Neutral Mutation Rate Research Articles

Recurrent selection shapes the genomic landscape of differentiation between a pair of host-specialized haplodiploids that diverged with gene flow.

Understanding the genetics of adaptation and speciation is critical for a complete picture of how biodiversity is generated and maintained. Heterogeneous genomic differentiation between diverging taxa is commonly documented, with genomic regions of high differentiation interpreted as resulting from differential gene flow, linked selection and reduced recombination rates. Disentangling the roles of each of these non-exclusive processes in shaping genome-wide patterns of divergence is challenging but will enhance our knowledge of the repeatability of genomic landscapes across taxa. Here, we combine whole-genome resequencing and genome feature data to investigate the processes shaping the genomic landscape of differentiation for a sister-species pair of haplodiploid pine sawflies, Neodiprion lecontei and Neodiprion pinetum. We find genome-wide correlations between genome features and summary statistics are consistent with pervasive linked selection, with patterns of diversity and divergence more consistently predicted by exon density and recombination rate than the neutral mutation rate (approximated by dS). We also find that both global and local patterns of FST, dXY and π provide strong support for recurrent selection as the primary selective process shaping variation across pine sawfly genomes, with some contribution from balancing selection and lineage-specific linked selection. Because inheritance patterns for haplodiploid genomes are analogous to those of sex chromosomes, we hypothesize that haplodiploids may be especially prone to recurrent selection, even if gene flow occurred throughout divergence. Overall, our study helps fill an important taxonomic gap in the genomic landscape literature and contributes to our understanding of the processes that shape genome-wide patterns of genetic variation.

Estimation of Neutral Mutation Rates and Quantification of Somatic Variant Selection Using cancereffectsizeR.

An R package provides streamlined, customizable estimation of underlying nucleotide mutation rates and of the oncogenic and epistatic effects of mutations in cancer cohorts.

The somatic molecular evolution of cancer: Mutation, selection, and epistasis

Cancer progression has been attributed to somatic changes in single-nucleotide variants, copy-number aberrations, loss of heterozygosity, chromosomal instability, epistatic interactions, and the tumor microenvironment. It is not entirely clear which of these changes are essential and which are ancillary to cancer. The dynamic nature of cancer evolution in a patient can be illuminated using several concepts and tools from classical evolutionary biology. Neutral mutation rates in cancer cells are calculable from genomic data such as synonymous mutations, and selective pressures are calculable from rates of fixation occurring beyond the expectation by neutral mutation and drift. However, these cancer effect sizes of mutations are complicated by epistatic interactions that can determine the likely sequence of gene mutations. In turn, longitudinal phylogenetic analyses of somatic cancer progression offer an opportunity to identify key moments in cancer evolution, relating the timing of driver mutations to corresponding landmarks in the clinical timeline. These analyses reveal temporal aspects of genetic and phenotypic change during tumorigenesis and across clinical timescales. Using a related framework, clonal deconvolution, physical locations of clones, and their phylogenetic relations can be used to infer tumor migration histories. Additionally, genetic interactions with the tumor microenvironment can be analyzed with longstanding approaches applied to organismal genotype-by-environment interactions. Fitness landscapes for cancer evolution relating to genotype, phenotype, and environment could enable more accurate, personalized therapeutic strategies. An understanding of the trajectories underlying the evolution of neoplasms, primary, and metastatic tumors promises fundamental advances toward accurate and personalized predictions of therapeutic response.

Base-substitution mutation rate across the nuclear genome of Alpheus snapping shrimp and the timing of isolation by the Isthmus of Panama

