We define the chromatin accessibility and transcriptional landscapes in 13 human primary blood cell types that span the hematopoietic hierarchy. Exploiting the finding that the enhancer landscape ...better reflects cell identity than mRNA levels, we enable 'enhancer cytometry' for enumeration of pure cell types from complex populations. We identify regulators governing hematopoietic differentiation and further show the lineage ontogeny of genetic elements linked to diverse human diseases. In acute myeloid leukemia (AML), chromatin accessibility uncovers unique regulatory evolution in cancer cells with a progressively increasing mutation burden. Single AML cells exhibit distinctive mixed regulome profiles corresponding to disparate developmental stages. A method to account for this regulatory heterogeneity identified cancer-specific deviations and implicated HOX factors as key regulators of preleukemic hematopoietic stem cell characteristics. Thus, regulome dynamics can provide diverse insights into hematopoietic development and disease.
A hallmark of the immune system is the interplay among specialized cell types transitioning between resting and stimulated states. The gene regulatory landscape of this dynamic system has not been ...fully characterized in human cells. Here we collected assay for transposase-accessible chromatin using sequencing (ATAC-seq) and RNA sequencing data under resting and stimulated conditions for up to 32 immune cell populations. Stimulation caused widespread chromatin remodeling, including response elements shared between stimulated B and T cells. Furthermore, several autoimmune traits showed significant heritability in stimulation-responsive elements from distinct cell types, highlighting the importance of these cell states in autoimmunity. Allele-specific read mapping identified variants that alter chromatin accessibility in particular conditions, allowing us to observe evidence of function for a candidate causal variant that is undetected by existing large-scale studies in resting cells. Our results provide a resource of chromatin dynamics and highlight the need to characterize the effects of genetic variation in stimulated cells.
Forebrain development is characterized by highly synchronized cellular processes, which, if perturbed, can cause disease. To chart the regulatory activity underlying these events, we generated a map ...of accessible chromatin in human three-dimensional forebrain organoids. To capture corticogenesis, we sampled glial and neuronal lineages from dorsal or ventral forebrain organoids over 20 months in vitro. Active chromatin regions identified in human primary brain tissue were observed in organoids at different developmental stages. We used this resource to map genetic risk for disease and to explore evolutionary conservation. Moreover, we integrated chromatin accessibility with transcriptomics to identify putative enhancer-gene linkages and transcription factors that regulate human corticogenesis. Overall, this platform brings insights into gene-regulatory dynamics at previously inaccessible stages of human forebrain development, including signatures of neuropsychiatric disorders.
There are numerous ways in which plants can influence the composition of soil communities. However, it remains unclear whether information on plant community attributes, including taxonomic, ...phylogenetic, or trait-based composition, can be used to predict the structure of soil communities. We tested, in both monocultures and field-grown mixed temperate grassland communities, whether plant attributes predict soil communities including taxonomic groups from across the tree of life (fungi, bacteria, protists, and metazoa). The composition of all soil community groups was affected by plant species identity, both in monocultures and in mixed communities. Moreover, plant community composition predicted additional variation in soil community composition beyond what could be predicted from soil abiotic characteristics. In addition, analysis of the field aboveground plant community composition and the composition of plant roots suggests that plant community attributes are better predictors of soil communities than root distributions. However, neither plant phylogeny nor plant traits were strong predictors of soil communities in either experiment. Our results demonstrate that grassland plant species form specific associations with soil community members and that information on plant species distributions can improve predictions of soil community composition. These results indicate that specific associations between plant species and complex soil communities are key determinants of biodiversity patterns in grassland soils.
The use of plant traits to predict ecosystem functions has been gaining growing attention. Above‐ground plant traits, such as leaf nitrogen (N) content and specific leaf area (SLA), have been shown ...to strongly relate to ecosystem productivity, respiration and nutrient cycling. Furthermore, increasing plant functional trait diversity has been suggested as a possible mechanism to increase ecosystem carbon (C) storage. However, it is uncertain whether below‐ground plant traits can be predicted by above‐ground traits, and if both above‐ and below‐ground traits can be used to predict soil properties and ecosystem‐level functions.
Here, we used two adjacent field experiments in temperate grassland to investigate if above‐ and below‐ground plant traits are related, and whether relationships between plant traits, soil properties and ecosystem C fluxes (i.e. ecosystem respiration and net ecosystem exchange) measured in potted monocultures could be detected in mixed field communities.
