A novel method for estimating heritability using molecular markers

Mousseau, Timothy A.; Ritland, Kermit; Heath, Daniel D.

doi:10.1038/sj.hdy.6882690

Cited by 36 publications

(64 citation statements)

References 15 publications

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“…Despite its great intuitive appeal, an unexpectedly reduced number of cases applying this method have been published either on plant or animal populations. Most representative examples are in Oncorhynchus tshawytscha (Mousseau et al 1998), Ovis aries (Thomas et al 2002), and Oncorhynchus mykiss (Wilson et al 2003). Klaper et al (2001), estimating the heritability of phenolic compounds in a population of Quercus laevis, showed that the method failed to estimate heritability because of the low and rather uniform coancestry among individuals.…”

Section: Introductionmentioning

confidence: 97%

“…Alternatively, if prior information is available on population structure, likelihood-based procedures may be implemented, in which pairs are placed into a predetermined population structure according to the probability of observing their genotype and phenotype (Mousseau et al 1998;Thomas et al , 2002. A third approach involves an explicit reconstruction of groups of a certain coancestry, which can then be used as pedigree information in a standard quantitative genetic analysis.…”

Section: Introductionmentioning

confidence: 99%

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The accuracy of a heritability estimator using molecular information

Rodríguez‐Ramilo

Toro²,

Caballero³

et al. 2007

Conserv Genet

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The heritability of a quantitative trait is a key parameter to quantify the genetic variation present in a population. Although estimates of heritability require accurate information on the genetic relationship among individuals, pedigree data is generally lacking in natural populations. Nowadays, the increasing availability of DNA markers is making possible the estimation of coancestries from neutral molecular information. In 1996, K. Ritland developed an approach to estimate heritability from the regression of the phenotypic similarity on the marker-based coancestry. We carried out simulations to analyze the accuracy of the estimates of heritability obtained by this method using information from a variable number of neutral codominant markers. Because the main application of the estimator is on populations with no family structure, such as natural populations, its accuracy was tested under this scenario. However, the method was also investigated under other scenarios, in order to test the influence of different factors (family structure, assortative mating and phenotypic selection) on the precision. Our results suggest that the main factor causing a directional bias in the estimated heritability is the presence of phenotypic selection, and that very noisy estimates are obtained in the absence of a familiar structure and for small population sizes. The estimated heritabilities from marker-based coancestries showed lower accuracy than the estimated heritabilities from genealogical coancestries. However, a large amount of bias occurred even in the most favourable situation where genealogical coancestries are known. The results also indicate that the molecular markers are more suitable to infer coancestry than inbreeding.

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Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

The accuracy of a heritability estimator using molecular information

Rodríguez‐Ramilo

Toro²,

Caballero³

et al. 2007

Conserv Genet

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show abstract

“…Pemberton 2008;Kruuk et al 2008). A range of similar approaches are currently available for pedigree construction (see Mousseau et al 1998;Ritland 2000;Wang 2004;Thomas 2005) and the consequences of imprecision on the subject under study can be to some extent anticipated (Pemberton 2008).…”

Section: Discussionmentioning

confidence: 97%

Applying QTL analysis to conservation genetics

2010

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Both analytical and molecular tools currently exist that can be used to prolifically apply quantitative trait loci (QTL) analysis to the study of natural populations. In this communication, we review and exemplify the use of QTL mapping tools and genetic modeling for conservation geneticists. We simulate populations inspired by relevant cases that can be encountered in the field and analyze them using the recently developed flexible intercross analysis (FIA) method. We then reanalyze these results with the also recently developed natural and orthogonal interactions (NOIA) model of genetic effects. Next, we further exemplify the potential of genetic modeling for the interpretation of the output of QTL analyses by reviewing studies on hybrids between wild individuals and their domesticated relatives. Based on the results here presented we emphasize several points that are pertinent in conservation genetics including (i) the advantages of FIA as a powerful tool to be applied to line crosses in which the parental lines are not inbred, (ii) the importance of obtaining estimates of genetic effects that are adequate to address the research issue under consideration, (iii) the versatility of genetic modeling, particularly NOIA, to dissect complex genetic architectures and (iv) the possibility of using currently available methods to address non-equilibrium multiallelic systems.

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“…Currently, analysis of relatedness has been used to estimate genetic components of variance of phenotypic trait in outbred populations (e.g. Mousseau et al, 1998), and thus can potentially be used in conservation to quantify the amount of phenotypically important genetic variation in endangered populations (Storfer, 1996;Carvajal-Rodríguez et al, 2005;Thomas, 2005). Furthermore information about the kin structure of populations can help inform conservation decisions (Regnaut et al, 2006).…”

Section: Relatedness and Pedigree Estimationmentioning

confidence: 99%

“…Point estimates can then be obtained by maximising the likelihood (Milligan, 2003). One use of the likelihood approach has been to estimate heritability in outbred populations (Mousseau et al 1998). For each pair of individuals the likelihood of the joint genotypes and phenotypes can be calculated as a function of the degree of relationship and parameters in a quantitative genetic model, which can then be inferred.…”

Section: Relatedness and Pedigree Estimationmentioning

confidence: 99%

Conservation Genetics

Beaumont¹

2007

Handbook of Statistical Genetics

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This chapter reviews some of the statistical methodologies used in the genetic analysis of endangered and managed populations. The topics covered include the estimation of effective population size, N e , the detection of past changes in population size, the estimation of admixture proportions, and the analysis of local population structure, kinship, and relatedness through genotypic methods. The reasons why it may be useful to measure N e are discussed. Using genetic information it is possible to estimate N e from changes in gene frequencies between samples taken at different times, or from genotypic disequilibria in one sample, or from differences in gene frequencies between two recently descended populations. The different statistical methodologies that have been applied are discussed in some detail. The ability to detect past changes in population size may also be useful in conservation management, and some of the more recent approaches are described. Another area of concern in conservation biology is introgressive hybridisation. At the population level it is possible to infer admixture proportions by comparing the gene frequencies in the admixed and non-admixed populations, providing they are available, and the different statistical approaches to analysing this problem are reviewed. Statistical methods have also been developed to detect immigrant and hybrid individuals from their multi-locus genotype, and the main methods developed in this area are also discussed.

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A novel method for estimating heritability using molecular markers

Cited by 36 publications

References 15 publications

The accuracy of a heritability estimator using molecular information

The accuracy of a heritability estimator using molecular information

Applying QTL analysis to conservation genetics

Conservation Genetics

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