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Rasmus Nielsen

Publications and source records attributed to Rasmus Nielsen.

At least 37 records · Page 2Linked to original sources

Bayesian and maximum likelihood estimation of genetic maps.

There has recently been increased interest in the use of Markov Chain Monte Carlo (MCMC)-based Bayesian methods for estimating genetic maps. The advantage of these methods is that they can deal accurately with missing data and genotyping errors. Here we present an extension of the previous methods that makes the Bayesian method applicable to large data sets. We present an extensive simulation study examining the statistical properties of the method and comparing it with the likelihood method implemented in Mapmaker. We show that the Maximum A Posteriori (MAP) estimator of the genetic distances, corresponding to the maximum likelihood estimator, performs better than estimators based on the posterior expectation. We also show that while the performance is similar between Mapmaker and the MCMC-based method in the absence of genotyping errors, the MCMC-based method has a distinct advantage in the presence of genotyping errors. A similar advantage of the Bayesian method was not observed for missing data. We also re-analyse a recently published set of data from the eggplant and show that the use of the MCMC-based method leads to smaller estimates of genetic distances.

Algorithms↗

Detecting coevolving amino acid sites using Bayesian mutational mapping.

MOTIVATION: The evolution of protein sequences is constrained by complex interactions between amino acid residues. Because harmful substitutions may be compensated for by other substitutions at neighboring sites, residues can coevolve. We describe a Bayesian phylogenetic approach to the detection of coevolving residues in protein families. This method, Bayesian mutational mapping (BMM), assigns mutations to the branches of the evolutionary tree stochastically, and then test statistics are calculated to determine whether a coevolutionary signal exists in the mapping. Posterior predictive P-values provide an estimate of significance, and specificity is maintained by integrating over uncertainty in the estimation of the tree topology, branch lengths and substitution rates. A coevolutionary Markov model for codon substitution is also described, and this model is used as the basis of several test statistics. RESULTS: Results on simulated coevolutionary data indicate that the BMM method can successfully detect nearly all coevolving sites when the model has been correctly specified, and that non-parametric statistics such as mutual information are generally less powerful than parametric statistics. On a dataset of eukaryotic proteins from the phosphoglycerate kinase (PGK) family, interdomain site contacts yield a significantly greater coevolutionary signal than interdomain non-contacts, an indication that the method provides information about interacting sites. Failure to account for the heterogeneity in rates across sites in PGK resulted in a less discriminating test, yielding a marked increase in the number of reported positives at both contact and non-contact sites. SUPPLEMENTARY INFORMATION: http://www.dimmic.net/supplement/

Amino Acids↗

Comparative genome sequencing of Drosophila pseudoobscura: chromosomal, gene, and cis-element evolution.

We have sequenced the genome of a second Drosophila species, Drosophila pseudoobscura, and compared this to the genome sequence of Drosophila melanogaster, a primary model organism. Throughout evolution the vast majority of Drosophila genes have remained on the same chromosome arm, but within each arm gene order has been extensively reshuffled, leading to a minimum of 921 syntenic blocks shared between the species. A repetitive sequence is found in the D. pseudoobscura genome at many junctions between adjacent syntenic blocks. Analysis of this novel repetitive element family suggests that recombination between offset elements may have given rise to many paracentric inversions, thereby contributing to the shuffling of gene order in the D. pseudoobscura lineage. Based on sequence similarity and synteny, 10,516 putative orthologs have been identified as a core gene set conserved over 25-55 million years (Myr) since the pseudoobscura/melanogaster divergence. Genes expressed in the testes had higher amino acid sequence divergence than the genome-wide average, consistent with the rapid evolution of sex-specific proteins. Cis-regulatory sequences are more conserved than random and nearby sequences between the species--but the difference is slight, suggesting that the evolution of cis-regulatory elements is flexible. Overall, a pattern of repeat-mediated chromosomal rearrangement, and high coadaptation of both male genes and cis-regulatory sequences emerges as important themes of genome divergence between these species of Drosophila.

Animals↗

Ascertainment bias in studies of human genome-wide polymorphism.

