Recent increases in assemblage rarity are linked to increasing local immigration

F.A.M.J.'s PhD was financed by the School of Biology, University of St Andrews. M.D. and A.E.M. acknowledge funding by the Leverhulme Trust. A.E.M. acknowledges funding from the European Research Council (ERC AdG BioTIME 250189 and ERC PoC BioCHANGE 727440).As pressures on biodiversity increase, a better understanding of how assemblages are responding is needed. Because rare species, defined here as those that have locally low abundances, make up a high proportion of assemblage species lists, understanding how the number of rare species within assemblages is changing will help elucidate patterns of recent biodiversity change. Here, we show that the number of rare species within assemblages is increasing, on average, across systems. This increase could arise in two ways: species already present in the assemblage decreasing in abundance but with no increase in extinctions, or additional species entering the assemblage in low numbers associated with an increase in immigration. The positive relationship between change in rarity and change in species richness provides evidence for the second explanation, i.e. higher net immigration than extinction among the rare species. These measurable changes in the structure of assemblages in the recent past underline the need to use multiple biodiversity metrics to understand biodiversity change.Publisher PDFPeer reviewe

Dominance structure of assemblages is regulated over a period of rapid environmental change

F.A.M.J. is financed by the School of Biology, University of St Andrews. A.E.M. acknowledges funding from the European Research Council (ERCAdG BioTIME 250189 and ERCPoC BioCHANGE 727440).Ecological assemblages are inherently uneven, with numerically dominant species contributing disproportionately to ecosystem services. Marked biodiversity change due to growing pressures on the world's ecosystems is now well documented. However, the hypothesis that dominant species are becoming relatively more abundant has not been tested. We examined the prediction that the dominance structure of contemporary communities is shifting, using a meta-analysis of 110 assemblage timeseries. Changes in relative and absolute dominance were evaluated with mixed and cyclic-shift permutation models. Our analysis uncovered no evidence of a systematic change in either form of dominance, but established that relative dominance is preserved even when assemblage size (total N) changes. This suggests that dominance structure is regulated alongside richness and assemblage size, and highlights the importance of investigating multiple components of assemblage diversity when evaluating ecosystem responses to environmental drivers.PostprintPeer reviewe

Gradients in predation risk in a tropical river system

We are grateful for 2 European Research Council grants (BIOTIME 250189 and BioCHANGE 727440).The importance of predation risk as a key driver of evolutionary change is exemplified by the Northern Range in Trinidad, where research on guppies living in multiple parallel streams has provided invaluable insights into the process of evolution by natural selection. Although Trinidadian guppies are now a textbook example of evolution in action, studies have generally categorized predation as a dichotomous variable, representing high or low risk. Yet, ecologists appreciate that community structure and the attendant predation risk vary substantially over space and time. Here, we use data from a longitudinal study of fish assemblages at 16 different sites in the Northern Range to quantify temporal and spatial variation in predation risk. Specifically we ask: 1) Is there evidence for a gradient in predation risk? 2) Does the ranking of sites (by risk) change with the definition of the predator community (in terms of species composition and abundance currency), and 3) Are site rankings consistent over time? We find compelling evidence that sites lie along a continuum of risk. However, site rankings along this gradient depend on how predation is quantified in terms of the species considered to be predators and the abundance currency is used. Nonetheless, for a given categorization and currency, rankings are relatively consistent over time. Our study suggests that consideration of predation gradients will lead to a more nuanced understanding of the role of predation risk in behavioral and evolutionary ecology. It also emphasizes the need to justify and report the definition of predation risk being used.Publisher PDFPeer reviewe

Program transformations using temporal logic side conditions

This paper describes an approach to program optimisation based on transformations, where temporal logic is used to specify side conditions, and strategies are created which expand the repertoire of transformations and provide a suitable level of abstraction. We demonstrate the power of this approach by developing a set of optimisations using our transformation language and showing how the transformations can be converted into a form which makes it easier to apply them, while maintaining trust in the resulting optimising steps. The approach is illustrated through a transformational case study where we apply several optimisations to a small program

