Introducing Trait Networks to Elucidate the Fluidity of Organismal Evolution Using Palaeontological Data

Abstract Explaining the evolution of animals requires ecological, developmental, paleontological, and phylogenetic considerations because organismal traits are affected by complex evolutionary processes. Modeling a plurality of processes, operating at distinct time-scales on potentially interdependent traits, can benefit from approaches that are complementary treatments to phylogenetics. Here, we developed an inclusive network approach, implemented in the command line software ComponentGrapher, and analyzed trait co-occurrence of rhinocerotoid mammals. We identified stable, unstable, and pivotal traits, as well as traits contributing to complexes, that may follow to a common developmental regulation, that point to an early implementation of the postcranial Bauplan among rhinocerotoids. Strikingly, most identified traits are highly dissociable, used repeatedly in distinct combinations and in different taxa, which usually do not form clades. Therefore, the genes encoding these traits are likely recruited into novel gene regulation networks during the course of evolution. Our evo-systemic framework, generalizable to other evolved organizations, supports a pluralistic modeling of organismal evolution, including trees and networks.

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Complex network approach for detecting tropical cyclones

Climate Dynamics ◽

10.1007/s00382-021-05871-0 ◽

2021 ◽

Author(s):

Shraddha Gupta ◽

Niklas Boers ◽

Florian Pappenberger ◽

Jürgen Kurths

Keyword(s):

Sea Level ◽

Tropical Cyclones ◽

Complex Network ◽

Time Scales ◽

Southern Oscillation ◽

Volcanic Eruptions ◽

Network Approach ◽

Sea Level Pressure ◽

Level Pressure ◽

Climate Networks

AbstractTropical cyclones (TCs) are one of the most destructive natural hazards that pose a serious threat to society, particularly to those in the coastal regions. In this work, we study the temporal evolution of the regional weather conditions in relation to the occurrence of TCs using climate networks. Climate networks encode the interactions among climate variables at different locations on the Earth’s surface, and in particular, time-evolving climate networks have been successfully applied to study different climate phenomena at comparably long time scales, such as the El Niño Southern Oscillation, different monsoon systems, or the climatic impacts of volcanic eruptions. Here, we develop and apply a complex network approach suitable for the investigation of the relatively short-lived TCs. We show that our proposed methodology has the potential to identify TCs and their tracks from mean sea level pressure (MSLP) data. We use the ERA5 reanalysis MSLP data to construct successive networks of overlapping, short-length time windows for the regions under consideration, where we focus on the north Indian Ocean and the tropical north Atlantic Ocean. We compare the spatial features of various topological properties of the network, and the spatial scales involved, in the absence and presence of a cyclone. We find that network measures such as degree and clustering exhibit significant signatures of TCs and have striking similarities with their tracks. The study of the network topology over time scales relevant to TCs allows us to obtain crucial insights into the effects of TCs on the spatial connectivity structure of sea-level pressure fields.

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Fast Network Component Analysis for Gene Regulation Networks

2007 IEEE Workshop on Machine Learning for Signal Processing ◽

10.1109/mlsp.2007.4414276 ◽

2007 ◽

Cited By ~ 3

Author(s):

Chunqi Chang ◽

Zhi Ding ◽

Yeung Sam Hung ◽

Peter C.W. Fung

Keyword(s):

Gene Regulation ◽

Component Analysis ◽

Network Component Analysis ◽

Gene Regulation Networks ◽

Fast Network ◽

Network Component

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GENE REGULATION AND ITS ROLE IN EVOLUTIONARY PROCESSES

Evolutionary Processes and Theory ◽

10.1016/b978-0-12-398760-0.50005-5 ◽

1986 ◽

pp. 3-36 ◽

Cited By ~ 5

Author(s):

Kenneth Paigen

Keyword(s):

Gene Regulation ◽

Evolutionary Processes

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Two classes of active transcription sites and their roles in developmental regulation

10.1101/2020.06.23.167338 ◽

2020 ◽

Author(s):

Sarah Robinson-Thiewes ◽

John McCloskey ◽

Judith Kimble

Keyword(s):

Single Molecule ◽

Developmental Regulation ◽

Full Length ◽

Genes Encoding ◽

Transcription Sites ◽

Core Components ◽

Active Transcription ◽

Multiple Levels ◽

Nascent Transcripts ◽

Transcriptional Output

AbstractGenes encoding powerful developmental regulators are exquisitely controlled, often at multiple levels. Here, we use single molecule FISH (smFISH) to investigate nuclear active transcription sites (ATS) and cytoplasmic mRNAs of three key regulatory genes along the C. elegans germline developmental axis. The genes encode ERK/MAP kinase and core components of the Notch-dependent transcription complex. Using differentially-labeled probes spanning either a long first intron or downstream exons, we identify two ATS classes that differ in transcriptional progression: iATS harbor partial nascent transcripts while cATS harbor full-length nascent transcripts. Remarkably, the frequencies of iATS and cATS are patterned along the germline axis in a gene-, stage- and sex-specific manner. Moreover, regions with more frequent iATS make fewer full-length nascent transcripts and mRNAs, whereas those with more frequent cATS produce more of them. We propose that the regulated balance of these two ATS classes has a major impact on transcriptional output during development.

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ELECTRONIC DESIGN OF SYNTHETIC GENETIC NETWORKS

International Journal of Bifurcation and Chaos ◽

10.1142/s0218127407019275 ◽

2007 ◽

Vol 17 (10) ◽

pp. 3507-3511 ◽

Cited By ~ 2

Author(s):

JAVIER M. BULDÚ ◽

JORDI GARCÍA-OJALVO ◽

ALEXANDRE WAGEMAKERS ◽

MIGUEL A. F. SANJUÁN

Keyword(s):

Gene Regulation ◽

Genetic Networks ◽

Nonlinear Circuits ◽

Synthetic Gene ◽

Electronic Circuits ◽

Biochemical System ◽

Gene Regulation Networks ◽

Electronic Elements ◽

Electronic Design

We propose the use of nonlinear electronic circuits to study synthetic gene regulation networks. Specifically, we have designed two electronic versions of a synthetic genetic clock, known as the "repressilator," making use of appropriate electronic elements linked in the same way as the original biochemical system. We study the effects of coupling in a population of electronic repressilators, with the aim of observing coherent oscillations of the whole population. With these results, we show that this kind of nonlinear circuits can be helpful in the design and understanding of synthetic genetic networks.

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