BackgroundThe formation of the Isthmus of Panama and final closure of the Central American Seaway (CAS) provides an independent calibration point for examining the rate of DNA substitutions. This vicariant event has been widely used to estimate the substitution rate across mitochondrial genomes and to date evolutionary events in other taxonomic groups. Nuclear sequence data is increasingly being used to complement mitochondrial datasets for phylogenetic and evolutionary investigations; these studies would benefit from information regarding the rate and pattern of DNA substitutions derived from the nuclear genome.ResultsTo estimate the genome-wide neutral mutation rate (µ), genotype-by-sequencing (GBS) datasets were generated for three transisthmian species pairs in Alpheus snapping shrimp. A range of bioinformatic filtering parameters were evaluated in order to minimize potential bias in mutation rate estimates that may result from SNP filtering. Using a Bayesian coalescent approach (G-PhoCS) applied to 44,960 GBS loci, we estimated µ to be 2.64E−9 substitutions/site/year, when calibrated with the closure of the CAS at 3 Ma. Post-divergence gene flow was detected in one species pair. Failure to account for this post-split migration inflates our substitution rate estimates, emphasizing the importance of demographic methods that can accommodate gene flow.ConclusionsResults from our study, both parameter estimates and bioinformatic explorations, have broad-ranging implications for phylogeographic studies in other non-model taxa using reduced representation datasets. Our best estimate of µ that accounts for coalescent and demographic processes is remarkably similar to experimentally derived mutation rates in model arthropod systems. These results contradicted recent suggestions that the closure of the Isthmus was completed much earlier (around 10 Ma), as mutation rates based on an early calibration resulted in uncharacteristically low genomic mutation rates. Also, stricter filtering parameters resulted in biased datasets that generated lower mutation rate estimates and influenced demographic parameters, serving as a cautionary tale for the adherence to conservative bioinformatic strategies when generating reduced-representation datasets at the species level. To our knowledge this is the first use of transisthmian species pairs to calibrate the rate of molecular evolution from GBS data.

A unified simulation model for understanding the diversity of cancer evolution.

Because cancer evolution underlies the therapeutic difficulties of cancer, it is clinically important to understand the evolutionary dynamics of cancer. Thus far, a number of evolutionary processes have been proposed to be working in cancer evolution. However, there exists no simulation model that can describe the different evolutionary processes in a unified manner. In this study, we constructed a unified simulation model for describing the different evolutionary processes and performed sensitivity analysis on the model to determine the conditions in which cancer growth is driven by each of the different evolutionary processes. Our sensitivity analysis has successfully provided a series of novel insights into the evolutionary dynamics of cancer. For example, we found that, while a high neutral mutation rate shapes neutral intratumor heterogeneity (ITH) characterized by a fractal-like pattern, a stem cell hierarchy can also contribute to shaping neutral ITH by apparently increasing the mutation rate. Although It has been reported that the evolutionary principle shaping ITH shifts from selection to accumulation of neutral mutations during colorectal tumorigenesis, our simulation revealed the possibility that this evolutionary shift is triggered by drastic evolutionary events that occur in a short time and confer a marked fitness increase on one or a few cells. This result helps us understand that each process works not separately but simultaneously and continuously as a series of phases of cancer evolution. Collectively, this study serves as a basis to understand in greater depth the diversity of cancer evolution.

A neutral mutated operator applied for DE algorithms

As an easily used and powerful heuristic search technique based on population, differential evolution (DE) algorithm has been widely used for many optimization and real engineering projects. Similar to other evolutionary algorithms (EA), DE could not avoid from premature convergence due to over concentrated population, which could be called losing population diversity. To improve the performance, a neutral mutation (NM) operator for DE algorithm is proposed. The proposed operator is inspired by neutral theory of molecular evolution, which claims that most mutations are neutral at the level of molecular. The NM operator maintains slightly deleterious trial vectors with a certain probability in the conventional selection operator of DE. At the same time, two control parameters of Neutral Mutation operator are investigated and a dynamic neutral mutation rate tuning strategy is designed. Besides, some of these trial vectors have a chance to be mutated neutrally within the search domain randomly. As a result, the population is diversified with costing negligible function evaluations. Comprehensive experimental results demonstrate that the presented NM operator could improve population diversity to some extent, especially when the population is not divergent at all. Moreover, a real word problem is used to further evaluate NM operator. Also, this operator can be easily used in other EAs to keep population diversity.

A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data

BackgroundDetailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration.ResultsTo take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models.We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures.ConclusionWe find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model for the mutational process; regions that deviate from the null model are candidates for elements that drive cancer development.

Dating the Cryptococcus gattii Dispersal to the North American Pacific Northwest.