The institutional shaping of management: in the tracks of English individualism

Globalisation raises important questions about the shaping of economic action by cultural factors. This article explores the formation of what is seen by some as a prime influence on the formation of British management: individualism. Drawing on a range of historical sources, it argues for a comparative approach. In this case, the primary comparison drawn is between England and Scotland. The contention is that there is a systemic approach to authority in Scotland that can be contrasted to a personal approach in England. An examination of the careers of a number of Scottish pioneers of management suggests the roots of this systemic approach in practices of church governance. Ultimately this systemic approach was to take a secondary role to the personal approach engendered by institutions like the universities of Oxford and Cambridge, but it found more success in the different institutional context of the USA. The complexities of dealing with historical evidence are stressed, as is the value of taking a comparative approach. In this case this indicates a need to take religious practice as seriously as religious belief as a source of transferable practice. The article suggests that management should not be seen as a simple response to economic imperatives, but as shaped by the social and cultural context from which it emerges

The spectrum and clinical impact of epigenetic modifier mutations in myeloma

Epigenetic dysregulation is known to be an important contributor to myeloma pathogenesis but, unlike in other B cell malignancies, the full spectrum of somatic mutations in epigenetic modifiers has not been previously reported. We sought to address this using results from whole-exome sequencing in the context of a large prospective clinical trial of newly diagnosed patients and targeted sequencing in a cohort of previously treated patients for comparison.Whole-exome sequencing analysis of 463 presenting myeloma cases entered in the UK NCRI Myeloma XI study and targeted sequencing analysis of 156 previously treated cases from the University of Arkansas for Medical Sciences. We correlated the presence of mutations with clinical outcome from diagnosis and compared the mutations found at diagnosis with later stages of disease.In diagnostic myeloma patient samples we identify significant mutations in genes encoding the histone 1 linker protein, previously identified in other B-cell malignancies. Our data suggest an adverse prognostic impact from the presence of lesions in genes encoding DNA methylation modifiers and the histone demethylase KDM6A/UTX. The frequency of mutations in epigenetic modifiers appears to increase following treatment most notably in genes encoding histone methyltransferases and DNA methylation modifiers.Numerous mutations identified raise the possibility of targeted treatment strategies for patients either at diagnosis or relapse supporting the use of sequencing-based diagnostics in myeloma to help guide therapy as more epigenetic targeted agents become available

Estimating species relative abundances from museum records

Funding: C.F., U.B. and D.J.R. acknowledge COST Action ‘European Soil-Biology Data Warehouse for Soil Protection’ (EUdaphobase), CA18237, supported by COST (European Cooperation in Science and Technology). AEM thanks the Leverhulme Trust (RPG-2019-401). D.B.B. was supported by an NSF Postdoc Research Fellowship in Biology (NSF 000733206), S.M.R. was supported by an NSERC Discovery Grant Author Contributions, A.V.S. was supported by NSF 1755336, C.S.M was supported by NSF 1398620 and N.J.G was supported by NSF 2019470.1. Dated, geo-referenced museum specimens are a rich data source for reconstructing species' distribution and abundance patterns. However, museum records are potentially biased towards over-representation of rare species, and it is unclear whether museum records can be used to estimate relative abundance in the field. 2. We assembled 17 coupled field and museum datasets to quantitatively compare relative abundance estimates with the Dirichlet distribution. Collectively, these datasets comprise 73,039 museum records and 1,405,316 field observations of 2,240 species. 3. Although museum records of rare species overestimated relative abundance by 1-fold to over 100-fold (median study = 9.0), the relative abundance of species estimated from museum occurrence records was strongly correlated with relative abundance estimated from standardized field surveys (r2 range of 0.10-0.91, median study = 0.43). 4. These analyses provide a justification for estimating species relative abundance with carefully curated museum occurrence records, which may allow for the detection of temporal or spatial shifts in the rank ordering of common and rare species.Publisher PDFPeer reviewe

Antiviral CD8(+) T Cells Restricted by Human Leukocyte Antigen Class II Exist during Natural HIV Infection and Exhibit Clonal Expansion.

