Balanced Genome Triplication in Wheat Causes Premature Growth Arrest and an Upheaval of Genome-Wide Gene Regulation

RAD51 is a recombinase that plays a pivotal role in homologous recombination. Although the role of RAD51 in homologous recombination has been extensively studied, it is unclear whether RAD51 can be involved in gene regulation as a co-factor. In this study, we found evidence that RAD51 may contribute to the regulation of genes involved in the autophagy pathway with E-box proteins such as USF1, USF2, and/or MITF in GM12878, HepG2, K562, and MCF-7 cell lines. The canonical USF binding motif (CACGTG) was significantly identified at RAD51-bound cis-regulatory elements in all four cell lines. In addition, genome-wide USF1, USF2, and/or MITF-binding regions significantly coincided with the RAD51-associated cis-regulatory elements in the same cell line. Interestingly, the promoters of genes associated with the autophagy pathway, such as ATG3 and ATG5, were significantly occupied by RAD51 and regulated by RAD51 in HepG2 and MCF-7 cell lines. Taken together, these results unveiled a novel role of RAD51 and provided evidence that RAD51-associated cis-regulatory elements could possibly be involved in regulating autophagy-related genes with E-box binding proteins.

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Genome-wide analysis of enhancer RNA in gene regulation across 12 mouse tissues

Scientific Reports ◽

10.1038/srep12648 ◽

2015 ◽

Vol 5 (1) ◽

Cited By ~ 31

Author(s):

Jen-Hao Cheng ◽

David Zhi-Chao Pan ◽

Zing Tsung-Yeh Tsai ◽

Huai-Kuang Tsai

Keyword(s):

Gene Regulation ◽

Genome Wide Analysis ◽

Enhancer Rna ◽

Genome Wide ◽

Mouse Tissues

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CTCF looping is established during gastrulation in medaka embryos

10.1101/454082 ◽

2018 ◽

Cited By ~ 2

Author(s):

Ryohei Nakamura ◽

Yuichi Motai ◽

Masahiko Kumagai ◽

Haruyo Nishiyama ◽

Neva C. Durand ◽

...

Keyword(s):

Gene Regulation ◽

Embryonic Development ◽

Protein Binding ◽

Early Development ◽

Great Increase ◽

Critical Role ◽

Early Embryogenesis ◽

Genome Architecture ◽

Time Points ◽

Genome Wide

Abstract:Genome architecture plays a critical role in gene regulation, but how the structures seen in mature cells emerge during embryonic development remains poorly understood. Here, we study early development in medaka (the Japanese killifish, Oryzias latipes) at 12 time points before, during, and after gastrulation which is the most dramatic event in early embryogenesis, and characterize transcription, protein binding, and genome architecture. We find that gastrulation is most associated with drastic changes in genome architecture, including the formation of the first loops between sites bound by the insulator protein CTCF and great increase in the size of contact domains. However, the position of CTCF is fixed throughout medaka embryogenesis. Interestingly, genome-wide transcription precedes the emergence of mature domains and CTCF-CTCF loops.

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Common genetic risk variants identified in the SPARK cohort implicate DDHD2 as a novel autism risk gene

10.1101/2020.01.13.20017319 ◽

2020 ◽

Cited By ~ 3

Author(s):

Nana Matoba ◽

Dan Liang ◽

Huaigu Sun ◽

Nil Aygün ◽

Jessica C. McAfee ◽

...

Keyword(s):

Gene Regulation ◽

Association Study ◽

Genetic Risk ◽

Molecular Mechanisms ◽

Autism Spectrum ◽

Risk Variants ◽

Genome Wide ◽

Common Genetic Variants ◽

A Genome ◽

Gene Regulatory

AbstractBackgroundAutism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder. Large genetically informative cohorts of individuals with ASD have led to the identification of three common genome-wide significant (GWS) risk loci to date. However, many more common genetic variants are expected to contribute to ASD risk given the high heritability. Here, we performed a genome-wide association study (GWAS) using the Simons Foundation Powering Autism Research for Knowledge (SPARK) dataset to identify additional common genetic risk factors and molecular mechanisms underlying risk for ASD.MethodsWe performed an association study on 6,222 case-pseudocontrol pairs from SPARK and meta-analyzed with a previous GWAS. We integrated gene regulatory annotations to map non-coding risk variants to their regulated genes. Further, we performed a massively parallel reporter assay (MPRA) to identify causal variant(s) within a novel risk locus.ResultsWe identified one novel GWS locus from the SPARK GWAS. The meta-analysis identified four significant loci, including an additional novel locus. We observed significant enrichment of ASD heritability within regulatory regions of the developing cortex, indicating that disruption of gene regulation during neurodevelopment is critical for ASD risk. The MPRA identified one variant at the novel locus with strong impacts on gene regulation (rs7001340), and expression quantitative trait loci data demonstrated an association between the risk allele and decreased expression of DDHD2 (DDHD domain containing 2) in both adult and pre-natal brains.ConclusionsBy integrating genetic association data with multi-omic gene regulatory annotations and experimental validation, we fine-mapped a causal risk variant and demonstrated that DDHD2 is a novel gene associated with ASD risk.