The emergence of Cryptococcus gattii, previously regarded as a predominantly tropical pathogen, in the temperate climate of the North American Pacific Northwest (PNW) in 1999 prompted several questions. The most prevalent among these was the timing of the introduction of this pathogen to this novel environment. Here, we infer tip-dated timing estimates for the three clonal C.gattii populations observed in the PNW, VGIIa, VGIIb, and VGIIc, based on whole-genome sequencing of 134 C.gattii isolates and using Bayesian evolutionary analysis by sampling trees (BEAST). We estimated the nucleotide substitution rate for each lineage (1.59 × 10-8, 1.59 × 10-8, and 2.70 × 10-8, respectively) to be an order of magnitude higher than common neutral fungal mutation rates (2.0 × 10-9), indicating a microevolutionary rate (e.g., successive clonal generations in a laboratory) in comparison to a species' slower, macroevolutionary rate (e.g., when using fossil records). The clonal nature of the PNW C.gattii emergence over a narrow number of years would therefore possibly explain our higher mutation rates. Our results suggest that the mean time to most recent common ancestor for all three sublineages occurred within the last 60 to 100years. While the cause of C.gattii dispersal to the PNW is still unclear, our research estimates that the arrival is neither ancient nor very recent (i.e., <25 years ago), making a strong case for an anthropogenic introduction. IMPORTANCE The recent emergence of the pathogenic fungus Cryptococcus gattii in the Pacific Northwest (PNW) resulted in numerous investigations into the epidemiological and enzootic impacts, as well as multiple genomic explorations of the three primary molecular subtypes of the fungus that were discovered. These studies lead to the general conclusion that the subtypes identified likely emerged out of Brazil. Here, we conducted genomic dating analyses to determine the ages of the various lineages seen in the PNW and propose hypothetical causes for the dispersal events. Bayesian evolutionary analysis strongly suggests that these independent fungal populations in the PNW are all 60 to 100 years old, providing a timing that is subsequent to the opening of the Panama Canal, which allowed for more direct shipping between Brazil and the western North American coastline, a possible driving event for these fungal translocation events.

Fitness cost of reassortment in human influenza.

Reassortment, which is the exchange of genome sequence between viruses co-infecting a host cell, plays an important role in the evolution of segmented viruses. In the human influenza virus, reassortment happens most frequently between co-existing variants within the same lineage. This process breaks genetic linkage and fitness correlations between viral genome segments, but the resulting net effect on viral fitness has remained unclear. In this paper, we determine rate and average selective effect of reassortment processes in the human influenza lineage A/H3N2. For the surface proteins hemagglutinin and neuraminidase, reassortant variants with a mean distance of at least 3 nucleotides to their parent strains get established at a rate of about 10−2 in units of the neutral point mutation rate. Our inference is based on a new method to map reassortment events from joint genealogies of multiple genome segments, which is tested by extensive simulations. We show that intra-lineage reassortment processes are, on average, under substantial negative selection that increases in strength with increasing sequence distance between the parent strains. The deleterious effects of reassortment manifest themselves in two ways: there are fewer reassortment events than expected from a null model of neutral reassortment, and reassortant strains have fewer descendants than their non-reassortant counterparts. Our results suggest that influenza evolves under ubiquitous epistasis across proteins, which produces fitness barriers against reassortment even between co-circulating strains within one lineage.

Branching Brownian motion and selection in the spatial $\Lambda$-Fleming–Viot process

We ask the question when will natural selection on a gene in a spatially structured population cause a detectable trace in the patterns of genetic variation observed in the contemporary population?. We focus on the situation in which 'neighbourhood size', that is the effective local population density, is small. The genealogy relating individuals in a sample from the population is embedded in a spatial version of the ancestral selection graph and through applying a diffusive scaling to this object we show that whereas in dimensions at least three, selection is barely impeded by the spatial structure, in the most relevant dimension, $d=2$, selection must be stronger (by a factor of $\log(1/\mu)$ where $\mu$ is the neutral mutation rate) if we are to have a chance of detecting it. The case $d=1$ was handled in Etheridge et al. (2015). The mathematical interest is that although the system of branching and coalescing lineages that forms the ancestral selection graph converges to a branching Brownian motion, this reflects a delicate balance of a branching rate that grows to infinity and the instant annullation of almost all branches through coalescence caused by the strong local competition in the population.

The impact of ancestral population size and incomplete lineage sorting on Bayesian estimation of species divergence times

Abstract Although the effects of the coalescent process on sequence divergence and genealogies are well understood, the virtual majority of studies that use molecular sequences to estimate times of divergence among species have failed to account for the coalescent process. Here we study the impact of ancestral population size and incomplete lineage sorting on Bayesian estimates of species divergence times under the molecular clock when the inference model ignores the coalescent process. Using a combination of mathematical analysis, computer simulations and analysis of real data, we find that the errors on estimates of times and the molecular rate can be substantial when ancestral populations are large and when there is substantial incomplete lineage sorting. For example, in a simple three-species case, we find that if the most precise fossil calibration is placed on the root of the phylogeny, the age of the internal node is overestimated, while if the most precise calibration is placed on the internal node, then the age of the root is underestimated. In both cases, the molecular rate is overestimated. Using simulations on a phylogeny of nine species, we show that substantial errors in time and rate estimates can be obtained even when dating ancient divergence events. We analyse the hominoid phylogeny and show that estimates of the neutral mutation rate obtained while ignoring the coalescent are too high. Using a coalescent-based technique to obtain geological times of divergence, we obtain estimates of the mutation rate that are within experimental estimates and we also obtain substantially older divergence times within the phylogeny.

