performance by 7.7%. Collectively, our results show that TFBS orientation and order have a significant effect on gene regulatory activity and need to be considered when analyzing the functional effect of variants on the activity of these sequences.

How gene regulatory elements regulate gene expression during cellular differentiation remains largely unknown. Here the authors use perturbation-based massively parallel reporter assays at early time points of neural differentiation to systematically characterize how regulatory elements and motifs within them guide different transcriptional patterns.

Summary: Alternative DNA conformations, termed non-B DNA structures, can affect transcription, but the underlying mechanisms and their functional impact have not been systematically characterized. Here, we used computational genomic analyses coupled with massively parallel reporter assays (MPRAs) to show that certain non-B DNA structures have a substantial effect on gene expression. Genomic analyses found that non-B DNA structures at promoters harbor an excess of germline variants. Analysis of multiple MPRAs, including a promoter library specifically designed to perturb non-B DNA structures, functionally validated that Z-DNA can significantly affect promoter activity. We also observed that biophysical properties of non-B DNA motifs, such as the length of Z-DNA motifs and the orientation of G-quadruplex structures relative to transcriptional direction, have a significant effect on promoter activity. Combined, their higher mutation rate and functional effect on transcription implicate a subset of non-B DNA motifs as major drivers of human gene-expression-associated phenotypes.

Interpreting genetic variation in the noncoding genome remains challenging, with functional effects difficult to predict. Here, the authors perform saturation mutagenesis combined with massively parallel reporter assays for 20 disease-associated regulatory elements, quantifying the effects of over 30,000 variants.

The Neanderthal and Denisovan genomes enabled the discovery of sequences that differ between modern and archaic humans, the majority of which are noncoding. However, our understanding of the regulatory consequences of these differences remains limited, in part due to the decay of regulatory marks in ancient samples. Here, we used a massively parallel reporter assay in embryonic stem cells, neural progenitor cells, and bone osteoblasts to investigate the regulatory effects of the 14,042 single-nucleotide modern human-specific variants. Overall, 1791 (13%) of sequences containing these variants showed active regulatory activity, and 407 (23%) of these drove differential expression between human groups. Differentially active sequences were associated with divergent transcription factor binding motifs, and with genes enriched for vocal tract and brain anatomy and function. This work provides insight into the regulatory function of variants that emerged along the modern human lineage and the recent evolution of human gene expression.

BACKGROUND Vascular healing response associated with adjunctive n‐3 polyunsaturated fatty acid therapy therapy in patients receiving strong statin therapy remains unclear. The aim of this study was to evaluate the effect of polyunsaturated fatty acid therapy with eicosapentaenoic acid (EPA) or docosahexaenoic acid (DHA) in addition to strong statin therapy on coronary atherosclerotic plaques using optical coherence tomography. METHODS AND RESULTS This prospective multicenter randomized controlled trial included 130 patients with acute coronary syndrome treated with strong statins. They were assigned to either statin only (control group, n=42), statin+high‐dose EPA (1800 mg/day) (EPA group, n=40), statin+EPA (930 mg/day)+DHA (750 mg/day) (EPA+DHA group, n=48). Optical coherence tomography was performed at baseline and at the 8‐month follow‐up. The target for optical coherence tomography analysis was a nonculprit lesion with a lipid plaque. Between baseline and the 8‐month follow‐up, fibrous cap thickness (FCT) significantly increased in all 3 groups. There were no significant differences in the percent change for minimum FCT between the EPA or EPA+DHA group and the control group. In patients with FCT

Abstract Background  Bleeding pelvic fracture patients with severe associated injuries have a high mortality rate that is exacerbated by several factors. To gain deeper etiological insights into this injury, we investigated the specific risk factors associated with the high mortality rate. Methods  A total of 102 bleeding pelvic fracture patients with severe associated injuries (abbreviated injury score ≥3) were treated at our level I trauma center between January 1994 and December 2004. Predictors of death within 24 h of arrival were determined by univariate and multivariate analyses using anatomic and physiologic parameters, including injured body part, shock symptoms, age, sex, injury severity score (ISS), and fracture type. Results  Overall, 47 of the 102 patients died within 24 h of arrival. Hemorrhage shock was responsible for the majority of deaths (47%). Other causes included central nervous system injury (21%), multiple injuries (central nervous system injury plus shock, 18%) and multiple organ failures (7%). Univariate analyses revealed that patients presenting with head and neck injuries and shock symptoms on arrival were associated with an increased risk of death (P Conclusions  Statistically significant risk factors were brain injuries and shock symptoms on arrival. Brain injuries should be heavily weighted when evaluating the prognosis of bleeding pelvic fracture patients. [ABSTRACT FROM AUTHOR]