Biology subjects

Rice, D. P.

Publications and source records attributed to Rice, D. P..

6 recordsLinked to original sources

bioRxiv2024

Study design and the sampling of deleterious rare variants in biobank-scale datasets

One key component of study design in population genetics is the "geographic breadth" of a sample (i.e., how broad a region across which individuals are sampled). How the geographic breadth of a sample impacts observations of rare, deleterious variants is unclear, even though such variants are of particular interest for biomedical and evolutionary applications. Here, in order to gain insight into the effects of sample design on ascertained genetic variants, we formulate a stochastic model of dispersal, genetic drift, selection, mutation, and geographically concentrated sampling. We use this model to understand the effects of the geographic breadth of sampling effort on the discovery of negatively selected variants. We find that samples which are more geographically broad will discover a greater number variants as compared geographically narrow samples (an effect we label "discovery"); though the variants will be detected at lower average frequency than in narrow samples (e.g. as singletons, an effect we label "dilution"). Importantly, these effects are amplified for larger sample sizes and moderated by the magnitude of fitness effects. We validate these results using both population genetic simulations and empirical analyses in the UK Biobank. Our results are particularly important in two contexts: the association of large-effect rare variants with particular phenotypes and the inference of negative selection from allele frequency data. Overall, our findings emphasize the importance of considering geographic breadth when designing and carrying out genetic studies, especially at biobank scale. SignificanceAs genetic studies grow, researchers are increasingly seeking to identify rare genetic variants with large impacts on traits. In this paper, we combine theoretical methods and data analysis to show how differences in sampling with respect to geographic location can influence the number and frequency of genetic variants that are found. Our results suggest that geographically broad samples will include more distinct genetic variants, though each variant will be found at a lower frequency, as compared to geographically narrow samples. Our results can help researchers to consider the implications of study design on expected results when constructing new genetic samples.

genetics↗

bioRxiv2023

Virus-like DNA tracers for characterizing wastewater-based pathogen monitoring systems

Wastewater-based pathogen monitoring has recently become a ubiquitous method for tracking the abundance and evolution of pathogens in a community or port of entry. But accurate inference of disease incidence from wastewater remains challenging, in large part due to noise and bias arising from wastewater transport and measurement. We developed a new system of tracer particles designed to enhance wastewater monitoring of viral pathogens. These tracers, which consist of synthetic DNA barcodes packaged into non-infectious viral capsids, can be deposited at known amounts and times into the sewer system and measured in wastewater samples to assess features such as assay sensitivity, and the decay and delay in viral signal arising from a shedding event. Here we describe the design, construction, and initial characterization of a 25-plex tracer library. Our tracer library supports simultaneous measurement of up to 5 distinct tracers by qPCR and up to 25 distinct tracers by amplicon or metagenomic sequencing. We demonstrate experimentally that the tracers are biologically inert and exhibit good stability and qPCR-assay performance in wastewater. These features collectively suggest that barcoded, virus-like tracers have the required properties for high-accuracy, high-resolution characterization of wastewater monitoring systems.

synthetic biology↗

bioRxiv2021

Polygenic score accuracy in ancient samples: quantifying the effects of allelic turnover

Polygenic scores link the genotypes of ancient individuals to their phenotypes, which are often unobservable, offering a tantalizing opportunity to reconstruct complex trait evolution. In practice, however, interpretation of ancient polygenic scores is subject to numerous assumptions. For one, the genome-wide association (GWA) studies from which polygenic scores are derived, can only estimate effect sizes for loci segregating in contemporary populations. Therefore, a GWA study may not correctly identify all loci relevant to trait variation in the ancient population. In addition, the frequencies of trait-associated loci may have changed in the intervening years. Here, we devise a theoretical framework to quantify the effect of this allelic turnover on the statistical properties of polygenic scores as functions of population genetic dynamics, trait architecture, power to detect significant loci, and the age of the ancient sample. We model the allele frequencies of loci underlying trait variation using the Wright-Fisher diffusion, and employ the spectral representation of its transition density to find analytical expressions for several error metrics, including the correlation between an ancient individuals polygenic score and true phenotype, referred to as polygenic score accuracy. Our theory also applies to a two-population scenario and demonstrates that allelic turnover alone may explain a substantial percentage of the reduced accuracy observed in cross-population predictions, akin to those performed in human genetics. Finally, we use simulations to explore the effects of recent directional selection, a bias-inducing process, on the statistics of interest. We find that even in the presence of bias, weak selection induces minimal deviations from our neutral expectations for the decay of polygenic score accuracy. By quantifying the limitations of polygenic scores in an explicit evolutionary context, our work lays the foundation for the development of more sophisticated statistical procedures to analyze both temporally and geographically resolved polygenic scores.