We found that certain shoot traits (e.g. shoot N and C, and leaf dry matter content) were related to root traits (e.g. root N, root C:N and root dry matter content) in monocultures, but such relationships were either weak or not detected in mixed communities. Some relationships between plant traits (i.e. shoot N, root N and/or shoot C:N) and soil properties (i.e. inorganic N availability and microbial community structure) were similar in monocultures and mixed communities, but they were more strongly linked to shoot traits in monocultures and root traits in mixed communities. Structural equation modelling showed that above‐ and below‐ground traits and soil properties improved predictions of ecosystem C fluxes in monocultures, but not in mixed communities on the basis of community‐weighted mean traits.
Synthesis. Our results from a single grassland habitat detected relationships in monocultures between above‐ and below‐ground plant traits, and between plant traits, soil properties and ecosystem C fluxes. However, these relationships were generally weaker or different in mixed communities. Our results demonstrate that while plant traits can be used to predict certain soil properties and ecosystem functions in monocultures, they are less effective for predicting how changes in plant species composition influence ecosystem functions in mixed communities.
Our results from a single grassland habitat detected relationships in monocultures between above‐ and below‐ground plant traits, and between plant traits, soil properties and ecosystem C fluxes. However, these relationships were generally weaker or different in mixed communities. Our results demonstrate that while plant traits can be used to predict certain soil properties and ecosystem functions in monocultures, they are less effective for predicting how changes in plant species composition influence ecosystem functions in mixed communities.
Soil microbial communities regulate global biogeochemical cycles and respond rapidly to changing environmental conditions. However, understanding how soil microbial communities respond to climate ...change, and how this influences biogeochemical cycles, remains a major challenge. This is especially pertinent in alpine regions where climate change is taking place at double the rate of the global average, with large reductions in snow cover and earlier spring snowmelt expected as a consequence. Here, we show that spring snowmelt triggers an abrupt transition in the composition of soil microbial communities of alpine grassland that is closely linked to shifts in soil microbial functioning and biogeochemical pools and fluxes. Further, by experimentally manipulating snow cover we show that this abrupt seasonal transition in wide-ranging microbial and biogeochemical soil properties is advanced by earlier snowmelt. Preceding winter conditions did not change the processes that take place during snowmelt. Our findings emphasise the importance of seasonal dynamics for soil microbial communities and the biogeochemical cycles that they regulate. Moreover, our findings suggest that earlier spring snowmelt due to climate change will have far reaching consequences for microbial communities and nutrient cycling in these globally widespread alpine ecosystems.
Powerful new technologies for perturbing genetic elements have recently expanded the study of genetic interactions in model systems ranging from yeast to human cell lines. However, technical ...artifacts can confound signal across genetic screens and limit the immense potential of parallel screening approaches. To address this problem, we devised a novel PCA‐based method for correcting genome‐wide screening data, bolstering the sensitivity and specificity of detection for genetic interactions. Applying this strategy to a set of 436 whole genome CRISPR screens, we report more than 1.5 million pairs of correlated “co‐functional” genes that provide finer‐scale information about cell compartments, biological pathways, and protein complexes than traditional gene sets. Lastly, we employed a gene community detection approach to implicate core genes for cancer growth and compress signal from functionally related genes in the same community into a single score. This work establishes new algorithms for probing cancer cell networks and motivates the acquisition of further CRISPR screen data across diverse genotypes and cell types to further resolve complex cellular processes.
Synopsis
Learning signatures of confounding in pooled gene knockout screens increases power to detect co‐essential gene pairs by an order of magnitude. Analysis of hundreds of deconfounded cancer cell line growth screens generates new hypotheses for cancer drug targets and tissue‐specific growth pathways.
Over 1.5 million pairs of correlated gene essentiality profiles are identified.
Co‐essential gene pairs are shown to be co‐functional interactions broadly enriched for known biological pathways.
One‐dimensional genetic screens performed in parallel suffice to build genome‐wide co‐functional networks that exhibit diffusion of signal through gene‐gene edges.
Hijacking of gene modules by cancer driver genes is implicated as the modus operandi for several well‐studied malignancies.
