2,793 research outputs found
Fundamental limits on the accuracy of demographic inference based on the sample frequency spectrum
The sample frequency spectrum (SFS) of DNA sequences from a collection of
individuals is a summary statistic which is commonly used for parametric
inference in population genetics. Despite the popularity of SFS-based inference
methods, currently little is known about the information-theoretic limit on the
estimation accuracy as a function of sample size. Here, we show that using the
SFS to estimate the size history of a population has a minimax error of at
least , where is the number of independent segregating sites
used in the analysis. This rate is exponentially worse than known convergence
rates for many classical estimation problems in statistics. Another surprising
aspect of our theoretical bound is that it does not depend on the dimension of
the SFS, which is related to the number of sampled individuals. This means
that, for a fixed number of segregating sites considered, using more
individuals does not help to reduce the minimax error bound. Our result
pertains to populations that have experienced a bottleneck, and we argue that
it can be expected to apply to many populations in nature.Comment: 17 pages, 1 figur
Multi-locus analysis of genomic time series data from experimental evolution.
Genomic time series data generated by evolve-and-resequence (E&R) experiments offer a powerful window into the mechanisms that drive evolution. However, standard population genetic inference procedures do not account for sampling serially over time, and new methods are needed to make full use of modern experimental evolution data. To address this problem, we develop a Gaussian process approximation to the multi-locus Wright-Fisher process with selection over a time course of tens of generations. The mean and covariance structure of the Gaussian process are obtained by computing the corresponding moments in discrete-time Wright-Fisher models conditioned on the presence of a linked selected site. This enables our method to account for the effects of linkage and selection, both along the genome and across sampled time points, in an approximate but principled manner. We first use simulated data to demonstrate the power of our method to correctly detect, locate and estimate the fitness of a selected allele from among several linked sites. We study how this power changes for different values of selection strength, initial haplotypic diversity, population size, sampling frequency, experimental duration, number of replicates, and sequencing coverage depth. In addition to providing quantitative estimates of selection parameters from experimental evolution data, our model can be used by practitioners to design E&R experiments with requisite power. We also explore how our likelihood-based approach can be used to infer other model parameters, including effective population size and recombination rate. Then, we apply our method to analyze genome-wide data from a real E&R experiment designed to study the adaptation of D. melanogaster to a new laboratory environment with alternating cold and hot temperatures
The In-Hospital Mortality Rates of Slaves and Freemen: Evidence from Touro Infirmary, New Orleans, Louisiana, 1855–1860
Using a rich sample of admission records from New Orleans Touro Infirmary, we examine the in-hospital mortality risk of free and enslaved patients. Despite a higher mortality rate in the general population, slaves were significantly less likely to die in the hospital than the whites. We analyze the determinants of in-hospital mortality at Touro using Oaxaca-type decomposition to aggregate our regression results. After controlling for differences in characteristics and maladies, we find that much of the mortality gap remains unexplained. In conclusion, we propose an alternative explanation for the mortality gap based on the selective hospital admission of slaves.hospital, slavery, Oaxaca-type decomposition, New Orleans, Touro
Inference of Population History using Coalescent HMMs: Review and Outlook
Studying how diverse human populations are related is of historical and
anthropological interest, in addition to providing a realistic null model for
testing for signatures of natural selection or disease associations.
Furthermore, understanding the demographic histories of other species is
playing an increasingly important role in conservation genetics. A number of
statistical methods have been developed to infer population demographic
histories using whole-genome sequence data, with recent advances focusing on
allowing for more flexible modeling choices, scaling to larger data sets, and
increasing statistical power. Here we review coalescent hidden Markov models, a
powerful class of population genetic inference methods that can effectively
utilize linkage disequilibrium information. We highlight recent advances, give
advice for practitioners, point out potential pitfalls, and present possible
future research directions.Comment: 12 pages, 2 figure
Cryo-EM structures of herpes simplex virus type 1 portal vertex and packaged genome.
Herpesviruses are enveloped viruses that are prevalent in the human population and are responsible for diverse pathologies, including cold sores, birth defects and cancers. They are characterized by a highly pressurized pseudo-icosahedral capsid-with triangulation number (T) equal to 16-encapsidating a tightly packed double-stranded DNA (dsDNA) genome1-3. A key process in the herpesvirus life cycle involves the recruitment of an ATP-driven terminase to a unique portal vertex to recognize, package and cleave concatemeric dsDNA, ultimately giving rise to a pressurized, genome-containing virion4,5. Although this process has been studied in dsDNA phages6-9-with which herpesviruses bear some similarities-a lack of high-resolution in situ structures of genome-packaging machinery has prevented the elucidation of how these multi-step reactions, which require close coordination among multiple actors, occur in an integrated environment. To better define the structural basis of genome packaging and organization in herpes simplex virus type 1 (HSV-1), we developed sequential localized classification and symmetry relaxation methods to process cryo-electron microscopy (cryo-EM) images of HSV-1 virions, which enabled us to decouple and reconstruct hetero-symmetric and asymmetric elements within the pseudo-icosahedral capsid. Here we present in situ structures of the unique portal vertex, genomic termini and ordered dsDNA coils in the capsid spooled around a disordered dsDNA core. We identify tentacle-like helices and a globular complex capping the portal vertex that is not observed in phages, indicative of herpesvirus-specific adaptations in the DNA-packaging process. Finally, our atomic models of portal vertex elements reveal how the fivefold-related capsid accommodates symmetry mismatch imparted by the dodecameric portal-a longstanding mystery in icosahedral viruses-and inform possible DNA-sequence recognition and headful-sensing pathways involved in genome packaging. This work showcases how to resolve symmetry-mismatched elements in a large eukaryotic virus and provides insights into the mechanisms of herpesvirus genome packaging
The in-hospital mortality rates of slaves and freemen: evidence from Touro infirmary, New Orleans, Louisiana, 1855 - 1860
Using a rich sample of admission records from New Orleans Touro Infirmary, we examine the in-hospital mortality risk of free and enslaved patients. Despite a higher mortality rate in the general population, slaves were significantly less likely to die in the hospital than the whites. We analyze the determinants of in-hospital mortality at Touro using Oaxaca-type decomposition to aggregate our regression results. After controlling for differences in characteristics and maladies, we find that much of the mortality gap remains unexplained. In conclusion, we propose an alternative explanation for the mortality gap based on the selective hospital admission of slaves
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