Fixation in finite populations evolving in fluctuating environments

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Fixation in finite populations evolving in fluctuating environments

Peter Ashcroft, Philipp M Altrock, Tobias Galla
(Submitted on 21 Jun 2014)

The environment in which a population evolves can have a crucial impact on selection. We study evolutionary dynamics in finite populations of fixed size in a changing environment. The population dynamics are driven by birth and death events. The rates of these events may vary in time depending on the state of the environment, which follows an independent Markov process. We develop a general theory for the fixation probability of a mutant in a population of wild-types, and for unconditional and conditional mean fixation times. We apply our theory to evolutionary games for which the payoff structure varies in time. The mutant can exploit the environmental noise; a dynamic environment that switches between two states can lead to a probability of fixation that is higher than in any of the individual environmental states. We provide an intuitive interpretation of this surprising effect. We also investigate stationary distributions of the population when mutations are more frequent. In this regime, we find two approximations of the stationary measure. One works well for rapid switching, the other for slowly fluctuating environments.

Hsp90 promotes kinase evolution

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Hsp90 promotes kinase evolution

Jennifer Lachowiec, Tzitziki Lemus, Elhanan Borenstein, Christine Queitsch

Heat-shock protein 90 (Hsp90) promotes the maturation and stability of its client proteins, including many kinases. In doing so, Hsp90 may allow its clients to accumulate mutations as previously proposed by the capacitor hypothesis. If true, Hsp90 clients should show increased evolutionary rate compared to non-clients; however, other factors, such as gene expression and protein connectivity, may confound or obscure the chaperone?s putative contribution. Here, we compared the evolutionary rates of many Hsp90 clients and non-clients in the human protein kinase superfamily. We show that Hsp90 client status promotes evolutionary rate independently of, but in a similar magnitude to, gene expression and protein connectivity. Hsp90?s effect on kinase evolutionary rate was detected across mammals and increased with time of divergence. Hsp90 clients also showed increased nucleotide diversity and harbored more damaging variation than non-client kinases across humans. These results are consistent with the central argument of the capacitor hypothesis that interaction with the chaperone allows its clients to harbor genetic variation. Hsp90 client status is thought to be highly dynamic with as few as one amino acid change rendering a protein dependent on the chaperone. Contrary to this expectation, we found that across protein kinase phylogeny Hsp90 client status tends to be gained, maintained, and shared among closely related kinases. We also infer that the ancestral protein kinase was not an Hsp90 client. Taken together, our results suggest that Hsp90 played an important role in shaping the kinase superfamily.

Approximation to the distribution of fitness effects across functional categories in human segregating polymorphisms

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Approximation to the distribution of fitness effects across functional categories in human segregating polymorphisms

Fernando Racimo, Joshua G Schraiber

Quantifying the proportion of polymorphic mutations that are deleterious or neutral is of fundamental importance to our understanding of evolution, disease genetics and the maintenance of variation genome-wide. Here, we develop an approximation to the distribution of fitness effects (DFE) of segregating single-nucleotide mutations in humans. Unlike previous methods, we do not assume that synonymous mutations are neutral or not strongly selected, and we do not rely on fitting the DFE of all new nonsynonymous mutations to a single probability distribution, which is poorly motivated on a biological level. We rely on a previously developed method that utilizes a variety of published annotations (including conservation scores, protein deleteriousness estimates and regulatory data) to score all mutations in the human genome based on how likely they are to be affected by negative selection, controlling for mutation rate. We map this score to a scale of fitness coefficients via maximum likelihood using diffusion theory and a Poisson random field model on SNP data. Our method serves to approximate the deleterious DFE of mutations that are segregating, regardless of their genomic consequence. We can then compare the proportion of mutations that are negatively selected or neutral across various categories, including different types of regulatory sites. We observe that the distribution of intergenic polymorphisms is highly peaked at neutrality, while the distribution of nonsynonymous polymorphisms is bimodal, with a neutral peak and a second peak at s ≈ −10^(−4). Other types of polymorphisms have shapes that fall roughly in between these two. We find that transcriptional start sites, strong CTCF-enriched elements and enhancers are the regulatory categories with the largest proportion of deleterious polymorphisms.

