scholarly journals Transcription-coupled and epigenome-encoded mechanisms direct H3K4 methylation

2021 ◽  
Author(s):  
Satoyo Oya ◽  
Mayumi Takahashi ◽  
Kazuya Takashima ◽  
Tetsuji Kakutani ◽  
Soichi Inagaki

Mono-, di-, and trimethylation of histone H3 lysine 4 (H3K4me1/2/3) are associated with transcription, yet it remains controversial whether H3K4me1/2/3 promote or result from transcription. Our previous characterizations of Arabidopsis H3K4 demethylases suggest roles for H3K4me1 in transcription. However, the control of H3K4me1 remains unexplored in Arabidopsis, in which no methylase for H3K4me1 has been identified. Here, we identified three Arabidopsis methylases that direct H3K4me1. Analyses of their genome-wide localization using ChIP-seq and machine learning revealed that one of the enzymes cooperates with the transcription machinery, while the other two are associated with specific histone modifications and DNA sequences. Importantly, these two types of localization patterns are also found for the other H3K4 methylases in Arabidopsis and mice. These results suggest that H3K4me1/2/3 are established and maintained via interplay with transcription as well as inputs from other chromatin features, presumably enabling elaborate gene control.

mBio ◽  
2019 ◽  
Vol 10 (4) ◽  
Author(s):  
Robert Jordan Price ◽  
Esther Weindling ◽  
Judith Berman ◽  
Alessia Buscaino

ABSTRACT Eukaryotic genomes are packaged into chromatin structures that play pivotal roles in regulating all DNA-associated processes. Histone posttranslational modifications modulate chromatin structure and function, leading to rapid regulation of gene expression and genome stability, key steps in environmental adaptation. Candida albicans, a prevalent fungal pathogen in humans, can rapidly adapt and thrive in diverse host niches. The contribution of chromatin to C. albicans biology is largely unexplored. Here, we generated the first comprehensive chromatin profile of histone modifications (histone H3 trimethylated on lysine 4 [H3K4me3], histone H3 acetylated on lysine 9 [H3K9Ac], acetylated lysine 16 on histone H4 [H4K16Ac], and γH2A) across the C. albicans genome and investigated its relationship to gene expression by harnessing genome-wide sequencing approaches. We demonstrated that gene-rich nonrepetitive regions are packaged into canonical euchromatin in association with histone modifications that mirror their transcriptional activity. In contrast, repetitive regions are assembled into distinct chromatin states; subtelomeric regions and the ribosomal DNA (rDNA) locus are assembled into heterochromatin, while major repeat sequences and transposons are packaged in chromatin that bears features of euchromatin and heterochromatin. Genome-wide mapping of γH2A, a marker of genome instability, identified potential recombination-prone genomic loci. Finally, we present the first quantitative chromatin profiling in C. albicans to delineate the role of the chromatin modifiers Sir2 and Set1 in controlling chromatin structure and gene expression. This report presents the first genome-wide chromatin profiling of histone modifications associated with the C. albicans genome. These epigenomic maps provide an invaluable resource to understand the contribution of chromatin to C. albicans biology and identify aspects of C. albicans chromatin organization that differ from that of other yeasts. IMPORTANCE The fungus Candida albicans is an opportunistic pathogen that normally lives on the human body without causing any harm. However, C. albicans is also a dangerous pathogen responsible for millions of infections annually. C. albicans is such a successful pathogen because it can adapt to and thrive in different environments. Chemical modifications of chromatin, the structure that packages DNA into cells, can allow environmental adaptation by regulating gene expression and genome organization. Surprisingly, the contribution of chromatin modification to C. albicans biology is still largely unknown. For the first time, we analyzed C. albicans chromatin modifications on a genome-wide basis. We demonstrate that specific chromatin states are associated with distinct regions of the C. albicans genome and identify the roles of the chromatin modifiers Sir2 and Set1 in shaping C. albicans chromatin and gene expression.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jiali Sun ◽  
Qingtai Wu ◽  
Dafeng Shen ◽  
Yangjun Wen ◽  
Fengrong Liu ◽  
...  

AbstractOne of the most important tasks in genome-wide association analysis (GWAS) is the detection of single-nucleotide polymorphisms (SNPs) which are related to target traits. With the development of sequencing technology, traditional statistical methods are difficult to analyze the corresponding high-dimensional massive data or SNPs. Recently, machine learning methods have become more popular in high-dimensional genetic data analysis for their fast computation speed. However, most of machine learning methods have several drawbacks, such as poor generalization ability, over-fitting, unsatisfactory classification and low detection accuracy. This study proposed a two-stage algorithm based on least angle regression and random forest (TSLRF), which firstly considered the control of population structure and polygenic effects, then selected the SNPs that were potentially related to target traits by using least angle regression (LARS), furtherly analyzed this variable subset using random forest (RF) to detect quantitative trait nucleotides (QTNs) associated with target traits. The new method has more powerful detection in simulation experiments and real data analyses. The results of simulation experiments showed that, compared with the existing approaches, the new method effectively improved the detection ability of QTNs and model fitting degree, and required less calculation time. In addition, the new method significantly distinguished QTNs and other SNPs. Subsequently, the new method was applied to analyze five flowering-related traits in Arabidopsis. The results showed that, the distinction between QTNs and unrelated SNPs was more significant than the other methods. The new method detected 60 genes confirmed to be related to the target trait, which was significantly higher than the other methods, and simultaneously detected multiple gene clusters associated with the target trait.


