RidgeRace: ridge regression for continuous ancestral character estimation on phylogenetic trees

Kratsch, Christina; McHardy, Alice C.

doi:10.1093/bioinformatics/btu477

Cited by 30 publications

(36 citation statements)

References 40 publications

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“…(C) Equivalent analyses were performed for eight additional environmental factors on a smaller amoA tree of 181 sequences. (D) Ancestral pH preferences are shown for the 370-sequence amoA tree based on a ridge regression approach (28), with estimates of ancestral pH provided at key nodes.…”

Section: Discussionmentioning

confidence: 99%

“…To further explore the hypothesis of a link between pH adaptation and diversification, we reconstructed ancestral soil pH adaptation across the 370-sequence amoA tree with the use of a recently developed method that models phenotypic evolution for every branch in a tree by using ridge regression, an extension of ordinary least-squares regression that accounts for phylogenetic structure (28). This analysis suggests that the thaumarchaeotal common ancestor was adapted to a pH of approximately 6.5 and that there were early shifts toward lower and higher pH preferences in the respective ancestors of the Nitrosotalea/ Nitrosopumilus and Nitrososphaera lineages (Fig.…”

Section: Changes In Ph Specialization At the Base Of The Thaumarchaeotalmentioning

confidence: 99%

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Coupling of diversification and pH adaptation during the evolution of terrestrial Thaumarchaeota

Gubry‐Rangin

Kratsch

Williams

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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105

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The Thaumarchaeota is an abundant and ubiquitous phylum of archaea that plays a major role in the global nitrogen cycle. Previous analyses of the ammonia monooxygenase gene amoA suggest that pH is an important driver of niche specialization in these organisms. Although the ecological distribution and ecophysiology of extant Thaumarchaeota have been studied extensively, the evolutionary rise of these prokaryotes to ecological dominance in many habitats remains poorly understood. To characterize processes leading to their diversification, we investigated coevolutionary relationships between amoA, a conserved marker gene for Thaumarchaeota, and soil characteristics, by using deep sequencing and comprehensive environmental data in Bayesian comparative phylogenetics. These analyses reveal a large and rapid increase in diversification rates during early thaumarchaeotal evolution; this finding was verified by independent analyses of 16S rRNA. Our findings suggest that the entire Thaumarchaeota diversification regime was strikingly coupled to pH adaptation but less clearly correlated with several other tested environmental factors. Interestingly, the early radiation event coincided with a period of pH adaptation that enabled the terrestrial Thaumarchaeota ancestor to initially move from neutral to more acidic and alkaline conditions. In contrast to classic evolutionary models, whereby niches become rapidly filled after adaptive radiation, global diversification rates have remained stably high in Thaumarchaeota during the past 400–700 million years, suggesting an ongoing high rate of niche formation or switching for these microbes. Our study highlights the enduring importance of environmental adaptation during thaumarchaeotal evolution and, to our knowledge, is the first to link evolutionary diversification to environmental adaptation in a prokaryotic phylum.

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Section: Discussionmentioning

confidence: 99%

Section: Changes In Ph Specialization At the Base Of The Thaumarchaeotalmentioning

confidence: 99%

Coupling of diversification and pH adaptation during the evolution of terrestrial Thaumarchaeota

Gubry‐Rangin

Kratsch

Williams

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

105

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“…R Rphylo develops on phylogenetic ridge regression as described in Kratsch and McHardy (), and Gubry‐Rangin et al. ().…”

Section: Methodsmentioning

confidence: 99%

“…Kratsch and McHardy () applied L2 (quadratic) penalization to estimate λ. We departed from this approach and applied a biologically oriented, conservative solution to the penalization problem, finding the maximum likelihood estimate of λ minimizing the rate (β coefficients) variation along the root to tip paths.…”