Large-scale SNP genotyping studies rely on an initial assessment of nucleotide variation to identify sites in the DNA sequence that harbor variation among individuals. This "SNP discovery" sample may be quite variable in size and composition, and it has been well established that properties of the SNPs that are found are influenced by the discovery sampling effort. The International HapMap project relied on nearly any piece of information available to identify SNPs-including BAC end sequences, shotgun reads, and differences between public and private sequences-and even made use of chimpanzee data to confirm human sequence differences. In addition, the ascertainment criteria shifted from using only SNPs that had been validated in population samples, to double-hit SNPs, to finally accepting SNPs that were singletons in small discovery samples. In contrast, Perlegen's primary discovery was a resequencing-by-hybridization effort using the 24 people of diverse origin in the Polymorphism Discovery Resource. Here we take these two data sets and contrast two basic summary statistics, heterozygosity and F(ST), as well as the site frequency spectra, for 500-kb windows spanning the genome. The magnitude of disparity between these samples in these measures of variability indicates that population genetic analysis on the raw genotype data is ill advised. Given the knowledge of the discovery samples, we perform an ascertainment correction and show how the post-correction data are more consistent across these studies. However, discrepancies persist, suggesting that the heterogeneity in the SNP discovery process of the HapMap project resulted in a data set resistant to complete ascertainment correction. Ascertainment bias will likely erode the power of tests of association between SNPs and complex disorders, but the effect will likely be small, and perhaps more importantly, it is unlikely that the bias will introduce false-positive inferences.

Databases, Genetic↗

Genomic scans for selective sweeps using SNP data.

Detecting selective sweeps from genomic SNP data is complicated by the intricate ascertainment schemes used to discover SNPs, and by the confounding influence of the underlying complex demographics and varying mutation and recombination rates. Current methods for detecting selective sweeps have little or no robustness to the demographic assumptions and varying recombination rates, and provide no method for correcting for ascertainment biases. Here, we present several new tests aimed at detecting selective sweeps from genomic SNP data. Using extensive simulations, we show that a new parametric test, based on composite likelihood, has a high power to detect selective sweeps and is surprisingly robust to assumptions regarding recombination rates and demography (i.e., has low Type I error). Our new test also provides estimates of the location of the selective sweep(s) and the magnitude of the selection coefficient. To illustrate the method, we apply our approach to data from the Seattle SNP project and to Chromosome 2 data from the HapMap project. In Chromosome 2, the most extreme signal is found in the lactase gene, which previously has been shown to be undergoing positive selection. Evidence for selective sweeps is also found in many other regions, including genes known to be associated with disease risk such as DPP10 and COL4A3.

Black or African American↗

Molecular signatures of natural selection.

There is an increasing interest in detecting genes, or genomic regions, that have been targeted by natural selection. The interest stems from a basic desire to learn more about evolutionary processes in humans and other organisms, and from the realization that inferences regarding selection may provide important functional information. This review provides a nonmathematical description of the issues involved in detecting selection from DNA sequences and SNP data and is intended for readers who are not familiar with population genetic theory. Particular attention is placed on issues relating to the analysis of large-scale genomic data sets.

Animals↗

Adaptive evolution of cytochrome c oxidase: Infrastructure for a carnivorous plant radiation.

Much recent attention in the study of adaptation of organismal form has centered on developmental regulation. As such, the highly conserved respiratory machinery of eukaryotic cells might seem an unlikely target for selection supporting novel morphologies. We demonstrate that a dramatic molecular evolutionary rate increase in subunit I of cytochrome c oxidase (COX) from an active-trapping lineage of carnivorous plants is caused by positive Darwinian selection. Bladderworts (Utricularia) trap plankton when water-immersed, negatively pressured suction bladders are triggered. The resetting of traps involves active ion transport, requiring considerable energy expenditure. As judged from the quaternary structure of bovine COX, the most profound adaptive substitutions are two contiguous cysteines absent in approximately 99.9% of databased COX I sequences from Eukaryota, Archaea, and Bacteria. This motif lies directly at the docking point of COX I helix 3 and cytochrome c, and modeling of bovine COX I suggests the possibility of an unprecedented helix-terminating disulfide bridge that could alter COX/cytochrome c dissociation kinetics. Thus, the key adaptation in Utricularia likely lies in molecular energetic changes that buttressed the mechanisms responsible for the bladderworts' radical morphological evolution. Along with evidence for COX evolution underlying expansion of the anthropoid neocortex, our findings underscore that important morphological and physiological innovations must often be accompanied by specific adaptations in proteins with basic cellular functions.

