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Regulatory pathway analysis of coat color genes in Mongolian horses

Overview of attention for article published in Hereditas, September 2017
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Title
Regulatory pathway analysis of coat color genes in Mongolian horses
Published in
Hereditas, September 2017
DOI 10.1186/s41065-017-0048-y
Pubmed ID
Authors

Bei Li, Xiaolong He, Yiping Zhao, Dongyi Bai, Wunierfu Shiraigo, Qinan Zhao, Dugarjaviin Manglai

Abstract

Studies on the molecular genetics of horse skin pigmentation have typically focused on very few genes and proteins. In this study, we used Illumina sequencing to determine the global gene expression profiles in horses with white-colored coats and those with black-colored coats, with the goal of identifying novel genes that could regulate horse coat color. Genes encoding ribosomal-associated proteins were highly expressed in horse skin. We found a total of 231 unigenes that were differentially expressed between horses with white coats and horses with black coats; 119 were down-regulated, and 112 were up-regulated. Many of the up-regulated genes in black horses, such as genes related to tyrosine metabolism, may directly regulate dark coat color. Keratin genes, MIA family genes, fatty acid-related genes, and melanoma-associated genes were also differentially regulated, which suggests that they may play important roles in coat color formation. These findings show that the transcription profiles from white and black horse skin provide useful information to understand the genetics underlying the control of skin melanin synthesis in horses, which may enhance our knowledge of human skin diseases, such as melanoma and albinism.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 27%
Student > Bachelor 1 9%
Student > Doctoral Student 1 9%
Student > Master 1 9%
Student > Ph. D. Student 1 9%
Other 0 0%
Unknown 4 36%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 18%
Agricultural and Biological Sciences 2 18%
Nursing and Health Professions 1 9%
Medicine and Dentistry 1 9%
Engineering 1 9%
Other 0 0%
Unknown 4 36%
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 05 October 2017.
All research outputs
#20,663,600
of 25,382,440 outputs
Outputs from Hereditas
#398
of 513 outputs
Outputs of similar age
#255,548
of 329,378 outputs
Outputs of similar age from Hereditas
#3
of 6 outputs
Altmetric has tracked 25,382,440 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 513 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 13th percentile – i.e., 13% 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 329,378 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.