CD8(+) T cell recognition of virus-infected cells is characteristically restricted by major histocompatibility complex (MHC) class I, although rare examples of MHC class II restriction have been reported in Cd4-deficient mice and a macaque SIV vaccine trial using a recombinant cytomegalovirus vector. Here, we demonstrate the presence of human leukocyte antigen (HLA) class II-restricted CD8(+) T cell responses with antiviral properties in a small subset of HIV-infected individuals. In these individuals, T cell receptor β (TCRβ) analysis revealed that class II-restricted CD8(+) T cells underwent clonal expansion and mediated killing of HIV-infected cells. In one case, these cells comprised 12% of circulating CD8(+) T cells, and TCRα analysis revealed two distinct co-expressed TCRα chains, with only one contributing to binding of the class II HLA-peptide complex. These data indicate that class II-restricted CD8(+) T cell responses can exist in a chronic human viral infection, and may contribute to immune control

A general co-expression network-based approach to gene expression analysis: comparison and applications

<p>Abstract</p> <p>Background</p> <p>Co-expression network-based approaches have become popular in analyzing microarray data, such as for detecting functional gene modules. However, co-expression networks are often constructed by ad hoc methods, and network-based analyses have not been shown to outperform the conventional cluster analyses, partially due to the lack of an unbiased evaluation metric.</p> <p>Results</p> <p>Here, we develop a general co-expression network-based approach for analyzing both genes and samples in microarray data. Our approach consists of a simple but robust rank-based network construction method, a parameter-free module discovery algorithm and a novel reference network-based metric for module evaluation. We report some interesting topological properties of rank-based co-expression networks that are very different from that of value-based networks in the literature. Using a large set of synthetic and real microarray data, we demonstrate the superior performance of our approach over several popular existing algorithms. Applications of our approach to yeast, Arabidopsis and human cancer microarray data reveal many interesting modules, including a fatal subtype of lymphoma and a gene module regulating yeast telomere integrity, which were missed by the existing methods.</p> <p>Conclusions</p> <p>We demonstrated that our novel approach is very effective in discovering the modular structures in microarray data, both for genes and for samples. As the method is essentially parameter-free, it may be applied to large data sets where the number of clusters is difficult to estimate. The method is also very general and can be applied to other types of data. A MATLAB implementation of our algorithm can be downloaded from <url>http://cs.utsa.edu/~jruan/Software.html</url>.</p

Network deconvolution as a general method to distinguish direct dependencies in networks

Recognizing direct relationships between variables connected in a network is a pervasive problem in biological, social and information sciences as correlation-based networks contain numerous indirect relationships. Here we present a general method for inferring direct effects from an observed correlation matrix containing both direct and indirect effects. We formulate the problem as the inverse of network convolution, and introduce an algorithm that removes the combined effect of all indirect paths of arbitrary length in a closed-form solution by exploiting eigen-decomposition and infinite-series sums. We demonstrate the effectiveness of our approach in several network applications: distinguishing direct targets in gene expression regulatory networks; recognizing directly interacting amino-acid residues for protein structure prediction from sequence alignments; and distinguishing strong collaborations in co-authorship social networks using connectivity information alone. In addition to its theoretical impact as a foundational graph theoretic tool, our results suggest network deconvolution is widely applicable for computing direct dependencies in network science across diverse disciplines.National Institutes of Health (U.S.) (grant R01 HG004037)National Institutes of Health (U.S.) (grant HG005639)Swiss National Science Foundation (Fellowship)National Science Foundation (U.S.) (NSF CAREER Award 0644282