Rare Variant Association Testing by Adaptive Combination of P-values

With the development of next-generation sequencing technology, there is a great demand for powerful statistical methods to detect rare variants (minor allele frequencies (MAFs)<1%) associated with diseases. Testing for each variant site individually is known to be underpowered, and therefore many methods have been proposed to test for the association of a group of variants with phenotypes, by pooling signals of the variants in a chromosomal region. However, this pooling strategy inevitably leads to the inclusion of a large proportion of neutral variants, which may compromise the power of association tests. To address this issue, we extend the -MidP method (Cheung et al., 2012, Genet Epidemiol 36: 675–685) and propose an approach (named ‘adaptive combination of P-values for rare variant association testing’, abbreviated as ‘ADA’) that adaptively combines per-site P-values with the weights based on MAFs. Before combining P-values, we first imposed a truncation threshold upon the per-site P-values, to guard against the noise caused by the inclusion of neutral variants. This ADA method is shown to outperform popular burden tests and non-burden tests under many scenarios. ADA is recommended for next-generation sequencing data analysis where many neutral variants may be included in a functional region.     

Association Testing of Clustered Rare Causal Variants in Case-Control Studies

Biological evidence suggests that multiple causal variants in a gene may cluster physically. Variants within the same protein functional domain or gene regulatory element would locate in close proximity on the DNA sequence. However, spatial information of variants is usually not used in current rare variant association analyses. We here propose a clustering method (abbreviated as “CLUSTER”), which is extended from the adaptive combination of P-values. Our method combines the association signals of variants that are more likely to be causal. Furthermore, the statistic incorporates the spatial information of variants. With extensive simulations, we show that our method outperforms several commonly-used methods in many scenarios. To demonstrate its use in real data analyses, we also apply this CLUSTER test to the Dallas Heart Study data. CLUSTER is among the best methods when the effects of causal variants are all in the same direction. As variants located in close proximity are more likely to have similar impact on disease risk, CLUSTER is recommended for association testing of clustered rare causal variants in case-control studies.     

VarSAn: associating pathways with a set of genomic variants using network analysis

There is a pressing need today to mechanistically interpret sets of genomic variants associated with diseases. Here we present a tool called ‘VarSAn’ that uses a network analysis algorithm to identify pathways relevant to a given set of variants. VarSAn analyzes a configurable network whose nodes represent variants, genes and pathways, using a Random Walk with Restarts algorithm to rank pathways for relevance to the given variants, and reports P-values for pathway relevance. It treats non-coding and coding variants differently, properly accounts for the number of pathways impacted by each variant and identifies relevant pathways even if many variants do not directly impact genes of the pathway. We use VarSAn to identify pathways relevant to variants related to cancer and several other diseases, as well as drug response variation. We find VarSAn''s pathway ranking to be complementary to the standard approach of enrichment tests on genes related to the query set. We adopt a novel benchmarking strategy to quantify its advantage over this baseline approach. Finally, we use VarSAn to discover key pathways, including the VEGFA-VEGFR2 pathway, related to de novo variants in patients of Hypoplastic Left Heart Syndrome, a rare and severe congenital heart defect.     

The Triangulation WIthin a STudy (TWIST) framework for causal inference within pharmacogenetic research

In this paper we review the methodological underpinnings of the general pharmacogenetic approach for uncovering genetically-driven treatment effect heterogeneity. This typically utilises only individuals who are treated and relies on fairly strong baseline assumptions to estimate what we term the ‘genetically moderated treatment effect’ (GMTE). When these assumptions are seriously violated, we show that a robust but less efficient estimate of the GMTE that incorporates information on the population of untreated individuals can instead be used. In cases of partial violation, we clarify when Mendelian randomization and a modified confounder adjustment method can also yield consistent estimates for the GMTE. A decision framework is then described to decide when a particular estimation strategy is most appropriate and how specific estimators can be combined to further improve efficiency. Triangulation of evidence from different data sources, each with their inherent biases and limitations, is becoming a well established principle for strengthening causal analysis. We call our framework ‘Triangulation WIthin a STudy’ (TWIST)’ in order to emphasise that an analysis in this spirit is also possible within a single data set, using causal estimates that are approximately uncorrelated, but reliant on different sets of assumptions. We illustrate these approaches by re-analysing primary-care-linked UK Biobank data relating to CYP2C19 genetic variants, Clopidogrel use and stroke risk, and data relating to APOE genetic variants, statin use and Coronary Artery Disease.     

