| 1. |
- Cameron, Sarina R., et al.
(författare)
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PTE, a novel module to target Polycomb Repressive Complex 1 to the human cyclin D2 (CCND2) oncogene
- 2018
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Ingår i: Journal of Biological Chemistry. - : American Society for Biochemistry and Molecular Biology. - 0021-9258 .- 1083-351X. ; 293:37, s. 14342-14358
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Tidskriftsartikel (refereegranskat)abstract
- Polycomb group proteins are essential epigenetic repressors. They form multiple protein complexes of which two kinds, PRC1 and PRC2, are indispensable for repression. Although much is known about their biochemical properties, how mammalian PRC1 and PRC2 are targeted to specific genes is poorly understood. Here, we establish the cyclin D2 (CCND2) oncogene as a simple model to address this question. We provide the evidence that the targeting of PRC1 to CCND2 involves a dedicated PRC1-targeting element (PTE). The PTE appears to act in concert with an adjacent cytosine-phosphate-guanine (CpG) island to arrange for the robust binding of PRC1 and PRC2 to repressed CCND2. Our findings pave the way to identify sequence-specific DNA-binding proteins implicated in the targeting of mammalian PRC1 complexes and provide novel link between polycomb repression and cancer.
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| 2. |
- Mahmud, A. K. M. Firoj, et al.
(författare)
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Exploring a Drosophila Transcription Factor Interaction Network to Identify Cis-Regulatory Modules
- 2020
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Ingår i: Journal of Computational Biology. - : Mary Ann Liebert. - 1066-5277 .- 1557-8666. ; 27:8, s. 1313-1328
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Tidskriftsartikel (refereegranskat)abstract
- Multiple transcription factors (TFs) bind to specific sites in the genome and interact among themselves to form the cis-regulatory modules (CRMs). They are essential in modulating the expression of genes, and it is important to study this interplay to understand gene regulation. In the present study, we integrated experimentally identified TF binding sites collected from published studies with computationally predicted TF binding sites to identifyDrosophilaCRMs. Along with the detection of the previously known CRMs, this approach identified novel protein combinations. We determined high-occupancy target sites, where a large number of TFs bind. Investigating these sites revealed that Giant, Dichaete, and Knirp are highly enriched in these locations. A common TAG team motif was observed at these sites, which might play a role in recruiting other TFs. While comparing the binding sites at distal and proximal promoters, we found that certain regulatory TFs, such as Zelda, were highly enriched in enhancers. Our study has shown that, from the information available concerning the TF binding sites, the real CRMs could be predicted accurately and efficiently. Although we only may claim co-occurrence of these proteins in this study, it may actually point to their interaction (as known interaction proteins typically co-occur together). Such an integrative approach can, therefore, help us to provide a better understanding of the interplay among the factors, even though further experimental verification is required.
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| 3. |
- Mahmud, A. K. M. Firoj, et al.
(författare)
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ProkSeq for complete analysis of RNA-Seq data from prokaryotes
- 2021
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Ingår i: Bioinformatics. - UK : Oxford University Press. - 1367-4803 .- 1367-4811 .- 1460-2059. ; 37:1, s. 126-128
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Tidskriftsartikel (refereegranskat)abstract
- Summary: Since its introduction, RNA-Seq technology has been used extensively in studies of pathogenic bacteria to identify and quantify differences in gene expression across multiple samples from bacteria exposed to different conditions. With some exceptions, tools for studying gene expression, determination of differential gene expression, downstream pathway analysis and normalization of data collected in extreme biological conditions is still lacking. Here, we describe ProkSeq, a user-friendly, fully automated RNA-Seq data analysis pipeline designed for prokaryotes. ProkSeq provides a wide variety of options for analysing differential expression, normalizing expression data and visualizing data and results.Availability and implementation: ProkSeq is implemented in Python and is published under the MIT source license. The pipeline is available as a Docker container https://hub.docker.com/repository/docker/snandids/prokseq-v2.0, or can be used through Anaconda: https://anaconda.org/snandiDS/prokseq. The code is available on Github: https://github.com/snandiDS/prokseq and a detailed user documentation, including a manual and tutorial can be found at https://prokseqV20.readthedocs.io.
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| 4. |
- Nandi, Soumyadeep, et al.
(författare)
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Identification of cis-regulatory modules in promoters of human genes exploiting mutual positioning of transcription factors
- 2013
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Ingår i: Nucleic Acids Research. - : Oxford University Press. - 0305-1048 .- 1362-4962. ; 41:19, s. 8822-8841
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Tidskriftsartikel (refereegranskat)abstract
- In higher organisms, gene regulation is controlled by the interplay of non-random combinations of multiple transcription factors (TFs). Although numerous attempts have been made to identify these combinations, important details, such as mutual positioning of the factors that have an important role in the TF interplay, are still missing. The goal of the present work is in silico mapping of some of such associating factors based on their mutual positioning, using computational screening. We have selected the process of myogenesis as a study case, and we focused on TF combinations involving master myogenic TF Myogenic differentiation (MyoD) with other factors situated at specific distances from it. The results of our work show that some muscle-specific factors occur together with MyoD within the range of +/- 100 bp in a large number of promoters. We confirm co-occurrence of the MyoD with muscle-specific factors as described in earlier studies. However, we have also found novel relationships of MyoD with other factors not specific for muscle. Additionally, we have observed that MyoD tends to associate with different factors in proximal and distal promoter areas. The major outcome of our study is establishing the genome-wide connection between biological interactions of TFs and close co-occurrence of their binding sites.
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