JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles.

JASPAR (http://jaspar.genereg.net) is an open-access database storing curated, non-redundant transcription factor (TF) binding profiles representing transcription factor binding preferences as position frequency matrices for multiple species in six taxonomic groups. For this 2016 release, we expanded the JASPAR CORE collection with 494 new TF binding profiles (315 in vertebrates, 11 in nematodes, 3 in insects, 1 in fungi and 164 in plants) and updated 59 profiles (58 in vertebrates and 1 in fungi). The introduced profiles represent an 83% expansion and 10% update when compared to the previous release. We updated the structural annotation of the TF DNA binding domains (DBDs) following a published hierarchical structural classification. In addition, we introduced 130 transcription factor flexible models trained on ChIP-seq data for vertebrates, which capture dinucleotide dependencies within TF binding sites. This new JASPAR release is accompanied by a new web tool to infer JASPAR TF binding profiles recognized by a given TF protein sequence. Moreover, we provide the users with a Ruby module complementing the JASPAR API to ease programmatic access and use of the JASPAR collection of profiles. Finally, we provide the JASPAR2016 R/Bioconductor data package with the data of this release

Formation and Evolution of Supermassive Black Holes

The correlation between the mass of supermassive black holes in galaxy nuclei and the mass of the galaxy spheroids or bulges (or more precisely their central velocity dispersion), suggests a common formation scenario for galaxies and their central black holes. The growth of bulges and black holes can commonly proceed through external gas accretion or hierarchical mergers, and are both related to starbursts. Internal dynamical processes control and regulate the rate of mass accretion. Self-regulation and feedback are the key of the correlation. It is possible that the growth of one component, either BH or bulge, takes over, breaking the correlation, as in Narrow Line Seyfert 1 objects. The formation of supermassive black holes can begin early in the universe, from the collapse of Population III, and then through gas accretion. The active black holes can then play a significant role in the re-ionization of the universe. The nuclear activity is now frequently invoked as a feedback to star formation in galaxies, and even more spectacularly in cooling flows. The growth of SMBH is certainly there self-regulated. SMBHs perturb their local environment, and the mergers of binary SMBHs help to heat and destroy central stellar cusps. The interpretation of the X-ray background yields important constraints on the history of AGN activity and obscuration, and the census of AGN at low and at high redshifts reveals the downsizing effect, already observed for star formation. History appears quite different for bright QSO and low-luminosity AGN: the first grow rapidly at high z, and their number density decreases then sharply, while the density of low-luminosity objects peaks more recently, and then decreases smoothly.Comment: 31 pages, 13 figures, review paper for Astrophysics Update

A Conserved Noncoding Locus Regulates Random Monoallelic Xist Expression across a Topological Boundary

cis-Regulatory communication is crucial in mammalian development and is thought to be restricted by the spatial partitioning of the genome in topologically associating domains (TADs). Here, we discovered that the Xist locus is regulated by sequences in the neighboring TAD. In particular, the promoter of the noncoding RNA Linx (LinxP) acts as a long-range silencer and influences the choice of X chromosome to be inactivated. This is independent of Linx transcription and independent of any effect on Tsix, the antisense regulator of Xist that shares the same TAD as Linx. Unlike Tsix, LinxP is well conserved across mammals, suggesting an ancestral mechanism for random monoallelic Xist regulation. When introduced in the same TAD as Xist, LinxP switches from a silencer to an enhancer. Our study uncovers an unsuspected regulatory axis for X chromosome inactivation and a class of cis-regulatory effects that may exploit TAD partitioning to modulate developmental decisions.Galupa et al. uncover elements important for Xist regulation in its neighboring TAD and reveal that these elements can influence gene regulation both within and between topological domains. These findings, in a context where dynamic, developmental expression is necessary, challenge current models for TAD-based gene-regulatory landscapes

Occupancy maps of 208 chromatin-associated proteins in one human cell type

Transcription factors are DNA-binding proteins that have key roles in gene regulation. Genome-wide occupancy maps of transcriptional regulators are important for understanding gene regulation and its effects on diverse biological processes. However, only a minority of the more than 1,600 transcription factors encoded in the human genome has been assayed. Here we present, as part of the ENCODE (Encyclopedia of DNA Elements) project, data and analyses from chromatin immunoprecipitation followed by high-throughput sequencing (ChIP–seq) experiments using the human HepG2 cell line for 208 chromatin-associated proteins (CAPs). These comprise 171 transcription factors and 37 transcriptional cofactors and chromatin regulator proteins, and represent nearly one-quarter of CAPs expressed in HepG2 cells. The binding profiles of these CAPs form major groups associated predominantly with promoters or enhancers, or with both. We confirm and expand the current catalogue of DNA sequence motifs for transcription factors, and describe motifs that correspond to other transcription factors that are co-enriched with the primary ChIP target. For example, FOX family motifs are enriched in ChIP–seq peaks of 37 other CAPs. We show that motif content and occupancy patterns can distinguish between promoters and enhancers. This catalogue reveals high-occupancy target regions at which many CAPs associate, although each contains motifs for only a minority of the numerous associated transcription factors. These analyses provide a more complete overview of the gene regulatory networks that define this cell type, and demonstrate the usefulness of the large-scale production efforts of the ENCODE Consortium

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Scanning the horizon: towards transparent and reproducible neuroimaging research

Functional neuroimaging techniques have transformed our ability to probe the neurobiological basis of behaviour and are increasingly being applied by the wider neuroscience community. However, concerns have recently been raised that the conclusions that are drawn from some human neuroimaging studies are either spurious or not generalizable. Problems such as low statistical power, flexibility in data analysis, software errors and a lack of direct replication apply to many fields, but perhaps particularly to functional MRI. Here, we discuss these problems, outline current and suggested best practices, and describe how we think the field should evolve to produce the most meaningful and reliable answers to neuroscientific questions

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease