Biology subjects

Ralph, P. L.

Publications and source records attributed to Ralph, P. L..

5 recordsLinked to original sources

bioRxiv2018

Are populations like a circuit? The relationship between isolation by distance and isolation by resistance

A number of methods commonly used in landscape genetics use an analogy to electrical resistance on a network to describe and fit barriers to movement across the landscape using genetic distance data. These are motivated by a mathematical equivalence between electrical resistance between two nodes of a network and the \"commute time\", which is the mean time for a random walk on that network to leave one node, visit the other, and return. However, genetic data are more accurately modeled by a different quantity, the coalescence time. Here, we describe the differences between resistance distance and coalescence time, and explore the consequences for inference. We implement a Bayesian method to infer effective movement rates and population sizes under both these models, and find that inference using commute times can produce misleading results in the presence of biased gene flow. We then use forwards-time simulation with continuous geography to demonstrate that coalescence-based inference remains more accurate than resistance-based methods on realistic data, but difficulties highlight the need for methods that explicitly model continuous, heterogeneous geography.

evolutionary biology↗

bioRxiv2018

Tree-sequence recording in SLiM opens new horizons for forward-time simulation of whole genomes

There is an increasing demand for evolutionary models to incorporate relatively realistic dynamics, ranging from selection at many genomic sites to complex demography, population structure, and ecological interactions. Such models can generally be implemented as individual-based forward simulations, but the large computational overhead of these models often makes simulation of whole chromosome sequences in large populations infeasible. This situation presents an important obstacle to the field that requires conceptual advances to overcome. The recently developed tree-sequence recording method (Kelleher et al., 2018), which stores the genealogical history of all genomes in the simulated population, could provide such an advance. This method has several benefits: (1) it allows neutral mutations to be omitted entirely from forward-time simulations and added later, thereby dramatically improving computational efficiency; (2) it allows neutral burn-in to be constructed extremely efficiently after the fact, using \"recapitation\"; (3) it allows direct examination and analysis of the genealogical trees along the genome; and (4) it provides a compact representation of a populations genealogy that can be analyzed in Python using the msprime package. We have implemented the tree-sequence recording method in SLiM 3 (a free, open-source evolutionary simulation software package) and extended it to allow the recording of non-neutral mutations, greatly broadening the utility of this method. To demonstrate the versatility and performance of this approach, we showcase several practical applications that would have been beyond the reach of previously existing methods, opening up new horizons for the modeling and exploration of evolutionary processes.

evolutionary biology↗

bioRxiv2018

The tempo of linked selection: emergence of a heterogeneous genomic landscape during a recent radiation of monkeyflowers

Speciation genomic studies aim to interpret patterns of genome-wide variation in light of the processes that give rise to new species. However, interpreting the genomic landscape of speciation is difficult, because many evolutionary processes can impact levels of variation. Facilitated by the first chromosome-level assembly for the group, we use whole-genome sequencing and simulations to shed light on the processes that have shaped the genomic landscape during a recent radiation of monkeyflowers. After inferring the phylogenetic relationships among the nine taxa in this radiation, we show that highly similar diversity ({pi}) and differentiation (FST) landscapes have emerged across the group. Variation in these landscapes was strongly predicted by the local density of functional elements and the recombination rate, suggesting that the landscapes have been shaped by widespread natural selection. Using the varying divergence times between pairs of taxa, we show that the correlations between FST and genome features arose almost immediately after a population split and have become stronger over time. Simulations of genomic landscape evolution suggest that background selection (i.e., selection against deleterious mutations) alone is too subtle to generate the observed patterns, but scenarios that involve positive selection and genetic incompatibilities are plausible alternative explanations. Finally, tests for introgression among these taxa reveal widespread evidence of heterogeneous selection against gene flow during this radiation. Thus, combined with existing evidence for adaptation in this system, we conclude that the correlation in FST among these taxa informs us about the genomic basis of adaptation and speciation in this system.\n\nAuthor summaryWhat can patterns of genome-wide variation tell us about the speciation process? The answer to this question depends upon our ability to infer the evolutionary processes underlying these patterns. This, however, is difficult, because many processes can leave similar footprints, but some have nothing to do with speciation per se. For example, many studies have found highly heterogeneous levels of genetic differentiation when comparing the genomes of emerging species. These patterns are often referred to as differentiation landscapes because they appear as a rugged topography of peaks and valleys as one scans across the genome. It has often been argued that selection against deleterious mutations, a process referred to as background selection, is primarily responsible for shaping differentiation landscapes early in speciation. If this hypothesis is correct, then it is unlikely that patterns of differentiation will reveal much about the genomic basis of speciation. However, using genome sequences from nine emerging species of monkeyflower coupled with simulations of genomic divergence, we show that it is unlikely that background selection is the primary architect of these landscapes. Rather, differentiation landscapes have probably been shaped by adaptation and gene flow, which are processes that are central to our understanding of speciation. Therefore, our work has important implications for our understanding of what patterns of differentiation can tell us about the genetic basis of adaptation and speciation.