Breaking bad: The mutagenic effect of DNA repair.

Species survival depends on the faithful replication of genetic information, which is continually monitored and maintained by DNA repair pathways that correct replication errors and the thousands of lesions that arise daily from the inherent chemical lability of DNA and the effects of genotoxic agents. Nonetheless, neutrally evolving DNA (not under purifying selection) accumulates base substitutions with time (the neutral mutation rate). Thus, repair processes are not 100% efficient. The neutral mutation rate varies both between and within chromosomes. For example it is 10-50 fold higher at CpGs than at non-CpG positions. Interestingly, the neutral mutation rate at non-CpG sites is positively correlated with CpG content. Although the basis of this correlation was not immediately apparent, some bioinformatic results were consistent with the induction of non-CpG mutations by DNA repair at flanking CpG sites. Recent studies with a model system showed that in vivo repair of preformed lesions (mismatches, abasic sites, single stranded nicks) can in fact induce mutations in flanking DNA. Mismatch repair (MMR) is an essential component for repair-induced mutations, which can occur as distant as 5 kb from the introduced lesions. Most, but not all, mutations involved the C of TpCpN (G of NpGpA) which is the target sequence of the C-preferring single-stranded DNA specific APOBEC deaminases. APOBEC-mediated mutations are not limited to our model system: Recent studies by others showed that some tumors harbor mutations with the same signature, as can intermediates in RNA-guided endonuclease-mediated genome editing. APOBEC deaminases participate in normal physiological functions such as generating mutations that inactivate viruses or endogenous retrotransposons, or that enhance immunoglobulin diversity in B cells. The recruitment of normally physiological error-prone processes during DNA repair would have important implications for disease, aging and evolution. This perspective briefly reviews both the bioinformatic and biochemical literature relevant to repair-induced mutagenesis and discusses future directions required to understand the mechanistic basis of this process.

Measuring Genetic Robustness in Vesicular Stomatitis Virus

Genetic robustness is the ability of a genome to incorporate mutations with the result of no fitness changes. Thus, more robust viruses have an increased neutral mutation rate. This property is particularly important in RNA viruses due to their high mutation rates. The most direct way of measuring robustness in vesicular stomatitis virus (VSV) is to carry out clonal analysis of populations: randomly isolating individual VSV strains (plaques), measuring the fitness of each one and generating fitness distributions (Novella et al., 2010). A second possibility is to carry out multiple replicates of repeated plaque-to-plaque passages, determining fitness in progeny populations and generating fitness distributions (Novella et al., 2010). Depending on the expected differences, the former may require hundreds of determinations, while the latter may require tens of determinations. A third approach consists of increasing the mutation rate of populations under analysis to magnify any differences that may exist and, instead of measuring fitness, measuring survival (Novella et al., 2013). One caveat of this method is that changes in survival can also be explained by changes in polymerase fidelity. For that reason, it is important to perform complementary experiments, in this case quantifying mutant frequency.

Evidence of non-random mutation rates suggests an evolutionary risk management strategy

A central tenet in evolutionary theory is that mutations occur randomly with respect to their value to an organism; selection then governs whether they are fixed in a population. This principle has been challenged by long-standing theoretical models predicting that selection could modulate the rate of mutation itself. However, our understanding of how the mutation rate varies between different sites within a genome has been hindered by technical difficulties in measuring it. Here we present a study that overcomes previous limitations by combining phylogenetic and population genetic techniques. Upon comparing 34 Escherichia coli genomes, we observe that the neutral mutation rate varies by more than an order of magnitude across 2,659 genes, with mutational hot and cold spots spanning several kilobases. Importantly, the variation is not random: we detect a lower rate in highly expressed genes and in those undergoing stronger purifying selection. Our observations suggest that the mutation rate has been evolutionarily optimized to reduce the risk of deleterious mutations. Current knowledge of factors influencing the mutation rate—including transcription-coupled repair and context-dependent mutagenesis—do not explain these observations, indicating that additional mechanisms must be involved. The findings have important implications for our understanding of evolution and the control of mutations.

