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Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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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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Genome-wide Association Studies-GWAS01:11

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
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Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes02:16

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The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...
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Comparing Copy Number Variations and SNPs02:26

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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
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Genome Size and the Evolution of New Genes03:21

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Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

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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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High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq
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EDGAR 2.0: an enhanced software platform for comparative gene content analyses.

Jochen Blom1, Julian Kreis2, Sebastian Spänig2

  • 1Bioinformatics & Systems Biology, Justus-Liebig-University Giessen, 35392 Giessen, Hesse, Germany jochen.blom@computational.bio.uni-giessen.de.

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Summary
This summary is machine-generated.

The EDGAR 2.0 platform enhances comparative microbial genomics with new features for analyzing gene content and evolutionary relationships. This bioinformatics tool aids researchers in discovering core and singleton genes across microbial genomes.

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Area of Science:

  • Bioinformatics
  • Comparative Genomics
  • Microbial Genomics

Background:

  • Increasing microbial genome data necessitates advanced bioinformatics tools for comparative analysis.
  • Comparative genomics reveals core and singleton genes, crucial for understanding microbial evolution and function.

Purpose of the Study:

  • To introduce EDGAR 2.0, an updated platform for comparative microbial genomics.
  • To provide enhanced features for analyzing gene content and evolutionary relationships among microbial genomes.

Main Methods:

  • Re-implementation of the gene orthology estimation approach.
  • Integration of Average Nucleotide Identity (ANI) and Average Amino Acid Identity (AAI) matrices.
  • Development of modernized visualizations including interactive synteny plots and Venn diagrams.

Main Results:

  • EDGAR 2.0 offers a re-designed gene orthology estimation.
  • New phylogenetic analysis features (AAI, ANI) and genome statistics are available.
  • Interactive visualizations facilitate the survey of evolutionary relationships and differential gene content.

Conclusions:

  • EDGAR 2.0 provides a user-friendly, web-based platform for microbial comparative genomics.
  • The updated features simplify the discovery of biological insights from microbial genome comparisons.
  • The platform supports efficient exploration of evolutionary relationships and gene content variations.