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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.
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Gene Evolution - Fast or Slow?02:05

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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...
Ribosome Profiling02:24

Ribosome Profiling

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Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

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Published on: July 12, 2022

PhyloCSF: a comparative genomics method to distinguish protein coding and non-coding regions.

Michael F Lin1, Irwin Jungreis, Manolis Kellis

  • 1Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar Street 32-D510, Cambridge, MA 02139, USA. mlin@mit.edu

Bioinformatics (Oxford, England)
|June 21, 2011
PubMed
Summary

PhyloCSF accurately classifies genomic regions as protein-coding or non-coding using comparative genomics. This novel method outperforms existing approaches in identifying conserved protein-coding regions across multiple species.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput transcriptome sequencing reveals numerous novel transcripts, necessitating precise methods for classifying genomic regions.
  • Distinguishing protein-coding from non-coding regions is crucial for understanding genome function and annotation.

Purpose of the Study:

  • To introduce PhyloCSF, a novel comparative genomics method for classifying genomic regions.
  • To assess the accuracy and applicability of PhyloCSF in distinguishing conserved protein-coding regions.

Main Methods:

  • PhyloCSF analyzes multispecies nucleotide sequence alignments.
  • It employs a formal statistical comparison of phylogenetic codon models.
  • The method evaluates the likelihood of a genomic region being protein-coding.

Main Results:

  • PhyloCSF demonstrated superior classification performance in 12-species Drosophila genome alignments compared to other methods.
  • The method is expected to be valuable for ongoing large-scale transcriptome sequencing projects.

Conclusions:

  • PhyloCSF provides an accurate and robust method for classifying protein-coding and non-coding genomic regions.
  • Its application is timely given the increasing volume of genomic and transcriptomic data and the growing interest in non-coding RNAs.