Natural Selection in Gene-Dense Regions Shapes the Genomic Pattern of Polymorphism in Wild and Domesticated Rice

Levels of nucleotide variability are frequently positively correlated with recombination rate and negatively associated with gene density due to the effects of selection on linked variation. These relationships are determined by properties that frequently differ among species, including the mating system, and aspects of genome organization such as how genes are distributed along chromosomes. In rice, genes are found at highest density in regions with frequent crossing-over. This association between gene density and recombination rate provides an opportunity to evaluate the effects of selection in a genomic context that differs from other model organisms. Using single-nucleotide polymorphism data from Asian domesticated rice Oryza sativa ssp. japonica and ssp. indica and their progenitor species O. rufipogon, we observe a significant negative association between levels of polymorphism and both gene and coding site density, but either no association, or a negative correlation, between nucleotide variability and recombination rate. We establish that these patterns are unlikely to be explained by neutral mutation rate biases and demonstrate that a model of background selection with variable rates of deleterious mutation is sufficient to account for the gene density effect in O. rufipogon. In O. sativa ssp. japonica, we report a strong negative correlation between polymorphism and recombination rate and greater losses of variation during domestication in the euchromatic chromosome arms than heterochromatin. This is consistent with Hill-Robertson interference in low-recombination regions, which may limit the efficacy of selection for domestication traits. Our results suggest that the physical distribution of selected mutations is a primary factor that determines the genomic pattern of polymorphism in wild and domesticated rice species.

Epistasis Increases the Rate of Conditionally Neutral Substitution in an Adapting Population

Kimura observed that the rate of neutral substitution should equal the neutral mutation rate. This classic result is central to our understanding of molecular evolution, and it continues to influence phylogenetics, genomics, and the interpretation of evolution experiments. By demonstrating that neutral mutations substitute at a rate independent of population size and selection at linked sites, Kimura provided an influential justification for the idea of a molecular clock and emphasized the importance of genetic drift in shaping molecular evolution. But when epistasis among sites is common, as numerous empirical studies suggest, do neutral mutations substitute according to Kimura's expectation? Here we study simulated, asexual populations of RNA molecules, and we observe that conditionally neutral mutations--i.e., mutations that do not alter the fitness of the individual in which they arise, but that may alter the fitness effects of subsequent mutations--substitute much more often than expected while a population is adapting. We quantify these effects using a simple population-genetic model that elucidates how the substitution rate at conditionally neutral sites depends on the population size, mutation rate, strength of selection, and prevalence of epistasis. We discuss the implications of these results for our understanding of the molecular clock, and for the interpretation of molecular variation in laboratory and natural populations.

Parasite-mediated evolution of the functional part of the MHC in primates

The major histocompatibility complex (MHC) is a key model of genetic polymorphism, but the mechanisms underlying its extreme variability are debated. Most hypotheses for MHC diversity focus on pathogen-driven selection and predict that MHC polymorphism evolves under the pressure of a diverse parasite fauna. Several studies reported that certain alleles offer protection against certain parasites, yet it remains unclear whether variation in parasite pressure more generally covaries with allelic diversity and rates of molecular evolution of MHC across species. We tested this prediction in a comparative study of 41 primate species. We characterized polymorphism of the exon 2 of DRB region of the MHC class II. Our phylogenetic analyses controlled for the potential effects of neutral mutation rate, population size, geographic origin and body mass and revealed that nematode species richness associates positively with nonsynonymous nucleotide substitution rate at the functional part of the molecule. We failed to find evidence for allelic diversity being strongly related to parasite species richness. Continental distribution was a strong predictor of both allelic diversity and substitution rate, with higher values in Malagasy and Neotropical primates. These results indicate that parasite pressure can influence the different estimates of MHC polymorphism, whereas geography plays an independent role in the natural history of MHC.

