Non-random Mechanisms Research Articles

Pattern recognition in the landscape of seemingly random chimeric transcripts

The molecular and functional diversity generated by chimeric transcripts (CTs) that are derived from two genes is indicated to contribute to tumor cell survival. Several gaps yet exist. The present research is a systematic study of the spectrum of CTs identified in RNA sequencing datasets of 160 ovarian cancer samples in the The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov). Structural annotation revealed complexities emerging from chromosomal localization of partner genes, differential splicing and inclusion of regulatory, untranslated regions. Identification of phenotype-specific associations further resolved a dynamically modulated mesenchymal signature during transformation. On an evolutionary background, protein-coding CTs were indicated to be highly conserved, while non-coding CTs may have evolved more recently. We also realized that the current premise postulating structural alterations or neighbouring gene readthrough generating CTs is not valid in instances wherein the parental genes are genomically distanced. In addressing this lacuna, we identified the essentiality of specific spatiotemporal arrangements mediated gene proximities in 3D space for the generation of CTs. All these features together suggest non-random mechanisms towards increasing the molecular diversity in a cell through chimera formation either in parallel or with cross-talks with the indigenous regulatory network.

Visual representations of canine cardiac arrhythmias with Lorenz (Poincaré) plots.

To characterize the patterns associated with Lorenz plots (LPs) or Poincaré plots derived from the Holter recordings of dogs with various cardiac rhythms. 77 dogs with 24-hour Holter recordings. A 1-hour period from the Holter recordings from each of 20 dogs without arrhythmias and from each of 57 dogs with arrhythmias (10 each with supraventricular premature complexes, complex supraventricular ectopy, ventricular premature complexes, complex ventricular ectopy, and atrial fibrillation, and 7 with high-grade second-degree atrioventricular block) were used to generate the LPs. Patterns depicted in the LPs were described. Arrhythmia-free Holter recordings yielded LPs with a Y-shaped pattern and variable silent zones. Recordings with single premature complexes yielded LPs with double side and triple side lobes. Complex ectopy was denoted by dots clustered in the lower left corner of the LPs. The LPs of recordings with atrial fibrillation had fan patterns consistent with a nonlinear relationship between atrial electrical impulses and atrioventricular nodal conduction. The recordings with atrioventricular block yielded LPs with island patterns consistent with variable atrioventricular nodal conduction. Distinct LP patterns were identified for common cardiac rhythms of dogs, supportive of nonrandom mechanisms as the cause of most rhythms. Visual interpretation of an LP generated from a Holter recording may aid in determining the arrhythmia type and understanding the arrhythmia's mechanism in dogs and other species.

From Bloch oscillations to many-body localization in clean interacting systems

In this work we demonstrate that nonrandom mechanisms that lead to single-particle localization may also lead to many-body localization, even in the absence of disorder. In particular, we consider interacting spins and fermions in the presence of a linear potential. In the noninteracting limit, these models show the well-known Wannier-Stark localization. We analyze the fate of this localization in the presence of interactions. Remarkably, we find that beyond a critical value of the potential gradient these models exhibit nonergodic behavior as indicated by their spectral and dynamical properties. These models, therefore, constitute a class of generic nonrandom models that fail to thermalize. As such, they suggest new directions for experimentally exploring and understanding the phenomena of many-body localization. We supplement our work by showing that by using machine-learning techniques the level statistics of a system may be calculated without generating and diagonalizing the Hamiltonian, which allows a generation of large statistics.

Exploring the human-animal interface of Ebola virus disease outbreaks.

Whereas the prevention and treatment of Ebola virus disease (EVD) have been well studied after the 2013-16 outbreak in West Africa, the emergence of human outbreaks and their mechanisms have yet to be explored in detail. In particular, it has yet to be clarified whether the emergence records offer any theoretical insight into the changing interface between humans and animal reservoirs. Here we explore the epidemiological record of emergence, investigating predominant causes of the introduction to the human population, their characteristics, and frequencies. We retrieved data of every outbreak that can be traced back to a single zoonotic spillover. Through statistical analysis, we have shown that (i) the leading cause of emergence was eating and hunting habits, (ii) primates act as the main source of zoonotic spillover, and (iii) Zaire ebolavirus is the most virulent type. Moreover, the trend of emergence was demonstrated not to be a Poisson process, indicating that some unknown, underlying, non-random mechanisms are likely to govern the spillover event. In the Democratic Republic of Congo, an increasing emergence trend was favored compared with a purely random emergence model. Outbreak event data and their causative viruses should be explored biologically and epidemiologically to possibly predict future outbreak events.