The power comparison of the haplotype-based collapsing tests and the variant-based collapsing tests for detecting rare variants in pedigrees

Background

Both common and rare genetic variants have been shown to contribute to the etiology of complex diseases. Recent genome-wide association studies (GWAS) have successfully investigated how common variants contribute to the genetic factors associated with common human diseases. However, understanding the impact of rare variants, which are abundant in the human population (one in every 17 bases), remains challenging. A number of statistical tests have been developed to analyze collapsed rare variants identified by association tests. Here, we propose a haplotype-based approach. This work inspired by an existing statistical framework of the pedigree disequilibrium test (PDT), which uses genetic data to assess the effects of variants in general pedigrees. We aim to compare the performance between the haplotype-based approach and the rare variant-based approach for detecting rare causal variants in pedigrees.

Results

Extensive simulations in the sequencing setting were carried out to evaluate and compare the haplotype-based approach with the rare variant methods that drew on a more conventional collapsing strategy. As assessed through a variety of scenarios, the haplotype-based pedigree tests had enhanced statistical power compared with the rare variants based pedigree tests when the disease of interest was mainly caused by rare haplotypes (with multiple rare alleles), and vice versa when disease was caused by rare variants acting independently. For most of other situations when disease was caused both by haplotypes with multiple rare alleles and by rare variants with similar effects, these two approaches provided similar power in testing for association.

Conclusions

The haplotype-based approach was designed to assess the role of rare and potentially causal haplotypes. The proposed rare variants-based pedigree tests were designed to assess the role of rare and potentially causal variants. This study clearly documented the situations under which either method performs better than the other. All tests have been implemented in a software, which was submitted to the Comprehensive R Archive Network (CRAN) for general use as a computer program named rvHPDT.     

Genome survey on invasive veined rapa whelk (<Emphasis Type="Italic">Rapana venosa</Emphasis>) and development of microsatellite loci on large scale

Increasing evidence shows that one variant can affect multiple traits, which is a widespread phenomenon in complex diseases. Joint analysis of multiple traits can increase statistical power of association analysis and uncover the underlying genetic mechanism. Although there are many statistical methods to analyse multiple traits, most of these methods are usually suitable for detecting common variants associated with multiple traits. However, because of low minor allele frequency of rare variant, these methods are not optimal for rare variant association analysis. In this paper, we extend an adaptive combination of P values method (termed ADA) for single trait to test association between multiple traits and rare variants in the given region. For a given region, we use reverse regression model to test each rare variant associated with multiple traits and obtain the P value of single-variant test. Further, we take the weighted combination of these P values as the test statistic. Extensive simulation studies show that our approach is more powerful than several other comparison methods in most cases and is robust to the inclusion of a high proportion of neutral variants and the different directions of effects of causal variants.     

Whole Exome Sequencing of Distant Relatives in Multiplex Families Implicates Rare Variants in Candidate Genes for Oral Clefts

A dozen genes/regions have been confirmed as genetic risk factors for oral clefts in human association and linkage studies, and animal models argue even more genes may be involved. Genomic sequencing studies should identify specific causal variants and may reveal additional genes as influencing risk to oral clefts, which have a complex and heterogeneous etiology. We conducted a whole exome sequencing (WES) study to search for potentially causal variants using affected relatives drawn from multiplex cleft families. Two or three affected second, third, and higher degree relatives from 55 multiplex families were sequenced. We examined rare single nucleotide variants (SNVs) shared by affected relatives in 348 recognized candidate genes. Exact probabilities that affected relatives would share these rare variants were calculated, given pedigree structures, and corrected for the number of variants tested. Five novel and potentially damaging SNVs shared by affected distant relatives were found and confirmed by Sanger sequencing. One damaging SNV in CDH1, shared by three affected second cousins from a single family, attained statistical significance (P = 0.02 after correcting for multiple tests). Family-based designs such as the one used in this WES study offer important advantages for identifying genes likely to be causing complex and heterogeneous disorders.     

