scholarly journals Studying statistical properties of regulatory DNA sequences, and their use in predicting regulatory regions in the eukaryotic genomes

2006 ◽  
Vol 7 (1) ◽  
pp. 48-54 ◽  
Author(s):  
Irina Abnizova ◽  
Walter R. Gilks
Keyword(s):  
Dna Sequences ◽  
Statistical Properties ◽  
Regulatory Regions ◽  
Regulatory Dna Sequences ◽  
Regulatory Dna ◽  
Eukaryotic Genomes

scholarly journals The borders of cis-regulatory DNA sequences harbor the divergent transcription factor binding motifs in the human genome

2018 ◽  
Author(s):  
Jia-Hsin Huang ◽  
Ryan Shun-Yuen Kwan ◽  
Zing Tsung-Yeh Tsai ◽  
Huai-Kuang Tsai
Keyword(s):  
Transcription Factor ◽  
Dna Sequences ◽  
Dynamic Change ◽  
Evolutionary Divergence ◽  
Evolutionary Time ◽  
Regulatory Regions ◽  
Binding Motifs ◽  
Regulatory Dna Sequences ◽  
Hypersensitive Sites ◽  
Regulatory Dna

AbstractChanges in the cis-regulatory DNA sequences and transcription factor (TF) repertoires provide major sources that shape the gene regulatory evolution in eukaryotes. However, it is currently unclear how dynamic change of DNA sequences introduce various divergence level of TF binding motifs in the genome over evolutionary time. Here, we estimated the evolutionary divergence level of the TF binding motifs, and quantified their occurrences in the DNase I hypersensitive sites. Results from our in silico motif scan and empirical TF-ChIP (chromatin immunoprecipitation) demonstrate that the divergent motifs tend to be introduced at the borders of the cis-regulatory regions, that are likely accompanied with the expansion through evolutionary time. Accordingly, we propose that an expansion by incorporating divergent motifs within the cis-regulatory regions provides a rationale for the evolutionary divergence of regulatory circuits.

scholarly journals Deciphering regulatory DNA sequences and noncoding genetic variants using neural network models of massively parallel reporter assays

PLoS ONE ◽  
2019 ◽  
Vol 14 (6) ◽  
pp. e0218073 ◽  
Author(s):  
Rajiv Movva ◽  
Peyton Greenside ◽  
Georgi K. Marinov ◽  
Surag Nair ◽  
Avanti Shrikumar ◽  
...  
Keyword(s):  
Neural Network ◽  
Dna Sequences ◽  
Genetic Variants ◽  
Network Models ◽  
Massively Parallel ◽  
Neural Network Models ◽  
Regulatory Dna Sequences ◽  
Reporter Assays ◽  
Regulatory Dna

Functional Comparison of the Upstream Regulatory DNA Sequences of Four Human Epidermal Keratin Genes

1991 ◽  
Vol 96 (2) ◽  
pp. 162-167 ◽  
Author(s):  
Chuan-Kui Jiang ◽  
Howard S Epstein ◽  
Marjana Tomic ◽  
Irwin M Freedberg ◽  
Miroslav Blumenberg
Keyword(s):  
Dna Sequences ◽  
Regulatory Dna Sequences ◽  
Regulatory Dna

scholarly journals Deciphering regulatory DNA sequences and noncoding genetic variants using neural network models of massively parallel reporter assays

2018 ◽  
Author(s):  
Rajiv Movva ◽  
Peyton Greenside ◽  
Georgi K. Marinov ◽  
Surag Nair ◽  
Avanti Shrikumar ◽  
...  
Keyword(s):  
Neural Network ◽  
Dna Sequences ◽  
Genetic Variants ◽  
Massively Parallel ◽  
Regulatory Sequence ◽  
Regulatory Activity ◽  
Neural Network Models ◽  
Regulatory Dna Sequences ◽  
Reporter Assays ◽  
Regulatory Dna

AbstractThe relationship between noncoding DNA sequence and gene expression is not well-understood. Massively parallel reporter assays (MPRAs), which quantify the regulatory activity of large libraries of DNA sequences in parallel, are a powerful approach to characterize this relationship. We present MPRA-DragoNN, a convolutional neural network (CNN)-based framework to predict and interpret the regulatory activity of DNA sequences as measured by MPRAs. While our method is generally applicable to a variety of MPRA designs, here we trained our model on the Sharpr-MPRA dataset that measures the activity of ~500,000 constructs tiling 15,720 regulatory regions in human K562 and HepG2 cell lines. MPRA-DragoNN predictions were moderately correlated (Spearman ρ = 0.28) with measured activity and were within range of replicate concordance of the assay. State-of-the-art model interpretation methods revealed high-resolution predictive regulatory sequence features that overlapped transcription factor (TF) binding motifs. We used the model to investigate the cell type and chromatin state preferences of predictive TF motifs. We explored the ability of our model to predict the allelic effects of regulatory variants in an independent MPRA experiment and fine map putative functional SNPs in loci associated with lipid traits. Our results suggest that interpretable deep learning models trained on MPRA data have the potential to reveal meaningful patterns in regulatory DNA sequences and prioritize regulatory genetic variants, especially as larger, higher-quality datasets are produced.