Mutation-specific effects in germline transmission of pathogenic mtDNA variants

Does germline selection (besides random genetic drift) play a role during the transmission of heteroplasmic pathogenic mitochondrial DNA (mtDNA) mutations in humans? We conclude that inheritance of mtDNA is mutation-specific and governed by a combination of random genetic drift and negative and/or positive selection. mtDNA inherits maternally through a genetic bottleneck, but the underlying mechanisms are largely unknown. Although random genetic drift is recognized as an important mechanism, selection mechanisms are thought to play a role as well. We determined the mtDNA mutation loads in 160 available oocytes, zygotes, and blastomeres of five carriers of the m.3243A>G mutation, one carrier of the m.8993T>G mutation, and one carrier of the m.14487T>C mutation. Mutation loads were determined in PGD samples using PCR assays and analysed mathematically to test for random sampling effects. In addition, a meta-analysis has been performed on mutation load transmission data in the literature to confirm the results of the PGD samples. By applying the Kimura distribution, which assumes random mechanisms, we found that mtDNA segregations patterns could be explained by variable bottleneck sizes among all our carriers (moment estimates ranging from 10 to 145). Marked differences in the bottleneck size would determine the probability that a carrier produces offspring with mutations markedly different than her own. We investigated whether bottleneck sizes might also be influenced by non-random mechanisms. We noted a consistent absence of high mutation loads in all our m.3243A>G carriers, indicating non-random events. To test this, we fitted a standard and a truncated Kimura distribution to the m.3243A>G segregation data. A Kimura distribution truncated at 76.5% heteroplasmy has a significantly better fit (P-value = 0.005) than the standard Kimura distribution. For the m.8993T>G mutation, we suspect a skewed mutation load distribution in the offspring. To test this hypothesis, we performed a meta-analysis on published blood mutation levels of offspring-mother (O-M) transmission for the m.3243A>G and m.8993T>G mutations. This analysis revealed some evidence that the O-M ratios for the m.8993T>G mutation are different from zero (P-value <0.001), while for the m.3243A>G mutation there was little evidence that the O-M ratios are non-zero. Lastly, for the m.14487T>G mutation, where the whole range of mutation loads was represented, we found no indications for selective events during its transmission. All data are included in the Results section of this article. The availability of human material for the mutations is scarce, requiring additional samples to confirm our findings. Our data show that non-random mechanisms are involved during mtDNA segregation. We aimed to provide the mechanisms underlying these selection events. One explanation for selection against high m.3243A>G mutation loads could be, as previously reported, a pronounced oxidative phosphorylation (OXPHOS) deficiency at high mutation loads, which prohibits oogenesis (e.g. progression through meiosis). No maximum mutation loads of the m.8993T>G mutation seem to exist, as the OXPHOS deficiency is less severe, even at levels close to 100%. In contrast, high mutation loads seem to be favoured, probably because they lead to an increased mitochondrial membrane potential (MMP), a hallmark on which healthy mitochondria are being selected. This hypothesis could provide a possible explanation for the skewed segregation pattern observed. Our findings are corroborated by the segregation pattern of the m.14487T>C mutation, which does not affect OXPHOS and MMP significantly, and its transmission is therefore predominantly determined by random genetic drift. Our conclusion is that mutation-specific selection mechanisms occur during mtDNA inheritance, which has implications for PGD and mitochondrial replacement therapy. This work has been funded by GROW-School of Oncology and Developmental Biology. The authors declare no competing interests.

