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Reconstruction of an ancestral Yersinia pestisgenome and comparison with an ancient sequence

Overview of attention for article published in BMC Genomics, October 2015
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Title
Reconstruction of an ancestral Yersinia pestisgenome and comparison with an ancient sequence
Published in
BMC Genomics, October 2015
DOI 10.1186/1471-2164-16-s10-s9
Pubmed ID
Authors

Wandrille Duchemin, Vincent Daubin, Eric Tannier

Abstract

We propose the computational reconstruction of a whole bacterial ancestral genome at the nucleotide scale, and its validation by a sequence of ancient DNA. This rare possibility is offered by an ancient sequence of the late middle ages plague agent. It has been hypothesized to be ancestral to extant Yersinia pestis strains based on the pattern of nucleotide substitutions. But the dynamics of indels, duplications, insertion sequences and rearrangements has impacted all genomes much more than the substitution process, which makes the ancestral reconstruction task challenging. We use a set of gene families from 13 Yersinia species, construct reconciled phylogenies for all of them, and determine gene orders in ancestral species. Gene trees integrate information from the sequence, the species tree and gene order. We reconstruct ancestral sequences for ancestral genic and intergenic regions, providing nearly a complete genome sequence for the ancestor, containing a chromosome and three plasmids. The comparison of the ancestral and ancient sequences provides a unique opportunity to assess the quality of ancestral genome reconstruction methods. But the quality of the sequencing and assembly of the ancient sequence can also be questioned by this comparison.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Unknown 46 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 32%
Researcher 8 17%
Student > Master 7 15%
Student > Bachelor 4 9%
Student > Postgraduate 4 9%
Other 7 15%
Unknown 2 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 49%
Biochemistry, Genetics and Molecular Biology 9 19%
Computer Science 5 11%
Immunology and Microbiology 3 6%
Arts and Humanities 1 2%
Other 2 4%
Unknown 4 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 July 2016.
All research outputs
#20,335,423
of 22,880,230 outputs
Outputs from BMC Genomics
#9,292
of 10,666 outputs
Outputs of similar age
#231,058
of 275,472 outputs
Outputs of similar age from BMC Genomics
#330
of 351 outputs
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