Z curve theory-based analysis of the dynamic nature of nucleosome positioning in Saccharomyces cerevisiae

Gene ◽  
2013 ◽  
Vol 530 (1) ◽  
pp. 8-18 ◽  
Author(s):  
Xueting Wu ◽  
Hui Liu ◽  
Hongbo Liu ◽  
Jianzhong Su ◽  
Jie Lv ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Nucleosome Positioning ◽  
Dynamic Nature ◽  
Curve Theory ◽  
Z Curve

scholarly journals ZCMM: A Novel Method Using Z-Curve Theory- Based and Position Weight Matrix for Predicting Nucleosome Positioning

Genes ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 765
Author(s):  
Cui ◽  
Xu ◽  
Li
Keyword(s):  
Position Weight Matrix ◽  
Characteristic Curve ◽  
Nucleosome Positioning ◽  
Weight Matrix ◽  
Support Vector ◽  
Novel Method ◽  
Curve Theory ◽  
Z Curve

Nucleosomes are the basic units of eukaryotes. The accurate positioning of nucleosomes plays a significant role in understanding many biological processes such as transcriptional regulation mechanisms and DNA replication and repair. Here, we describe the development of a novel method, termed ZCMM, based on Z-curve theory and position weight matrix (PWM). The ZCMM was trained and tested using the nucleosomal and linker sequences determined by support vector machine (SVM) in Saccharomyces cerevisiae (S. cerevisiae), and experimental results showed that the sensitivity (Sn), specificity (Sp), accuracy (Acc), and Matthews correlation coefficient (MCC) values for ZCMM were 91.40%, 96.56%, 96.75%, and 0.88, respectively, and the average area under the receiver operating characteristic curve (AUC) value was 0.972. A ZCMM predictor was developed to predict nucleosome positioning in Homo sapiens (H. sapiens), Caenorhabditis elegans (C. elegans), and Drosophila melanogaster (D. melanogaster) genomes, and the accuracy (Acc) values were 77.72%, 85.34%, and 93.62%, respectively. The maximum AUC values of the four species were 0.982, 0.861, 0.912 and 0.911, respectively. Another independent dataset for S. cerevisiae was used to predict nucleosome positioning. Compared with the results of Wu's method, it was found that the Sn, Sp, Acc, and MCC of ZCMM results for S. cerevisiae were all higher, reaching 96.72%, 96.54%, 94.10%, and 0.88. Compared with the Guo’s method ‘iNuc-PseKNC’, the results of ZCMM for D. melanogaster were better. Meanwhile, the ZCMM was compared with some experimental data in vitro and in vivo for S. cerevisiae, and the results showed that the nucleosomes predicted by ZCMM were highly consistent with those confirmed by these experiments. Therefore, it was further confirmed that the ZCMM method has good accuracy and reliability in predicting nucleosome positioning.

scholarly journals Nucleosome positioning on large tandem DNA repeats of the '601' sequence engineered in Saccharomyces cerevisiae

2021 ◽  
Author(s):  
Astrid Lancrey ◽  
Alexandra Joubert ◽  
Evelyne Duvernois-Berthet ◽  
Etienne Routhier ◽  
Saurabh Raj ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Dna Sequence ◽  
Dna Sequences ◽  
Nucleosome Occupancy ◽  
Nucleosome Positioning ◽  
Dna Repeats ◽  
Repeat Array ◽  
Synthetic Dna

The so-called 601 DNA sequence is often used to constrain the position of nucleosomes on a DNA molecule in vitro. Although the ability of the 147 base pair sequence to precisely position a nucleosome in vitro is well documented, in vivo application of this property has been explored only in a few studies and yielded contradictory conclusions. Our goal in the present study was to test the ability of the 601 sequence to dictate nucleosome positioning in Saccharomyces cerevisiae in the context of a long tandem repeat array inserted in a yeast chromosome. We engineered such arrays with three different repeat size, namely 167, 197 and 237 base pairs. Although our arrays are able to position nucleosomes in vitro as expected, analysis of nucleosome occupancy on these arrays in vivo revealed that nucleosomes are not preferentially positioned as expected on the 601-core sequence along the repeats and that the measured nucleosome repeat length does not correspond to the one expected by design. Altogether our results demonstrate that the rules defining nucleosome positions on this DNA sequence in vitro are not valid in vivo, at least in this chromosomal context, questioning the relevance of using the 601 sequence in vivo to achieve precise nucleosome positioning on designer synthetic DNA sequences.