Monotypic species and extinction risk: looking at lagomorphs

news and update ISSN 1948-6596 commentary Monotypic species and extinction risk: looking at lagomorphs Innovative perspectives in meta-analyses, like the study of lagomorph diversity produced by Verde Arregoitia et al. (2013), are clarifying the poorly understood relationship between biodiversity and ecosystem function. As a result, maintaining cur- rent ecosystem function relies on the preservation of as much biodiversity as possible, especially for rare or unusual clades that may have specialized roles in their environments. Species-poor verte- brate clades are more common than predicted to occur by chance (Ricklefs et al. 2007), suggesting that non-random mechanisms promote the persis- tence of relict species, members of once-large clades that rarely generate new species (Fig. 1). These species-poor clades, which have low net diversification, are thought to be at greater extinc- tion risk in the anthropogenic world because of their propensity to contain species with marginal, specialized niches (Verde Arregoitia et al. 2015; Ricklefs et al. 2007). Loss of these clades would disproportionately impact global biodiversity, due to their evolutionary uniqueness, and potentially ecosystem function if evolutionary uniqueness is also related to both unusual and important func- tional characteristics (Hampe and Petit 2005). In Lagomorpha, unlike other mammalian orders (such as Rodentia), there is a direct correla- tion between genus size and extinction risk, where species-poor clades are more likely to include threatened species (Verde Arregoitia et al. 2013). This correlation may explain why an unusually high proportion of lagomorphs overall is under threat of extinction. In a follow-up study, Verde Arregoitia et al. (2015) seek to explain the poten- tial underlying causes of this pattern. They find that lagomorph diversity tends to be low in bioti- cally diverse areas like the tropics, and high in are- as with low richness of other mammal species. They find that lagomorphs are most diverse in temperate latitudes, opposing the latitudinal di- versity gradient that predominates in most taxa. Sensitivity to high temperatures restricts the geo- graphic ranges of many of these species (Rolland et al. 2014). Verde Arregoitia et al. (2015) also find that evolutionary distinctiveness does not corre- late with biogeographic patterns like range size. These counterintuitive results may also have im- plications for niche breadth, which is often related to range size. Classic ecological studies of species and their habitats offer snapshots of species’ current niches. However, they may not provide broad- enough information about a species’ extinction risk or whether relatives should be expected to share similar risks. In conjunction with fossils and paleoenvironmental data, phylogenetics can be used to reconstruct within-clade evolutionary re- lationships, providing historical and evolutionary insight into potential threats (Cavender-Bares et al. 2012). Measures of extinction risk can often be informed by study of processes that have driven extinction in a clade in the past or through analy- sis of risk to related species by highlighting ecolog- ical, biogeographic, and evolutionary similarities and differences between family members (Ricklefs Contrary to expectations, Verde Arregoitia et al. (2015) found that there may not be a direct relationship between evolutionary distance and extinction risk for species-poor lagomorph genera. Rather (p.9), “...threatened and species-poor gen- era... occur in productive megadiverse areas that currently experience strong habitat degrada- tion...” and increasing anthropogenic pressure, whereas species in more diverse genera tend to live in harsher environments that have much low- er overall mammalian diversity. Thus, the correla- tion between genus size and extinction risk is driv- en by a relationship between genus size and habi- tat quality, in which high-productivity and at-risk habitats contain a disproportionately large num- ber of species-poor lagomorph genera. Further work is necessary to determine whether this rela- tionship is due to lagomorphs’ ability to exploit nutrient-poor habitats (Hirakawa 2002 Hacklander et al. 2008), or due to neutral processes. This relationship between genus size and habitat quality contradicts a common explanation frontiers of biogeography 7.2, 2015 — © 2015 the authors; journal compilation © 2015 The International Biogeography Society

Molecular characterization of 9p21 deletions shows a minimal common deleted region removing CDKN2A exon 1 and CDKN2B exon 2 in diffuse large b‐cell lymphomas

Diffuse large B cell lymphoma represent the most frequent subtype of non Hodgkin's lymphoma, accounting for 30-40% of cases. Several studies have shown that CDKN2A and CDKN2B deletions are frequent in these lymphomas. These genes encode the P14ARF, CDKN2A, and CDKN2B proteins which play a key role in the control of the G1/S transition of the cell cycle. Using array CGH and a quantitative multiplex PCR method, we have previously identified such deletions in 36% of cases at diagnosis. Using a walking strategy to approach the breakpoints of these deletions we could identify the breakpoints junction of thirteen deletions in 11 patients and of two unbalanced translocation leading to a loss of these genes. A minimal common deleted region of 22.4 kb containing exon 1β of CDKN2A encoding P14ARF and exon 2 of CDKN2B encoding CDKN2B was present in all cases but one. Analysis by quantitative RT PCR showed that the expression level of these genes was decreased in these patients as compared with non deleted cases and that this level was correlated with the deletion status of P14ARF, CDKN2A, and CDKN2B. Analysis of the breakpoint sequences showed that some of them were clustered within a few hundred base-pairs suggesting, even if we failed to identify any clear recombination prone sequences, that in these deletions the rearrangement results from non-random mechanisms.

The effect of care leave on burden and job performance

In this article the expected effects of the introduction of a fully paid long-term care leave programme in the Netherlands are investigated. In particular we are interested in the effects on perceived burden and job performance. We analyse data from a survey among workers who care for a person in their social circle for longer than two weeks. The caring workers with a high perceived burden and intention to participate in the programme were asked questions regarding the expected effects on burden. An econometric model in which we account for these two potentially nonrandom selection mechanisms is set up to analyse the expected reduction in burden due to the intended take-up of care leave. As a result of the introduction of the programme about 60% of the intended participants who perceive a high burden expect a reduction in their burden. The relation between burden and job performance shows that the programme would reduce the number of caring workers who perform less precise in their job by one-third. A modified version of the programme with more stringent requirements than analysed in this article was introduced in The Netherlands in 2005.