evolutionary biology↗

bioRxiv2017

System drift and speciation

Even if a species phenotype does not change over evolutionary time, the underlying mechanism may change, as distinct molecular pathways can realize identical phenotypes. Here we use linear system theory to explore the consequences of this idea, describing how a gene network underlying a conserved phenotype evolves, as the genetic drift of small changes to these molecular pathways cause a population to explore the set of mechanisms with identical phenotypes. To do this, we model an organisms internal state as a linear system of differential equations for which the environment provides input and the phenotype is the output, in which context there exists an exact characterization of the set of all mechanisms that give the same input-output relationship. This characterization implies that selectively neutral directions in genotype space should be common and that the evolutionary exploration of these distinct but equivalent mechanisms can lead to the reproductive incompatibility of independently evolving populations. This evolutionary exploration, or system drift, is expected to proceed at a rate proportional to the amount of intrapopulation genetic variation divided by the effective population size (Ne). At biologically reasonable parameter values this could lead to substantial interpopulation incompatibility, and thus speciation, on a time scale of Ne generations. This model also naturally predicts Haldanes rule, thus providing a concrete explanation of why heterogametic hybrids tend to be disrupted more often than homogametes during the early stages of speciation.

evolutionary biology↗

bioRxiv2017

Desert Tortoises in the Genomic Age: Population Genetics and the Landscape

The California Department of Fish and Wildlife (CDFW) provided research funds to study the conservation genomics and landscape genomics of the Mojave desert tortoise, Gopherus agassizii, in response to the Desert Renewable Energy Conservation Plan (DRECP). To do this, we consolidated tissue samples of the desert tortoise from across the species range within California and southern Nevada, generated a DNA dataset consisting of full genomes of 270 tortoises, and analyzed the way in which the environment of the desert tortoise has determined modern patterns of relatedness and genetic diversity across the landscape. Here we present the implications of these results for the conservation and landscape genomics of the desert tortoise. Our work strongly indicates that several well-defined genetic groups exist within the species, including a primary north-south genetic discontinuity at the Ivanpah Valley and another separating western from eastern Mojave samples. We also use existing desert tortoise habitat modeling data with a novel extension of genetic \"resistance distance\" using geographic maps of continuous space to predict the relative impacts of five proposed development alternatives within the DRECP and rank them with respect to their likely impacts on desert tortoise gene flow and connectivity in the Mojave. Finally, we analyzed the impacts of each of the 214 distinct proposed development area \"chunks,\" derived from the proposed development polygons, and ranked each chunk in terms of its range-wide impacts on desert tortoise gene flow.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC=\"FIGDIR/small/195743_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (147K):\norg.highwire.dtl.DTLVardef@b60416org.highwire.dtl.DTLVardef@1c649f2org.highwire.dtl.DTLVardef@120e625org.highwire.dtl.DTLVardef@e59b34_HPS_FORMAT_FIGEXP M_FIG C_FIG PrefaceO_ST_ABSContextC_ST_ABSThe following document is a report that was submitted to the California Department of Fish and Wildlife, describing a series of analyses to help understand the impacts of several alternative spatial configurations of renewable energy development on gene flow of the federally threatened Mojave desert tortoise. These development alternatives were the centerpiece of the Desert Renewable Energy Conservation Plan (DRECP), a landscape-level land use planning initiative undertaken by the Bureau of Land Management (BLM), U.S. Fish and Wildlife Service (USFWS), California Energy Commission (CEC), and the California Department of Fish and Wildlife (CDFW). We were tasked by the California Department of Fish and Wildlife with providing a detailed analysis of these alternative plans on desert tortoise gene flow, and submitted the report for the public comment period for the initial implementation of the DRECP.