Article

2 Unifying Life History Analyses for Inference of Fitness and Population Growth

Department of Ecology, Evolution, and Behavior, Minnesota Center for Community Genetics, University of Minnesota, St. Paul, Minnesota 55108, USA.
The American Naturalist (Impact Factor: 4.45). 08/2008; 172(1):E35-47. DOI: 10.1086/588063
Source: PubMed

ABSTRACT The lifetime fitnesses of individuals comprising a population determine its numerical dynamics, and genetic variation in fitness results in evolutionary change. This dual importance of individual fitness is well understood, but empirical fitness records generally violate the assumptions of standard statistical approaches. This problem has undermined comprehensive study of fitness and impeded empirical synthesis of the numerical and genetic dynamics of populations. Recently developed aster models remedy this problem by explicitly modeling the dependence of later-expressed components of fitness (e.g., fecundity) on those expressed earlier (e.g., survival to reproduce). Moreover, aster models employ different sampling distributions for different components of fitness (e.g., binomial for survival over a given interval and Poisson for fecundity). Analysis is done by maximum likelihood, and the resulting distributions for lifetime fitness closely approximate observed data. We illustrate the breadth of aster models' utility with three examples demonstrating estimation of the finite rate of increase, comparison of mean fitness among genotypic groups, and analysis of phenotypic selection. Aster models offer a unified approach to addressing the breadth of questions in evolution and ecology for which life-history data are gathered.

