Journal
ANNUAL REVIEW OF GENETICS, VOL 47
Volume 47, Issue -, Pages 75-+Publisher
ANNUAL REVIEWS
DOI: 10.1146/annurev-genet-111212-133258
Keywords
quantitative traits; whole-genome methods; additive genetic variance; genomic relationship; mixed linear model; genetic architecture
Categories
Funding
- DIVISION OF EPIDEMIOLOGY AND CLINICAL APPLICATIONS [N01HC025195] Funding Source: NIH RePORTER
- NATIONAL CENTER FOR RESEARCH RESOURCES [UL1RR025005] Funding Source: NIH RePORTER
- NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [R01HL087641, R01HL059367, R01HL086694, R01HL064278] Funding Source: NIH RePORTER
- NATIONAL HUMAN GENOME RESEARCH INSTITUTE [U01HG004402] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [P01GM099568, R01GM075091] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF MENTAL HEALTH [R01MH100141] Funding Source: NIH RePORTER
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Understanding genetic variation of complex traits in human populations has moved from the quantification of the resemblance between close relatives to the dissection of genetic variation into the contributions of individual genomic loci. However, major questions remain unanswered: How much phenotypic variation is genetic; how much of the genetic variation is additive and can be explained by fitting all genetic variants simultaneously in one model, and what is the joint distribution of effect size and allele frequency at causal variants? We review and compare three whole-genome analysis methods that use mixed linear models (MLMs) to estimate genetic variation. In all methods, genetic variation is estimated from the relationship between close or distant relatives on the basis of pedigree information and/or single nucleotide polymorphisms (SNPs). We discuss theory, estimation procedures, bias, and precision of each method and review recent advances in the dissection of genetic variation of complex traits in human populations. By using genome-wide data, it is now established that SNPs in total account for far more of the genetic variation than the statistically highly significant SNPs that have been detected in genome-wide association studies. All SNPs together, however, do not account for all of the genetic variance estimated by pedigree-based methods. We explain possible reasons for this remaining missing heritability.
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