Smoothing Observational Data: A Philosophy and Implementation for the Health Sciences

Summary Standard statistical methods (such as regression analysis) presume the data are generated by an identifiable random process, and attempt to model that process in a parsimonious fashion. In contrast, observational data in the health sciences are generated by complex, nonidentified, and largely nonrandom mechanisms, and are analyzed to form inferences on latent structures. Despite this gap between the methods and reality, most observational data analysis comprises application of standard methods, followed by narrative discussion of the problems of entailed by doing so. Alternative approaches employ latent‐structure models that include components for nonidentified mechanisms. Standard methods can still be useful, however, provided their modeling philosophy is modified to encourage preservation of structure, rather than achieving parsimonious description. With this modification they can be viewed as smoothing or filtering methods for separating noise from signal before the task of latent‐structure modeling begins. I here give a detailed justification of this view, and a hierarchical‐modeling implementation that can be carried out with popular software. Concepts are illustrated in the smoothing of a contingency table from an analysis of magnetic fields and childhood leukemia.

Pseudorandom Sampling has a Real Effect on Test Size

Abstract A dangerous trend toward nonrandom sampling mechanisms has been observed in several fields of the applied sciences. These sampling designs are attempts to avoid tail observations, resulting in smaller estimated standard errors and inflated claims of statistical significance. Often, the researchers go to some lengths to make the sampling mechanisms appear random; yet, they clearly are not. The effect of these pseudorandom sampling designs on the power and size of the hypothesis tests is investigated and shown to be substantial.

Analysis of incomplete data under non-random mechanisms: bayesian inference

Inferences are made concerning population proportions when data are not missing at random.Both one sample and two sample situations are considered with examples in clinical trials.The one samplesituation involves the existence of response related incomplete data in a study conducted to make inferences involving the proportion. The two sample problem involves comparing two treatments in clinical trials when there exists dropouts due to both the treatment and the response to the treatment.Bayes procedures are used in estimating parameters of interest and testing hypotheses of interest in these two situations. An ad-hoc approach to the classical inference is presented for each ofthe two situations and compared with the Bayesian approach discussed. To illustrate the theory developed, data from clinical trials of severe head trauma patients at the Medical College of Virginia Head Injury Center from 1984 to 1987 is considered

Protecting Against Nonrandomly Missing Data in Longitudinal Studies

Nonrandomly missing data can pose serious problems in longitudinal studies. We generally have little knowledge about how missingness is related to the data values, and longitudinal studies are often far from complete. Two approaches that have been used to handle missing data--use of maximum likelihood with an ignorable mechanism and direct modeling of the missing data mechanism--have the disadvantage of not giving consistent estimates under important classes of nonrandom mechanisms. We introduce two protective estimators, that is, estimators that retain their consistency over a wide range of nonrandom mechanisms. We compare these protective estimators using longitudinal data from a mental health panel study. We also investigate their robustness to certain departures from normality.

Comparing incomplete paired binomial data under non-random mechanisms.

In many paired experiments designed to compare two treatments, various mechanisms can lead to the data being incomplete. Such mechanisms may be of a non-random nature and may depend on the treatment or the outcome. This paper considers several methods for testing the equality of two correlated binomial proportions when the incompleteness is caused by non-random mechanisms. Several simple procedures are justified in certain cases. The tests based on all available data are more efficient compared to those utilizing only portions of the data. McNemar's test based only on the complete paired observations and the likelihood test are the most robust, although no efficient test exists when the mechanisms are not independent.

Chromosomal characteristics of secondary human brain tumours

The chromosomes in 20 secondary neoplasms in the CNS were studied in fixations taken directly from the tumours. Three quarters of the metastases had a triploid mode, and three quarters of these were in the hypotriploid zone. Near-diploid stemlines were next in frequency; a hypodiploid mode was most common, and 2 such tumours had as low stemline number as 34 and 36, respectively. Tetraploid stemlines were not seen, but 1 metastasis had a pentaploid mode. In ordinary chromosome groups the deviations particularly involved groups C, D and G. Markers, and often a very high number, were ou nd in all but one stemline. A statistical analysis of the chromosomal representation demonstrated a correlation between the extent of the decrease of the acrocentrics and the frequency of markers. A study of the relative size of four different marker types indicated that these were formed by non-random mechanisms. In comparison with findings in neoplastic effusions the brain metastases showed more extreme numerical and structural features, possibly a property of neoplastic elements with a capacity to metastasize to the CNS.