Estimating realized heritability in panmictic populations

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24510%2F18%3A00006227" target="_blank" >RIV/46747885:24510/18:00006227 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/60460709:41320/18:78634

Výsledek na webu

<a href="https://syndication.highwire.org/content/doi/10.1534/genetics.117.300508" target="_blank" >https://syndication.highwire.org/content/doi/10.1534/genetics.117.300508</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1534/genetics.117.300508" target="_blank" >10.1534/genetics.117.300508</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Estimating realized heritability in panmictic populations

Popis výsledku v původním jazyce

Narrow sense heritability (h2) is a key concept in quantitative genetics, as it expresses the proportion of the observed phenotypic variation that is transmissible from parents to offspring. h2 determines the resemblance among relatives, and the rate of response to artificial and natural selection. Classical methods for estimating h2 use random samples of individuals with known relatedness, as well as response to artificial selection, when it is called realized heritability. Here, we present a method for estimating realized h2 based on a simple assessment of a random-mating population with no artificial manipulation of the population structure, and derive SE of the estimates. This method can be applied to arbitrary phenotypic segments of the population (for example, the topranking p parents and offspring), rather than random samples. It can thus be applied to nonpedigreed random mating populations, where relatedness is determined from molecular markers in the p selected parents and offspring, thus substantially saving on genotyping costs. Further, we assessed the method by stochastic simulations, and, as expected from the mathematical derivation, it provides unbiased estimates of h2: We compared our approach to the regression and maximum-likelihood approaches utilizing Galton’s dataset on human heights, and all three methods provided identical results.

Název v anglickém jazyce

Estimating realized heritability in panmictic populations

Popis výsledku anglicky

Narrow sense heritability (h2) is a key concept in quantitative genetics, as it expresses the proportion of the observed phenotypic variation that is transmissible from parents to offspring. h2 determines the resemblance among relatives, and the rate of response to artificial and natural selection. Classical methods for estimating h2 use random samples of individuals with known relatedness, as well as response to artificial selection, when it is called realized heritability. Here, we present a method for estimating realized h2 based on a simple assessment of a random-mating population with no artificial manipulation of the population structure, and derive SE of the estimates. This method can be applied to arbitrary phenotypic segments of the population (for example, the topranking p parents and offspring), rather than random samples. It can thus be applied to nonpedigreed random mating populations, where relatedness is determined from molecular markers in the p selected parents and offspring, thus substantially saving on genotyping costs. Further, we assessed the method by stochastic simulations, and, as expected from the mathematical derivation, it provides unbiased estimates of h2: We compared our approach to the regression and maximum-likelihood approaches utilizing Galton’s dataset on human heights, and all three methods provided identical results.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10602 - Biology (theoretical, mathematical, thermal, cryobiology, biological rhythm), Evolutionary biology

Projekt

<a href="/cs/project/GA15-00243S" target="_blank" >GA15-00243S: Robustní inference na náhodných procesech a funkcionálních datech s aplikacemi především v ekonometrii a financích</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

GENETICS

ISSN

0016-6731

e-ISSN

—

Svazek periodika

208

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

7

Strana od-do

89-95

Kód UT WoS článku

000419356300006

EID výsledku v databázi Scopus

2-s2.0-85040128495