scholarly journals HNF4A defines tissue-specific circadian rhythms by beaconing BMAL1::CLOCK chromatin binding and shaping the rhythmic chromatin landscape

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Meng Qu ◽  
Han Qu ◽  
Zhenyu Jia ◽  
Steve A. Kay
Keyword(s):  
Circadian Rhythms ◽  
Cell Types ◽  
Wide Distribution ◽  
General Mechanism ◽  
Chromatin Binding ◽  
Tissue Specific ◽  
Genome Wide ◽  
Clock Component ◽  
Circadian Control ◽  
Diabetic Model

AbstractTranscription modulated by the circadian clock is diverse across cell types, underlying circadian control of peripheral metabolism and its observed perturbation in human diseases. We report that knockout of the lineage-specifying Hnf4a gene in mouse liver causes associated reductions in the genome-wide distribution of core clock component BMAL1 and accessible chromatin marks (H3K4me1 and H3K27ac). Ectopically expressing HNF4A remodels chromatin landscape and nucleates distinct tissue-specific BMAL1 chromatin binding events, predominantly in enhancer regions. Circadian rhythms are disturbed in Hnf4a knockout liver and HNF4A-MODY diabetic model cells. Additionally, the epigenetic state and accessibility of the liver genome dynamically change throughout the day, synchronized with chromatin occupancy of HNF4A and clustered expression of circadian outputs. Lastly, Bmal1 knockout attenuates HNF4A genome-wide binding in the liver, likely due to downregulated Hnf4a transcription. Our results may provide a general mechanism for establishing circadian rhythm heterogeneity during development and disease progression, governed by chromatin structure.

scholarly journals Nuclear receptor HNF4A transrepresses CLOCK:BMAL1 and modulates tissue-specific circadian networks

2018 ◽  
Vol 115 (52) ◽  
pp. E12305-E12312 ◽  
Author(s):  
Meng Qu ◽  
Tomas Duffy ◽  
Tsuyoshi Hirota ◽  
Steve A. Kay
Keyword(s):  
Nuclear Receptor ◽  
Metabolic Pathways ◽  
Feedback Loop ◽  
Transcriptional Activity ◽  
Transcript Level ◽  
Colon Cells ◽  
Tissue Specific ◽  
Metabolic Genes ◽  
Genome Wide ◽  
Circadian Control

Either expression level or transcriptional activity of various nuclear receptors (NRs) have been demonstrated to be under circadian control. With a few exceptions, little is known about the roles of NRs as direct regulators of the circadian circuitry. Here we show that the nuclear receptor HNF4A strongly transrepresses the transcriptional activity of the CLOCK:BMAL1 heterodimer. We define a central role for HNF4A in maintaining cell-autonomous circadian oscillations in a tissue-specific manner in liver and colon cells. Not only transcript level but also genome-wide chromosome binding of HNF4A is rhythmically regulated in the mouse liver. ChIP-seq analyses revealed cooccupancy of HNF4A and CLOCK:BMAL1 at a wide array of metabolic genes involved in lipid, glucose, and amino acid homeostasis. Taken together, we establish that HNF4A defines a feedback loop in tissue-specific mammalian oscillators and demonstrate its recruitment in the circadian regulation of metabolic pathways.

scholarly journals The somatic mutation landscape of the human body

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Pablo E. García-Nieto ◽  
Ashby J. Morrison ◽  
Hunter B. Fraser
Keyword(s):  
Mismatch Repair ◽  
Somatic Mutations ◽  
Wide Distribution ◽  
Mismatch Repair Gene ◽  
Repair Gene ◽  
Nonsense Mutations ◽  
Tissue Samples ◽  
Tissue Specific ◽  
Somatic Evolution ◽  
Genome Wide

Abstract Background Somatic mutations in healthy tissues contribute to aging, neurodegeneration, and cancer initiation, yet they remain largely uncharacterized. Results To gain a better understanding of the genome-wide distribution and functional impact of somatic mutations, we leverage the genomic information contained in the transcriptome to uniformly call somatic mutations from over 7500 tissue samples, representing 36 distinct tissues. This catalog, containing over 280,000 mutations, reveals a wide diversity of tissue-specific mutation profiles associated with gene expression levels and chromatin states. For example, lung samples with low expression of the mismatch-repair gene MLH1 show a mutation signature of deficient mismatch repair. In addition, we find pervasive negative selection acting on missense and nonsense mutations, except for mutations previously observed in cancer samples, which are under positive selection and are highly enriched in many healthy tissues. Conclusions These findings reveal fundamental patterns of tissue-specific somatic evolution and shed light on aging and the earliest stages of tumorigenesis.

scholarly journals Leveraging Gene Co-expression Patterns to Infer Trait-Relevant Tissues in Genome-wide Association Studies

2019 ◽  
Author(s):  
Lulu Shang ◽  
Jennifer A. Smith ◽  
Xiang Zhou
Keyword(s):  
Autoimmune Diseases ◽  
Single Cell ◽  
Neurological Disorders ◽  
Association Studies ◽  
Cell Types ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Tissue Specific ◽  
Genome Wide ◽  
Rnaseq Data

