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Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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...
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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.
In contrast, regions which code...
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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.
In contrast, regions which code...
Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
The...
Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved DNA...
Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes02:16

Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes

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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Related Experiment Video

Updated: Jun 8, 2026

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
09:14

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Published on: June 28, 2018

Murasaki: a fast, parallelizable algorithm to find anchors from multiple genomes.

Kris Popendorf1, Hachiya Tsuyoshi, Yasunori Osana

  • 1Department of Biosciences and Informatics, Keio University, Yokohama, Japan.

Plos One
|October 2, 2010
PubMed
Summary

Murasaki efficiently identifies genomic anchors in multiple large genomes, overcoming computational challenges. This new algorithm offers faster, more accurate genome comparisons for large-scale analyses.

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Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
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Last Updated: Jun 8, 2026

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
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Published on: June 28, 2018

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
09:37

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Genome sequence data is rapidly increasing, posing challenges for multiple-genome analyses.
  • Identifying conserved sequences (anchors) is crucial for comparing genomes with rearrangements.
  • Existing methods like BLASTZ and TBA face computational limitations with growing genome data.

Purpose of the Study:

  • To develop an efficient algorithm for identifying anchors across multiple large genomes.
  • To address the computational bottleneck in large-scale comparative genomics.

Main Methods:

  • Developed Murasaki, an algorithm utilizing adaptive hash function generation and parallelizable execution.
  • Employed spaced seeds for efficient comparison of multiple mammalian genomes.
  • Performed single-pass, in-core anchoring of eight mammalian genomes.

Main Results:

  • Murasaki identifies anchors in multiple large sequences (hundreds of megabases) within minutes on a single CPU.
  • Anchoring eight mammalian genomes required only 21 hours of CPU time (42 minutes wall time).
  • Murasaki demonstrates near-linear time complexity, outperforming the quadratic time of BLASTZ and TBA, with improved accuracy.

Conclusions:

  • Murasaki offers an open-source platform for accurate, computationally efficient multi-genome anchoring.
  • Leverages novel hash algorithms and cluster computing for significant performance gains.
  • Provides a practical solution for large-scale comparative genomics research.