Evolutionary Quantitative Genetics: How Little Do We Know

Barton, Narelle

doi:10.1146/annurev.genet.23.1.337

Cited by 94 publications

(87 citation statements)

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“…The rate of phenotypic evolution will therefore depend upon the amount of additive genetic variance for a given trait,(9) and the response to selection will also be influenced by factors such as the number of loci underlying the phenotype and whether the fitness of each genotype is linearly related to the trait value. (10,11) The implications are that within species “evolvability” will be facilitated or constrained by the specific patterns of genetic variation, genetic architecture, and developmental constraints operating in any given lineage. (12,13)…”

Section: Introductionmentioning

confidence: 99%

RNA editing: a driving force for adaptive evolution?

2009

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Genetic variability is considered a key to the evolvability of species. The conversion of an adenosine (A) to inosine (I) in primary RNA transcripts can result in an amino acid change in the encoded protein, a change in secondary structure of the RNA, creation or destruction of a splice consensus site, or otherwise alter RNA fate. Substantial transcriptome and proteome variability is generated by A-to-I RNA editing through site-selective post-transcriptional recoding of single nucleotides. We posit that this epigenetic source of phenotypic variation is an unrecognized mechanism of adaptive evolution. The genetic variation introduced through editing occurs at low evolutionary cost since predominant production of the wild-type protein is retained. This property even allows exploration of sequence space that is inaccessible through mutation, leading to increased phenotypic plasticity and provides an evolutionary advantage for acclimatization as well as long-term adaptation. Furthermore, continuous probing for novel RNA editing sites throughout the transcriptome is an intrinsic property of the editing machinery and represents the molecular basis for increased adaptability. We propose that higher organisms have therefore evolved to systems with increasing RNA editing activity and, as a result, to more complex systems.

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Section: Introductionmentioning

confidence: 99%

RNA editing: a driving force for adaptive evolution?

2009

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“…survival and fecundity) tends to be lower than that of morphological and behavioral traits, which generally are less closely associated with fitness [16,22-24]. However, the narrow sense heritability ( h 2 ) of a trait represents the ratio of additive genetic variance ( V A ) to the total phenotypic variance ( V P ) and the heritability of traits largely affected by non-additive effects or environmental factors will thus by definition be low [25-28]. Heritability estimates may therefore often be inappropriate for quantifying the long-term evolutionary potential of a trait (see discussion in [21]) and they are entirely inadequate for detecting epistatic interactions.…”

Section: Introductionmentioning

confidence: 99%

The genetic architecture of fitness in a seed beetle: assessing the potential for indirect genetic benefits of female choice

et al. 2008

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BackgroundQuantifying the amount of standing genetic variation in fitness represents an empirical challenge. Unfortunately, the shortage of detailed studies of the genetic architecture of fitness has hampered progress in several domains of evolutionary biology. One such area is the study of sexual selection. In particular, the evolution of adaptive female choice by indirect genetic benefits relies on the presence of genetic variation for fitness. Female choice by genetic benefits fall broadly into good genes (additive) models and compatibility (non-additive) models where the strength of selection is dictated by the genetic architecture of fitness. To characterize the genetic architecture of fitness, we employed a quantitative genetic design (the diallel cross) in a population of the seed beetle Callosobruchus maculatus, which is known to exhibit post-copulatory female choice. From reciprocal crosses of inbred lines, we assayed egg production, egg-to-adult survival, and lifetime offspring production of the outbred F1 daughters (F1 productivity).ResultsWe used the bio model to estimate six components of genetic and environmental variance in fitness. We found sizeable additive and non-additive genetic variance in F1 productivity, but lower genetic variance in egg-to-adult survival, which was strongly influenced by maternal and paternal effects.ConclusionOur results show that, in order to gain a relevant understanding of the genetic architecture of fitness, measures of offspring fitness should be inclusive and should include quantifications of offspring reproductive success. We note that our estimate of additive genetic variance in F1 productivity (CVA = 14%) is sufficient to generate indirect selection on female choice. However, our results also show that the major determinant of offspring fitness is the genetic interaction between parental genomes, as indicated by large amounts of non-additive genetic variance (dominance and/or epistasis) for F1 productivity. We discuss the processes that may maintain additive and non-additive genetic variance for fitness and how these relate to indirect selection for female choice.

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“…Any observation of lineage-specific cis -acting regulatory variation from our approach is of immediate evolutionary interest: a species-specific excess of variants at unlinked loci of common function would be unlikely under neutrality, and would represent a potential signature of positive selection if fixed across individuals of the species. In the study of trans -acting regulatory variation, a priori a case of apparent accelerated evolution of a pathway could be driven by a single mutation of large effect maintained by drift in a species, as in any phenomenological analysis of trait evolution [13], [34]. Our results indicate that for correlated gene groups, the latter issue can be largely resolved by a simple transformation in which expression of each gene is normalized against the mean of all genes in the pathway.…”

Section: Discussionmentioning

confidence: 84%

Inferring Evolutionary Histories of Pathway Regulation from Transcriptional Profiling Data

et al. 2013

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One of the outstanding challenges in comparative genomics is to interpret the evolutionary importance of regulatory variation between species. Rigorous molecular evolution-based methods to infer evidence for natural selection from expression data are at a premium in the field, and to date, phylogenetic approaches have not been well-suited to address the question in the small sets of taxa profiled in standard surveys of gene expression. We have developed a strategy to infer evolutionary histories from expression profiles by analyzing suites of genes of common function. In a manner conceptually similar to molecular evolution models in which the evolutionary rates of DNA sequence at multiple loci follow a gamma distribution, we modeled expression of the genes of an a priori-defined pathway with rates drawn from an inverse gamma distribution. We then developed a fitting strategy to infer the parameters of this distribution from expression measurements, and to identify gene groups whose expression patterns were consistent with evolutionary constraint or rapid evolution in particular species. Simulations confirmed the power and accuracy of our inference method. As an experimental testbed for our approach, we generated and analyzed transcriptional profiles of four Saccharomyces yeasts. The results revealed pathways with signatures of constrained and accelerated regulatory evolution in individual yeasts and across the phylogeny, highlighting the prevalence of pathway-level expression change during the divergence of yeast species. We anticipate that our pathway-based phylogenetic approach will be of broad utility in the search to understand the evolutionary relevance of regulatory change.

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Evolutionary Quantitative Genetics: How Little Do We Know

Cited by 94 publications

References 0 publications

RNA editing: a driving force for adaptive evolution?

RNA editing: a driving force for adaptive evolution?

The genetic architecture of fitness in a seed beetle: assessing the potential for indirect genetic benefits of female choice

Inferring Evolutionary Histories of Pathway Regulation from Transcriptional Profiling Data

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