Computational Interrogation of Transcriptional and Post-Transcriptional Mechanisms Regulating Dendritic Development Article Swipe
The specification and modulation of cell-type specific dendritic morphologies plays a pivotal role in nervous system development, connectivity, structural plasticity, and function. Regulation of gene expression is controlled by a wide variety of cellular and molecular mechanisms, of which two major types are transcription factors (TFs) and microRNAs (miRNAs). In Drosophila, dendritic complexity of dendritic arborization (da) sensory neurons of the peripheral nervous system are known to be regulated by two transcription factors Cut and Knot, although much remains unknown about the molecular mechanisms and regulatory networks via which they regulate the final arbor shape through spatio-temporal modulation of dendritic development and dynamics. Here we use bioinformatics analysis of transcriptomic data to identify putative genomic targets of these TFs with a particular emphasis on those that effect neuronal cytoskeletal architecture. We use transcriptomic, as well as data from various genomic and protein interaction databases, to build a weighted functional gene regulatory network for Knot, to identify the biological pathways and downstream genes that this TF regulates. To corroborate bioinformatics network predictions, knot putative targets, which classify into neuronal and cytoskeletal functional groups, have been experimentally validated by in vivo genetic perturbations to elucidate their role in Knot-mediated Class IV (CIV) dendritogenesis. MicroRNAs (miRNAs) have emerged as key post-transcriptional regulators of gene expression, however identification of biologically-relevant target genes for this epigenetic regulatory mechanism remains a significant challenge. To address this knowledge gap, we have developed a novel R based tool, IntramiR-ExploreR, that facilitates integrated discovery of miRNA targets by incorporating target databases and novel target prediction algorithm to arrive at high confidence intragenic miRNA target predictions. We have explored the efficacy of this tool using D.melanogaster as a model organism for bioinformatics analyses and functional validation, and identified targets for 83 intragenic miRNAs. Predicted targets were validated, using in vivo genetic perturbation. Moreover, we are constructing interaction maps of intragenic miRNAs focusing on neural tissues to uncover regulatory codes via which these molecules regulate gene expression to direct cellular development.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://scholarworks.gsu.edu/biology_diss/190
- https://scholarworks.gsu.edu/cgi/viewcontent.cgi?article=1202&context=biology_diss
- OA Status
- green
- References
- 65
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W2741653051
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2741653051Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.57709/10462858Digital Object Identifier
- Title
-
Computational Interrogation of Transcriptional and Post-Transcriptional Mechanisms Regulating Dendritic DevelopmentWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-04-12Full publication date if available
- Authors
-
Surajit BhattacharyaList of authors in order
- Landing page
-
https://scholarworks.gsu.edu/biology_diss/190Publisher landing page
- PDF URL
-
https://scholarworks.gsu.edu/cgi/viewcontent.cgi?article=1202&context=biology_dissDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://scholarworks.gsu.edu/cgi/viewcontent.cgi?article=1202&context=biology_dissDirect OA link when available
- Concepts
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Interrogation, Biology, Computer science, Computational biology, Cell biology, Political science, LawTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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65Number of works referenced by this work
- Related works (count)
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20Other works algorithmically related by OpenAlex
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| abstract_inverted_index.organism | 279 |
| abstract_inverted_index.pathways | 158 |
| abstract_inverted_index.putative | 113, 172 |
