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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
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The endosymbiont theory is the most widely accepted theory of eukaryotic evolution; however, its progression is still somewhat debated. According to the nucleus-first hypothesis, the ancestral prokaryote first evolved a membrane to enclose DNA and form the nucleus. Conversely, the mitochondria-first hypothesis suggests that the nucleus was formed after endosymbiosis of mitochondria.
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While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
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Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
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What to compare and how: Comparative transcriptomics for Evo-Devo.

Julien Roux1,2,3, Marta Rosikiewicz1,2, Marc Robinson-Rechavi1,2

  • 1Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.

Journal of Experimental Zoology. Part B, Molecular and Developmental Evolution
|April 14, 2015
PubMed
Summary
This summary is machine-generated.

Evolutionary developmental biology uses gene expression to study anatomical evolution. New transcriptomics data present challenges in comparing species, which bioinformatics tools like Bgee aim to solve.

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Area of Science:

  • Evolutionary developmental biology
  • Comparative genomics
  • Bioinformatics

Background:

  • Relating anatomical evolution to gene expression patterns is a historical approach in evolutionary developmental biology.
  • Modern transcriptomics offers enhanced capabilities for studying evolutionary convergence, constraint, and innovation in anatomy and development across species.
  • Scaling up these studies reveals significant computational and methodological challenges.

Purpose of the Study:

  • To review the challenges in integrating transcriptomics with evolutionary developmental biology.
  • To highlight ongoing bioinformatics efforts addressing these challenges.
  • To showcase the implementation of these solutions within the Bgee database.

Main Methods:

  • Utilizing ontologies for standardized anatomical and developmental term annotation.
  • Developing evolutionary statistical methods for cross-species transcriptomic data comparison.
  • Implementing data curation and bioinformatics pipelines for robust analysis.
  • Focusing on the development and application of the Bgee database.

Main Results:

  • Identification of key computational challenges in anatomical homology and organ function definition.
  • Establishment of criteria for comparing developmental stages across species.
  • Advancements in annotating transcriptomic data to relevant biological terms.
  • Development of statistical frameworks for detecting conserved or divergent gene expression.

Conclusions:

  • Bioinformatics, ontologies, and statistical methods are crucial for overcoming challenges in evolutionary developmental biology.
  • The Bgee database serves as a platform for implementing and applying these solutions.
  • Addressing these challenges enables a deeper understanding of the molecular mechanisms underlying evolutionary changes in anatomy and development.