Adaptive evolution of UGT2B17 copy-number variation

The human UGT2B17 gene varies in copy number from zero to two per individual and also differs in mean number between populations from Africa, Europe, and East Asia. We show that such a high degree of geographical variation is unusual and investigate its evolutionary history. This required first reinterpreting the reference sequence in this region of the genome, which is misassembled from the two different alleles separated by an artifactual gap. A corrected assembly identifies the polymorphism as a 117 kb deletion arising by nonallelic homologous recombination between ~4.9 kb segmental duplications and allows the deletion breakpoint to be identified. We resequenced ~12 kb of DNA spanning the breakpoint in 91 humans from three HapMap and one extended HapMap populations and one chimpanzee. Diversity was unusually high and the time to the most recent common ancestor was estimated at ~2.4 or ~3.0 million years by two different methods, with evidence of balancing selection in Europe. In contrast, diversity was low in East Asia where a single haplotype predominated, suggesting positive selection for the deletion in this part of the world.     

Genetic algorithms and evolution

The genetic algorithm (GA) as developed by Holland (1975, Adaptation in Natural and Artificial Systems. Ann Arbor: University of Michigan Press) is an optimization technique based on natural selection. We use a modified version of this technique to investigate which aspects of natural selection make it an efficient search procedure. Our main modification to Holland's GA is the subdividing of the population into semi-isolated demes. We consider two examples. One is a fitness landscape with many local optima. The other is a model of singing in birds that has been previously analysed using dynamic programming. Both examples have epistatic interactions. In the first example we show that the GA can find the global optimum and that its success is improved by subdividing the population. In the second example we show that GAs can evolve to the optimal policy found by dynamic programming.     

High-resolution copy-number variation map reflects human olfactory receptor diversity and evolution

Olfactory receptors (ORs), which are involved in odorant recognition, form the largest mammalian protein superfamily. The genomic content of OR genes is considerably reduced in humans, as reflected by the relatively small repertoire size and the high fraction ( approximately 55%) of human pseudogenes. Since several recent low-resolution surveys suggested that OR genomic loci are frequently affected by copy-number variants (CNVs), we hypothesized that CNVs may play an important role in the evolution of the human olfactory repertoire. We used high-resolution oligonucleotide tiling microarrays to detect CNVs across 851 OR gene and pseudogene loci. Examining genomic DNA from 25 individuals with ancestry from three populations, we identified 93 OR gene loci and 151 pseudogene loci affected by CNVs, generating a mosaic of OR dosages across persons. Our data suggest that approximately 50% of the CNVs involve more than one OR, with the largest CNV spanning 11 loci. In contrast to earlier reports, we observe that CNVs are more frequent among OR pseudogenes than among intact genes, presumably due to both selective constraints and CNV formation biases. Furthermore, our results show an enrichment of CNVs among ORs with a close human paralog or lacking a one-to-one ortholog in chimpanzee. Interestingly, among the latter we observed an enrichment in CNV losses over gains, a finding potentially related to the known diminution of the human OR repertoire. Quantitative PCR experiments performed for 122 sampled ORs agreed well with the microarray results and uncovered 23 additional CNVs. Importantly, these experiments allowed us to uncover nine common deletion alleles that affect 15 OR genes and five pseudogenes. Comparison to the chimpanzee reference genome revealed that all of the deletion alleles are human derived, therefore indicating a profound effect of human-specific deletions on the individual OR gene content. Furthermore, these deletion alleles may be used in future genetic association studies of olfactory inter-individual differences.     