\n\nFuture PlansO_ST_ABSCurrent state of landscape-level planning for the Mojave desert tortoiseC_ST_ABSThe five proposed land use configuration alternatives analyzed in the subsequent report include public and private lands spread across several counties in California. Shortly after the end of the DRECPs public comment period, the government agencies that developed the DRECP announced that they would be splitting its implementation into two phases: one that deals with land use decisions on BLM-controlled lands and one that deals with non-BLM areas (Sahagun 2015).\n\nPhase I of the DRECP was approved by the Bureau of Land Management on September 14, 2016 (U.S. Bureau of Land Management 2016). This phase includes land use planning decisions for BLM-administered lands. Specifically, 388,000 acres of public lands were designated as development focus areas (DFAs). In applications for leasing lands for renewable energy development, DFAs will not require the same degree of environmental evaluation prior to permitting, as theyve already been evaluated in the context of the DRECP. The application process for renewable energy development within DFAs will be streamlined to encourage development in these areas. Phase I also designated a total of 6,527,000 acres for natural resource conservation. This includes California Desert National Conservation Lands, Areas of Critical Environmental Concern, and Wildlife Allocations. A further 2,691,000 acres were designated for recreation under Phase I. Phase II of the DRECP is currently under development in conjunction with county-level governments to extend this landscape-level planning beyond BLM-administered lands.\n\nAuthor ContributionsThis was a collaborative report. Evan McCartney-Melstad performed the simulations of the low-coverage full genome approach (see Figure 2); conducted all of the laboratory work to generate the genome sequences; performed all of the bioinformatic analyses to bring the raw sequence data to the various stages required for different analyses; wrote the software to quickly estimate pairwise genetic relationships between individuals using read count data in low coverage sequence data (www.github.com/atcg/cPWP); performed some of the population genetic analyses; and wrote and edited several sections of the report.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC=\"FIGDIR/small/195743_fig2.gif\" ALT=\"Figure 2\">\nView larger version (16K):\norg.highwire.dtl.DTLVardef@30a49forg.highwire.dtl.DTLVardef@187c3d8org.highwire.dtl.DTLVardef@4abe98org.highwire.dtl.DTLVardef@126febe_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 2.C_FLOATNO Comparison of two different sequencing approaches in their ability to differentiate very slightly differentiated populations (Fst=0.001)\n\nC_FIG Peter Ralph (in collaboration with Gideon Bradburd and Erik Lundgren) invented and implemented the random walk-based gene flow model that we used to estimate reductions in gene flow due to development, and also developed the theory behind the read-based pairwise pi and genetic covariance estimation used here, in addition to writing and editing several sections of the report. Gideon Bradburd also performed some of the population genetic analyses and wrote and edited several sections of the report. Jannet Vu collected and curated the spatial environmental data and generated the maps that are included in the report (Figures 10, A10-A13), and also wrote Appendices I and IV. Bridgette Hagerty, Fran Sandmeier, Chava Weitzman, and C. Richard Tracy contributed approximately 1,000 desert tortoise blood samples that they collected (at great effort), in addition to knowledge of tortoise ecology and conservation, as well as the results of previous microsatellite-based genetic analyses and editing of the report. H. Bradley Shaffer wrote and edited several sections of the report, and is listed as the lead author for his role in conceiving of and obtaining funding support for the project.\n\nO_FIG O_LINKSMALLFIG WIDTH=154 HEIGHT=200 SRC=\"FIGDIR/small/195743_fig10.gif\" ALT=\"Figure 10\">\nView larger version (82K):\norg.highwire.dtl.DTLVardef@11e99acorg.highwire.dtl.DTLVardef@1faf2f5org.highwire.dtl.DTLVardef@64c440org.highwire.dtl.DTLVardef@1907837_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 10.C_FLOATNO Spatial configuration of the proposed development chunks (see Appendix 4).\n\nC_FIG

evolutionary biology↗