Section: Methodsmentioning

confidence: 99%

A new method for testing evolutionary rate variation and shifts in phenotypic evolution

et al. 2018

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Quantifying phenotypic evolutionary rates and their variation across phylogenetic trees is a major issue in evolutionary biology. A number of phylogenetic comparative methods (PCMs) currently perform such task. However, available PCMs can locate rate shifts pertaining to entire portions of the phylogeny, but not those expected to occur at the level of individual species and lineages, such as with the idea that body size changes more rapidly in insular vertebrates. Still, most PCMs cannot deal with fossil phylogenies, albeit fossils provide highly desirable information when it comes to understand trait variation and evolution. We developed a PCM based on phylogenetic ridge regression, which we named RRphylo, which assigns an evolutionary rate to each branch of the phylogeny, and is designed to locate rate shifts relating to entire clades, as well as to unrelated tree tips. We tested RRphylo on simulated trees and data to assess its performance under different conditions. Then, we repeated its application with two real case scenarios, the evolution of flight in ornithodirans and mammals and body size evolution in insular mammals, which are usually subsumed to evolve under different range regimes than terrestrial and continental species respectively. RRphylo performs well across all different conditions. The simulation experiments demonstrated it has low Type I and Type II error rate. We found significant evidence that flight accelerates the rate of body size evolution in vertebrates, and that the acquisition of very large body size slows down the rate. Still, insular mammals body size evolution is not faster than in continental species. RRphylo is a new PCM ideal to estimate variation and shift in the rate of phenotypic evolution with fossil data. In addition to testing evolutionary rate variation, it is open to a variety of further questions, such as the evolution of rates in time, the estimation of ancestral states and the estimation of phenotypic trends over time.

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“…Our approach seeks to automatically identify exceptional shifts in the rate of phenotypic evolution, defined as instances in which accelerated evolutionary change contributes more than half the total amount of expected phenotypic change along a branch. This follows our own work and that of others who have linked the rate of morphological evolution to adaptation (Eastman et al ., ; Venditti et al ., ; Revell et al ., ; Thomas & Freckleton, ; Kutsukake & Innan, , ; Kratsch & McHardy, ; Rabosky, ).…”

Section: Introductionmentioning

confidence: 99%

Positive phenotypic selection inferred from phylogenies

Baker

Meade

Pagel

et al. 2015

Biol. J. Linn. Soc.

188

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Rates of phenotypic evolution vary widely in nature and these rates may often reflect the intensity of natural selection. Here we outline an approach for detecting exceptional shifts in the rate of phenotypic evolution across phylogenies. We introduce a simple new branch-specific metric Δ V /Δ B that divides observed phenotypic change along a branch into two components: (1) that attributable to the background rate (Δ B ), and (2) that attributable to departures from the background rate (Δ V ). Where the amount of expected change derived from variation in the rate of morphological evolution doubles that explained by to the background rate (Δ V /Δ B > 2), we identify this as positive phenotypic selection. We apply our approach to six datasets, finding multiple instances of positive selection in each. Our results support the growing appreciation that the traditional gradual view of phenotypic evolution is rarely upheld, with a more episodic view taking its place. This moves focus away from viewing phenotypic evolution as a simple homogeneous process and facilitates reconciliation with macroevolutionary interpretations from a genetic perspective, paving the way to novel insights into the link between genotype and phenotype. The ability to detect positive selection when genetic data are unavailable or unobtainable represents an attractive prospect for extant species, but when applied to fossil data it can reveal patterns of natural selection in deep time that would otherwise be impossible.

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RidgeRace: ridge regression for continuous ancestral character estimation on phylogenetic trees

Cited by 30 publications

References 40 publications

Coupling of diversification and pH adaptation during the evolution of terrestrial Thaumarchaeota

Coupling of diversification and pH adaptation during the evolution of terrestrial Thaumarchaeota

A new method for testing evolutionary rate variation and shifts in phenotypic evolution

Positive phenotypic selection inferred from phylogenies

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