↓ Skip to main content

Genetic structure, divergence and admixture of Han Chinese, Japanese and Korean populations

Overview of attention for article published in Hereditas, April 2018
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#7 of 475)
  • High Attention Score compared to outputs of the same age (92nd percentile)

Mentioned by

blogs
1 blog
twitter
27 tweeters
wikipedia
29 Wikipedia pages

Citations

dimensions_citation
61 Dimensions

Readers on

mendeley
51 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
Genetic structure, divergence and admixture of Han Chinese, Japanese and Korean populations
Published in
Hereditas, April 2018
DOI 10.1186/s41065-018-0057-5
Pubmed ID
Authors

Yuchen Wang, Dongsheng Lu, Yeun-Jun Chung, Shuhua Xu

Abstract

Han Chinese, Japanese and Korean, the three major ethnic groups of East Asia, share many similarities in appearance, language and culture etc., but their genetic relationships, divergence times and subsequent genetic exchanges have not been well studied. We conducted a genome-wide study and evaluated the population structure of 182 Han Chinese, 90 Japanese and 100 Korean individuals, together with the data of 630 individuals representing 8 populations wordwide. Our analyses revealed that Han Chinese, Japanese and Korean populations have distinct genetic makeup and can be well distinguished based on either the genome wide data or a panel of ancestry informative markers (AIMs). Their genetic structure corresponds well to their geographical distributions, indicating geographical isolation played a critical role in driving population differentiation in East Asia. The most recent common ancestor of the three populations was dated back to 3000 ~ 3600 years ago. Our analyses also revealed substantial admixture within the three populations which occurred subsequent to initial splits, and distinct gene introgression from surrounding populations, of which northern ancestral component is dominant. These estimations and findings facilitate to understanding population history and mechanism of human genetic diversity in East Asia, and have implications for both evolutionary and medical studies.

Twitter Demographics

The data shown below were collected from the profiles of 27 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 20%
Student > Ph. D. Student 8 16%
Student > Bachelor 8 16%
Student > Master 6 12%
Professor 4 8%
Other 9 18%
Unknown 6 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 31%
Agricultural and Biological Sciences 11 22%
Neuroscience 3 6%
Medicine and Dentistry 2 4%
Social Sciences 2 4%
Other 10 20%
Unknown 7 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 32. 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 08 August 2022.
All research outputs
#982,161
of 21,807,934 outputs
Outputs from Hereditas
#7
of 475 outputs
Outputs of similar age
#23,700
of 299,369 outputs
Outputs of similar age from Hereditas
#1
of 1 outputs
Altmetric has tracked 21,807,934 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 475 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done particularly well, scoring higher than 98% 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 299,369 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 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them