Assessing Technical Performance in Differential Gene Expression Experiments with External Spike-in RNA Control Ratio Mixtures

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Assessing Technical Performance in Differential Gene Expression Experiments with External Spike-in RNA Control Ratio Mixtures

Sarah A. Munro, Steve P. Lund, P. Scott Pine, Hans Binder, Djork-Arné Clevert, Ana Conesa, Joaquin Dopazo, Mario Fasold, Sepp Hochreiter, Huixiao Hong, Nederah Jafari, David P. Kreil, Paweł P. Łabaj, Sheng Li, Yang Liao, Simon Lin, Joseph Meehan, Christopher E. Mason, Javier Santoyo, Robert A. Setterquist, Leming Shi, Wei Shi, Gordon K. Smyth, Nancy Stralis-Pavese, Zhenqiang Su, Weida Tong, Charles Wang, Jian Wang, Joshua Xu, Zhan Ye, Yong Yang, Ying Yu, Marc Salit
(Submitted on 18 Jun 2014)

There is a critical need for standard approaches to assess, report, and compare the technical performance of genome-scale differential gene expression experiments. We assess technical performance with a proposed “standard” dashboard of metrics derived from analysis of external spike-in RNA control ratio mixtures. These control ratio mixtures with defined abundance ratios enable assessment of diagnostic performance of differentially expressed transcript lists, limit of detection of ratio (LODR) estimates, and expression ratio variability and measurement bias. The performance metrics suite is applicable to analysis of a typical experiment, and here we also apply these metrics to evaluate technical performance among laboratories. An interlaboratory study using identical samples shared amongst 12 laboratories with three different measurement processes demonstrated generally consistent diagnostic power across 11 laboratories. Ratio measurement variability and bias were also comparable amongst laboratories for the same measurement process. Different biases were observed for measurement processes using different mRNA enrichment protocols.

Parametric Inference using Persistence Diagrams: A Case Study in Population Genetics

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Parametric Inference using Persistence Diagrams: A Case Study in Population Genetics

Kevin Emmett, Daniel Rosenbloom, Pablo Camara, Raul Rabadan
(Submitted on 18 Jun 2014)

Persistent homology computes topological invariants from point cloud data. Recent work has focused on developing statistical methods for data analysis in this framework. We show that, in certain models, parametric inference can be performed using statistics defined on the computed invariants. We develop this idea with a model from population genetics, the coalescent with recombination. We apply our model to an influenza dataset, identifying two scales of topological structure which have a distinct biological interpretation.

Identifiability of the unrooted species tree topology under the coalescent model with time-reversible substitution processes

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Identifiability of the unrooted species tree topology under the coalescent model with time-reversible substitution processes

Julia Chifman, Laura Kubatko
(Submitted on 18 Jun 2014)

The inference of the evolutionary history of a collection of organisms is a problem of fundamental importance in evolutionary biology. The abundance of DNA sequence data arising from genome sequencing projects has led to significant challenges in the inference of these phylogenetic relationships. Among these challenges is the inference of the evolutionary history of a collection of species based on sequence information from several distinct genes sampled throughout the genome. It is widely accepted that each individual gene has its own phylogeny, which may not agree with the species tree. Many possible causes of this gene tree incongruence are known. The best studied is incomplete lineage sorting, which is commonly modeled by the coalescent process. Numerous methods based on the coalescent process have been proposed for estimation of the phylogenetic species tree given multi-locus DNA sequence data. However, use of these methods assumes that the phylogenetic species tree can be identified from DNA sequence data at the leaves of the tree, although this has not been formally established. We prove that the unrooted topology of the n-leaf phylogenetic species tree is generically identifiable given observed data at the leaves of the tree that are assumed to have arisen from the coalescent process with time-reversible substitution.

The overdue promise of short tandem repeat variation for heritability

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The overdue promise of short tandem repeat variation for heritability.

Maximilian Press, Keisha D. Carlson, Christine Queitsch

Short tandem repeat (STR) variation has been proposed as a major explanatory factor in the heritability of complex traits in humans and model organisms. However, we still struggle to incorporate STR variation into genotype-phenotype maps. Here, we review the promise of STRs in contributing to complex trait heritability, and highlight the challenges that STRs pose due to their repetitive nature. We argue that STR variants are more likely than single nucleotide variants to have epistatic interactions, reiterate the need for targeted assays to accurately genotype STRs, and call for more appropriate statistical methods in detecting STR-phenotype associations. Lastly, somatic STR variation within individuals may serve as a read-out of disease susceptibility, and is thus potentially a valuable covariate for future association studies.