Complexity in organic evolution

The present state of knowledge of the formation of the Compounds I of peroxidases and catalases is discussed in terms of the restrictions which must be placed upon a valid mechanism. It is likely that all Compounds I contain one oxygen atom bound to the heme-iron as in the Compound I of chloroperoxidase. Thus the formation of Compound I, obtained after molecular hydrogen peroxide and the enzyme diffuse together, involves a minimum of two bond ruptures and the formation of two new bonds. Yet this amazing reaction proceeds with an activation energy equal to or less than that for the fluidity of water. This result can only be accounted for by including at least one reversible step. Since Compound I formation requires the formation of an “inner sphere” complex, the presence or absence of water in the sixth co-ordination position of the heme-iron is of crucial importance. A comparison of the rates of ligand binding with the rate of Compound I formation indicate that the inner sphere complex leading to Compound I formation is formed by an excellent nucleophile, probably the peroxide anion, formed by a proton transfer from hydrogen peroxide. This proton cannot equilibrate with the bulk solvent. A proton derived from the active site would appear to be added to the hydroxide ion which permits a molecule of water to depart upon oxygen atom addition (or substitution) to (or at) the heme-iron. It is tentatively suggested that Compound I of catalase has a single active site per subunit molecule and that Compound I of peroxidase normally has two reactive sites.     

Complexity and evolution: What everybody knows

The consensus among evolutionists seems to be (and has been for at least a century) that the morphological complexity of organisms increases in evolution, although almost no empirical evidence for such a trend exists. Most studies of complexity have been theoretical, and the few empirical studies have not, with the exception of certain recent ones, been especially rigorous; reviews are presented of both the theoretical and empirical literature. The paucity of evidence raises the question of what sustains the consensus, and a number of suggestions are offered, including the possibility that certain cultural and/or perceptual biases are at work. In addition, a shift in emphasis from theoretical to empirical inquiry is recommended for the study of complexity, and guidelines for future empirical studies are proposed.     

Exact algorithms for planted motif problems.

The problem of identifying meaningful patterns (i.e., motifs) from biological data has been studied extensively due to its paramount importance. Three versions of this problem have been identified in the literature. One of these three problems is the planted (l, d)-motif problem. Several instances of this problem have been posed as a challenge. Numerous algorithms have been proposed in the literature that address this challenge. Many of these algorithms fall under the category of heuristic algorithms. In this paper we present algorithms for the planted (l, d)-motif problem that always find the correct answer(s). Our algorithms are very simple and are based on some ideas that are fundamentally different from the ones employed in the literature. We believe that the techniques we introduce in this paper will find independent applications.     

Linear-time algorithms for the multiple gene duplication problems

A fundamental problem arising in the evolutionary molecular biology is to discover the locations of gene duplications and multiple gene duplication episodes based on the phylogenetic information. The solutions to the MULTIPLE GENE DUPLICATION problems can provide useful clues to place the gene duplication events onto the locations of a species tree and to expose the multiple gene duplication episodes. In this paper, we study two variations of the MULTIPLE GENE DUPLICATION problems: the EPISODE-CLUSTERING (EC) problem and the MINIMUM EPISODES (ME) problem. For the EC problem, we improve the results of Burleigh et al. with an optimal linear-time algorithm. For the ME problem, on the basis of the algorithm presented by Bansal and Eulenstein, we propose an optimal linear-time algorithm.     

Efficient algorithms for quantitative trait loci mapping problems.

Rapid advances in molecular genetics push the need for efficient data analysis. Advanced algorithms are necessary for extracting all possible information from large experimental data sets. We present a general linear algebra framework for quantitative trait loci (QTL) mapping, using both linear regression and maximum likelihood estimation. The formulation simplifies future comparisons between and theoretical analyses of the methods. We show how the common structure of QTL analysis models can be used to improve the kernel algorithms, drastically reducing the computational effort while retaining the original analysis results. We have evaluated our new algorithms on data sets originating from two large F(2) populations of domestic animals. Using an updating approach, we show that 1-3 orders of magnitude reduction in computational demand can be achieved for matrix factorizations. For interval-mapping/composite-interval-mapping settings using a maximum likelihood model, we also show how to use the original EM algorithm instead of the ECM approximation, significantly improving the convergence and further reducing the computational time. The algorithmic improvements makes it feasible to perform analyses which have previously been deemed impractical or even impossible. For example, using the new algorithms, it is reasonable to perform permutation testing using exhaustive search on populations of 200 individuals using an epistatic two-QTL model.     

