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Genome biogeography reveals the intraspecific spread of adaptive mutations for a complex trait.

ABSTRACT: Physiological novelties are often studied at macro-evolutionary scales such that their micro-evolutionary origins remain poorly understood. Here, we test the hypothesis that key components of a complex trait can evolve in isolation and later be combined by gene flow. We use C4 photosynthesis as a study system, a derived physiology that increases plant productivity in warm, dry conditions. The grass Alloteropsis semialata includes C4 and non-C4 genotypes, with some populations using laterally acquired C4 -adaptive loci, providing an outstanding system to track the spread of novel adaptive mutations. Using genome data from C4 and non-C4 A. semialata individuals spanning the species' range, we infer and date past migrations of different parts of the genome. Our results show that photosynthetic types initially diverged in isolated populations, where key C4 components were acquired. However, rare but recurrent subsequent gene flow allowed the spread of adaptive loci across genetic pools. Indeed, laterally acquired genes for key C4 functions were rapidly passed between populations with otherwise distinct genomic backgrounds. Thus, our intraspecific study of C4 -related genomic variation indicates that components of adaptive traits can evolve separately and later be combined through secondary gene flow, leading to the assembly and optimization of evolutionary innovations.

SUBMITTER: Olofsson JK

PROVIDER: S-EPMC6849575 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Genome biogeography reveals the intraspecific spread of adaptive mutations for a complex trait.

Olofsson Jill K JK Bianconi Matheus M Besnard Guillaume G Dunning Luke T LT Lundgren Marjorie R MR Holota Helene H Vorontsova Maria S MS Hidalgo Oriane O Leitch Ilia J IJ Nosil Patrik P Osborne Colin P CP Christin Pascal-Antoine PA

Molecular ecology 20161130 24

Physiological novelties are often studied at macro-evolutionary scales such that their micro-evolutionary origins remain poorly understood. Here, we test the hypothesis that key components of a complex trait can evolve in isolation and later be combined by gene flow. We use C4 photosynthesis as a study system, a derived physiology that increases plant productivity in warm, dry conditions. The grass Alloteropsis semialata includes C4 and non-C4 genotypes, with som ...[more]

PMID: 27862505

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Project description:Intraspecific trait variation (ITV) is common feature of natural communities and has gained increasing attention due to its significant ecological effects on community dynamics and ecosystem functioning. However, the estimation of ITV per se has yet to receive much attention, despite the need for accurate ITV estimation for trait-based ecological inferences. It remains unclear if, and to what extent, current estimations of ITV are biased. The most common method used to quantify ITV is the coefficient of variation (CV), which is dimensionless and can therefore be compared across traits, species, and studies. Here, we asked which CV estimator and data normalization method are optimal for quantifying ITV, and further identified the minimum sample size required for ±5% accuracy assuming a completely random sample scheme. To these ends, we compared the performance of four existing CV estimators, together with new simple composite estimators, across different data normalizations, and sample sizes using both a simulated and empirical trait datasets from local to regional scales. Our results consistently showed that the most commonly used ITV estimator (CV 1= σsample /μsample ), often underestimated ITV-in some cases by nearly 50%-and that underestimation varies largely among traits and species. The extent of this bias depends on the sample size, skewness and kurtosis of the trait value distribution. The bias in ITV can be substantially reduced by using log-transforming trait data and alternative CV estimators that take into consideration the above dependencies. We find that the CV4 estimator, also known as Bao's CV estimator, combined with log data normalization, exhibits the lowest bias and can reach ±5% accuracy with sample sizes greater than 20 for almost all examined traits and species. These results demonstrated that many previous ITV measurements may be substantially underestimated and, further, that these underestimations are not equal among species and traits even using the same sample size. These problems can be largely solved by log-transforming trait data first and then using the Bao's CV to quantify ITV. Together, our findings facilitate a more accurate understanding of ITV in community structures and dynamics, and may also benefit studies in other research areas that depend on accurate estimation of CV.

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Genome biogeography reveals the intraspecific spread of adaptive mutations for a complex trait.

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Genome biogeography reveals the intraspecific spread of adaptive mutations for a complex trait.

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