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The orange phenol hesperidin can induce genome-wide hypomethylation in cancer cells as a non-genotoxic mechanism of gene regulation

Toxicology Letters ◽

10.1016/j.toxlet.2011.05.195 ◽

2011 ◽

Vol 205 ◽

pp. S50 ◽

Cited By ~ 1

Author(s):

Z. Fernández-Bedmar ◽

J. Anter ◽

M. Villatoro-Pulido ◽

V. Martin-Palanco ◽

M. Del Río-Celestino ◽

...

Keyword(s):

Gene Regulation ◽

Cancer Cells ◽

Genome Wide

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Long Non-Coding RNAs as Endogenous Target Mimics and Exploration of Their Role in Low Nutrient Stress Tolerance in Plants

Genes ◽

10.3390/genes9090459 ◽

2018 ◽

Vol 9 (9) ◽

pp. 459 ◽

Cited By ~ 5

Author(s):

Priyanka Borah ◽

Antara Das ◽

Matthew Milner ◽

Arif Ali ◽

Alison Bentley ◽

...

Keyword(s):

Gene Regulation ◽

Next Generation Sequencing ◽

Non Coding Rna ◽

Genome Wide ◽

Non Coding Rnas ◽

Endogenous Target ◽

Long Non Coding Rna ◽

Nutrient Homeostasis ◽

Generation Sequencing

Long non-coding RNA (lncRNA) research in plants has recently gained momentum taking cues from studies in animals systems. The availability of next-generation sequencing has enabled genome-wide identification of lncRNA in several plant species. Some lncRNAs are inhibitors of microRNA expression and have a function known as target mimicry with the sequestered transcript known as an endogenous target mimic (eTM). The lncRNAs identified to date show diverse mechanisms of gene regulation, most of which remain poorly understood. In this review, we discuss the role of identified putative lncRNAs that may act as eTMs for nutrient-responsive microRNAs (miRNAs) in plants. If functionally validated, these putative lncRNAs would enhance current understanding of the role of lncRNAs in nutrient homeostasis in plants.

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An integrative approach for fine-mapping chromatin interactions

Bioinformatics ◽

10.1093/bioinformatics/btz843 ◽

2019 ◽

Vol 36 (6) ◽

pp. 1704-1711

Author(s):

Artur Jaroszewicz ◽

Jason Ernst

Keyword(s):

Gene Regulation ◽

High Resolution ◽

Biological Significance ◽

Computational Method ◽

Supplementary Information ◽

Integrative Approach ◽

Genome Architecture ◽

Open Chromatin ◽

Chromatin Interactions ◽

Genome Wide

Abstract Motivation Chromatin interactions play an important role in genome architecture and gene regulation. The Hi-C assay generates such interactions maps genome-wide, but at relatively low resolutions (e.g. 5-25 kb), which is substantially coarser than the resolution of transcription factor binding sites or open chromatin sites that are potential sources of such interactions. Results To predict the sources of Hi-C-identified interactions at a high resolution (e.g. 100 bp), we developed a computational method that integrates data from DNase-seq and ChIP-seq of TFs and histone marks. Our method, χ-CNN, uses this data to first train a convolutional neural network (CNN) to discriminate between called Hi-C interactions and non-interactions. χ-CNN then predicts the high-resolution source of each Hi-C interaction using a feature attribution method. We show these predictions recover original Hi-C peaks after extending them to be coarser. We also show χ-CNN predictions enrich for evolutionarily conserved bases, eQTLs and CTCF motifs, supporting their biological significance. χ-CNN provides an approach for analyzing important aspects of genome architecture and gene regulation at a higher resolution than previously possible. Availability and implementation χ-CNN software is available on GitHub (https://github.com/ernstlab/X-CNN). Supplementary information Supplementary data are available at Bioinformatics online.

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