NucMap: a database of genome-wide nucleosome positioning map across species

Zhao, Yongbing; Wang, Jinyue; Fang, Liang; Liu, Yanxia; Wang, Qi; Zhang, Hao; Jiang, Meiye; Zhang, Zhewen; Zhao, Wenming; Bào, Yīmíng; Zhang, Zhang; Wu, Jiayan; Asmann, Yan W.; Li, Rujiao; Xiao, Jingfa

doi:10.1093/nar/gky980

Cited by 37 publications

(28 citation statements)

References 33 publications

(31 reference statements)

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“…MNase-seq data were from Mieczkowski et al 2016 sample GSM2083140 [ 50 ], and analyzed as previously described [ 51 , 52 ]. Additional analysis of MNase-seq datasets from [ 53 ] was performed using the NucMap database [ 54 ] using nucleosome positions determined with DANPOS or iNPS [ 55 , 56 ]. Symmetry of nucleosome occupancy at p63BS was determined with ArchAlign with 0-bp shifts and region reversal enabled [ 23 ].…”

Section: Methodsmentioning

confidence: 99%

ΔNp63 is a pioneer factor that binds inaccessible chromatin and elicits chromatin remodeling

Singh

Tabrejee

et al. 2021

Epigenetics & Chromatin

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Background ΔNp63 is a master transcriptional regulator playing critical roles in epidermal development and other cellular processes. Recent studies suggest that ΔNp63 functions as a pioneer factor that can target its binding sites within inaccessible chromatin and induce chromatin remodeling. Methods In order to examine if ΔNp63 can bind to inaccessible chromatin and to determine if specific histone modifications are required for binding, we induced ΔNp63 expression in two p63-naïve cell lines. ΔNp63 binding was then examined by ChIP-seq and the chromatin at ΔNp63 targets sites was examined before and after binding. Further analysis with competitive nucleosome binding assays was used to determine how ΔNp63 directly interacts with nucleosomes. Results Our results show that before ΔNp63 binding, targeted sites lack histone modifications, indicating ΔNp63’s capability to bind at unmodified chromatin. Moreover, the majority of the sites that are bound by ectopic ΔNp63 expression exist in an inaccessible state. Once bound, ΔNp63 induces acetylation of the histone and the repositioning of nucleosomes at its binding sites. Further analysis with competitive nucleosome binding assays reveal that ΔNp63 can bind directly to nucleosome edges with significant binding inhibition occurring within 50 bp of the nucleosome dyad. Conclusion Overall, our results demonstrate that ΔNp63 is a pioneer factor that binds nucleosome edges at inaccessible and unmodified chromatin sites and induces histone acetylation and nucleosome repositioning.

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Section: Methodsmentioning

confidence: 99%

ΔNp63 is a pioneer factor that binds inaccessible chromatin and elicits chromatin remodeling

Singh

Tabrejee

et al. 2021

Epigenetics & Chromatin

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“…Nucleosome occupancy models trained on yeast data have been reported to produce predictions that correlate well with nucleosome maps from other organisms (Awazu, 2017; Gupta et al, 2008). However, we found that applying the in vitro and in vivo ChromWave models to 23,156 human promoter regions produced terrible agreement with MNase-seq datasets (Gaffney et al, 2012; Zhao et al, 2018), with average Pearson correlation coefficients of 0.002 and −0.0003, respectively.…”

Section: Resultsmentioning

confidence: 90%

ChromWave: Deciphering the DNA-encoded competition between transcription factors and nucleosomes with deep neural networks

Cakiroglu

Steinhauser

Smith

et al. 2021

Preprint

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SummaryTranscription factors (TFs) regulate gene expression by recognising and binding specific DNA sequences. At times, these regulatory elements may be occluded by nucleosomes, making them inaccessible for TF-binding. The competition for DNA occupancy between TFs and nucleosomes, and associated gene regulatory outputs, are important consequences of the cis-regulatory information encoded in the genome. However, these sequence patterns are subtle and remain difficult to interpret. Here, we introduce ChromWave, a deep-learning model that, for the first time, predicts the competing profiles for TF and nucleosomes occupancies with remarkable accuracy. Models trained using short- and long-fragment MNase-Seq data successfully learn the sequence preferences underlying TF and nucleosome occupancies across the entire yeast genome. They recapitulate nucleosome evictions from regions containing “strong” TF binding sites and knock-out simulations show nucleosomes gaining occupancy in the absence of these TFs, accompanied by lateral rearrangement of adjacent nucleosomes. At a local level, models anticipate with high accuracy the outcomes of detailed experimental analysis of partially unwrapped nucleosomes at the GAL4 UAS locus. Finally, we trained a ChromWave model that successfully predicts nucleosome positions at promoters in the human genome. We find that human promoters generally contain few sites at which simple sequence changes can alter nucleosome occupancies and that these positions align well with causal variants linked to DNase hypersensitivity. ChromWave is readily combined with diverse genomic datasets and can be trained to predict any output that is linked to the underlying genomic sequence. ChromWave’s application is limited only by the user’s imagination and availability of training data.

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“…NucMap (http://bigd.big.ac. cn/nucmap) (Zhao et al, 2019), the first database of genomewide nucleosome positioning maps, contains 15 plant nucleosomes from different developmental stages and/or tissues. Taken together, all these resources are publicly available and free to use.…”

Section: Molecular Plantmentioning

confidence: 99%

Database Resources in BIG Data Center: Submission, Archiving, and Integration of Big Data in Plant Science

Song

Zhang

2019

Molecular Plant

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With the rapid advancement of sequencing technologies and the growing volume of omics data in plants, there is much anticipation in digging out the treasure from such big data and accordingly refining the current agricultural practice to be applied in the near future. Toward this end, database resources that deliver web services for plant omics data submission, archiving, and integration are urgently needed. As a part of Beijing Institute of Genomics (BIG) of the Chinese Academy of Sciences (CAS), BIG Data Center (http://bigd.big.ac.cn) provides open access to a suite of database resources (Table 1), with the aim of supporting plant research activities for domestic and international users in both academia and industry to translate big data into big discoveries (

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NucMap: a database of genome-wide nucleosome positioning map across species

Cited by 37 publications

References 33 publications

ΔNp63 is a pioneer factor that binds inaccessible chromatin and elicits chromatin remodeling

ΔNp63 is a pioneer factor that binds inaccessible chromatin and elicits chromatin remodeling

ChromWave: Deciphering the DNA-encoded competition between transcription factors and nucleosomes with deep neural networks

Database Resources in BIG Data Center: Submission, Archiving, and Integration of Big Data in Plant Science

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