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Genome-Wide Survey for Biologically Functional Pseudogenes

Overview of attention for article published in PLoS Computational Biology, May 2006
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Title
Genome-Wide Survey for Biologically Functional Pseudogenes
Published in
PLoS Computational Biology, May 2006
DOI 10.1371/journal.pcbi.0020046
Pubmed ID
Authors

Örjan Svensson, Lars Arvestad, Jens Lagergren

Abstract

According to current estimates there exist about 20,000 pseudogenes in a mammalian genome. The vast majority of these are disabled and nonfunctional copies of protein-coding genes which, therefore, evolve neutrally. Recent findings that a Makorin1 pseudogene, residing on mouse Chromosome 5, is, indeed, in vivo vital and also evolutionarily preserved, encouraged us to conduct a genome-wide survey for other functional pseudogenes in human, mouse, and chimpanzee. We identify to our knowledge the first examples of conserved pseudogenes common to human and mouse, originating from one duplication predating the human-mouse species split and having evolved as pseudogenes since the species split. Functionality is one possible way to explain the apparently contradictory properties of such pseudogene pairs, i.e., high conservation and ancient origin. The hypothesis of functionality is tested by comparing expression evidence and synteny of the candidates with proper test sets. The tests suggest potential biological function. Our candidate set includes a small set of long-lived pseudogenes whose unknown potential function is retained since before the human-mouse species split, and also a larger group of primate-specific ones found from human-chimpanzee searches. Two processed sequences are notable, their conservation since the human-mouse split being as high as most protein-coding genes; one is derived from the protein Ataxin 7-like 3 (ATX7NL3), and one from the Spinocerebellar ataxia type 1 protein (ATX1). Our approach is comparative and can be applied to any pair of species. It is implemented by a semi-automated pipeline based on cross-species BLAST comparisons and maximum-likelihood phylogeny estimations. To separate pseudogenes from protein-coding genes, we use standard methods, utilizing in-frame disablements, as well as a probabilistic filter based on Ka/Ks ratios.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 6%
Germany 3 3%
Brazil 3 3%
Sweden 3 3%
Turkey 1 <1%
Netherlands 1 <1%
Russia 1 <1%
Korea, Republic of 1 <1%
Unknown 98 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 26%
Researcher 21 18%
Student > Master 17 14%
Professor > Associate Professor 13 11%
Student > Bachelor 12 10%
Other 21 18%
Unknown 3 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 71 60%
Biochemistry, Genetics and Molecular Biology 18 15%
Computer Science 10 8%
Medicine and Dentistry 3 3%
Pharmacology, Toxicology and Pharmaceutical Science 2 2%
Other 8 7%
Unknown 6 5%