Characterizing rare and low-frequency height-associated variants in the Japanese population

Human height is a representative phenotype to elucidate genetic architecture. However, the majority of large studies have been performed in European population. To investigate the rare and low-frequency variants associated with height, we construct a reference panel (N = 3,541) for genotype imputation by integrating the whole-genome sequence data from 1,037 Japanese with that of the 1000 Genomes Project, and perform a genome-wide association study in 191,787 Japanese. We report 573 height-associated variants, including 22 rare and 42 low-frequency variants. These 64 variants explain 1.7% of the phenotypic variance. Furthermore, a gene-based analysis identifies two genes with multiple height-increasing rare and low-frequency nonsynonymous variants (SLC27A3 and CYP26B1; PSKAT-O < 2.5 × 10−6). Our analysis shows a general tendency of the effect sizes of rare variants towards increasing height, which is contrary to findings among Europeans, suggesting that height-associated rare variants are under different selection pressure in Japanese and European populations. Thousands of genetic loci are known to associate with human height, but these are mainly based on studies in European ancestry populations. Here, Akiyama et al. construct a genotype reference panel for the Japanese population followed by GWAS and report 573 height associated variants in 191,787 Japanese.

[1]  The International HapMap Consortium A haplotype map of the human genome , 2005 .

[2]  M. Olivier A haplotype map of the human genome , 2003, Nature.

[3]  M. Olivier A haplotype map of the human genome. , 2003, Nature.

[4]  Delbert Dueck,et al.  Clustering by Passing Messages Between Data Points , 2007, Science.

[5]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[6]  P. Donnelly,et al.  A Flexible and Accurate Genotype Imputation Method for the Next Generation of Genome-Wide Association Studies , 2009, PLoS genetics.

[7]  H. Hakonarson,et al.  ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data , 2010, Nucleic acids research.

[8]  G. Abecasis,et al.  MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes , 2010, Genetic epidemiology.

[9]  S. Robertson,et al.  Craniosynostosis and multiple skeletal anomalies in humans and zebrafish result from a defect in the localized degradation of retinoic acid. , 2011, American journal of human genetics.

[10]  P. Visscher,et al.  GCTA: a tool for genome-wide complex trait analysis. , 2011, American journal of human genetics.

[11]  P. Visscher,et al.  Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits , 2012, Nature Genetics.

[12]  M. Rieder,et al.  Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies. , 2012, American journal of human genetics.

[13]  P. Visscher,et al.  Five years of GWAS discovery. , 2012, American journal of human genetics.

[14]  Cameron D. Palmer,et al.  Evidence of widespread selection on standing variation in Europe at height-associated SNPs , 2012, Nature Genetics.

[15]  O. Delaneau,et al.  A linear complexity phasing method for thousands of genomes , 2011, Nature Methods.

[16]  Ross M. Fraser,et al.  Defining the role of common variation in the genomic and biological architecture of adult human height , 2014, Nature Genetics.

[17]  J. Hirschhorn,et al.  Biological interpretation of genome-wide association studies using predicted gene functions , 2015, Nature Communications.

[18]  Gabor T. Marth,et al.  A global reference for human genetic variation , 2015, Nature.

[19]  P. Visscher,et al.  Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index , 2015, Nature Genetics.

[20]  M. P. Concas,et al.  Height-reducing variants and selection for short stature in Sardinia , 2015, Nature Genetics.

[21]  Tom R. Gaunt,et al.  Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel , 2015, Nature Communications.

[22]  B. Berger,et al.  Efficient Bayesian mixed model analysis increases association power in large cohorts , 2014, Nature Genetics.

[23]  M. Daly,et al.  LD Score regression distinguishes confounding from polygenicity in genome-wide association studies , 2014, Nature Genetics.

[24]  Todd A. Johnson,et al.  Meta-analysis of genome-wide association studies of adult height in East Asians identifies 17 novel loci. , 2015, Human molecular genetics.

[25]  Robert D. Finn,et al.  The Pfam protein families database: towards a more sustainable future , 2015, Nucleic Acids Res..

[26]  D. Gudbjartsson,et al.  Epigenetic and genetic components of height regulation , 2016, Nature Communications.

[27]  Daniel Marbach,et al.  Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics , 2016, PLoS Comput. Biol..

[28]  Po-Ru Loh,et al.  Fast and accurate long-range phasing in a UK Biobank cohort , 2015, Nature Genetics.

[29]  Y. Kamatani,et al.  Overview of the BioBank Japan Project: Study design and profile , 2017, Journal of epidemiology.

[30]  Marcelo P. Segura-Lepe,et al.  Rare and low-frequency coding variants alter human adult height , 2016, Nature.

[31]  M. Kanai,et al.  Genome-wide association study identifies 112 new loci for body mass index in the Japanese population , 2017, Nature Genetics.

[32]  Jie Huang,et al.  Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits , 2017, American journal of human genetics.

[33]  Y. Kamatani,et al.  Cross-sectional analysis of BioBank Japan clinical data: A large cohort of 200,000 patients with 47 common diseases , 2017, Journal of epidemiology.

[34]  Chuandong Wang,et al.  Cyclic compressive stress-induced scinderin regulates progress of developmental dysplasia of the hip. , 2017, Biochemical and biophysical research communications.

[35]  P. Visscher,et al.  Meta-analysis of genome-wide association studies for height and body mass index in ∼700,000 individuals of European ancestry , 2018, bioRxiv.

[36]  M. Kanai,et al.  Genetic analysis of quantitative traits in the Japanese population links cell types to complex human diseases , 2018, Nature Genetics.

[37]  Kazuhiko Yamamoto,et al.  Deep whole-genome sequencing reveals recent selection signatures linked to evolution and disease risk of Japanese , 2018, Nature Communications.