AbstractGenome-wide association studies (GWASs) have identified many SNPs associated with various common diseases. Understanding the biological functions of these identified SNP associations requires identifying disease/trait relevant tissues or cell types. Here, we develop a network method, CoCoNet, to facilitate the identification of trait-relevant tissues or cell types. Different from existing approaches, CoCoNet incorporates tissue-specific gene co-expression networks constructed from either bulk or single cell RNA sequencing (RNAseq) studies with GWAS data for trait-tissue inference. In particular, CoCoNet relies on a covariance regression network model to express gene-level effect sizes for the given GWAS trait as a function of the tissue-specific co-expression adjacency matrix. With a composite likelihood-based inference algorithm, CoCoNet is scalable to tens of thousands of genes. We validate the performance of CoCoNet through extensive simulations. We apply CoCoNet for an in-depth analysis of four neurological disorders and four autoimmune diseases, where we integrate the corresponding GWASs with bulk RNAseq data from 38 tissues and single cell RNAseq data from 10 cell types. In the real data applications, we show how CoCoNet can help identify specific glial cell types relevant for neurological disorders and identify disease-targeted colon tissues as relevant for autoimmune diseases. Our results also provide empirical evidence supporting one hypothesis of the omnigenic model: that trait-relevant gene co-expression networks underlie disease etiology.

scholarly journals Genetic analysis of amyotrophic lateral sclerosis identifies contributing pathways and cell types

2021 ◽  
Vol 7 (3) ◽  
pp. eabd9036
Author(s):  
Sara Saez-Atienzar ◽  
Sara Bandres-Ciga ◽  
Rebekah G. Langston ◽  
Jonggeol J. Kim ◽  
Shing Wan Choi ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Membrane Trafficking ◽  
Molecular Mechanisms ◽  
Cell Types ◽  
Polygenic Risk Score ◽  
Genome Wide ◽  
Genome Wide Data ◽  
Data Driven Approach ◽  
Single Nucleus ◽  
Lateral Sclerosis

Despite the considerable progress in unraveling the genetic causes of amyotrophic lateral sclerosis (ALS), we do not fully understand the molecular mechanisms underlying the disease. We analyzed genome-wide data involving 78,500 individuals using a polygenic risk score approach to identify the biological pathways and cell types involved in ALS. This data-driven approach identified multiple aspects of the biology underlying the disease that resolved into broader themes, namely, neuron projection morphogenesis, membrane trafficking, and signal transduction mediated by ribonucleotides. We also found that genomic risk in ALS maps consistently to GABAergic interneurons and oligodendrocytes, as confirmed in human single-nucleus RNA-seq data. Using two-sample Mendelian randomization, we nominated six differentially expressed genes (ATG16L2, ACSL5, MAP1LC3A, MAPKAPK3, PLXNB2, and SCFD1) within the significant pathways as relevant to ALS. We conclude that the disparate genetic etiologies of this fatal neurological disease converge on a smaller number of final common pathways and cell types.

scholarly journals Adult tissue-resident stem cells—fact or fiction?

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Deepa Bhartiya
Keyword(s):  
Stem Cells ◽  
Single Cell ◽  
Adult Stem Cells ◽  
Cell Types ◽  
Specific Cell ◽  
Tissue Specific ◽  
Cardiac Tissues ◽  
Adult Tissues ◽  
Resident Stem Cells ◽  
Abundant Cytoplasm

AbstractLife-long tissue homeostasis of adult tissues is supposedly maintained by the resident stem cells. These stem cells are quiescent in nature and rarely divide to self-renew and give rise to tissue-specific “progenitors” (lineage-restricted and tissue-committed) which divide rapidly and differentiate into tissue-specific cell types. However, it has proved difficult to isolate these quiescent stem cells as a physical entity. Recent single-cell RNAseq studies on several adult tissues including ovary, prostate, and cardiac tissues have not been able to detect stem cells. Thus, it has been postulated that adult cells dedifferentiate to stem-like state to ensure regeneration and can be defined as cells capable to replace lost cells through mitosis. This idea challenges basic paradigm of development biology regarding plasticity that a cell enters point of no return once it initiates differentiation. The underlying reason for this dilemma is that we are putting stem cells and somatic cells together while processing for various studies. Stem cells and adult mature cell types are distinct entities; stem cells are quiescent, small in size, and with minimal organelles whereas the mature cells are metabolically active and have multiple organelles lying in abundant cytoplasm. As a result, they do not pellet down together when centrifuged at 100–350g. At this speed, mature cells get collected but stem cells remain buoyant and can be pelleted by centrifuging at 1000g. Thus, inability to detect stem cells in recently published single-cell RNAseq studies is because the stem cells were unknowingly discarded while processing and were never subjected to RNAseq. This needs to be kept in mind before proposing to redefine adult stem cells.

scholarly journals Author Correction: Determinants of genome-wide distribution and evolution of uORFs in eukaryotes