Direct Measure of the De Novo Mutation Rate in Autism and Schizophrenia Cohorts

The role of de novo mutations (DNMs) in common diseases remains largely unknown. Nonetheless, the rate of de novo deleterious mutations and the strength of selection against de novo mutations are critical to understanding the genetic architecture of a disease. Discovery of high-impact DNMs requires substantial high-resolution interrogation of partial or complete genomes of families via resequencing. We hypothesized that deleterious DNMs may play a role in cases of autism spectrum disorders (ASD) and schizophrenia (SCZ), two etiologically heterogeneous disorders with significantly reduced reproductive fitness. We present a direct measure of the de novo mutation rate (μ) and selective constraints from DNMs estimated from a deep resequencing data set generated from a large cohort of ASD and SCZ cases (n = 285) and population control individuals (n = 285) with available parental DNA. A survey of ∼430 Mb of DNA from 401 synapse-expressed genes across all cases and 25 Mb of DNA in controls found 28 candidate DNMs, 13 of which were cell line artifacts. Our calculated direct neutral mutation rate (1.36 × 10(-8)) is similar to previous indirect estimates, but we observed a significant excess of potentially deleterious DNMs in ASD and SCZ individuals. Our results emphasize the importance of DNMs as genetic mechanisms in ASD and SCZ and the limitations of using DNA from archived cell lines to identify functional variants.

The mutational spectrum of non-CpG DNA varies with CpG content

The accumulation of base substitutions (mutations) not subject to natural selection is the neutral mutation rate. Because this rate reflects the in vivo processes involved in maintaining the integrity of genetic information, the factors that affect the neutral mutation rate are of considerable interest. Mammals exhibit two dramatically different neutral mutation rates: the CpG mutation rate, wherein the C of most CpGs (i.e., methyl-CpG) mutate at 10-50 times that of C in any other context or of any other base. The latter mutations constitute the non-CpG rate. The high CpG rate results from the spontaneous deamination of methyl-C to T and incomplete restoration of the ensuing T:G mismatches to C:Gs. Here, we determined the neutral non-CpG mutation rate as a function of CpG content by comparing sequence divergence of thousands of pairs of neutrally evolving chimpanzee and human orthologs that differ primarily in CpG content. Both the mutation rate and the mutational spectrum (transition/transversion ratio) of non-CpG residues change in parallel as sigmoidal (logistic) functions of CpG content. As different mechanisms generate transitions and transversions, these results indicate that both mutation rate and mutational processes are contingent on the local CpG content. We consider several possible mechanisms that might explain how CpG exerts these effects.

Abstract 101: The mechanism of clonal expansion determines the tempo and mode of neoplastic progression in Barrett's esophagus

Abstract Barrett's Esophagus is a pre-malignant condition with a low rate of progression to esophageal adenocarcinoma. Endoscopic surveillance is recommended for early detection of cancer, which allows the study neoplastic progression in vivo over space and time. Since genetic clonal diversity predicts neoplastic progression (Maley Nat. Gen. 38, 468-473 (2006)), we developed an agent-based model to explore the effect of different parameters, such as mutation rate, selective effect of mutations and clonal expansion probability, on the spatio-temporal dynamics of genetic diversity. A typical Barrett's segment contains ∼90,000 crypts and we assume that clonal expansion occurs by crypt bifurcation, since the rate of crypt bifurcation is high in other diseases marked by chronic inflammation (Cheng The Anat. Record 216, 44-48 (1986)). The Barrett's segment is a cylinder that we model as a two-dimensional 300 by 300 hexagonal grid, wrapped around along one dimension. Crypts (agents) divide, die or mutate according to basal division, death and mutation rates as well as the mutation states of loci conferring reproductive and survival advantages. If a crypt needs to divide, and all of its six neighbors are alive, a daughter crypt displaces one of the neighbors at random with probability r, the “mechanism of clonal expansion probability”. We use a Gillespie algorithm for rapid simulation of the evolutionary dynamics of the constant-size crypt population, consistent with the stability of the Barrett's segment length. We ran 1080 simulations, varying selective mutation rate from 1e-5 to 1e-8, neutral mutation rate from 1e-4 to 1e-7, selective effect of mutations conferring reproductive or survival advantage from 0.001 to 2, and mechanism of clonal expansion probability r from 0 to 1. Our results show that when r is high, clones expand rapidly, selective sweeps occur often and a single dominant clone bearing all reproductive advantage mutations is likely to emerge. When r is low, clones expand slowly, clonal interference occurs often and multiple independent competing clones emerge. This model predicts that genetic diversity increases over time, since a clone only expanded when it acquired mutations conferring quicker crypt division rate, which is coupled to higher stem cell division and mutation rates, thereby generating higher diversity within the expanding clone compared to its surroundings. Our results suggest that designing experiments to measure the rate and mechanism of crypt bifurcation will help distinguish between two neoplastic progression modes: clonal evolution with successive selective sweeps versus multiple independent interfering clones. We also show that sampling few cells from many biopsies estimates the underlying genetic diversity better than sampling many cells from few biopsies. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 101.