↓ Skip to main content

Characterization of linkage disequilibrium, consistency of gametic phase and admixture in Australian and Canadian goats

Overview of attention for article published in BMC Genomic Data, June 2015
Altmetric Badge

Mentioned by

twitter
2 X users

Citations

dimensions_citation
67 Dimensions

Readers on

mendeley
85 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Characterization of linkage disequilibrium, consistency of gametic phase and admixture in Australian and Canadian goats
Published in
BMC Genomic Data, June 2015
DOI 10.1186/s12863-015-0220-1
Pubmed ID
Authors

Luiz F. Brito, Mohsen Jafarikia, Daniela A. Grossi, James W. Kijas, Laercio R. Porto-Neto, Ricardo V. Ventura, Mehdi Salgorzaei, Flavio S. Schenkel

Abstract

Basic understanding of linkage disequilibrium (LD) and population structure, as well as the consistency of gametic phase across breeds is crucial for genome-wide association studies and successful implementation of genomic selection. However, it is still limited in goats. Therefore, the objectives of this research were: (i) to estimate genome-wide levels of LD in goat breeds using data generated with the Illumina Goat SNP50 BeadChip; (ii) to study the consistency of gametic phase across breeds in order to evaluate the possible use of a multi-breed training population for genomic selection and (iii) develop insights concerning the population history of goat breeds. Average r(2) between adjacent SNP pairs ranged from 0.28 to 0.11 for Boer and Rangeland populations. At the average distance between adjacent SNPs in the current 50 k SNP panel (~0.06 Mb), the breeds LaMancha, Nubian, Toggenburg and Boer exceeded or approached the level of linkage disequilibrium that is useful (r(2) > 0.2) for genomic predictions. In all breeds LD decayed rapidly with increasing inter-marker distance. The estimated correlations for all the breed pairs, except Canadian and Australian Boer populations, were lower than 0.70 for all marker distances greater than 0.02 Mb. These results are not high enough to encourage the pooling of breeds in a single training population for genomic selection. The admixture analysis shows that some breeds have distinct genotypes based on SNP50 genotypes, such as the Boer, Cashmere and Nubian populations. The other groups share higher genome proportions with each other, indicating higher admixture and a more diverse genetic composition. This work presents results of a diverse collection of breeds, which are of great interest for the implementation of genomic selection in goats. The LD results indicate that, with a large enough training population, genomic selection could potentially be implemented within breed with the current 50 k panel, but some breeds might benefit from a denser panel. For multi-breed genomic evaluation, a denser SNP panel also seems to be required.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 1%
Unknown 84 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 18%
Student > Master 15 18%
Student > Ph. D. Student 11 13%
Student > Bachelor 8 9%
Student > Doctoral Student 8 9%
Other 13 15%
Unknown 15 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 48 56%
Biochemistry, Genetics and Molecular Biology 7 8%
Veterinary Science and Veterinary Medicine 2 2%
Environmental Science 2 2%
Medicine and Dentistry 2 2%
Other 4 5%
Unknown 20 24%
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 26 June 2015.
All research outputs
#20,655,488
of 25,373,627 outputs
Outputs from BMC Genomic Data
#861
of 1,204 outputs
Outputs of similar age
#203,296
of 278,348 outputs
Outputs of similar age from BMC Genomic Data
#34
of 44 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
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 278,348 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.