Literature DB >> 31045279

Correlations between relatives: From Mendelian theory to complete genome sequence.

Elizabeth A Thompson1.   

Abstract

It is 100 years since R. A. Fisher proposed that a Mendelian model of genetic variant effects, additive over loci, could explain the patterns of observed phenotypic correlations between relatives. His loci were hypothetical and his model theoretical. It is only about 50 years since the first genetic markers allowed the detection of even variants with major effects on phenotype, and only 20 years since the development of single-nucleotide polymorphism technology provided dense markers over the genome. Then both mappings in defined pedigrees and population-based genome-wide association studies samples allowed the detection of multiple contributing variants of smaller effect. Finally, with methods based on genotypic correlations between individuals, or on allelic associations between loci, the additive heritability contributions of the genome can be estimated from large population samples. In this review we trace, from 1918 to 2018, the analysis of observed phenotypic correlations between relatives to estimate underlying genetic components of traits in human populations. As with studies from 1918 onward, we use height as the example trait where not only data are readily available, but where Fisher's model of large numbers of variants of infinitesimal effect appears to provide a good approximation to reality. However, we also trace the use of phenotypic and genotypic correlations between relatives in mapping causal variants and resolving genetic contributions to more complex human traits. With the availability of DNA sequence data, we can hope to not only estimate the total genetic contribution to a trait, but to resolve effects of individual genetic variants on biological function.
© 2019 Wiley Periodicals, Inc.

Entities:  

Keywords:  additive models; assortative mating; genotypic correlation matrix; heritability; identity by function; population structure; realized descent

Mesh:

Substances:

Year:  2019        PMID: 31045279      PMCID: PMC6559867          DOI: 10.1002/gepi.22206

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  45 in total

1.  Merlin--rapid analysis of dense genetic maps using sparse gene flow trees.

Authors:  Gonçalo R Abecasis; Stacey S Cherny; William O Cookson; Lon R Cardon
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2.  Inferring coancestry in population samples in the presence of linkage disequilibrium.

Authors:  M D Brown; C G Glazner; C Zheng; E A Thompson
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3.  Limitations of GCTA as a solution to the missing heritability problem.

Authors:  Siddharth Krishna Kumar; Marcus W Feldman; David H Rehkopf; Shripad Tuljapurkar
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4.  Model-free Estimation of Recent Genetic Relatedness.

Authors:  Matthew P Conomos; Alexander P Reiner; Bruce S Weir; Timothy A Thornton
Journal:  Am J Hum Genet       Date:  2016-01-07       Impact factor: 11.025

5.  Extensions to pedigree analysis. III. Variance components by the scoring method.

Authors:  K Lange; J Westlake; M A Spence
Journal:  Ann Hum Genet       Date:  1976-05       Impact factor: 1.670

6.  Efficient Estimation of Realized Kinship from Single Nucleotide Polymorphism Genotypes.

Authors:  Bowen Wang; Serge Sverdlov; Elizabeth Thompson
Journal:  Genetics       Date:  2017-01-18       Impact factor: 4.562

7.  Linear mixed model for heritability estimation that explicitly addresses environmental variation.

Authors:  David Heckerman; Deepti Gurdasani; Carl Kadie; Cristina Pomilla; Tommy Carstensen; Hilary Martin; Kenneth Ekoru; Rebecca N Nsubuga; Gerald Ssenyomo; Anatoli Kamali; Pontiano Kaleebu; Christian Widmer; Manjinder S Sandhu
Journal:  Proc Natl Acad Sci U S A       Date:  2016-07-05       Impact factor: 11.205

Review 8.  Relatedness in the post-genomic era: is it still useful?

Authors:  Doug Speed; David J Balding
Journal:  Nat Rev Genet       Date:  2014-11-18       Impact factor: 53.242

9.  The secular trend in human physical growth: a biological view.

Authors:  T J Cole
Journal:  Econ Hum Biol       Date:  2003-06       Impact factor: 2.184

10.  Partitioning heritability by functional annotation using genome-wide association summary statistics.

Authors:  Hilary K Finucane; Brendan Bulik-Sullivan; Alexander Gusev; Gosia Trynka; Yakir Reshef; Po-Ru Loh; Verneri Anttila; Han Xu; Chongzhi Zang; Kyle Farh; Stephan Ripke; Felix R Day; Shaun Purcell; Eli Stahl; Sara Lindstrom; John R B Perry; Yukinori Okada; Soumya Raychaudhuri; Mark J Daly; Nick Patterson; Benjamin M Neale; Alkes L Price
Journal:  Nat Genet       Date:  2015-09-28       Impact factor: 38.330

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