2021 ◽  
Author(s):  
Roman Hillje ◽  
Lucilla Luzi ◽  
Stefano Amatori ◽  
Mirco Fanelli ◽  
Pier Giuseppe Pelicci ◽  
...  

Abstract To disclose the epigenetic drift of time passing, we determined the genome-wide distributions of mono- and tri-methylated lysine 4 and acetylated and tri-methylated lysine 27 of histone H3 in the livers of healthy 3, 6 and 12 months old C57BL/6 mice. The comparison of different age profiles of histone H3 marks revealed global redistribution of histone H3 modifications with time, in particular in intergenic regions and near transcription start sites, as well as altered correlation between the profiles of different histone modifications. Moreover, feeding mice with caloric restriction diet, a treatment known to retard aging, preserved younger state of histone H3 in these genomic regions.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Wan Kin Au Yeung ◽  
Osamu Maruyama ◽  
Hiroyuki Sasaki

Abstract Background Epigenetic modifications, including CG methylation (a major form of DNA methylation) and histone modifications, interact with each other to shape their genomic distribution patterns. However, the entire picture of the epigenetic crosstalk regulating the CG methylation pattern is unknown especially in cells that are available only in a limited number, such as mammalian oocytes. Most machine learning approaches developed so far aim at finding DNA sequences responsible for the CG methylation patterns and were not tailored for studying the epigenetic crosstalk. Results We built a machine learning model named epiNet to predict CG methylation patterns based on other epigenetic features, such as histone modifications, but not DNA sequence. Using epiNet, we identified biologically relevant epigenetic crosstalk between histone H3K36me3, H3K4me3, and CG methylation in mouse oocytes. This model also predicted the altered CG methylation pattern of mutant oocytes having perturbed histone modification, was applicable to cross-species prediction of the CG methylation pattern of human oocytes, and identified the epigenetic crosstalk potentially important in other cell types. Conclusions Our findings provide insight into the epigenetic crosstalk regulating the CG methylation pattern in mammalian oocytes and other cells. The use of epiNet should help to design or complement biological experiments in epigenetics studies.


Chromosoma ◽  
2020 ◽  
Vol 129 (3-4) ◽  
pp. 285-297
Author(s):  
M. Baez ◽  
Y. T. Kuo ◽  
Y. Dias ◽  
T. Souza ◽  
A. Boudichevskaia ◽  
...  

AbstractFor a long time, the Cyperid clade (Thurniceae-Juncaceae-Cyperaceae) was considered a group of species possessing holocentromeres exclusively. The basal phylogenetic position of Prionium serratum (Thunb.) Drège (Thurniceae) within Cyperids makes this species an important specimen to understand the centromere evolution within this clade. In contrast to the expectation, the chromosomal distribution of the centromere-specific histone H3 (CENH3), alpha-tubulin and different centromere-associated post-translational histone modifications (H3S10ph, H3S28ph and H2AT120ph) demonstrate a monocentromeric organisation of P. serratum chromosomes. Analysis of the high-copy repeat composition resulted in the identification of two centromere-localised satellite repeats. Hence, monocentricity was the ancestral condition for the Juncaceae-Cyperaceae-Thurniaceae Cyperid clade, and holocentricity in this clade has independently arisen at least twice after differentiation of the three families, once in Juncaceae and the other one in Cyperaceae. In this context, methods suitable for the identification of holocentromeres are discussed.


2006 ◽  
Vol 282 (7) ◽  
pp. 4408-4416 ◽  
Author(s):  
Karl P. Nightingale ◽  
Susanne Gendreizig ◽  
Darren A. White ◽  
Charlotte Bradbury ◽  
Florian Hollfelder ◽  
...  

Histones are subject to a wide variety of post-translational modifications that play a central role in gene activation and silencing. We have used histone modification-specific antibodies to demonstrate that two histone modifications involved in gene activation, histone H3 acetylation and H3 lysine 4 methylation, are functionally linked. This interaction, in which the extent of histone H3 acetylation determines both the abundance and the “degree” of H3K4 methylation, plays a major role in the epigenetic response to histone deacetylase inhibitors. A combination of in vivo knockdown experiments and in vitro methyltransferase assays shows that the abundance of H3K4 methylation is regulated by the activities of two opposing enzyme activities, the methyltransferase MLL4, which is stimulated by acetylated substrates, and a novel and as yet unidentified H3K4me3 demethylase.


Author(s):  
M. Baez ◽  
Y.T. Kuo ◽  
Y. Dias ◽  
T. Souza ◽  
A. Boudichevskaia ◽  
...  

