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Related Concept Videos

Genetic Variation01:25

Genetic Variation

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Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
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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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Evolutionary Relationships through Genome Comparisons02:54

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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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Genomics02:02

Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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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.
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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.
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Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
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Genome Complexity Browser: Visualization and quantification of genome variability.

Alexander Manolov1, Dmitry Konanov1, Dmitry Fedorov1

  • 1Federal Research and Clinical Center of Physical and Chemical Medicine, Federal Medical and Biological Agency of Russia, Moscow, Russian Federation.

Plos Computational Biology
|October 9, 2020
PubMed
Summary
This summary is machine-generated.

We developed the Genome Complexity Browser to visualize and quantify gene variability across hundreds of prokaryotic genomes. This tool helps identify conserved and variable genomic regions, aiding comparative genomics research.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Comparative genomics is crucial for understanding genome architecture and gene organization in organisms.
  • Numerous prokaryotic genomes are available, but tools for large-scale comparative analysis are limited.
  • Existing methods struggle to simultaneously compare hundreds of genomes efficiently.

Purpose of the Study:

  • To develop a computational tool for visualizing and quantifying gene context variability across large-scale genomic datasets.
  • To introduce a novel metric, 'complexity,' for measuring genome variability.
  • To facilitate the identification of conserved and variable genomic segments within and between species.

Main Methods:

  • Development of the Genome Complexity Browser, a graph-based visualization tool.
  • Implementation of a 'complexity' metric to quantify genome variability.
  • Application of the tool for intraspecies and interspecies comparative genomic analyses.

Main Results:

  • The Genome Complexity Browser enables simultaneous visualization of gene contexts across hundreds of genomes.
  • The 'complexity' metric effectively quantifies genome variability.
  • High complexity regions were found to be located in areas conserved across different strains and species.

Conclusions:

  • The Genome Complexity Browser addresses the need for scalable comparative genomics tools.
  • The 'complexity' metric provides a quantitative measure for genome variability.
  • Comparative genomics using this tool can reveal insights into genome architecture and conserved regions.