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The ChinaMAP analytics of deep whole genome sequences in 10,588 individuals
by
Li, Lin
, Xu, Yu
, Tang, Xulei
, Cao, Yanan
, Yan, Li
, Xu, Min
, Sun, Xiaohui
, Lu, Jieli
, Hu, Ruying
, Bi, Yufang
, Wang, Weiqing
, Wang, Tiange
, Chen, Lulu
, Gao, Zhengnan
, Chen, Gang
, Ye, Zhen
, Du, Peina
, Feng, Zhimin
, Zhang, Yinfei
, Shi, Lixin
, Ning, Guang
in
45
/ 45/23
/ 45/43
/ 631/1647/2217/457
/ 631/1647/48
/ Alleles
/ Base Sequence
/ Biomedical and Life Sciences
/ Blood Glucose - metabolism
/ Body Mass Index
/ Cell Biology
/ China
/ Databases, Genetic
/ Drug metabolism
/ Frequency spectrum
/ Gene Frequency - genetics
/ Gene sequencing
/ Genetic Variation
/ Genetics
/ Genetics, Population
/ Genome, Human
/ Genomes
/ Genotype
/ Humans
/ Life Sciences
/ Metabolic disorders
/ Metabolism
/ Minority & ethnic groups
/ Multifactorial Inheritance - genetics
/ Nutrition
/ Pharmaceutical Preparations - metabolism
/ Population genetics
/ Population structure
/ Risk Factors
/ Whole Genome Sequencing
2020
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The ChinaMAP analytics of deep whole genome sequences in 10,588 individuals
by
Li, Lin
, Xu, Yu
, Tang, Xulei
, Cao, Yanan
, Yan, Li
, Xu, Min
, Sun, Xiaohui
, Lu, Jieli
, Hu, Ruying
, Bi, Yufang
, Wang, Weiqing
, Wang, Tiange
, Chen, Lulu
, Gao, Zhengnan
, Chen, Gang
, Ye, Zhen
, Du, Peina
, Feng, Zhimin
, Zhang, Yinfei
, Shi, Lixin
, Ning, Guang
in
45
/ 45/23
/ 45/43
/ 631/1647/2217/457
/ 631/1647/48
/ Alleles
/ Base Sequence
/ Biomedical and Life Sciences
/ Blood Glucose - metabolism
/ Body Mass Index
/ Cell Biology
/ China
/ Databases, Genetic
/ Drug metabolism
/ Frequency spectrum
/ Gene Frequency - genetics
/ Gene sequencing
/ Genetic Variation
/ Genetics
/ Genetics, Population
/ Genome, Human
/ Genomes
/ Genotype
/ Humans
/ Life Sciences
/ Metabolic disorders
/ Metabolism
/ Minority & ethnic groups
/ Multifactorial Inheritance - genetics
/ Nutrition
/ Pharmaceutical Preparations - metabolism
/ Population genetics
/ Population structure
/ Risk Factors
/ Whole Genome Sequencing
2020
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The ChinaMAP analytics of deep whole genome sequences in 10,588 individuals
by
Li, Lin
, Xu, Yu
, Tang, Xulei
, Cao, Yanan
, Yan, Li
, Xu, Min
, Sun, Xiaohui
, Lu, Jieli
, Hu, Ruying
, Bi, Yufang
, Wang, Weiqing
, Wang, Tiange
, Chen, Lulu
, Gao, Zhengnan
, Chen, Gang
, Ye, Zhen
, Du, Peina
, Feng, Zhimin
, Zhang, Yinfei
, Shi, Lixin
, Ning, Guang
in
45
/ 45/23
/ 45/43
/ 631/1647/2217/457
/ 631/1647/48
/ Alleles
/ Base Sequence
/ Biomedical and Life Sciences
/ Blood Glucose - metabolism
/ Body Mass Index
/ Cell Biology
/ China
/ Databases, Genetic
/ Drug metabolism
/ Frequency spectrum
/ Gene Frequency - genetics
/ Gene sequencing
/ Genetic Variation
/ Genetics
/ Genetics, Population
/ Genome, Human
/ Genomes
/ Genotype
/ Humans
/ Life Sciences
/ Metabolic disorders
/ Metabolism
/ Minority & ethnic groups
/ Multifactorial Inheritance - genetics
/ Nutrition
/ Pharmaceutical Preparations - metabolism
/ Population genetics
/ Population structure
/ Risk Factors
/ Whole Genome Sequencing
2020
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The ChinaMAP analytics of deep whole genome sequences in 10,588 individuals
Journal Article
The ChinaMAP analytics of deep whole genome sequences in 10,588 individuals
2020
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Overview
Metabolic diseases are the most common and rapidly growing health issues worldwide. The massive population-based human genetics is crucial for the precise prevention and intervention of metabolic disorders. The China Metabolic Analytics Project (ChinaMAP) is based on cohort studies across diverse regions and ethnic groups with metabolic phenotypic data in China. Here, we describe the centralized analysis of the deep whole genome sequencing data and the genetic bases of metabolic traits in 10,588 individuals from the ChinaMAP. The frequency spectrum of variants, population structure, pathogenic variants and novel genomic characteristics were analyzed. The individual genetic evaluations of Mendelian diseases, nutrition and drug metabolism, and traits of blood glucose and BMI were integrated. Our study establishes a large-scale and deep resource for the genetics of East Asians and provides opportunities for novel genetic discoveries of metabolic characteristics and disorders.
Publisher
Springer Singapore,Nature Publishing Group
Subject
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