Adenosine Triphosphate↗

The population structure of African cultivated rice oryza glaberrima (Steud.): evidence for elevated levels of linkage disequilibrium caused by admixture with O. sativa and ecological adaptation.

Genome-wide linkage disequilibrium (LD) was investigated for 198 accessions of Oryza glaberrima using 93 nuclear microsatellite markers. Significantly elevated levels of LD were detected, even among distantly located markers. Free recombination among loci at the population genetic level was shown (1) by a lack of decay in LD among markers on the same chromosome and (2) by a strictly increasing composite likelihood function for the recombination parameter. This suggested that the elevation in LD was due not to physical linkage but to other factors, such as population structure. A Bayesian clustering analysis confirmed this hypothesis, indicating that the sample of O. glaberrima in this study was subdivided into at least five cryptic subpopulations. Two of these subpopulations clustered with control samples of O. sativa, subspecies indica and japonica, indicating that some O. glaberrima accessions represent admixtures. The remaining three O. glaberrima subpopulations were significantly associated with specific combinations of phenotypic traits-possibly reflecting ecological adaptation to different growing environments.

Acclimatization↗

Reconstituting the frequency spectrum of ascertained single-nucleotide polymorphism data.

Most of the available SNP data have eluded valid population genetic analysis because most population genetical methods do not correctly accommodate the special discovery process used to identify SNPs. Most of the available SNP data have allele frequency distributions that are biased by the ascertainment protocol. We here show how this problem can be corrected by obtaining maximum-likelihood estimates of the true allele frequency distribution. In simple cases, the ML estimate of the true allele frequency distribution can be obtained analytically, but in other cases computational methods based on numerical optimization or the EM algorithm must be used. We illustrate the new correction method by analyzing some previously published SNP data from the SNP Consortium. Appropriate treatment of SNP ascertainment is vital to our ability to make correct inferences from the data of the International HapMap Project.

Alleles↗

Using nuclear haplotypes with microsatellites to study gene flow between recently separated Cichlid species.

When populations or species have recently separated they often share genetic variation. However, it can be difficult to determine whether shared polymorphisms are the result of gene flow, the result of the persistence of variation in both populations since the time of common ancestry, or both of these factors. We have developed an empirical protocol for using loci that include unique nuclear DNA sequence haplotypes together with linked microsatellites or short tandem repeats (STRs). These 'HapSTRs' offer the potentially high resolution associated with the high mutation rate of STRs, together with the advantages of low homoplasy of unique sequence DNA. We also describe a new procedure for estimating the likelihood of HapSTR data under an Isolation with Migration model. An example using Cichlid fishes from Lake Malawi is described. The analysis suggests that the species have been exchanging genes since the time they began to diverge.

Animals↗

Population genetic analysis of ascertained SNP data.

The large single nucleotide polymorphism (SNP) typing projects have provided an invaluable data resource for human population geneticists. Almost all of the available SNP loci, however, have been identified through a SNP discovery protocol that will influence the allelic distributions in the sampled loci. Standard methods for population genetic analysis based on the available SNP data will, therefore, be biased. This paper discusses the effect of this ascertainment bias on allelic distributions and on methods for quantifying linkage disequilibrium and estimating demographic parameters. Several recently developed methods for correcting for the ascertainment bias will also be discussed.

Bias↗

Detecting selection in noncoding regions of nucleotide sequences.

We present a maximum-likelihood method for examining the selection pressure and detecting positive selection in noncoding regions using multiple aligned DNA sequences. The rate of substitution in noncoding regions relative to the rate of synonymous substitution in coding regions is modeled by a parameter zeta. When a site in a noncoding region is evolving neutrally zeta = 1, while zeta > 1 indicates the action of positive selection, and zeta < 1 suggests negative selection. Using a combined model for the evolution of noncoding and coding regions, we develop two likelihood-ratio tests for the detection of selection in noncoding regions. Data analysis of both simulated and real viral data is presented. Using the new method we show that positive selection in viruses is acting primarily in protein-coding regions and is rare or absent in noncoding regions.

Base Sequence↗

Microsatellite mutation models: insights from a comparison of humans and chimpanzees.

Using genomic data from homologous microsatellite loci of pure AC repeats in humans and chimpanzees, several models of microsatellite evolution are tested and compared using likelihood-ratio tests and the Akaike information criterion. A proportional-rate, linear-biased, one-phase model emerges as the best model. A focal length toward which the mutational and/or substitutional process is linearly biased is a crucial feature of microsatellite evolution. We find that two-phase models do not lead to a significantly better fit than their one-phase counterparts. The performance of models based on the fit of their stationary distributions to the empirical distribution of microsatellite lengths in the human genome is consistent with that based on the human-chimp comparison. Microsatellites interrupted by even a single point mutation exhibit a twofold decrease in their mutation rate when compared to pure AC repeats. In general, models that allow chimps to have a larger per-repeat unit slippage rate and/or a shorter focal length compared to humans give a better fit to the human-chimp data as well as the human genomic data.

Animals↗

Multilocus methods for estimating population sizes, migration rates and divergence time, with applications to the divergence of Drosophila pseudoobscura and D. persimilis.

The genetic study of diverging, closely related populations is required for basic questions on demography and speciation, as well as for biodiversity and conservation research. However, it is often unclear whether divergence is due simply to separation or whether populations have also experienced gene flow. These questions can be addressed with a full model of population separation with gene flow, by applying a Markov chain Monte Carlo method for estimating the posterior probability distribution of model parameters. We have generalized this method and made it applicable to data from multiple unlinked loci. These loci can vary in their modes of inheritance, and inheritance scalars can be implemented either as constants or as parameters to be estimated. By treating inheritance scalars as parameters it is also possible to address variation among loci in the impact via linkage of recurrent selective sweeps or background selection. These methods are applied to a large multilocus data set from Drosophila pseudoobscura and D. persimilis. The species are estimated to have diverged approximately 500,000 years ago. Several loci have nonzero estimates of gene flow since the initial separation of the species, with considerable variation in gene flow estimates among loci, in both directions between the species.

Animals↗

Linkage disequilibrium as a signature of selective sweeps.

The hitchhiking effect of a beneficial mutation, or a selective sweep, generates a unique distribution of allele frequencies and spatial distribution of polymorphic sites. A composite-likelihood test was previously designed to detect these signatures of a selective sweep, solely on the basis of the spatial distribution and marginal allele frequencies of polymorphisms. As an excess of linkage disequilibrium (LD) is also known to be a strong signature of a selective sweep, we investigate how much statistical power is increased by the inclusion of information regarding LD. The expected pattern of LD is predicted by a genealogical approach. Both theory and simulation suggest that strong LD is generated in narrow regions at both sides of the location of beneficial mutation. However, a lack of LD is expected across the two sides. We explore various ways to detect this signature of selective sweeps by statistical tests. A new composite-likelihood method is proposed to incorporate information regarding LD. This method enables us to detect selective sweeps and estimate the parameters of the selection model better than the previous composite-likelihood method that does not take LD into account. However, the improvement made by including LD is rather small, suggesting that most of the relevant information regarding selective sweeps is captured by the spatial distribution and marginal allele frequencies of polymorphisms.

Computer Simulation↗

Accuracy and power of statistical methods for detecting adaptive evolution in protein coding sequences and for identifying positively selected sites.

The parsimony method of Suzuki and Gojobori (1999) and the maximum likelihood method developed from the work of Nielsen and Yang (1998) are two widely used methods for detecting positive selection in homologous protein coding sequences. Both methods consider an excess of nonsynonymous (replacement) substitutions as evidence for positive selection. Previously published simulation studies comparing the performance of the two methods show contradictory results. Here we conduct a more thorough simulation study to cover and extend the parameter space used in previous studies. We also reanalyzed an HLA data set that was previously proposed to cause problems when analyzed using the maximum likelihood method. Our new simulations and a reanalysis of the HLA data demonstrate that the maximum likelihood method has good power and accuracy in detecting positive selection over a wide range of parameter values. Previous studies reporting poor performance of the method appear to be due to numerical problems in the optimization algorithms and did not reflect the true performance of the method. The parsimony method has a very low rate of false positives but very little power for detecting positive selection or identifying positively selected sites.

Algorithms↗