gcodeml: A Grid-enabled Tool for Detecting Positive Selection in Biological Evolution

One of the important questions in biological evolution is to know if certain changes along protein coding genes have contributed to the adaptation of species. This problem is known to be biologically complex and computationally very expensive. It, therefore, requires efficient Grid or cluster solutions to overcome the computational challenge. We have developed a Grid-enabled tool (gcodeml) that relies on the PAML (codeml) package to help analyse large phylogenetic datasets on both Grids and computational clusters. Although we report on results for gcodeml, our approach is applicable and customisable to related problems in biology or other scientific domains.

Risk assessment of recurrence in sporadic retinoblastoma using a molecular-based algorithm.

PURPOSE: Most RB1 mutations are unique and distributed throughout the RB1 gene. Their detection can be time-consuming and the yield especially low in cases of conservatively-treated sporadic unilateral retinoblastoma (Rb) patients. In order to identify patients with true risk of developing Rb, and to reduce the number of unnecessary examinations under anesthesia in all other cases, we developed a universal sensitive, efficient and cost-effective strategy based on intragenic haplotype analysis. METHODS: This algorithm allows the calculation of the a posteriori risk of developing Rb and takes into account (a) RB1 loss of heterozygosity in tumors, (b) preferential paternal origin of new germline mutations, (c) a priori risk derived from empirical data by Vogel, and (d) disease penetrance of 90% in most cases. We report the occurrence of Rb in first degree relatives of patients with sporadic Rb who visited the Jules Gonin Eye Hospital, Lausanne, Switzerland, from January 1994 to December 2006 compared to expected new cases of Rb using our algorithm. RESULTS: A total of 134 families with sporadic Rb were enrolled; testing was performed in 570 individuals and 99 patients younger than 4 years old were identified. We observed one new case of Rb. Using our algorithm, the cumulated total a posteriori risk of recurrence was 1.77. CONCLUSIONS: This is the first time that linkage analysis has been validated to monitor the risk of recurrence in sporadic Rb. This should be a useful tool in genetic counseling, especially when direct RB1 screening for mutations leaves a negative result or is unavailable.

Treatment algorithm for moderate to severe ulcerative colitis.

The care for a patient with ulcerative colitis (UC) remains challenging despite the fact that morbidity and mortality rates have been considerably reduced during the last 30 years. The traditional management with intravenous corticosteroids was modified by the introduction of ciclosporin and infliximab. In this review, we focus on the treatment of patients with moderate to severe UC. Four typical clinical scenarios are defined and discussed in detail. The treatment recommendations are based on current literature, published guidelines and reviews, and were discussed at a consensus meeting of Swiss experts in the field. Comprehensive treatment algorithms were developed, aimed for daily clinical practice.

Algorithm optimization for solving crew scheduling problems

In this paper, we are proposing a methodology to determine the most efficient and least costly way of crew pairing optimization. We are developing a methodology based on algorithm optimization on Eclipse opensource IDE using the Java programming language to solve the crew scheduling problems.

Fishery-induced selection on an Alpine whitefish: quantifying genetic and environmental effects on individual growth rate

Size-selective fishing, environmental changes and reproductive strategies are expected to affect life-history traits such as the individual growth rate. The relative contribution of these factors is not clear, particularly whether size-selective fishing can have a substantial impact on the genetics and hence on the evolution of individual growth rates in wild populations. We analysed a 25-year monitoring survey of an isolated population of the Alpine whitefish Coregonus palaea. We determined the selection differentials on growth rate, the actual change of growth rate over time and indicators of reproductive strategies that may potentially change over time. The selection differential can be reliably estimated in our study population because almost all the fish are harvested within their first years of life, i.e. few fish escape fishing mortality. We found a marked decline in average adult growth rate over the 25 years and a significant selection differential for adult growth, but no evidence for any linear change in reproductive strategies over time. Assuming that the heritability of growth in this whitefish corresponds to what was found in other salmonids, about a third of the observed decline in growth rate would be linked to fishery-induced evolution. Size-selective fishing seems to affect substantially the genetics of individual growth in our study population.

Stick insect genomes reveal natural selection's role in parallel speciation.