genetics↗

bioRxiv2020

Geographic patterns of human allele frequency variation: a variant-centric perspective

A key challenge in human genetics is to describe and understand the distribution of human genetic variation. Often genetic variation is described by showing relationships among populations or individuals, in each case drawing inferences over a large number of variants. Here, we present an alternative representation of human genetic variation that reveals the relative abundance of different allele frequency patterns across populations. This approach allows viewers to easily see several features of human genetic structure: (1) most variants are rare and geographically localized, (2) variants that are common in a single geographic region are more likely to be shared across the globe than to be private to that region, and (3) where two individuals differ, it is most often due to variants that are common globally, regardless of whether the individuals are from the same region or different regions. To guide interpretation of the results, we also apply the visualization to contrasting theoretical scenarios with varying levels of divergence and gene flow. Our variant-centric visualization clarifies the major geographic patterns of human variation and can be used to help correct potential misconceptions about the extent and nature of genetic differentiation among populations.

evolutionary biology↗

bioRxiv2018

Distinguishing multiple-merger from Kingman coalescence using two-site frequency spectra

Demographic inference methods in population genetics typically assume that the ancestry of a sample can be modeled by the Kingman coalescent. A defining feature of this stochastic process is that it generates genealogies that are binary trees: no more than two ancestral lineages may coalesce at the same time. However, this assumption breaks down under several scenarios. For example, pervasive natural selection and extreme variation in offspring number can both generate genealogies with "multiple-merger" events in which more than two lineages coalesce instantaneously. Therefore, detecting multiple mergers (and other violations of the Kingman assumptions) is important both for understanding which forces have shaped the diversity of a population and for avoiding fitting misspecified models to data. Current methods to detect multiple mergers in genomic data rely primarily on the site frequency spectrum (SFS). However, the signatures of multiple mergers in the SFS are also consistent with a Kingman coalescent with a time-varying population size. Here, we present a new statistical test for determining whether the Kingman coalescent with any population size history is consistent with population data. Our approach is based on information contained in the two-site joint frequency spectrum (2-SFS) for pairs of linked sites, which has a different dependence on the topologies of genealogies than the SFS. Our statistical test is global in the sense that it can detect when the genome-wide genetic diversity is inconsistent with the Kingman model, rather than detecting outlier regions, as in selection scan methods. We validate this test using simulations, and then apply it to demonstrate that genomic diversity data from Drosophila melanogaster is inconsistent with the Kingman coalescent.

evolutionary biology↗

bioRxiv2017

Long-term adaptive evolution of genomically recoded Escherichia coli

Efforts are underway to construct several recoded genomes anticipated to exhibit multi-virus resistance, enhanced non-standard amino acid (NSAA) incorporation, and capability for synthetic biocontainment. Though we succeeded in pioneering the first genomically recoded organism (Escherichia coli strain C321.{Delta}A), its fitness is far lower than that of its non-recoded ancestor, particularly in defined media. This fitness deficit severely limits its utility for NSAA-linked applications requiring defined media such as live cell imaging, metabolic engineering, and industrial-scale protein production. Here, we report adaptive evolution of C321.{Delta}A for more than 1,000 generations in independent replicate populations grown in glucose minimal media. Evolved recoded populations significantly exceed the growth rates of both the ancestral C321.{Delta}A and non-recoded strains, permitting use of the recoded chassis in several new contexts. We use next-generation sequencing to identify genes mutated in multiple independent populations, and we reconstruct individual alleles in ancestral strains via multiplex automatable genome engineering (MAGE) to quantify their effects on fitness. Several selective mutations occur only in recoded evolved populations, some of which are associated with altering the translation apparatus in response to recoding, whereas others are not apparently associated with recoding, but instead correct for off-target mutations that occurred during initial genome engineering. This report demonstrates that laboratory evolution can be applied after engineering of recoded genomes to streamline fitness recovery compared to application of additional targeted engineering strategies that may introduce further unintended mutations. In doing so, we provide the most comprehensive insight to date into the physiology of the commonly used C321.{Delta}A strain.\n\nSignificance StatementAfter demonstrating construction of an organism with an altered genetic code, we sought to evolve this organism for many generations to improve its fitness and learn what unique changes natural selection would bestow upon it. Although this organism initially had impaired fitness, we observed that adaptive laboratory evolution resulted in several selective mutations that corrected for insufficient translation termination and for unintended mutations that occurred when originally altering the genetic code. This work further bolsters our understanding of the pliability of the genetic code, it will help guide ongoing and future efforts seeking to recode genomes, and it results in a useful strain for non-standard amino acid incorporation in numerous contexts relevant for research and industry.

evolutionary biology↗