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Revealing misassembled segments in the bovine reference genome by high resolution linkage disequilibrium scan

Overview of attention for article published in BMC Genomics, September 2016
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Title
Revealing misassembled segments in the bovine reference genome by high resolution linkage disequilibrium scan
Published in
BMC Genomics, September 2016
DOI 10.1186/s12864-016-3049-8
Pubmed ID
Authors

Adam T. H. Utsunomiya, Daniel J. A. Santos, Solomon A. Boison, Yuri T. Utsunomiya, Marco Milanesi, Derek M. Bickhart, Paolo Ajmone-Marsan, Johann Sölkner, José F. Garcia, Ricardo da Fonseca, Marcos V. G. B. da Silva

Abstract

Misassembly signatures, created by shuffling the order of sequences while assembling a genome, can be detected by the unexpected behavior of marker linkage disequilibrium (LD) decay. We developed a heuristic process to identify misassembly signatures, applied it to the bovine reference genome assembly (UMDv3.1) and presented the consequences of misassemblies in two case studies. We identified 2,906 single nucleotide polymorphism (SNP) markers presenting unexpected LD decay behavior in 626 putative misassembled contigs, which comprised less than 1 % of the whole genome. Although this represents a small fraction of the reference sequence, these poorly assembled segments can lead to severe implications to local genome context. For instance, we showed that one of the misassembled regions mapped to the POLL locus, which affected the annotation of positional candidate genes in a GWAS case study for polledness in Nellore (Bos indicus beef cattle). Additionally, we found that poorly performing markers in imputation mapped to putative misassembled regions, and that correction of marker positions based on LD was capable to recover imputation accuracy. This heuristic approach can be useful to cross validate reference assemblies and to filter out markers located at low confidence genomic regions before conducting downstream analyses.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
New Zealand 1 3%
Unknown 37 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 26%
Student > Ph. D. Student 8 21%
Student > Master 5 13%
Student > Doctoral Student 3 8%
Student > Bachelor 2 5%
Other 5 13%
Unknown 5 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 55%
Biochemistry, Genetics and Molecular Biology 5 13%
Medicine and Dentistry 2 5%
Environmental Science 1 3%
Psychology 1 3%
Other 1 3%
Unknown 7 18%
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 07 September 2016.
All research outputs
#15,383,207
of 22,886,568 outputs
Outputs from BMC Genomics
#6,702
of 10,668 outputs
Outputs of similar age
#214,158
of 335,711 outputs
Outputs of similar age from BMC Genomics
#169
of 289 outputs
Altmetric has tracked 22,886,568 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,668 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
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We're also able to compare this research output to 289 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.