scholarly journals De novo transcriptome assembly and analysis of the freshwater araphid diatom Fragilaria radians, Lake Baikal

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Yuri Pavlovich Galachyants ◽  
Yulia Robertovna Zakharova ◽  
Nadezda Antonovna Volokitina ◽  
Alexey Anatolyevich Morozov ◽  
Yelena Valentinovna Likhoshway ◽  
...  
Keyword(s):  
Lake Baikal ◽  
Regulatory Networks ◽  
De Novo ◽  
Current Knowledge ◽  
Transcriptome Assembly ◽  
Early Response ◽  
Exponential Growth Phase ◽  
Gene Regulatory ◽  
Almost All ◽  
Made In

Abstract Diatoms are a group of eukaryotic microalgae populating almost all aquatic and wet environments. Their abundance and species diversity make these organisms significant contributors to biogeochemical cycles and important components of aquatic ecosystems. Although significant progress has been made in studies of Diatoms (Bacillariophyta) over the last two decades, since the spread of “omics” technologies, our current knowledge of the molecular processes and gene regulatory networks that facilitate environmental adaptation remain incomplete. Here, we present a transcriptome analysis of Fragilaria radians isolated from Lake Baikal. The resulting assembly contains 27,446 transcripts encoding 21,996 putative proteins. The transcriptome assembly and annotation were coupled with quantitative experiments to search for differentially expressed transcripts between (i) exponential growth phase and dark-acclimated cell cultures, and (ii) those changing expression level during the early response to light treatment in dark-acclimated cells. The availability of F. radians genome and transcriptome data provides the basis for future targeted studies of this species. Furthermore, our results extend taxonomic and environmental sampling of Bacillariophyta, opening new opportunities for comparative omics-driven surveys.

scholarly journals What else is in an evolved name? Exploring evolvable specificity with SignalGP

2018 ◽  
Author(s):  
Alexander Lalejini ◽  
Charles Ofria
Keyword(s):  
Adaptive Evolution ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
De Novo ◽  
Direct Access ◽  
Evolutionary Transitions ◽  
Fine Grained ◽  
Flexible Mechanism ◽  
Gene Regulatory ◽  
Program Modules

Tags are evolvable labels that provide genetic programs a flexible mechanism for specification. Tags are used to label and refer to programmatic elements, such as functions or jump targets. However, tags differ from traditional, more rigid methods for handling labeling because they allow for inexact references; that is, a referring tag need not exactly match its referent. Here, we explore how adjusting the threshold for how what qualifies as a match affects adaptive evolution. Further, we propose broadened applications of tags in the context of a genetic programming (GP) technique called SignalGP. SignalGP gives evolution direct access to the event-driven paradigm. Program modules in SignalGP are tagged and can be triggered by signals (with matching tags) from the environment, from other agents, or due to internal regulation. Specifically, we propose to extend this tag based system to: (1) provide more fine-grained control over module execution and regulation (e.g., promotion and repression) akin to natural gene regulatory networks, (2) employ a mosaic of GP representations within a single program, and (3) facilitate major evolutionary transitions in individuality (i.e., allow hierarchical program organization to evolve de novo).

scholarly journals Gynoecium size and ovule number are interconnected traits that impact seed yield

2020 ◽  
Vol 71 (9) ◽  
pp. 2479-2489 ◽  
Author(s):  
Mara Cucinotta ◽  
Maurizio Di Marzo ◽  
Andrea Guazzotti ◽  
Stefan de Folter ◽  
Martin M Kater ◽  
...  
Keyword(s):  
Seed Yield ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Current Knowledge ◽  
Fine Tuning ◽  
World Population ◽  
Meristematic Tissue ◽  
Reproductive Part ◽  
Ovule Number ◽  
Gene Regulatory

Abstract Angiosperms form the largest group of land plants and display an astonishing diversity of floral structures. The development of flowers greatly contributed to the evolutionary success of the angiosperms as they guarantee efficient reproduction with the help of either biotic or abiotic vectors. The female reproductive part of the flower is the gynoecium (also called pistil). Ovules arise from meristematic tissue within the gynoecium. Upon fertilization, these ovules develop into seeds while the gynoecium turns into a fruit. Gene regulatory networks involving transcription factors and hormonal communication regulate ovule primordium initiation, spacing on the placenta, and development. Ovule number and gynoecium size are usually correlated and several genetic factors that impact these traits have been identified. Understanding and fine-tuning the gene regulatory networks influencing ovule number and pistil length open up strategies for crop yield improvement, which is pivotal in light of a rapidly growing world population. In this review, we present an overview of the current knowledge of the genes and hormones involved in determining ovule number and gynoecium size. We propose a model for the gene regulatory network that guides the developmental processes that determine seed yield.

