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Related Concept Videos

Combinatorial Gene Control02:33

Combinatorial Gene Control

Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).Mechanisms of Genetic VariationThe original sources of genetic variation are mutations,...
Gene Duplication and Divergence02:37

Gene Duplication and Divergence

The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was  generated by gene duplication and divergence, indicating its critical role in evolution.
The duplicated copies of the gene are called Paralogs. Paralogs with similar sequences and functions form a gene family. Across several species, a large number of gene families are characterized.
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

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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Design and Synthesis of a Reconfigurable DNA Accordion Rack
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CAGE: Combinatorial Analysis of Gene-cluster Evolution.

Giltae Song1, Louxin Zhang, Tomas Vinar

  • 1Center for Comparative Genomics and Bioinformatics, Penn State University, University Park, PA 16802, USA. gsong@bx.psu.edu

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|September 30, 2010
PubMed
Summary
This summary is machine-generated.

We developed a new computational method to reconstruct gene cluster evolution. This approach improves analysis of gene families and evolutionary processes in complex genomic regions.

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Area of Science:

  • Genomics
  • Evolutionary Biology
  • Bioinformatics

Background:

  • Gene clusters are crucial for evolutionary innovation, allowing gene copies to gain new functions.
  • Existing computational tools struggle with analyzing gene cluster evolution due to data inaccuracies in these genomic regions.

Purpose of the Study:

  • To introduce a novel computational method for reconstructing the evolutionary history of gene clusters.
  • To address limitations in current methods for analyzing evolutionary activity within gene families.

Main Methods:

  • Development of a new algorithm for evolutionary history reconstruction.
  • Performance evaluation using simulated sequence data.
  • Validation on actual human gene cluster datasets.

Main Results:

  • The new method demonstrates effective reconstruction of recent evolutionary histories for gene clusters.
  • Performance is validated across both simulated and real-world human genomic data.

Conclusions:

  • The developed method offers an improved approach for studying gene cluster evolution.
  • This tool enhances the analysis of evolutionary dynamics in complex genomic regions.