Natural selection can drive the repeated evolution of reproductive isolation, but the genomic basis of parallel speciation remains poorly understood. We analyzed whole-genome divergence between replicate pairs of stick insect populations that are adapted to different host plants and undergoing parallel speciation. We found thousands of modest-sized genomic regions of accentuated divergence between populations, most of which are unique to individual population pairs. We also detected parallel genomic divergence across population pairs involving an excess of coding genes with specific molecular functions. Regions of parallel genomic divergence in nature exhibited exceptional allele frequency changes between hosts in a field transplant experiment. The results advance understanding of biological diversification by providing convergent observational and experimental evidence for selection's role in driving repeatable genomic divergence.

Tackling self-selection into treatment and self-selection into the sample biases in VAA research

Self‐selection into treatment and self‐selection into the sample are major concerns of VAA research and need to be controlled for if the aim is to deduce causal effects from VAA use in observational data. This paper focuses on the methodological aspects of VAA research and outlines omnipresent endogeneity issues, partly imposed through unobserved factors that affect both whether individuals chose to use VAAs and their electoral behavior. We promote using Heckman selection models and apply various versions of the model to data from the Swiss electorate and smartvote users in order to see to what extent selection biases interfere with the estimated effects of interest.

The evolution of XY recombination: sexually antagonistic selection versus deleterious mutation load.

Recombination arrest between X and Y chromosomes, driven by sexually antagonistic genes, is expected to induce their progressive differentiation. However, in contrast to birds and mammals (which display the predicted pattern), most cold-blooded vertebrates have homomorphic sex chromosomes. Two main hypotheses have been proposed to account for this, namely high turnover rates of sex-determining systems and occasional XY recombination. Using individual-based simulations, we formalize the evolution of XY recombination (here mediated by sex reversal; the "fountain-of-youth" model) under the contrasting forces of sexually antagonistic selection and deleterious mutations. The shift between the domains of elimination and accumulation occurs at much lower selection coefficients for the Y than for the X. In the absence of dosage compensation, mildly deleterious mutations accumulating on the Y depress male fitness, thereby providing incentives for XY recombination. Under our settings, this occurs via "demasculinization" of the Y, allowing recombination in XY (sex-reversed) females. As we also show, this generates a conflict with the X, which coevolves to oppose sex reversal. The resulting rare events of XY sex reversal are enough to purge the Y from its load of deleterious mutations. Our results support the "fountain of youth" as a plausible mechanism to account for the maintenance of sex-chromosome homomorphy.

Simulation methods with extended stability for stiff biochemical kinetics

Background: With increasing computer power, simulating the dynamics of complex systems in chemistry and biology is becoming increasingly routine. The modelling of individual reactions in (bio)chemical systems involves a large number of random events that can be simulated by the stochastic simulation algorithm (SSA). The key quantity is the step size, or waiting time, τ, whose value inversely depends on the size of the propensities of the different channel reactions and which needs to be re-evaluated after every firing event. Such a discrete event simulation may be extremely expensive, in particular for stiff systems where τ can be very short due to the fast kinetics of some of the channel reactions. Several alternative methods have been put forward to increase the integration step size. The so-called τ-leap approach takes a larger step size by allowing all the reactions to fire, from a Poisson or Binomial distribution, within that step. Although the expected value for the different species in the reactive system is maintained with respect to more precise methods, the variance at steady state can suffer from large errors as τ grows. Results: In this paper we extend Poisson τ-leap methods to a general class of Runge-Kutta (RK) τ-leap methods. We show that with the proper selection of the coefficients, the variance of the extended τ-leap can be well-behaved, leading to significantly larger step sizes.Conclusions: The benefit of adapting the extended method to the use of RK frameworks is clear in terms of speed of calculation, as the number of evaluations of the Poisson distribution is still one set per time step, as in the original τ-leap method. The approach paves the way to explore new multiscale methods to simulate (bio)chemical systems.