Comprehensive Assessment of Genetic Sequence Variants in the Antioxidant ‘Master Regulator’ Nrf2 in Idiopathic Parkinson’s Disease

Parkinson’s disease (PD) is a complex neurodegenerative disorder influenced by a combination of genetic and environmental factors. The molecular mechanisms that underlie PD are unknown; however, oxidative stress and impairment of antioxidant defence mechanisms have been implicated as major contributors to disease pathogenesis. Previously, we have reported a PD patient-derived cellular model generated from biopsies of the olfactory mucosa, termed hONS cells, in which the NRF2-mediated antioxidant response pathway genes were among the most differentially-expressed. To date, few studies have examined the role of the NRF2 encoding gene, NFE2L2, and PD. In this study, we comprehensibly assessed whether rare and common NFE2L2 genetic variations modify susceptibility to PD using a large Australian case-control sample (PD=1338, controls=1379). We employed a haplotype-tagging approach that identified an association with the tagging SNP rs2364725 and PD (OR = 0.849 (0.760-0.948), P = 0.004). Further genetic screening in hONS cell lines produced no obvious pathogenic variants in the coding regions of NFE2L2. Finally, we investigated the relationship between xenobiotic exposures and NRF2 function, through gene-environment interactions, between NFE2L2 SNPs and smoking or pesticide exposure. Our results demonstrated a significant interaction between rs2706110 and pesticide exposure (OR = 0.597 (0.393-0.900), P = 0.014). In addition, we were able to identify some age-at-onset modifying SNPs and replicate an ‘early-onset’ haplotype that contains a previously identified ‘functional promoter’ SNP (rs6721961). Our results suggest a role of NFE2L2 genetic variants in modifying PD susceptibility and onset. Our findings also support the utility of testing gene-environment interactions in genetic studies of PD.     

Investigating the genetic architecture of conditional strategies using the environmental threshold model

The threshold expression of dichotomous phenotypes that are environmentally cued or induced comprise the vast majority of phenotypic dimorphisms in colour, morphology, behaviour and life history. Modelled as conditional strategies under the framework of evolutionary game theory, the quantitative genetic basis of these traits is a challenge to estimate. The challenge exists firstly because the phenotypic expression of the trait is dichotomous and secondly because the apparent environmental cue is separate from the biological signal pathway that induces the switch between phenotypes. It is the cryptic variation underlying the translation of cue to phenotype that we address here. With a ‘half-sib common environment’ and a ‘family-level split environment’ experiment, we examine the environmental and genetic influences that underlie male dimorphism in the earwig Forficula auricularia. From the conceptual framework of the latent environmental threshold (LET) model, we use pedigree information to dissect the genetic architecture of the threshold expression of forceps length. We investigate for the first time the strength of the correlation between observable and cryptic ‘proximate’ cues. Furthermore, in support of the environmental threshold model, we found no evidence for a genetic correlation between cue and the threshold between phenotypes. Our results show strong correlations between observable and proximate cues and less genetic variation for thresholds than previous studies have suggested. We discuss the importance of generating better estimates of the genetic variation for thresholds when investigating the genetic architecture and heritability of threshold traits. By investigating genetic architecture by means of the LET model, our study supports several key evolutionary ideas related to conditional strategies and improves our understanding of environmentally cued decisions.     

Robust detection of point mutations involved in multidrug-resistant Mycobacterium tuberculosis in the presence of co-occurrent resistance markers

Tuberculosis disease is a major global public health concern and the growing prevalence of drug-resistant Mycobacterium tuberculosis is making disease control more difficult. However, the increasing application of whole-genome sequencing as a diagnostic tool is leading to the profiling of drug resistance to inform clinical practice and treatment decision making. Computational approaches for identifying established and novel resistance-conferring mutations in genomic data include genome-wide association study (GWAS) methodologies, tests for convergent evolution and machine learning techniques. These methods may be confounded by extensive co-occurrent resistance, where statistical models for a drug include unrelated mutations known to be causing resistance to other drugs. Here, we introduce a novel ‘cannibalistic’ elimination algorithm (“Hungry, Hungry SNPos”) that attempts to remove these co-occurrent resistant variants. Using an M. tuberculosis genomic dataset for the virulent Beijing strain-type (n = 3,574) with phenotypic resistance data across five drugs (isoniazid, rifampicin, ethambutol, pyrazinamide, and streptomycin), we demonstrate that this new approach is considerably more robust than traditional methods and detects resistance-associated variants too rare to be likely picked up by correlation-based techniques like GWAS.     

