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Imputation of microsatellite alleles from dense SNP genotypes for parentage verification across multiple Bos taurus and Bos indicus breeds

Overview of attention for article published in Frontiers in Genetics, January 2013
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

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1 news outlet
blogs
1 blog
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3 X users

Citations

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22 Dimensions

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64 Mendeley
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Title
Imputation of microsatellite alleles from dense SNP genotypes for parentage verification across multiple Bos taurus and Bos indicus breeds
Published in
Frontiers in Genetics, January 2013
DOI 10.3389/fgene.2013.00176
Pubmed ID
Authors

Matthew C. McClure, Tad S. Sonstegard, George R. Wiggans, Alison L. Van Eenennaam, Kristina L. Weber, Cecilia T. Penedo, Donagh P. Berry, John Flynn, Jose F. Garcia, Adriana S. Carmo, Luciana C. A. Regitano, Milla Albuquerque, Marcos V. G. B. Silva, Marco A. Machado, Mike Coffey, Kirsty Moore, Marie-Yvonne Boscher, Lucie Genestout, Raffaele Mazza, Jeremy F. Taylor, Robert D. Schnabel, Barry Simpson, Elisa Marques, John C. McEwan, Andrew Cromie, Luiz L. Coutinho, Larry A. Kuehn, John W. Keele, Emily K. Piper, Jim Cook, Robert Williams, Bovine HapMap Consortium, Curtis P. Van Tassell

Abstract

To assist cattle producers transition from microsatellite (MS) to single nucleotide polymorphism (SNP) genotyping for parental verification we previously devised an effective and inexpensive method to impute MS alleles from SNP haplotypes. While the reported method was verified with only a limited data set (N = 479) from Brown Swiss, Guernsey, Holstein, and Jersey cattle, some of the MS-SNP haplotype associations were concordant across these phylogenetically diverse breeds. This implied that some haplotypes predate modern breed formation and remain in strong linkage disequilibrium. To expand the utility of MS allele imputation across breeds, MS and SNP data from more than 8000 animals representing 39 breeds (Bos taurus and B. indicus) were used to predict 9410 SNP haplotypes, incorporating an average of 73 SNPs per haplotype, for which alleles from 12 MS markers could be accurately be imputed. Approximately 25% of the MS-SNP haplotypes were present in multiple breeds (N = 2 to 36 breeds). These shared haplotypes allowed for MS imputation in breeds that were not represented in the reference population with only a small increase in Mendelian inheritance inconsistancies. Our reported reference haplotypes can be used for any cattle breed and the reported methods can be applied to any species to aid the transition from MS to SNP genetic markers. While ~91% of the animals with imputed alleles for 12 MS markers had ≤1 Mendelian inheritance conflicts with their parents' reported MS genotypes, this figure was 96% for our reference animals, indicating potential errors in the reported MS genotypes. The workflow we suggest autocorrects for genotyping errors and rare haplotypes, by MS genotyping animals whose imputed MS alleles fail parentage verification, and then incorporating those animals into the reference dataset.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Finland 1 2%
Netherlands 1 2%
United States 1 2%
Argentina 1 2%
Unknown 60 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 36%
Student > Master 11 17%
Other 5 8%
Professor > Associate Professor 3 5%
Student > Bachelor 2 3%
Other 10 16%
Unknown 10 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 35 55%
Biochemistry, Genetics and Molecular Biology 5 8%
Veterinary Science and Veterinary Medicine 3 5%
Environmental Science 2 3%
Unspecified 1 2%
Other 4 6%
Unknown 14 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 11 October 2018.
All research outputs
#1,962,569
of 22,721,584 outputs
Outputs from Frontiers in Genetics
#450
of 11,757 outputs
Outputs of similar age
#20,169
of 280,761 outputs
Outputs of similar age from Frontiers in Genetics
#26
of 319 outputs
Altmetric has tracked 22,721,584 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,757 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 280,761 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 319 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.