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A simple strategy for managing many recessive disorders in a dairy cattle breeding program

Overview of attention for article published in Genetics Selection Evolution, November 2015
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  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

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Title
A simple strategy for managing many recessive disorders in a dairy cattle breeding program
Published in
Genetics Selection Evolution, November 2015
DOI 10.1186/s12711-015-0174-9
Pubmed ID
Authors

John B. Cole

Abstract

High-density single nucleotide polymorphism genotypes have recently been used to identify a number of novel recessive mutations that adversely affect fertility in dairy cattle, as well as to track other conditions such as red coat color and polled. Most current methods for mate allocation fail to consider this information, and it will become increasingly difficult to manage matings as the number of recessive mutations to be accounted for increases. A modified version of a mating strategy that constrains inbreeding based on genomics (the Pryce method) was developed that also accounts for the economic effects of Mendelian disorders on overall economic merit (modified Pryce method) and compared with random mating, truncation selection, and the Pryce scheme. Several scenarios were considered, including scenarios with six hypothetical recessive alleles and 12 recessive alleles that are currently segregating in the US Holstein population. The Pryce method and the modified Pryce method showed similar ability to reduce frequencies of recessive alleles, particularly for loci with frequencies greater than 0.30. The modified Pryce method outperformed the Pryce method for low-frequency alleles with small economic value. Cumulative genetic gain for the selection objective was slightly greater when using the Pryce method, but rates of inbreeding were similar across methods. The proposed method reduces allele frequencies faster than other methods, and also can be used to maintain or increase the frequency of desirable recessives. It can be easily implemented in software for mate allocation, and the code used in this study is freely available as a reference implementation.

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X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Finland 1 1%
Unknown 68 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 31%
Student > Ph. D. Student 10 14%
Student > Master 10 14%
Student > Bachelor 7 10%
Student > Doctoral Student 4 6%
Other 5 7%
Unknown 13 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 51%
Veterinary Science and Veterinary Medicine 8 11%
Biochemistry, Genetics and Molecular Biology 6 8%
Mathematics 2 3%
Business, Management and Accounting 2 3%
Other 2 3%
Unknown 15 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 10 August 2021.
All research outputs
#7,148,903
of 25,374,647 outputs
Outputs from Genetics Selection Evolution
#226
of 822 outputs
Outputs of similar age
#102,242
of 395,377 outputs
Outputs of similar age from Genetics Selection Evolution
#2
of 17 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 822 research outputs from this source. They receive a mean Attention Score of 4.1. This one has gotten more attention than average, scoring higher than 71% 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 395,377 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.