Back

Comprehensive analysis of Japanese population history by detecting ancestry-marker polymorphisms without using ancestral genomic information

Watanabe, Y.; Ohashi, J.

2020-12-07 evolutionary biology
10.1101/2020.12.07.414037 bioRxiv
Show abstract

Modern Japanese have two major ancestral populations: the indigenous Jomon hunter gatherers and continental East Asian farmers. To figure out the formation process of current Japanese population, we developed a reference-free detection method of variants derived from ancestral populations using a summary statistic, the ancestry-marker index (AMI). We confirmed by computer simulations that AMI can detect ancestry-derived variants even in an admixed population of recently diverged source populations with high accuracy, which cannot be achieved by the most widely used statistics, S*, for identifying archaic ancestry. We applied the AMI to modern Japanese samples and identified 208,648 single nucleotide polymorphisms (SNPs) that were likely derived from the Jomon people (Jomon-derived variants). The analysis of Jomon-derived variants in 10,842 modern Japanese individuals recruited from all over Japan revealed that the admixture proportions of the Jomon people varied between prefectures, probably due to the differences of population sizes of immigrants in the final Jomon to the Yayoi period. The estimated allele frequencies of genome-wide SNPs in the ancestral populations of modern Japanese suggested their phenotypic characteristics possibly for adaptation to their respective livelihoods; higher triglycerides and blood sugar for the Jomon ancestry and higher C-reactive protein and eosinophil counts for continental ancestry. According to our findings, we propose a formation model of modern Japanese population; regional variations in admixture proportions of the Jomon people and continental East Asians formed genotypic and phenotypic gradations of current Japanese archipelago populations.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Communications Biology
993 papers in training set
Top 0.1%
14.9%
2
eLife
5828 papers in training set
Top 10%
9.6%
3
National Science Review
21 papers in training set
Top 0.1%
8.8%
4
Nature Communications
5641 papers in training set
Top 20%
8.8%
5
Scientific Reports
3612 papers in training set
Top 8%
7.8%
6
Journal of Genetics and Genomics
38 papers in training set
Top 0.1%
6.6%
50% of probability mass above
7
Science Bulletin
21 papers in training set
Top 0.1%
4.3%
8
Molecular Biology and Evolution
542 papers in training set
Top 2%
4.0%
9
Genomics, Proteomics & Bioinformatics
172 papers in training set
Top 0.6%
3.4%
10
Genome Research
468 papers in training set
Top 2%
3.2%
11
Science Advances
1243 papers in training set
Top 13%
2.7%
12
iScience
1154 papers in training set
Top 9%
2.6%
13
Genome Biology
637 papers in training set
Top 4%
2.4%
14
Proceedings of the National Academy of Sciences
2444 papers in training set
Top 24%
2.1%
15
Frontiers in Genetics
230 papers in training set
Top 3%
1.7%
16
Cell Genomics
172 papers in training set
Top 2%
1.5%
17
DNA Research
26 papers in training set
Top 0.2%
1.3%
18
Nature Ecology & Evolution
113 papers in training set
Top 1%
1.1%
19
Genomics, Proteomics & Bioinformatics
16 papers in training set
Top 0.2%
0.8%
20
Nucleic Acids Research
1281 papers in training set
Top 15%
0.6%
21
Nature Human Behaviour
95 papers in training set
Top 3%
0.6%
22
GigaScience
212 papers in training set
Top 5%
0.6%
23
BMC Ecology and Evolution
51 papers in training set
Top 2%
0.6%
24
Journal of Systematics and Evolution
11 papers in training set
Top 0.2%
0.6%
25
Cell Reports
1498 papers in training set
Top 30%
0.6%