AbstractFor a long time, the Cyperid clade (Thurniceae-Juncaceae-Cyperaceae) was considered as a group of species possessing holocentromeres exclusively. The basal phylogenetic position of Prionium serratum L. f. Drège (Thurniceae) within Cyperids makes this species an important specimen to understand the centromere evolution within this clade. Unlike expected, the chromosomal distribution of the centromere-specific histone H3 (CENH3), alpha-tubulin and different centromere associated post-translational histone modifications (H3S10ph, H3S28ph and H2AT120ph) demonstrate a monocentromeric organisation of P. serratum chromosomes. Analysis of the high-copy repeat composition resulted in the identification of a centromere-localised satellite repeat. Hence, monocentricity was the ancestral condition for the Juncaceae-Cyperaceae-Thurniaceae Cyperid clade and holocentricity in this clade has independently arisen at least twice after differentiation of the three families, once in Juncaceae and the other one in Cyperaceae. Methods suitable for the identification of holocentromeres are discussed.


2013 ◽  
Vol 41 (3) ◽  
pp. 789-796 ◽  
Author(s):  
Asmita Tingare ◽  
Bernard Thienpont ◽  
H. Llewelyn Roderick

Understanding the molecular mechanisms underlying cardiac development and growth has been a longstanding goal for developing therapies for cardiovascular disorders. The heart adapts to a rise in its required output by an increase in muscle mass and alteration in the expression of a large number of genes. However, persistent stress diminishes the plasticity of the heart, consequently resulting in its maladaptive growth, termed pathological hypertrophy. Recent developments suggest that the concomitant genome-wide remodelling of the gene expression programme is largely driven through epigenetic mechanisms such as post-translational histone modifications and DNA methylation. In the last few years, the distinct functions of histone modifications and of the enzymes catalysing their formation have begun to be elucidated in processes important for cardiac development, disease and cardiomyocyte proliferation. The present review explores how repressive histone modifications, in particular methylation of H3K9 (histone H3 Lys9), govern aspects of cardiac biology.


Author(s):  
Yanrong Ji ◽  
Zhihan Zhou ◽  
Han Liu ◽  
Ramana V Davuluri

Abstract Motivation Deciphering the language of non-coding DNA is one of the fundamental problems in genome research. Gene regulatory code is highly complex due to the existence of polysemy and distant semantic relationship, which previous informatics methods often fail to capture especially in data-scarce scenarios. Results To address this challenge, we developed a novel pre-trained bidirectional encoder representation, named DNABERT, to capture global and transferrable understanding of genomic DNA sequences based on up and downstream nucleotide contexts. We compared DNABERT to the most widely used programs for genome-wide regulatory elements prediction and demonstrate its ease of use, accuracy and efficiency. We show that the single pre-trained transformers model can simultaneously achieve state-of-the-art performance on prediction of promoters, splice sites and transcription factor binding sites, after easy fine-tuning using small task-specific labeled data. Further, DNABERT enables direct visualization of nucleotide-level importance and semantic relationship within input sequences for better interpretability and accurate identification of conserved sequence motifs and functional genetic variant candidates. Finally, we demonstrate that pre-trained DNABERT with human genome can even be readily applied to other organisms with exceptional performance. We anticipate that the pre-trained DNABERT model can be fined tuned to many other sequence analyses tasks. Availability and implementation The source code, pretrained and finetuned model for DNABERT are available at GitHub (https://github.com/jerryji1993/DNABERT). Supplementary information Supplementary data are available at Bioinformatics online.


2021 ◽  
Vol 45 (10) ◽  
Author(s):  
Inés Robles Mendo ◽  
Gonçalo Marques ◽  
Isabel de la Torre Díez ◽  
Miguel López-Coronado ◽  
Francisco Martín-Rodríguez

AbstractDespite the increasing demand for artificial intelligence research in medicine, the functionalities of his methods in health emergency remain unclear. Therefore, the authors have conducted this systematic review and a global overview study which aims to identify, analyse, and evaluate the research available on different platforms, and its implementations in healthcare emergencies. The methodology applied for the identification and selection of the scientific studies and the different applications consist of two methods. On the one hand, the PRISMA methodology was carried out in Google Scholar, IEEE Xplore, PubMed ScienceDirect, and Scopus. On the other hand, a review of commercial applications found in the best-known commercial platforms (Android and iOS). A total of 20 studies were included in this review. Most of the included studies were of clinical decisions (n = 4, 20%) or medical services or emergency services (n = 4, 20%). Only 2 were focused on m-health (n = 2, 10%). On the other hand, 12 apps were chosen for full testing on different devices. These apps dealt with pre-hospital medical care (n = 3, 25%) or clinical decision support (n = 3, 25%). In total, half of these apps are based on machine learning based on natural language processing. Machine learning is increasingly applicable to healthcare and offers solutions to improve the efficiency and quality of healthcare. With the emergence of mobile health devices and applications that can use data and assess a patient's real-time health, machine learning is a growing trend in the healthcare industry.


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