scholarly journals Human exonization through differential nucleosome occupancy

2018 ◽  
Vol 115 (35) ◽  
pp. 8817-8822 ◽  
Author(s):  
Yumei Li ◽  
Chen Li ◽  
Shuxian Li ◽  
Qi Peng ◽  
Ni A. An ◽  
...  

Nucleosomal modifications have been implicated in fundamental epigenetic regulation, but the roles of nucleosome occupancy in shaping changes through evolution remain to be addressed. Here we present high-resolution nucleosome occupancy profiles for multiple tissues derived from human, macaque, tree shrew, mouse, and pig. Genome-wide comparison reveals conserved nucleosome occupancy profiles across both different species and tissue types. Notably, we found significantly higher levels of nucleosome occupancy in exons than in introns, a pattern correlated with the different exon–intron GC content. We then determined whether this biased occupancy may play roles in the origination of new exons through evolution, rather than being a downstream effect of exonization, through a comparative approach to sequentially trace the order of the exonization and biased nucleosome binding. By identifying recently evolved exons in human but not in macaque using matched RNA sequencing, we found that higher exonic nucleosome occupancy also existed in macaque regions orthologous to these exons. Presumably, such biased nucleosome occupancy facilitates the origination of new exons by increasing the splice strength of the ancestral nonexonic regions through driving a local difference in GC content. These data thus support a model that sites bound by nucleosomes are more likely to evolve into exons, which we term the “nucleosome-first” model.

2021 ◽  
Author(s):  
Yuanhao Huang ◽  
Bingjiang Wang ◽  
Jie Liu

Although poorly positioned nucleosomes are ubiquitous in the prokaryote genome, they are difficult to identify with existing nucleosome identification methods. Recently available enhanced high-throughput chromatin conformation capture techniques such as Micro-C, DNase Hi-C, and Hi-CO characterize nucleosome-level chromatin proximity, probing the positions of mono-nucleosomes and the spacing between nucleosome pairs at the same time, enabling profiling of nucleosomes in poorly positioned regions. Here we develop a novel computational approach, NucleoMap, to identify nucleosome positioning from ultra-high resolution chromatin contact maps. By integrating nucleosome binding preferences, read density, and pairing information, NucleoMap precisely locates nucleosomes in both eukaryotic and prokaryotic genomes and outperforms existing nucleosome identification methods in sensitivity and specificity. We rigorously characterize genome-wide association in eukaryotes between the spatial organization of mono-nucleosomes and their corresponding histone modifications, protein binding activities, and higher-order chromatin functions. We also predict two tetra-nucleosome folding structures in human embryonic stem cells using machine learning methods and analysis their distribution at different structural and functional regions. Based on the identified nucleosomes, nucleosome contact maps are constructed, reflecting the inter-nucleosome distances and preserving the original data's contact distance profile.


Chromosoma ◽  
2021 ◽  
Vol 130 (1) ◽  
pp. 27-40
Author(s):  
Guoqing Liu ◽  
Hongyu Zhao ◽  
Hu Meng ◽  
Yongqiang Xing ◽  
Lu Cai

AbstractWe present a deformation energy model for predicting nucleosome positioning, in which a position-dependent structural parameter set derived from crystal structures of nucleosomes was used to calculate the DNA deformation energy. The model is successful in predicting nucleosome occupancy genome-wide in budding yeast, nucleosome free energy, and rotational positioning of nucleosomes. Our model also indicates that the genomic regions underlying the MNase-sensitive nucleosomes in budding yeast have high deformation energy and, consequently, low nucleosome-forming ability, while the MNase-sensitive non-histone particles are characterized by much lower DNA deformation energy and high nucleosome preference. In addition, we also revealed that remodelers, SNF2 and RSC8, are likely to act in chromatin remodeling by binding to broad nucleosome-depleted regions that are intrinsically favorable for nucleosome positioning. Our data support the important role of position-dependent physical properties of DNA in nucleosome positioning.


2009 ◽  
Vol 16 (4) ◽  
pp. 555-564 ◽  
Author(s):  
Andrey Ilatovskiy ◽  
Michael Petukhov

2010 ◽  
Vol 35 (7) ◽  
pp. 1172-1183.e7 ◽  
Author(s):  
Barbara B. Shih ◽  
May Tassabehji ◽  
James S. Watson ◽  
Angus D. McGrouther ◽  
Ardeshir Bayat

Placenta ◽  
2011 ◽  
Vol 32 ◽  
pp. S282
Author(s):  
Paola Scaruffi ◽  
Sara Stigliani ◽  
Annamaria Jane Nicoletti ◽  
Pier Luigi Venturini ◽  
Gian Paolo Tonini ◽  
...  

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Qiu Sun ◽  
Alan Perez-Rathke ◽  
Daniel M. Czajkowsky ◽  
Zhifeng Shao ◽  
Jie Liang

AbstractSingle-cell chromatin studies provide insights into how chromatin structure relates to functions of individual cells. However, balancing high-resolution and genome wide-coverage remains challenging. We describe a computational method for the reconstruction of large 3D-ensembles of single-cell (sc) chromatin conformations from population Hi-C that we apply to study embryogenesis in Drosophila. With minimal assumptions of physical properties and without adjustable parameters, our method generates large ensembles of chromatin conformations via deep-sampling. Our method identifies specific interactions, which constitute 5–6% of Hi-C frequencies, but surprisingly are sufficient to drive chromatin folding, giving rise to the observed Hi-C patterns. Modeled sc-chromatins quantify chromatin heterogeneity, revealing significant changes during embryogenesis. Furthermore, >50% of modeled sc-chromatin maintain topologically associating domains (TADs) in early embryos, when no population TADs are perceptible. Domain boundaries become fixated during development, with strong preference at binding-sites of insulator-complexes upon the midblastula transition. Overall, high-resolution 3D-ensembles of sc-chromatin conformations enable further in-depth interpretation of population Hi-C, improving understanding of the structure-function relationship of genome organization.


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