Error correction and assembly complexity of single molecule sequencing reads.

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Error correction and assembly complexity of single molecule sequencing reads.

Hayan Lee, James Gurtowski, Shinjae Yoo, Shoshana Marcus, W. Richard McCombie, Michael Schatz

Third generation single molecule sequencing technology is poised to revolutionize genomics by enabling the sequencing of long, individual molecules of DNA and RNA. These technologies now routinely produce reads exceeding 5,000 basepairs, and can achieve reads as long as 50,000 basepairs. Here we evaluate the limits of single molecule sequencing by assessing the impact of long read sequencing in the assembly of the human genome and 25 other important genomes across the tree of life. From this, we develop a new data-driven model using support vector regression that can accurately predict assembly performance. We also present a novel hybrid error correction algorithm for long PacBio sequencing reads that uses pre-assembled Illumina sequences for the error correction. We apply it several prokaryotic and eukaryotic genomes, and show it can achieve near-perfect assemblies of small genomes (< 100Mbp) and substantially improved assemblies of larger ones. All source code and the assembly model are available open-source.

Bayesian inference of sampled ancestor trees for epidemiology and fossil calibration

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Bayesian inference of sampled ancestor trees for epidemiology and fossil calibration

Alexandra Gavryushkina, David Welch, Tanja Stadler, Alexei Drummond
(Submitted on 18 Jun 2014)

Phylogenetic analyses which include fossils or molecular sequences that are sampled through time require models that allow one sample to be a direct ancestor of another sample. As previously available phylogenetic inference tools assume that all samples are tips, they do not allow for this possibility. We have developed and implemented a Bayesian Markov Chain Monte Carlo (MCMC) algorithm to infer what we call sampled ancestor trees, that is, trees in which sampled individuals can be direct ancestors of other sampled individuals. We use a family of birth-death models where individuals may remain in the tree process after the sampling, in particular we extend the birth-death skyline model [Stadler et al, 2013] to sampled ancestor trees. This method allows the detection of sampled ancestors as well as estimation of the probability that an individual will be removed from the process when it is sampled. We show that sampled ancestor birth-death models where all samples come from different time points are non-identifiable and thus require one parameter to be known in order to infer other parameters. We apply this method to epidemiological data, where the possibility of sampled ancestors enables us to identify individuals that infected other individuals after being sampled and to infer fundamental epidemiological parameters. We also apply the method to infer divergence times and diversification rates when fossils are included among the species samples, so that fossilisation events are modelled as a part of the tree branching process. Such modelling has many advantages as argued in literature. The sampler is available as an open-source BEAST2 package (this https URL ancestors/).

Nanopore Sequencing of the phi X 174 genome

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Nanopore Sequencing of the phi X 174 genome

Andrew H. Laszlo, Ian M. Derrington, Brian C. Ross, Henry Brinkerhoff, Andrew Adey, Ian C. Nova, Jonathan M. Craig, Kyle W. Langford, Jenny Mae Samson, Riza Daza, Kenji Doering, Jay Shendure, Jens H. Gundlach
(Submitted on 17 Jun 2014)

Nanopore sequencing of DNA is a single-molecule technique that may achieve long reads, low cost, and high speed with minimal sample preparation and instrumentation. Here, we build on recent progress with respect to nanopore resolution and DNA control to interpret the procession of ion current levels observed during the translocation of DNA through the pore MspA. As approximately four nucleotides affect the ion current of each level, we measured the ion current corresponding to all 256 four-nucleotide combinations (quadromers). This quadromer map is highly predictive of ion current levels of previously unmeasured sequences derived from the bacteriophage phi X 174 genome. Furthermore, we show nanopore sequencing reads of phi X 174 up to 4,500 bases in length that can be unambiguously aligned to the phi X 174 reference genome, and demonstrate proof-of-concept utility with respect to hybrid genome assembly and polymorphism detection. All methods and data are made fully available.