scholarly journals Cell-free gene-regulatory network engineering with synthetic transcription factors

2019 ◽  
Vol 116 (13) ◽  
pp. 5892-5901 ◽  
Author(s):  
Zoe Swank ◽  
Nadanai Laohakunakorn ◽  
Sebastian J. Maerkl
Keyword(s):  
Transcription Factors ◽  
High Throughput ◽  
Gene Regulatory Networks ◽  
Protein Interactions ◽  
Transcriptional Repression ◽  
Regulatory Networks ◽  
De Novo ◽  
Mechanistic Modeling ◽  
Free System ◽  
Gene Regulatory

Gene-regulatory networks are ubiquitous in nature and critical for bottom-up engineering of synthetic networks. Transcriptional repression is a fundamental function that can be tuned at the level of DNA, protein, and cooperative protein–protein interactions, necessitating high-throughput experimental approaches for in-depth characterization. Here, we used a cell-free system in combination with a high-throughput microfluidic device to comprehensively study the different tuning mechanisms of a synthetic zinc-finger repressor library, whose affinity and cooperativity can be rationally engineered. The device is integrated into a comprehensive workflow that includes determination of transcription-factor binding-energy landscapes and mechanistic modeling, enabling us to generate a library of well-characterized synthetic transcription factors and corresponding promoters, which we then used to build gene-regulatory networks de novo. The well-characterized synthetic parts and insights gained should be useful for rationally engineering gene-regulatory networks and for studying the biophysics of transcriptional regulation.

scholarly journals Identification of cis-regulatory mutations generating de novo edges in personalized cancer gene regulatory networks

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Zeynep Kalender Atak ◽  
Hana Imrichova ◽  
Dmitry Svetlichnyy ◽  
Gert Hulselmans ◽  
Valerie Christiaens ◽  
...  
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
De Novo ◽  
Cancer Gene ◽  
Regulatory Mutations ◽  
Gene Regulatory ◽  
Personalized Cancer

scholarly journals What else is in an evolved name? Exploring evolvable specificity with SignalGP

2018 ◽  
Author(s):  
Alexander Lalejini ◽  
Charles Ofria
Keyword(s):  
Adaptive Evolution ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
De Novo ◽  
Direct Access ◽  
Evolutionary Transitions ◽  
Fine Grained ◽  
Flexible Mechanism ◽  
Gene Regulatory ◽  
Program Modules

Tags are evolvable labels that provide genetic programs a flexible mechanism for specification. Tags are used to label and refer to programmatic elements, such as functions or jump targets. However, tags differ from traditional, more rigid methods for handling labeling because they allow for inexact references; that is, a referring tag need not exactly match its referent. Here, we explore how adjusting the threshold for how what qualifies as a match affects adaptive evolution. Further, we propose broadened applications of tags in the context of a genetic programming (GP) technique called SignalGP. SignalGP gives evolution direct access to the event-driven paradigm. Program modules in SignalGP are tagged and can be triggered by signals (with matching tags) from the environment, from other agents, or due to internal regulation. Specifically, we propose to extend this tag based system to: (1) provide more fine-grained control over module execution and regulation (e.g., promotion and repression) akin to natural gene regulatory networks, (2) employ a mosaic of GP representations within a single program, and (3) facilitate major evolutionary transitions in individuality (i.e., allow hierarchical program organization to evolve de novo).

scholarly journals Uncovering Early Response of Gene Regulatory Networks in ESCs by Systematic Induction of Transcription Factors

2009 ◽  
Vol 5 (4) ◽  
pp. 420-433 ◽  
Author(s):  
Akira Nishiyama ◽  
Li Xin ◽  
Alexei A. Sharov ◽  
Marshall Thomas ◽  
Gregory Mowrer ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Early Response ◽  
Gene Regulatory

scholarly journals Automated generation of context-specific Gene Regulatory Networks with a weighted approach in D. melanogaster

2020 ◽  
Author(s):  
Leandro Murgas ◽  
Sebastian Contreras-Riquelme ◽  
J. Eduardo Martínez ◽  
Camilo Villaman ◽  
Rodrigo Santibáñez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Current Knowledge ◽  
Regulation Of Gene Expression ◽  
Chromatin Accessibility ◽  
Reference Network ◽  
Specific Gene ◽  
Gene Regulatory