Download full-text

Full-text

Available from: Julie R Etterson, Aug 19, 2015
0 Followers
 · 
98 Views
  • Source
    • "For these traits, the genetic basis is too complex to be untangled using traditional molecular genetic approaches, although genome-wide association mapping is being used to identify individual genes that contribute to the variation. Given the inability to map phenotypic variation of complex traits to the individual molecular determinants, statistical approaches based on relatedness among individuals have been used to disentangle the relative contributions of genetics and environment to phenotypic variation (Fisher 1918; Falconer & Mackay 1996), and predicting expected evolutionary responses to selection (Lande & Arnold 1983; Shaw et al. 2008). The effectiveness of formal statistical approaches for predicting response to selection without explicitly identifying the molecular mechanisms is demonstrated by the advances achieved by plant and animal breeders in the past 100 years (Moose, Dudley & Rocheford 2004). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Heritability (h2) represents the potential for short-term response of a quantitative trait to selection. Unfortunately, estimating h2 through traditional crossing experiments is not practical for many species, and even for those in which mating can be manipulated, it may not be possible to assay them in ecologically relevant environments.We evaluated an approach, GCTA, that uses relatedness estimated from genomic data to estimate the proportion of phenotypic variance due to genotyped SNPs, which can be used to infer h2. Using phenotypic and genotypic data from eight replicates of experimentally grown plants of the annual legume Medicago truncatula, we examined how h2 estimates from GCTA (h2GCTA) related to traditional estimates of heritability (clonal repeatability for these inbred lines). Further, we examined how h2GCTA estimates were affected by SNP number, minor allele frequency, the number of individuals assayed and the exclusion of causative SNPs.We found that the average h2GCTA estimates for each trait made with the full data set (>5 million SNPs, 200 individuals) were strongly correlated (r = 0·99) with estimates of clonal repeatability. However, this result masks considerable variation among replicate estimates of h2GCTA, even in relatively uniform greenhouse conditions. h2GCTA estimates with 250 000 and 25 000 SNPs were very similar to those obtained with >5 million SNPs, but with 2500 SNPs, h2GCTA were lower and had higher variance than those with ≥25 k SNPs. h2GCTA estimates were slightly lower when only common SNPs were used. Excluding putatively causative SNPs had little effect on the estimates of h2GCTA, suggesting that genotyping putatively causative SNPs is not necessary to obtain accurate estimates of h2. The number of accessions sampled had the greatest effect on h2GCTA estimates, and variance greatly increased as fewer accessions were included. With only 50 accessions sampled, the range of h2GCTA ranged from 0 to 1 for all traits.These results indicate that the GCTA method may be useful for estimating h2 using data sets of a size that are available from reduced-representation genotyping but that hundreds of individuals may need to be sampled to obtain robust estimates of h2.
    Methods in Ecology and Evolution 12/2013; 4(12). DOI:10.1111/2041-210X.12129 · 5.32 Impact Factor
  • Source
    • "Since the introduction of standard methods for the estimation of selection on phenotypic traits in the wild (e.g. Lande & Arnold, 1983; Mitchell-Olds & Shaw, 1987; Schluter, 1988; Shaw et al., 2008; Morrissey & Sakrejda, 2013), many studies have explored the patterns of natural selection (reviewed in Hoekstra et al., 2001; Kingsolver et al., 2001, 2012; Hereford, Hansen & Houle, 2004; Siepielski, DiBattista & Carlson, 2009). In the context of speciation with gene flow (Smadja & Butlin, 2011), hybrid zones (sensu Harrison, 1990) represent ideal systems to study the fitness of recombinant genotypes in situ (Barton & Hewitt, 1985; Abbott et al., 2013). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Unravelling the form of selection acting on hybrids of ecotypes undergoing ecological speciation is essential to understand the mechanisms behind the evolution of reproductive isolation in the face of gene flow. Shell phenotype is known to be affected by natural selection and is involved in the fitness of the marine snail Littorina saxatilis. Here, we studied the association between shell traits and fitness in hybrids in order to determine the relative role of exogenous and endogenous selection in this hybrid zone of L. saxatilis. We show that directional selection is the predominant mode of selection among hybrids. We also show its heterogeneity, affecting different shell traits, within populations at the level of the microhabitat. Therefore, endogenous selection mechanisms are most probably lacking in this hybrid zone and exogenous barriers (pre- and post-zygotic) are possibly one of the main forces behind the evolution of barriers to gene flow between these ecologically divergent ecotypes. This study shows how this barrier might represent an important type of reproductive isolation within ecological speciation, and this should be taken into account in future studies of speciation in hybrid zones. © 2013 The Linnean Society of London, Biological Journal of the Linnean Society, 2013, ●●, ●●–●●.
    Biological Journal of the Linnean Society 12/2013; 111(2). DOI:10.1111/bij.12197 · 2.54 Impact Factor
  • Source
    • "Thus, here we analyze only the pod number data, which does have straightforward aster analysis and serves as a better example, even though this makes our reanalysis not really comparable with the analysis in Etterson (2004b) which does use the seed counts. To aid design of future experiments, Shaw et al. (2008), page E43, explain two alternative experimental designs that permit straightforward aster analysis (including random effects aster models). Stanton-Geddes, Shaw and Tiffin (2012) used one of these designs. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Random effects are implemented for aster models using two approximations taken from Breslow and Clayton [J. Amer. Statist. Assoc. 88 (1993) 9–25]. Random effects are analytically integrated out of the Laplace approximation to the complete data log likelihood, giving a closed-form expression for an approximate missing data log likelihood. Third and higher derivatives of the complete data log likelihood with respect to the random effects are ignored, giving a closed-form expression for second derivatives of the approximate missing data log likelihood, hence approximate observed Fisher information. This method is applicable to any exponential family random effects model. It is implemented in the CRAN package aster (R Core Team [R: A Language and Environment for Statistical Computing (2012) R Foundation for Statistical Computing], Geyer [R package aster (2012) http://cran.r-project.org/package=aster]). Applications are analyses of local adaptation in the invasive California wild radish (Raphanus sativus) and the slender wild oat (Avena barbata) and of additive genetic variance for fitness in the partridge pea (Chamaecrista fasciculata).
    The Annals of Applied Statistics 09/2013; 7(3). DOI:10.1214/13-AOAS653 · 1.69 Impact Factor
Show more