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hong Zhang ◽  
Yirong Wang ◽  
Xinkai Wu ◽  
Xiaolu Tang ◽  
Changcheng Wu ◽  
...  
Keyword(s):  
Wide Distribution ◽  
Genome Wide

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22435-2

scholarly journals Comment on “Circadian rhythms in the absence of the clock gene Bmal1”

Science ◽  
2021 ◽  
Vol 372 (6539) ◽  
pp. eabe9230 ◽  
Author(s):  
Elan Ness-Cohn ◽  
Ravi Allada ◽  
Rosemary Braun
Keyword(s):  
Circadian Rhythms ◽  
Clock Gene ◽  
Insufficient Evidence ◽  
The Core ◽  
Clock Component ◽  
Mouse Tissues ◽  
Associated Data

Ray et al. (Reports, 14 February 2020, p. 800) report apparent transcriptional circadian rhythms in mouse tissues lacking the core clock component BMAL1. To better understand these surprising results, we reanalyzed the associated data. We were unable to reproduce the original findings, nor could we identify reliably cycling genes. We conclude that there is insufficient evidence to support circadian transcriptional rhythms in the absence of Bmal1.

scholarly journals Mitochondrial DNA Heteroplasmy as an Informational Reservoir Dynamically Linked to Metabolic and Immunological Processes Associated with COVID-19 Neurological Disorders

2021 ◽  
Author(s):  
George B. Stefano ◽  
Richard M. Kream
Keyword(s):  
Mitochondrial Dna ◽  
Mitochondrial Function ◽  
Neurological Disorders ◽  
Nuclear Dna ◽  
Mitochondrial Dynamics ◽  
Cell Types ◽  
Tissue Specific ◽  
Copy Numbers ◽  
The Central Nervous System ◽  
Mitochondrial Dna Heteroplasmy

AbstractMitochondrial DNA (mtDNA) heteroplasmy is the dynamically determined co-expression of wild type (WT) inherited polymorphisms and collective time-dependent somatic mutations within individual mtDNA genomes. The temporal expression and distribution of cell-specific and tissue-specific mtDNA heteroplasmy in healthy individuals may be functionally associated with intracellular mitochondrial signaling pathways and nuclear DNA gene expression. The maintenance of endogenously regulated tissue-specific copy numbers of heteroplasmic mtDNA may represent a sensitive biomarker of homeostasis of mitochondrial dynamics, metabolic integrity, and immune competence. Myeloid cells, monocytes, macrophages, and antigen-presenting dendritic cells undergo programmed changes in mitochondrial metabolism according to innate and adaptive immunological processes. In the central nervous system (CNS), the polarization of activated microglial cells is dependent on strategically programmed changes in mitochondrial function. Therefore, variations in heteroplasmic mtDNA copy numbers may have functional consequences in metabolically competent mitochondria in innate and adaptive immune processes involving the CNS. Recently, altered mitochondrial function has been demonstrated in the progression of coronavirus disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Accordingly, our review is organized to present convergent lines of empirical evidence that potentially link expression of mtDNA heteroplasmy by functionally interactive CNS cell types to the extent and severity of acute and chronic post-COVID-19 neurological disorders.

scholarly journals E-MAGMA: an eQTL-informed method to identify risk genes using genome-wide association study summary statistics

2021 ◽  
Author(s):  
Zachary F Gerring ◽  
Angela Mina-Vargas ◽  
Eric R Gamazon ◽  
Eske M Derks
Keyword(s):  
Genome Wide Association ◽  
Chromosome 1 ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Tissue Specific ◽  
Complex Disorders ◽  
Risk Variants ◽  
Genome Wide ◽  
Causal Genes

Abstract Motivation Genome-wide association studies have successfully identified multiple independent genetic loci that harbour variants associated with human traits and diseases, but the exact causal genes are largely unknown. Common genetic risk variants are enriched in non-protein-coding regions of the genome and often affect gene expression (expression quantitative trait loci, eQTL) in a tissue-specific manner. To address this challenge, we developed a methodological framework, E-MAGMA, which converts genome-wide association summary statistics into gene-level statistics by assigning risk variants to their putative genes based on tissue-specific eQTL information. Results We compared E-MAGMA to three eQTL informed gene-based approaches using simulated phenotype data. Phenotypes were simulated based on eQTL reference data using GCTA for all genes with at least one eQTL at chromosome 1. We performed 10 simulations per gene. The eQTL-h2 (i.e., the proportion of variation explained by the eQTLs) was set at 1%, 2%, and 5%. We found E-MAGMA outperforms other gene-based approaches across a range of simulated parameters (e.g. the number of identified causal genes). When applied to genome-wide association summary statistics for five neuropsychiatric disorders, E-MAGMA identified more putative candidate causal genes compared to other eQTL-based approaches. By integrating tissue-specific eQTL information, these results show E-MAGMA will help to identify novel candidate causal genes from genome-wide association summary statistics and thereby improve the understanding of the biological basis of complex disorders. Availability A tutorial and input files are made available in a github repository: https://github.com/eskederks/eMAGMA-tutorial. Supplementary information Supplementary data are available at Bioinformatics online.

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