Inter-rater agreement and reliability of the COSMIN (COnsensus-based Standards for the selection of health status Measurement Instruments) Checklist

Background: The COSMIN checklist is a tool for evaluating the methodological quality of studies on measurement properties of health-related patient-reported outcomes. The aim of this study is to determine the inter-rater agreement and reliability of each item score of the COSMIN checklist (n = 114). Methods: 75 articles evaluating measurement properties were randomly selected from the bibliographic database compiled by the Patient-Reported Outcome Measurement Group, Oxford, UK. Raters were asked to assess the methodological quality of three articles, using the COSMIN checklist. In a one-way design, percentage agreement and intraclass kappa coefficients or quadratic-weighted kappa coefficients were calculated for each item. Results: 88 raters participated. Of the 75 selected articles, 26 articles were rated by four to six participants, and 49 by two or three participants. Overall, percentage agreement was appropriate (68% was above 80% agreement), and the kappa coefficients for the COSMIN items were low (61% was below 0.40, 6% was above 0.75). Reasons for low inter-rater agreement were need for subjective judgement, and accustom to different standards, terminology and definitions.Conclusions: Results indicated that raters often choose the same response option, but that it is difficult on item level to distinguish between articles. When using the COSMIN checklist in a systematic review, we recommend getting some training and experience, completing it by two independent raters, and reaching consensus on one final rating. Instructions for using the checklist are improved.

Structured RNAs in the ENCODE selected regions of the human genome

Functional RNA structures play an important role both in the context of noncoding RNA transcripts as well as regulatory elements in mRNAs. Here we present a computational study to detect functional RNA structures within the ENCODE regions of the human genome. Since structural RNAs in general lack characteristic signals in primary sequence, comparative approaches evaluating evolutionary conservation of structures are most promising. We have used three recently introduced programs based on either phylogenetic–stochastic context-free grammar (EvoFold) or energy directed folding (RNAz and AlifoldZ), yielding several thousand candidate structures (corresponding to ∼2.7% of the ENCODE regions). EvoFold has its highest sensitivity in highly conserved and relatively AU-rich regions, while RNAz favors slightly GC-rich regions, resulting in a relatively small overlap between methods. Comparison with the GENCODE annotation points to functional RNAs in all genomic contexts, with a slightly increased density in 3′-UTRs. While we estimate a significant false discovery rate of ∼50%–70% many of the predictions can be further substantiated by additional criteria: 248 loci are predicted by both RNAz and EvoFold, and an additional 239 RNAz or EvoFold predictions are supported by the (more stringent) AlifoldZ algorithm. Five hundred seventy RNAz structure predictions fall into regions that show signs of selection pressure also on the sequence level (i.e., conserved elements). More than 700 predictions overlap with noncoding transcripts detected by oligonucleotide tiling arrays. One hundred seventy-five selected candidates were tested by RT-PCR in six tissues, and expression could be verified in 43 cases (24.6%).

Distribution of events of positive selection and population differentiation in a metabolic pathway: the case of asparagine N-glycosylation

Background: Asparagine N-Glycosylation is one of the most important forms of protein post-translational modification in eukaryotes. This metabolic pathway can be subdivided into two parts: an upstream sub-pathway required for achieving proper folding for most of the proteins synthesized in the secretory pathway, and a downstream sub-pathway required to give variability to trans-membrane proteins, and involved in adaptation to the environment andinnate immunity. Here we analyze the nucleotide variability of the genes of this pathway in human populations, identifying which genes show greater population differentiation and which genes show signatures of recent positive selection. We also compare how these signals are distributed between the upstream and the downstream parts of the pathway, with the aim of exploring how forces of population differentiation and positive selection vary among genes involved in the same metabolic pathway but subject to different functional constraints. Results:Our results show that genes in the downstream part of the pathway are more likely to show a signature of population differentiation, while events of positive selection are equally distributed among the two parts of the pathway. Moreover, events of positive selection arefrequent on genes that are known to be at bifurcation points, and that are identified as beingin key position by a network-level analysis such as MGAT3 and GCS1.Conclusions: These findings indicate that the upstream part of the Asparagine N-Glycosylation pathway has lower diversity among populations, while the downstream part is freer to tolerate diversity among populations. Moreover, the distribution of signatures of population differentiation and positive selection can change between parts of a pathway, especially between parts that are exposed to different functional constraints. Our results support the hypothesis that genes involved in constitutive processes can be expected to show lower population differentiation, while genes involved in traits related to the environment should show higher variability. Taken together, this work broadens our knowledge on how events of population differentiation and of positive selection are distributed among different parts of a metabolic pathway.