scholarly journals The role of maternal pioneer factors in predefining first zygotic responses to inductive signals

2018 ◽  
Author(s):  
George E. Gentsch ◽  
Thomas Spruce ◽  
Nick D. L. Owens ◽  
James C. Smith
Keyword(s):  
Dna Sequences ◽  
Cell Types ◽  
Regulatory Elements ◽  
Regulatory Dna Sequences ◽  
Cell Type Specific ◽  
Pioneer Factors ◽  
Developmental Principles ◽  
Regulatory Dna ◽  
Different Cell Types ◽  
Inductive Signals

ABSTRACTEmbryonic development yields many different cell types in response to just a few families of inductive signals. The property of a signal-receiving cell that determines how it responds to such signals, including the activation of cell type-specific genes, is known as its competence. Here, we show how maternal factors modify chromatin to specify initial competence in the frog Xenopus tropicalis. We identified the earliest engaged regulatory DNA sequences, and inferred from them critical activators of the zygotic genome. Of these, we showed that the pioneering activity of the maternal pluripotency factors Pou5f3 and Sox3 predefines competence for germ layer formation by extensively remodeling compacted chromatin before the onset of signaling. The remodeling includes the opening and marking of thousands of regulatory elements, extensive chromatin looping, and the co-recruitment of signal-mediating transcription factors. Our work identifies significant developmental principles that inform our understanding of how pluripotent stem cells interpret inductive signals.

Nuclear receptors and disease: androgen receptor

2004 ◽  
Vol 40 ◽  
pp. 121-136 ◽  
Author(s):  
Bruce Gottlieb ◽  
Lenore K Beitel ◽  
Jianhui Wu ◽  
Youssef A Elhaji ◽  
Mark Trifiro
Keyword(s):  
Androgen Receptor ◽  
Dna Sequences ◽  
Muscular Atrophy ◽  
Binding Domain ◽  
Spinobulbar Muscular Atrophy ◽  
Precise Control ◽  
Research Areas ◽  
Regulatory Dna Sequences ◽  
Active Research ◽  
Regulatory Dna

The androgen receptor (AR) protein regulates transcription of certain genes. Usually this depends upon a central DNA-binding domain that permits the binding of androgen–AR complexes to regulatory DNA sequences near or in a target gene. The AR also has a C-terminal ligand-binding domain and an Nterminal transcription modulatory domain. These N- and C-terminal domains interact directly, and with co-regulatory, non-receptor proteins, to exert precise control over a gene’s transcription rate. The precise roles of these proteins are active research areas. Severe X-linked AR gene (AR) mutations cause complete androgen insensitivity, mild ones impair virilization with or without infertility, and moderate ones yield a wide phenotypic spectrum sometimes among siblings. Different phenotype expressivity may reflect variability of ARinteractive proteins. Mutations occur throughout the AR but are concentrated in specific areas of the gene known as hot spots. A number of these mutations of somatic origin are associated with prostate cancer. N-terminal polyglutamine (polyGln) tract expansion reduces AR transactivation, and when there are more than 38 glutamine residues it causes spinobulbar muscular atrophy, a motor neuron disease, due to a gain of function. Variations in polyGln tract length have been associated as risk factors with prostate, breast, uterine, endometrial and colorectal cancer, as well as male infertility.

Retrovirus-induced insertional mutagenesis: mechanism of collagen mutation in Mov13 mice

1991 ◽  
Vol 11 (10) ◽  
pp. 5154-5163
Author(s):  
D D Barker ◽  
H Wu ◽  
S Hartung ◽  
M Breindl ◽  
R Jaenisch
Keyword(s):  
Dna Sequences ◽  
Insertional Mutagenesis ◽  
De Novo ◽  
Induced Mutations ◽  
Cis Acting ◽  
First Intron ◽  
Regulatory Dna Sequences ◽  
Regulatory Dna ◽  
Collagen Promoter ◽  
Murine Leukemia

The Mov13 mouse strain carries a mutation in the alpha 1(I) procollagen gene which is due to the insertion of a Moloney murine leukemia provirus into the first intron. This insertion results in the de novo methylation of the provirus and flanking DNA, the alteration of chromatin structure, and the transcriptional inactivity of the collagen promoter. To address the mechanism of mutagenesis, we reintroduced a cloned and therefore demethylated version of the Mov13 mutant allele into mouse fibroblasts. The transfected gene was not transcribed, indicating that the transcriptional defect was not due to the hypermethylation. Rather, this result strongly suggests that the mutation is due to the displacement or disruption of cis-acting regulatory DNA sequences within the first intron. We also constructed a Mov13 variant allele containing a single long terminal repeat instead of the whole provirus. This construct also failed to express mRNA, indicating that the Mov13 mutation does not revert by provirus excision as has been observed for other retrovirus-induced mutations.

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