Identifying rare and common disease associated variants in genomic data using Parkinson’s disease as a model

Background

Genome-wide association studies have been successful in identifying common genetic variants for human diseases. However, much of the heritable variation associated with diseases such as Parkinson’s disease remains unknown suggesting that many more risk loci are yet to be identified. Rare variants have become important in disease association studies for explaining missing heritability. Methods for detecting this type of association require prior knowledge on candidate genes and combining variants within the region. These methods may suffer from power loss in situations with many neutral variants or causal variants with opposite effects.

Results

We propose a method capable of scanning genetic variants to identify the region most likely harbouring disease gene with rare and/or common causal variants. Our method assigns a score at each individual variant based on our scoring system. It uses aggregate scores to identify the region with disease association. We evaluate performance by simulation based on 1000 Genomes sequencing data and compare with three commonly used methods. We use a Parkinson’s disease case–control dataset as a model to demonstrate the application of our method.Our method has better power than CMC and WSS and similar power to SKAT-O with well-controlled type I error under simulation based on 1000 Genomes sequencing data. In real data analysis, we confirm the association of α-synuclein gene (SNCA) with Parkinson’s disease (p = 0.005). We further identify association with hyaluronan synthase 2 (HAS2, p = 0.028) and kringle containing transmembrane protein 1 (KREMEN1, p = 0.006). KREMEN1 is associated with Wnt signalling pathway which has been shown to play an important role for neurodegeneration in Parkinson’s disease.

Conclusions

Our method is time efficient and less sensitive to inclusion of neutral variants and direction effect of causal variants. It can narrow down a genomic region or a chromosome to a disease associated region. Using Parkinson’s disease as a model, our method not only confirms association for a known gene but also identifies two genes previously found by other studies. In spite of many existing methods, we conclude that our method serves as an efficient alternative for exploring genomic data containing both rare and common variants.

Electronic supplementary material

The online version of this article (doi:10.1186/s12929-014-0088-9) contains supplementary material, which is available to authorized users.     

Effects of Infection by Belonolaimus longicaudatus on Rooting Dynamics among St. Augustinegrass and Bermudagrass Genotypes

Understanding rooting dynamics using the minirhizotron technique is useful for cultivar selection and to quantify nematode damage to roots. A 2-yr microplot study including five bermudagrass (‘Tifway’, Belonolaimus longicaudatus susceptible; two commercial cultivars [TifSport and Celebration] and two genotypes [‘BA132’ and ‘PI 291590’], which have been reported to be tolerant to B. longicaudatus) and two St. Augustinegrass (‘FX 313’, susceptible, and ‘Floratam’ that was reported as tolerant to B. longicaudatus) genotypes in a 5 x 2 and 2 x 2 factorial design with four replications, respectively, was initiated in 2012. Two treatments included were uninoculated and B. longicaudatus inoculated. In situ root images were captured each month using a minirhizotron camera system from April to September of 2013 and 2014. Mixed models analysis and comparison of least squares means indicated significant differences in root parameters studied across the genotypes and soil depths of both grass species. ‘Celebration’, ‘TifSport’ and ‘PI 291590’ bermudagrass, and ‘Floratam’ St. Augustinegrass had significantly different root parameters compared to the corresponding susceptible genotypes (P ≤ 0.05). Only ‘TifSport’ had no significant root loss when infested with B. longicaudatus compared to non-infested. ‘Celebration’ and ‘PI 291590’ had significant root loss but retained significantly greater root densities than ‘Tifway’ in B. longicaudatus-infested conditions (P ≤ 0.05). Root lengths were greater at the 0 to 5 cm depth followed by 5 to 10 and 10 to 15 cm of vertical soil depth for both grass species (P ≤ 0.05). ‘Celebration’, ‘TifSport’, and ‘PI 291590’ had better root vigor against B. longicaudatus compared to Tifway.     

Differential Responses of CO2 Assimilation,Carbohydrate Allocation and Gene Expression to NaCl Stress in Perennial Ryegrass with Different Salt Tolerance