MLGA--a rapid and cost-efficient assay for gene copy-number analysis

Structural variation is an important cause of genetic variation. Whole genome analysis techniques can efficiently identify copy-number variable regions but there is a need for targeted methods, to verify and accurately size variable regions, and to diagnose large sample cohorts. We have developed a technique based on multiplex amplification of size-coded selectively circularized genomic fragments, which is robust, cheaper and more rapid than current multiplex targeted copy-number assays.     

Maximum likelihood models and algorithms for gene tree evolution with duplications and losses

Background

The abundance of new genomic data provides the opportunity to map the location of gene duplication and loss events on a species phylogeny. The first methods for mapping gene duplications and losses were based on a parsimony criterion, finding the mapping that minimizes the number of duplication and loss events. Probabilistic modeling of gene duplication and loss is relatively new and has largely focused on birth-death processes.

Results

We introduce a new maximum likelihood model that estimates the speciation and gene duplication and loss events in a gene tree within a species tree with branch lengths. We also provide an, in practice, efficient algorithm that computes optimal evolutionary scenarios for this model. We implemented the algorithm in the program DrML and verified its performance with empirical and simulated data.

Conclusions

In test data sets, DrML finds optimal gene duplication and loss scenarios within minutes, even when the gene trees contain sequences from several hundred species. In many cases, these optimal scenarios differ from the lca-mapping that results from a parsimony gene tree reconciliation. Thus, DrML provides a new, practical statistical framework on which to study gene duplication.

     

Functional evolution: origin and problems

In the article the history of comparative and evolutionary physiology since the early XIX is given. The most substantial methods of evolutionary physiology are described. In the mid-50ies Orbely put forward the suggestion concerning two tasks facing evolutionary physiology, namely the study of evolution of functions and functional evolution. In the present work attention is given to the principles underlying evolution of functions on different levels of physiological systems. The main aspects of functional evolution are discussed.     

Some problems of regressive evolution

The concept of morphophysiological regress as one of the main ways to biological progress, as well as its major factors (the sedentary and parasitic modes of life), are discussed. Some notions of regressive evolution are critically reviewed. Special attention is paid to evolutionary transformations of the nervous system, one of the main integrating factors in the body. All theories of evolutionary progress based on sedentary organisms are demonstrated to be untenable. The entire progressive evolution of Metazoa has been related to mobile life. Since regressive trends are common in the evolution, the phylogenetic tree of Metazoa requires serious revision.     

Energy problems in life evolution

Evolutionary aspects of bioenergetics are considered. These include the origin of the first organisms, UV-protection and the beginnings of anoxygenic photosynthesis, the electron donor problem of life and the appearance of oxygenic photosynthesis, oxygen danger and strategies of defense, and the role of oxygen in programmed cell death.Translated from Biokhimiya, Vol. 70, No. 2, 2005, pp. 302–307.Original Russian Text Copyright © 2005 by Samuilov.This revised version was published online in April 2005 with corrections to the post codes.     

The neutral coalescent process for recent gene duplications and copy-number variants

I describe a method for simulating samples from gene families of size two under a neutral coalescent process, for the case where the duplicate gene either has fixed recently in the population or is still segregating. When a duplicate locus has recently fixed by genetic drift, diversity in the new gene is expected to be reduced, and an excess of rare alleles is expected, relative to the predictions of the standard coalescent model. The expected patterns of polymorphism in segregating duplicates ("copy-number variants") depend both on the frequency of the duplicate in the sample and on the rate of crossing over between the two loci. When the crossover rate between the ancestral gene and the copy-number variant is low, the expected pattern of variability in the ancestral gene will be similar to the predictions of models of either balancing or positive selection, if the frequency of the duplicate in the sample is intermediate or high, respectively. Simulations are used to investigate the effect of crossing over between loci, and gene conversion between the duplicate loci, on levels of variability and the site-frequency spectrum.     

MLGA—a rapid and cost-efficient assay for gene copy-number analysis

Structural variation is an important cause of genetic variation. Whole genome analysis techniques can efficiently identify copy-number variable regions but there is a need for targeted methods, to verify and accurately size variable regions, and to diagnose large sample cohorts. We have developed a technique based on multiplex amplification of size-coded selectively circularized genomic fragments, which is robust, cheaper and more rapid than current multiplex targeted copy-number assays.     