Nucleosome positioning, nucleotide excision repair and photoreactivation in Saccharomyces cerevisiae

DNA Repair ◽  
2015 ◽  
Vol 36 ◽  
pp. 98-104 ◽  
Author(s):  
Laetitia Guintini ◽  
Romain Charton ◽  
François Peyresaubes ◽  
Fritz Thoma ◽  
Antonio Conconi
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Nucleotide Excision Repair ◽  
Excision Repair ◽  
Nucleosome Positioning ◽  
Nucleotide Excision

scholarly journals Spt4 Facilitates the Movement of RNA Polymerase II through the +2 Nucleosomal Barrier

2021 ◽  
Author(s):  
Ülkü Uzun ◽  
Thomas Brown ◽  
Harry Fischl ◽  
Andrew Angel ◽  
Jane Mellor
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Rna Polymerase ◽  
Rna Polymerase Ii ◽  
Elongation Factor ◽  
Nucleosome Positioning ◽  
Gene Body ◽  
Precise Position ◽  
Transcription Elongation Factor

AbstractSpt4 is a transcription elongation factor, with homologues in organisms with nucleosomes. Structural and in vitro studies implicate Spt4 in transcription through nucleosomes, yet the in vivo function of Spt4 is unclear. Here we assessed the precise position of Spt4 during transcription and the consequences of loss of Spt4 on RNA polymerase II (RNAPII) dynamics and nucleosome positioning in Saccharomyces cerevisiae. In the absence of Spt4, the spacing between gene-body nucleosomes increases and RNAPII accumulates upstream of the nucleosomal dyad, most dramatically at nucleosome +2. Spt4 associates with elongating RNAPII early in transcription and its association dynamically changes depending on nucleosome positions. Together, our data show that Spt4 regulates early elongation dynamics, participates in co-transcriptional nucleosome positioning, and promotes RNAPII movement through the gene-body nucleosomes, especially the +2 nucleosome.

Highly Accurate Gene Essentiality Prediction with w-nucleotide Z Curve Features and Feature Selection Technique in Saccharomyces Cerevisiae

2021 ◽  
Vol 16 ◽  
Author(s):  
Wen-Xin Zheng ◽  
Shu-Xuan Wang ◽  
Hong Liu
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Feature Selection ◽  
Sequence Data ◽  
Protein Domain ◽  
Prediction Algorithm ◽  
Support Vector ◽  
Gene Essentiality ◽  
Sequence Composition ◽  
Ppi Networks ◽  
Z Curve

Background: Many studies have been conducted on essentiality prediction in the Saccharomyces cerevisiae genome, but the accuracy is not as high as those in bacterial or human genomes. The most frequently used features are protein-protein interaction (PPI) networks combined with some other features, such as evolutionary conservation, expression level, and protein domain information. Sequence composition features are used least often. Objective: To improve the accuracy of essentiality prediction in the Saccharomyces cerevisiae genome, we proposed a highly accurate gene essentiality prediction algorithm. Methods: In this paper, we propose an algorithm based on a linear support vector machine (SVM) using sequence features only. The variables in this paper are derived from sequence data based on the w-nucleotide Z curve format without any other information. Results: After feature selection, the best area under the receiver operating characteristic curve (AUC) was 0.944 for 5-fold cross-validation. From 1- to 6-nucleotide Z curve variables, feature extraction can increase the AUC in all cases. Conclusion: Prediction only on sequence composition is promising, particularly when a feature filtering method is used, and maybe a good complement for algorithms based on other features.

Dynamics and stability: epigenetic conversions in position effect variegation

2013 ◽  
Vol 91 (1) ◽  
pp. 6-13 ◽  
Author(s):  
Krassimir Yankulov
Keyword(s):  
Gene Expression ◽  
Saccharomyces Cerevisiae ◽  
Position Effect ◽  
Specific Gene ◽  
Position Effect Variegation ◽  
Human Pathogens ◽  
Dynamic Nature ◽  
Host Environment ◽  
Effect Variegation ◽  
Transcription And Replication

Position effect variegation (PEV) refers to quasi-stable patterns of gene expression that are observed at specific loci throughout the genomes of eukaryotes. The genes subjected to PEV can be completely silenced or fully active. Stochastic conversions between these 2 states are responsible for the variegated phenotypes. Positional variegation is used by human pathogens (Trypanosoma, Plasmodium, and Candida) to evade the immune system or adapt to the host environment. In the yeasts Saccharomyces cerevisiae and S accharomyces pombe, telomeric PEV aids the adaptation to a changing environment. In metazoans, similar epigenetic conversions are likely to accompany cell differentiation and the setting of tissue-specific gene expression programs. Surprisingly, we know very little about the mechanisms of epigenetic conversions. In this article, earlier models on the nature of PEV are revisited and recent advances on the dynamic nature of chromatin are reviewed. The normal dynamic histone turnover during transcription and DNA replication and its perturbation at transcription and replication pause sites are discussed. It is proposed that such perturbations play key roles in epigenetic conversions and in PEV.

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