8 research outputs found

    Sucrose and Ethylene Signaling Interact to Modulate the Circadian Clock.

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    Circadian clocks drive rhythmic physiology and metabolism to optimize plant growth and performance under daily environmental fluctuations caused by the rotation of the planet. Photosynthesis is a key metabolic process that must be appropriately timed to the light-dark cycle. The circadian clock contributes to the regulation of photosynthesis, and in turn the daily accumulation of sugars from photosynthesis also feeds back to regulate the circadian oscillator. We have previously shown that GIGANTEA (GI) is required to sustain Suc-dependent circadian rhythms in darkness. The mechanism by which Suc affects the circadian oscillator in a GI-dependent manner was unknown. Here, we identify that Suc sustains rhythms in the dark by stabilizing GI protein, dependent on the F-box protein ZEITLUPE, and implicate CONSTITUTIVE TRIPLE RESPONSE1 (CTR1), a negative regulator of ethylene signaling. Our identification of a role for CTR1 in the response to Suc prompted a reinvestigation of the effects of ethylene on the circadian oscillator. We demonstrate that ethylene shortens the circadian period, conditional on the effects of Suc and requiring GI These findings reveal that Suc affects the stability of circadian oscillator proteins and can mask the effects of ethylene on the circadian system, identifying novel molecular pathways for input of sugar to the Arabidopsis (Arabidopsis thaliana) circadian network.This research was supported by the BBSRC (BB/H006826/1 and BB/L021188/1

    Cost optimization and risk minimization during teamwork organization

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    In the paper the problem of personnel allocation under threat was presented. The possibilities of undertaking optimization measures in the process of workers’ health and safety and expenses incurred were emphasized. A mathematical model for this issue has been formulated. An algorithm solving the problem of staff allocation was presented. The evaluation criterion for this assignment was the minimization of worker safety risks. Simultaneous optimization of expenses incurred in the implementation of production tasks was taken into account. The productivity of the staff and all existing jobs with the skills of the employees also was considered. This problem was solved using GNU Octave. The example presented in the paper shows that in case of the most unfavorable allocation of tasks to employees, it will lead to a significant reduction in profits and may increase the risk of undesirable situations. The proposed analysis is the starting point for determining the risk in case of multi-position work

    Intra- and interchromosomal contact mapping reveals the Igh locus has extensive conformational heterogeneity and interacts with B-lineage genes

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    Summary: To produce a diverse antibody repertoire, immunoglobulin heavy-chain (Igh) loci undergo large-scale alterations in structure to facilitate juxtaposition and recombination of spatially separated variable (VH), diversity (DH), and joining (JH) genes. These chromosomal alterations are poorly understood. Uncovering their patterns shows how chromosome dynamics underpins antibody diversity. Using tiled Capture Hi-C, we produce a comprehensive map of chromatin interactions throughout the 2.8-Mb Igh locus in progenitor B cells. We find that the Igh locus folds into semi-rigid subdomains and undergoes flexible looping of the VH genes to its 3â€Č end, reconciling two views of locus organization. Deconvolution of single Igh locus conformations using polymer simulations identifies thousands of different structures. This heterogeneity may underpin the diversity of V(D)J recombination events. All three immunoglobulin loci also participate in a highly specific, developmentally regulated network of interchromosomal interactions with genes encoding B cell-lineage factors. This suggests a model of interchromosomal coordination of B cell development

    Identification of LZTFL1 as a candidate effector gene at a COVID-19 risk locus

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    The severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) disease (COVID-19) pandemic has caused millions of deaths worldwide. Genome-wide association studies identified the 3p21.31 region as conferring a twofold increased risk of respiratory failure. Here, using a combined multiomics and machine learning approach, we identify the gain-of-function risk A allele of an SNP, rs17713054G>A, as a probable causative variant. We show with chromosome conformation capture and gene-expression analysis that the rs17713054-affected enhancer upregulates the interacting gene, leucine zipper transcription factor like 1 (LZTFL1). Selective spatial transcriptomic analysis of lung biopsies from patients with COVID-19 shows the presence of signals associated with epithelial–mesenchymal transition (EMT), a viral response pathway that is regulated by LZTFL1. We conclude that pulmonary epithelial cells undergoing EMT, rather than immune cells, are likely responsible for the 3p21.31-associated risk. Since the 3p21.31 effect is conferred by a gain-of-function, LZTFL1 may represent a therapeutic target

    Comprehensive epigenomic profiling reveals the extent of disease-specific chromatin states and informs target discovery in ankylosing spondylitis

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    International audienceAnkylosing spondylitis (AS) is a common, highly heritable inflammatory arthritis characterized by enthesitis of the spine and sacroiliac joints. Genome-wide association studies (GWASs) have revealed more than 100 genetic associations whose functional effects remain largely unresolved. Here, we present a comprehensive transcriptomic and epigenomic map of disease-relevant blood immune cell subsets from AS patients and healthy controls. We find that, while CD14+ monocytes and CD4+ and CD8+ T cells show disease-specific differences at the RNA level, epigenomic differences are only apparent upon multi-omics integration. The latter reveals enrichment at disease-associated loci in monocytes. We link putative functional SNPs to genes using high-resolution Capture-C at 10 loci, including PTGER4 and ETS1, and show how disease-specific functional genomic data can be integrated with GWASs to enhance therapeutic target discovery. This study combines epigenetic and transcriptional analysis with GWASs to identify disease-relevant cell types and gene regulation of likely pathogenic relevance and prioritize drug targets
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