Learning signatures of confounding in pooled gene knockout screens increases power to detect co‐essential gene pairs by an order of magnitude. Analysis of hundreds of deconfounded cancer cell line growth screens generates new hypotheses for cancer drug targets and tissue‐specific growth pathways.
Gene regulatory networks ensure that important genes are expressed at precise levels. When gene expression is sufficiently perturbed, it can lead to disease. To understand how gene expression ...disruptions percolate through a network, we must first map connections between regulatory genes and their downstream targets. However, we lack comprehensive knowledge of the upstream regulators of most genes. Here, we developed an approach for systematic discovery of upstream regulators of critical immune factors-IL2RA, IL-2 and CTLA4-in primary human T cells. Then, we mapped the network of the target genes of these regulators and putative cis-regulatory elements using CRISPR perturbations, RNA-seq and ATAC-seq. These regulators form densely interconnected networks with extensive feedback loops. Furthermore, this network is enriched for immune-associated disease variants and genes. These results provide insight into how immune-associated disease genes are regulated in T cells and broader principles about the structure of human gene regulatory networks.
Oxygen minimum zones (OMZs) contain the largest pools of oceanic methane but its origin and fate are poorly understood. High-resolution (<15 m) water column profiles revealed a 300 m thick layer of ...elevated methane (20-105 nM) in the anoxic core of the largest OMZ, the Eastern Tropical North Pacific. Sediment core incubations identified a clear benthic methane source where the OMZ meets the continental shelf, between 350 and 650 m, with the flux reflecting the concentration of methane in the overlying anoxic water. Further incubations characterised a methanogenic potential in the presence of both porewater sulphate and nitrate of up to 88 nmol g
day
in the sediment surface layer. In these methane-producing sediments, the majority (85%) of methyl coenzyme M reductase alpha subunit (mcrA) gene sequences clustered with Methanosarcinaceae (⩾96% similarity to Methanococcoides sp.), a family capable of performing non-competitive methanogenesis. Incubations with
C-CH
showed potential for both aerobic and anaerobic methane oxidation in the waters within and above the OMZ. Both aerobic and anaerobic methane oxidation is corroborated by the presence of particulate methane monooxygenase (pmoA) gene sequences, related to type I methanotrophs and the lineage of Candidatus Methylomirabilis oxyfera, known to perform nitrite-dependent anaerobic methane oxidation (N-DAMO), respectively.
Background & Aims:
Long-term safety data for infliximab and other therapies in Crohn’s disease (CD) are needed.
Methods:
We prospectively evaluated patients for prespecified safety-related outcomes.
...Results:
As of August 2004, 6290 patients were enrolled; 3179 received infliximab (5519 patient-years), 87% of whom received at least 2 infusions, and 3111 received other therapies (6123 patient-years). The mean length of follow-up evaluation was 1.9 years. More infliximab-treated patients had moderate-to-severe (30.8% vs 10.3%) or severe-fulminant (2.5% vs .6%) CD, and had surgical (17.5% vs 13.8%) or medical (14.4% vs 9.1%) hospitalizations in the previous year. More patients were taking prednisone (27.4% vs 16.1%), immunomodulators (49.4% vs 32.2%), or narcotic analgesics (9.8% vs 5.4%) when compared with those receiving other therapies (
P < .001, all comparisons). The mortality rates were similar for infliximab- and non–infliximab-treated patients (.53 per 100 patient-years vs .43; relative risk, 1.24; 95% confidence interval CI, .73–2.10). In multivariate logistic regression analysis, only prednisone was associated with an increased mortality risk (odds ratio OR, 2.10; 95% CI, 1.15–3.83;
P = .016). Although the unadjusted analysis showed an increased risk for infection with infliximab use, multivariate logistic regression analysis suggested that infliximab was not an independent predictor of serious infections (OR, .99; 95% CI, .64–1.54). Factors independently associated with serious infections included prednisone use (OR, 2.21; 95% CI, 1.46–3.34;
P < .001), narcotic analgesic use (OR, 2.38; 95% CI, 1.56–3.63;
P < .001), and moderate-to-severe disease activity (OR, 2.11; 95% CI, 1.10–4.05;
P = .024).
Conclusions:
Mortality rates were similar between infliximab- and non–infliximab-treated patients. The increased risk for serious infection observed with infliximab likely was owing to disease severity and prednisone use.
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