Allele-specific copy-number discovery from whole-genome and whole-exome sequencing

Copy-number variants (CNVs) are a major form of genetic variation and a risk factor for various human diseases, so it is crucial to accurately detect and characterize them. It is conceivable that allele-specific reads from high-throughput sequencing data could be leveraged to both enhance CNV detection and produce allele-specific copy number (ASCN) calls. Although statistical methods have been developed to detect CNVs using whole-genome sequence (WGS) and/or whole-exome sequence (WES) data, information from allele-specific read counts has not yet been adequately exploited. In this paper, we develop an integrated method, called AS-GENSENG, which incorporates allele-specific read counts in CNV detection and estimates ASCN using either WGS or WES data. To evaluate the performance of AS-GENSENG, we conducted extensive simulations, generated empirical data using existing WGS and WES data sets and validated predicted CNVs using an independent methodology. We conclude that AS-GENSENG not only predicts accurate ASCN calls but also improves the accuracy of total copy number calls, owing to its unique ability to exploit information from both total and allele-specific read counts while accounting for various experimental biases in sequence data. Our novel, user-friendly and computationally efficient method and a complete analytic protocol is freely available at https://sourceforge.net/projects/asgenseng/.     

Shorelines of islands of tractability: algorithms for parsimony and minimum perfect phylogeny haplotyping problems

The problem Parsimony Haplotyping (PH) asks for the smallest set of haplotypes which can explain a given set of genotypes, and the problem Minimum Perfect Phylogeny Haplotyping (MPPH) asks for the smallest such set which also allows the haplotypes to be embedded in a perfect phylogeny, an evolutionary tree with biologically-motivated restrictions. For PH, we extend recent work by further mapping the interface between ;;easy' and ;;hard' instances, within the framework of (k,l)-bounded instances where the number of 2's per column and row of the input matrix is restricted. By exploring, in the same way, the tractability frontier of MPPH we provide the first concrete, positive results for this problem. In addition, we construct for both PH and MPPH polynomial time approximation algorithms, based on properties of the columns of the input matrix.     

Self-adaptive memetic algorithms for multi-objective single machine learning-effect scheduling problems with release times

Flexible Services and Manufacturing Journal - This paper proposes a single machine scheduling problem with learning-effect and release times by considering two objectives requiring minimization of...     

Segmental duplications and copy-number variation in the human genome

The human genome contains numerous blocks of highly homologous duplicated sequence. This higher-order architecture provides a substrate for recombination and recurrent chromosomal rearrangement associated with genomic disease. However, an assessment of the role of segmental duplications in normal variation has not yet been made. On the basis of the duplication architecture of the human genome, we defined a set of 130 potential rearrangement hotspots and constructed a targeted bacterial artificial chromosome (BAC) microarray (with 2,194 BACs) to assess copy-number variation in these regions by array comparative genomic hybridization. Using our segmental duplication BAC microarray, we screened a panel of 47 normal individuals, who represented populations from four continents, and we identified 119 regions of copy-number polymorphism (CNP), 73 of which were previously unreported. We observed an equal frequency of duplications and deletions, as well as a 4-fold enrichment of CNPs within hotspot regions, compared with control BACs (P < .000001), which suggests that segmental duplications are a major catalyst of large-scale variation in the human genome. Importantly, segmental duplications themselves were also significantly enriched >4-fold within regions of CNP. Almost without exception, CNPs were not confined to a single population, suggesting that these either are recurrent events, having occurred independently in multiple founders, or were present in early human populations. Our study demonstrates that segmental duplications define hotspots of chromosomal rearrangement, likely acting as mediators of normal variation as well as genomic disease, and it suggests that the consideration of genomic architecture can significantly improve the ascertainment of large-scale rearrangements. Our specialized segmental duplication BAC microarray and associated database of structural polymorphisms will provide an important resource for the future characterization of human genomic disorders.