| Title |
Is black coat color in wolves of Iran an evidence of admixed ancestry with dogs?
|
|---|---|
| Published in |
Journal of Applied Genetics, August 2014
|
| DOI | 10.1007/s13353-014-0237-6 |
| Pubmed ID | |
| Authors |
Rasoul Khosravi, Marzieh Asadi Aghbolaghi, Hamid Reza Rezaei, Elham Nourani, Mohammad Kaboli |
| Abstract |
Melanism is not considered a typical characteristic in wolves of Iran and dark wolves are believed to have originated from crossbreeding with dogs. Such hybrid individuals can be identified with the combined use of genetic and morphological markers. We analyzed two black wolves using a 544 base pairs (bp) fragment of the mtDNA control region and 15 microsatellite loci in comparison with 28 dogs, 28 wolves, and four known hybrids. The artificial neural networks (ANNs) method was applied to microsatellite data to separate genetically differentiated samples of wolves, dogs, and hybrids, and to determine the correct class for the black specimens. Individual assignments based on ANNs showed that black samples were genetically closer to wolves. Also, in the neighbor-joining network of mtDNA haplotypes, wolves and dogs were separated, with the dark specimens located in the wolf branch as two separate haplotypes. Furthermore, we compared 20 craniometrical characters of the two black individuals with 14 other wolves. The results showed that craniometrical measures of the two black wolves fall within the range of wolf skulls. We found no trace of recent hybridization with free-ranging dogs in the two black wolves. Dark coat color might be the result of a natural combination of alleles in the coat-color-determining gene, mutation in the K locus due to past hybridization with free-ranging dogs, or the effect of ecological factors and adaption to habitat conditions. |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 28 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 29% |
| Researcher | 4 | 14% |
| Student > Master | 3 | 11% |
| Student > Bachelor | 2 | 7% |
| Student > Postgraduate | 2 | 7% |
| Other | 3 | 11% |
| Unknown | 6 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 36% |
| Biochemistry, Genetics and Molecular Biology | 4 | 14% |
| Environmental Science | 3 | 11% |
| Arts and Humanities | 1 | 4% |
| Mathematics | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 8 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 15 August 2020.
All research outputs
#6,941,235
of 22,759,618 outputs
Outputs from Journal of Applied Genetics
#67
of 392 outputs
Outputs of similar age
#66,352
of 229,696 outputs
Outputs of similar age from Journal of Applied Genetics
#2
of 12 outputs
Altmetric has tracked 22,759,618 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 392 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done well, scoring higher than 82% of its peers.
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We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.