AbstractMotivationThe regulation of gene expression is a key factor in the development and maintenance of life in all organisms. This process is carried out mainly through the action of transcription factors (TFs), although other actors such as ncRNAs are involved. In this work, we propose a new method to construct Gene Regulatory Networks (GRNs) depicting regulatory events in a certain context for Drosophila melanogaster. Our approach is based on known relationships between epigenetics and the activity of transcription factors.ResultsWe developed method, Tool for Weighted Epigenomic Networks in D. melanogaster (Fly T-WEoN), which generates GRNs starting from a reference network that contains all known gene regulations in the fly. Regulations that are unlikely taking place are removed by applying a series of knowledge-based filters. Each of these filters is implemented as an independent module that considers a type of experimental evidence, including DNA methylation, chromatin accessibility, histone modifications, and gene expression. Fly T-WEoN is based on heuristic rules that reflect current knowledge on gene regulation in D. melanogaster obtained from literature. Experimental data files can be generated with several standard procedures and used solely when and if available.Fly T-WEoN is available as a Cytoscape application that permits integration with other tools, and facilitates downstream network analysis. In this work, we first demonstrate the reliability of our method to then provide a relevant application case of our tool: early development of D. melanogaster.AvailabilityFly T-WEoN, together with its step-by-step guide is available at https://[email protected]

scholarly journals Automated generation of context-specific gene regulatory networks with a weighted approach in Drosophila melanogaster

2021 ◽  
Vol 11 (4) ◽  
pp. 20200076 ◽  
Author(s):  
Leandro Murgas ◽  
Sebastian Contreras-Riquelme ◽  
J. Eduardo Martínez-Hernandez ◽  
Camilo Villaman ◽  
Rodrigo Santibáñez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Drosophila Melanogaster ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Current Knowledge ◽  
Regulation Of Gene Expression ◽  
Reference Network ◽  
Specific Gene ◽  
Gene Regulatory ◽  
Context Specific

The regulation of gene expression is a key factor in the development and maintenance of life in all organisms. Even so, little is known at whole genome scale for most genes and contexts. We propose a method, Tool for Weighted Epigenomic Networks in Drosophila melanogaster (Fly T-WEoN), to generate context-specific gene regulatory networks starting from a reference network that contains all known gene regulations in the fly. Unlikely regulations are removed by applying a series of knowledge-based filters. Each of these filters is implemented as an independent module that considers a type of experimental evidence, including DNA methylation, chromatin accessibility, histone modifications and gene expression. Fly T-WEoN is based on heuristic rules that reflect current knowledge on gene regulation in D. melanogaster obtained from the literature. Experimental data files can be generated with several standard procedures and used solely when and if available. Fly T-WEoN is available as a Cytoscape application that permits integration with other tools and facilitates downstream network analysis. In this work, we first demonstrate the reliability of our method to then provide a relevant application case of our tool: early development of D. melanogaster . Fly T-WEoN together with its step-by-step guide is available at https://weon.readthedocs.io .

scholarly journals Cell-free gene regulatory network engineering with synthetic transcription factors

2018 ◽  
Author(s):  
Zoe Swank ◽  
Nadanai Laohakunakorn ◽  
Sebastian J. Maerkl
Keyword(s):  
Transcription Factors ◽  
High Throughput ◽  
Gene Regulatory Networks ◽  
Protein Interactions ◽  
Transcriptional Repression ◽  
Regulatory Networks ◽  
De Novo ◽  
Mechanistic Modeling ◽  
Free System ◽  
Gene Regulatory

AbstractGene regulatory networks are ubiquitous in nature and critical for bottom-up engineering of synthetic networks. Transcriptional repression is a fundamental function that can be tuned at the level of DNA, protein, and cooperative protein – protein interactions, necessitating high-throughput experimental approaches for in-depth characterization. Here we used a cell-free system in combination with a high-throughput microfluidic device to comprehensively study the different tuning mechanisms of a synthetic zinc-finger repressor library, whose affinity and cooperativity can be rationally engineered. The device is integrated into a comprehensive workflow that includes determination of transcription factor binding energy landscapes and mechanistic modeling, enabling us to generate a library of well-characterized synthetic transcription factors and corresponding promoters, which we then used to build gene regulatory networks de novo. The well-characterized synthetic parts and insights gained should be useful for rationally engineering gene regulatory networks and for studying the biophysics of transcriptional regulation.

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