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Interlocus gene conversion explains at least 2.7 % of single nucleotide variants in human segmental duplications

Overview of attention for article published in BMC Genomics, June 2015
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Title
Interlocus gene conversion explains at least 2.7 % of single nucleotide variants in human segmental duplications
Published in
BMC Genomics, June 2015
DOI 10.1186/s12864-015-1681-3
Pubmed ID
Authors

Beth L. Dumont

Abstract

Interlocus gene conversion (IGC) is a recombination-based mechanism that results in the unidirectional transfer of short stretches of sequence between paralogous loci. Although IGC is a well-established mechanism of human disease, the extent to which this mutagenic process has shaped overall patterns of segregating variation in multi-copy regions of the human genome remains unknown. One expected manifestation of IGC in population genomic data is the presence of one-to-one paralogous SNPs that segregate identical alleles. Here, I use SNP genotype calls from the low-coverage phase 3 release of the 1000 Genomes Project to identify 15,790 parallel, shared SNPs in duplicated regions of the human genome. My approach for identifying these sites accounts for the potential redundancy of short read mapping in multi-copy genomic regions, thereby effectively eliminating false positive SNP calls arising from paralogous sequence variation. I demonstrate that independent mutation events to identical nucleotides at paralogous sites are not a significant source of shared polymorphisms in the human genome, consistent with the interpretation that these sites are the outcome of historical IGC events. These putative signals of IGC are enriched in genomic contexts previously associated with non-allelic homologous recombination, including clear signals in gene families that form tandem intra-chromosomal clusters. Taken together, my analyses implicate IGC, not point mutation, as the mechanism generating at least 2.7 % of single nucleotide variants in duplicated regions of the human genome.

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The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 44%
Researcher 5 19%
Student > Master 2 7%
Professor 2 7%
Other 1 4%
Other 3 11%
Unknown 2 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 52%
Biochemistry, Genetics and Molecular Biology 8 30%
Arts and Humanities 1 4%
Unspecified 1 4%
Unknown 3 11%
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 17 June 2015.
All research outputs
#20,280,315
of 22,813,792 outputs
Outputs from BMC Genomics
#9,277
of 10,651 outputs
Outputs of similar age
#199,503
of 239,955 outputs
Outputs of similar age from BMC Genomics
#229
of 246 outputs
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