| abstract_inverted_index.regulate | 90, 323 |
| abstract_inverted_index.specific | 6 |
| abstract_inverted_index.targets, | 173 |
| abstract_inverted_index.weighted | 147 |
| abstract_inverted_index.(miRNAs). | 48 |
| abstract_inverted_index.MicroRNAs | 201 |
| abstract_inverted_index.Moreover, | 302 |
| abstract_inverted_index.Predicted | 293 |
| abstract_inverted_index.algorithm | 256 |
| abstract_inverted_index.cell-type | 5 |
| abstract_inverted_index.databases | 251 |
| abstract_inverted_index.dendritic | 7, 51, 54, 99 |
| abstract_inverted_index.developed | 234 |
| abstract_inverted_index.discovery | 244 |
| abstract_inverted_index.dynamics. | 102 |
| abstract_inverted_index.elucidate | 192 |
| abstract_inverted_index.function. | 21 |
| abstract_inverted_index.knowledge | 230 |
| abstract_inverted_index.mechanism | 222 |
| abstract_inverted_index.microRNAs | 47 |
| abstract_inverted_index.molecular | 35, 82 |
| abstract_inverted_index.molecules | 322 |
| abstract_inverted_index.regulated | 68 |
| abstract_inverted_index.validated | 185 |
| abstract_inverted_index.Regulation | 22 |
| abstract_inverted_index.biological | 157 |
| abstract_inverted_index.challenge. | 226 |
| abstract_inverted_index.complexity | 52 |
| abstract_inverted_index.confidence | 261 |
| abstract_inverted_index.controlled | 27 |
| abstract_inverted_index.databases, | 143 |
| abstract_inverted_index.downstream | 160 |
| abstract_inverted_index.epigenetic | 220 |
| abstract_inverted_index.expression | 25, 325 |
| abstract_inverted_index.functional | 148, 180, 284 |
| abstract_inverted_index.identified | 287 |
| abstract_inverted_index.integrated | 243 |
| abstract_inverted_index.intragenic | 262, 291, 309 |
| abstract_inverted_index.mechanisms | 83 |
| abstract_inverted_index.modulation | 3, 97 |
| abstract_inverted_index.particular | 121 |
| abstract_inverted_index.peripheral | 61 |
| abstract_inverted_index.prediction | 255 |
| abstract_inverted_index.regulates. | 165 |
| abstract_inverted_index.regulators | 208 |
| abstract_inverted_index.regulatory | 85, 150, 221, 317 |
| abstract_inverted_index.structural | 18 |
| abstract_inverted_index.validated, | 296 |
| abstract_inverted_index.Drosophila, | 50 |
| abstract_inverted_index.corroborate | 167 |
| abstract_inverted_index.development | 100 |
| abstract_inverted_index.expression, | 211 |
| abstract_inverted_index.facilitates | 242 |
| abstract_inverted_index.interaction | 142, 306 |
| abstract_inverted_index.mechanisms, | 36 |
| abstract_inverted_index.plasticity, | 19 |
| abstract_inverted_index.significant | 225 |
| abstract_inverted_index.validation, | 285 |
| abstract_inverted_index.arborization | 55 |
| abstract_inverted_index.constructing | 305 |
| abstract_inverted_index.cytoskeletal | 128, 179 |
| abstract_inverted_index.development, | 16 |
| abstract_inverted_index.development. | 329 |
| abstract_inverted_index.morphologies | 8 |
| abstract_inverted_index.predictions, | 170 |
| abstract_inverted_index.predictions. | 265 |
| abstract_inverted_index.Knot-mediated | 196 |
| abstract_inverted_index.architecture. | 129 |
| abstract_inverted_index.connectivity, | 17 |
| abstract_inverted_index.incorporating | 249 |
| abstract_inverted_index.perturbation. | 301 |
| abstract_inverted_index.perturbations | 190 |
| abstract_inverted_index.specification | 1 |
| abstract_inverted_index.transcription | 43, 71 |
| abstract_inverted_index.D.melanogaster | 275 |
| abstract_inverted_index.bioinformatics | 106, 168, 281 |
| abstract_inverted_index.experimentally | 184 |
| abstract_inverted_index.identification | 213 |
| abstract_inverted_index.transcriptomic | 109 |
| abstract_inverted_index.spatio-temporal | 96 |
| abstract_inverted_index.transcriptomic, | 132 |
| abstract_inverted_index.dendritogenesis. | 200 |
| abstract_inverted_index.IntramiR-ExploreR, | 240 |
| abstract_inverted_index.post-transcriptional | 207 |
| abstract_inverted_index.biologically-relevant | 215 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5075842709 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 1 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.47999998927116394 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile.value | 0.00119188 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |