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We have developed a pruning algorithm for likelihood estimation of a tree of populations. This algorithm enables us to compute the likelihood for large trees. Thus, it gives an efficient way of obtaining the maximum-likelihood estimate (MLE) for a given tree topology. Our method utilizes the differences accumulated by random genetic drift in allele count data from single-nucleotide polymorphisms (SNPs), ignoring the effect of mutation after divergence from the common ancestral population. The computation of the maximum-likelihood tree involves both maximizing likelihood over branch lengths of a given topology and comparing the maximum-likelihood across topologies. Here our focus is the maximization of likelihood over branch lengths of a given topology. The pruning algorithm computes arrays of probabilities at the root of the tree from the data at the tips of the tree; at the root, the arrays determine the likelihood. The arrays consist of probabilities related to the number of coalescences and allele counts for the partially coalesced lineages. Computing these probabilities requires an unusual two-stage algorithm. Our computation is exact and avoids time-consuming Monte Carlo methods. We can also correct for ascertainment bias.

Many pleiotropic roles have been ascribed to small abundant HMG-Box (HMGB) proteins in higher eukaryotes but their precise function has remained enigmatic. To investigate their function genetically we have generated a defined deficiency uncovering the functionally redundant genes encoding HMGD and HMGZ, the Drosophila counterparts of HMGB1-3 in mammals. The resulting mutant is a strong hypomorphic allele of HmgD/Z Surprisingly this allele is viable and exhibits only minor morphological defects even when homozygous. However, this allele interacts strongly with mutants of the Brahma chromatin remodeling complex, while no interaction was observed with mutant alleles of other remodeling complexes. We also observe genetic interactions between the HmgD/Z deficiency and some, but not all, known Brahma targets. These include the homeotic genes Sex combs reduced and Antennapedia, as well as the gene encoding the cell-signaling protein Rhomboid. In contrast to more general structural roles previously suggested for these proteins, we infer that a major function of the abundant HMGB proteins in Drosophila is to participate in Brahma-dependent chromatin remodeling at a specific subset of Brahma-dependent promoters.

An isolated population is a group of individuals who are descended from a founding population who lived some time ago. If the founding individuals are assumed to be noninbred and unrelated, a chromosome sampled from the population can be represented as a mosaic of segments of the original ancestral types. A population in which chromosomes are made up of a few long segments will exhibit linkage disequilibrium due to founder effect over longer distances than a population in which the chromosomes are made up of many short segments. We study the length of intact ancestral segments by obtaining the expected number of junctions (points where DNA of two distinct ancestral types meet) in a chromosome. Assuming random mating, we study analytically the effects of population age, growth patterns, and internal structure on the expected number of junctions in a chromosome. We demonstrate that the type of growth a population has experienced can influence the expected number of junctions, as can population subdivision. These effects are substantial only when population sizes are very small. We also develop an approximation to the variance of the number of junctions and show that the variance is large.

The probability that at least p% of an individual's genome is passed on collectively to his children is calculated. With data availability the consideration of the chromosome as a whole rather than discrete loci becomes of increasing practical importance. Assuming the genomic continuum model, which allows for recombination, the crossover process in a chromosome pedigree is viewed as a continuous-time Markov random walk on the vertices of a hypercube with time parameter map distance along the chromosome. The desired probability corresponds to the probability of sojourn times of the process in a small set of vertices, which are well approximated via the Poisson clumping heuristic. Results are given for the human genome. It is very likely that an individual with at least four children passes on at least 90% of his genome. There exists no 'equivalent' number of independently segregating loci for this distribution.

A population's effective size is an important quantity for conservation and management. The effective size may be estimated from the change of allele frequencies observed in temporally spaced genetic samples taken from the population. Though moment-based estimators exist, recently Williamson and Slatkin demonstrated the advantages of a maximum-likelihood approach that they applied to data on diallelic genetic markers. Their computational methods, however, do not extend to data on multiallelic markers, because in such cases exact evaluation of the likelihood is impossible, requiring an intractable sum over latent variables. We present a Monte Carlo approach to compute the likelihood with data on multiallelic markers. So as to be computationally efficient, our approach relies on an importance-sampling distribution constructed by a forward-backward method. We describe the Monte Carlo formulation and the importance-sampling function and then demonstrate their use on both simulated and real datasets.

In disequilibrium mapping from data on a rare allele, interest may focus on the ancestry of a random sample of current descendants of a mutation. The mutation is assumed to have been introduced into the population as a single copy a known time ago and to have reached a given copy number within the population. Theory has been developed to describe the ancestral distribution under arbitrary patterns of population expansion. Further results permit convenient realization of the ancestry for a random sample of copies of a rare allele within populations of constant size or within populations growing or shrinking at constant exponential rate. In this article, we present an efficient approximate method for realizing coalescence times under more general patterns of population growth. We also apply diagnostics, checking the age of the mutation. In the course of the derivation, some additional insight is gained into the dynamics of the descendants of the mutation.

Realized kinship is a key statistic in analyses of genetic data involving relatedness of individuals or structure of populations. There are several estimators of kinship that make use of dense SNP genotypes. We introduce a class of estimators, of which some existing estimators are special cases. Within this class, we derive properties of the estimators and determine an optimal estimator. Additionally, we introduce an alternative marker weighting that takes allelic associations [linkage disequilibrium (LD)] into account, and apply this weighting to several estimators. In a simulation study, we show that improved estimators are obtained (1) by optimal weighting of markers, (2) by taking physical contiguity of genome into account, and (3) by weighting on the basis of LD. [ABSTRACT FROM AUTHOR]