Little is known about the effects of NaCl stress on perennial ryegrass (Lolium perenne L.) photosynthesis and carbohydrate flux. The objective of this study was to understand the carbohydrate metabolism and identify the gene expression affected by salinity stress. Seventy-four days old seedlings of two perennial ryegrass accessions (salt-sensitive ‘PI 538976’ and salt-tolerant ‘Overdrive’) were subjected to three levels of salinity stress for 5 days. Turf quality in all tissues (leaves, stems and roots) of both grass accessions negatively and significantly correlated with GFS (Glu+Fru+Suc) content, except for ‘Overdrive’ stems. Relative growth rate (RGR) in leaves negatively and significantly correlated with GFS content in ‘Overdrive’ (P<0.01) and ‘PI 538976’ (P<0.05) under salt stress. ‘Overdrive’ had higher CO₂ assimilation and F_v/F_m than ‘PI 538976’. Intercellular CO₂ concentration, however, was higher in ‘PI 538976’ treated with 400 mM NaCl relative to that with 200 mM NaCl. GFS content negatively and significantly correlated with RGR in ‘Overdrive’ and ‘PI 538976’ leaves and in ‘PI 538976’ stems and roots under salt stress. In leaves, carbohydrate allocation negatively and significantly correlated with RGR (r² = 0.83, P<0.01) and turf quality (r² = 0.88, P<0.01) in salt-tolerant ‘Overdrive’, however, the opposite trend for salt-sensitive ‘PI 538976’ (r² = 0.71, P<0.05 for RGR; r² = 0.62, P>0.05 for turf quality). A greater up-regulation in the expression of SPS, SS, SI, 6-SFT gene was observed in ‘Overdrive’ than ‘PI 538976’. A higher level of SPS and SS expression in leaves was found in ‘PI 538976’ relative to ‘Overdrive’. Accumulation of hexoses in roots, stems and leaves can induce a feedback repression to photosynthesis in salt-stressed perennial ryegrass and the salt tolerance may be changed with the carbohydrate allocation in leaves and stems.     

Rare Genomic Structural Variants in Complex Disease: Lessons from the Replication of Associations with Obesity

The limited ability of common variants to account for the genetic contribution to complex disease has prompted searches for rare variants of large effect, to partly explain the ‘missing heritability’. Analyses of genome-wide genotyping data have identified genomic structural variants (GSVs) as a source of such rare causal variants. Recent studies have reported multiple GSV loci associated with risk of obesity. We attempted to replicate these associations by similar analysis of two familial-obesity case-control cohorts and a population cohort, and detected GSVs at 11 out of 18 loci, at frequencies similar to those previously reported. Based on their reported frequencies and effect sizes (OR≥25), we had sufficient statistical power to detect the large majority (80%) of genuine associations at these loci. However, only one obesity association was replicated. Deletion of a 220 kb region on chromosome 16p11.2 has a carrier population frequency of 2×10⁻⁴ (95% confidence interval [9.6×10⁻⁵–3.1×10⁻⁴]); accounts overall for 0.5% [0.19%–0.82%] of severe childhood obesity cases (P = 3.8×10⁻¹⁰; odds ratio = 25.0 [9.9–60.6]); and results in a mean body mass index (BMI) increase of 5.8 kg.m⁻² [1.8–10.3] in adults from the general population. We also attempted replication using BMI as a quantitative trait in our population cohort; associations with BMI at or near nominal significance were detected at two further loci near KIF2B and within FOXP2, but these did not survive correction for multiple testing. These findings emphasise several issues of importance when conducting rare GSV association, including the need for careful cohort selection and replication strategy, accurate GSV identification, and appropriate correction for multiple testing and/or control of false discovery rate. Moreover, they highlight the potential difficulty in replicating rare CNV associations across different populations. Nevertheless, we show that such studies are potentially valuable for the identification of variants making an appreciable contribution to complex disease.     

Psychological and physiological effect in humans of touching plant foliage - using the semantic differential method and cerebral activity as indicators

Background

Numerous studies have reported on the healing powers of plants and nature, but there have not been so many instances of experimental research. In particular, there are very few psychological and physiological studies using tactile stimuli. This study examines the psychological and physiological effects of touching plant foliage by using an evaluation profile of the subjects’ impressions and investigating cerebral blood flow.

Methods

The subjects were 14 young Japanese men aged from 21 to 27 years (mean ± standard deviation: 23.6 ± 2.4). With their eyes closed, the subjects touched four different tactile samples including a leaf of natural pothos (Epipremnum aureum). The physiological indices were compared before and after each stimulus. Psychological indices were obtained using a ‘semantic differential’ method.

Results

The fabric stimulus gave people ‘soft’ and ‘rough’ impressions, ‘kind’, ‘peaceful’ and ‘pleasant’ feelings psychologically, and a sense of physiological calm. On the other hand, the metal stimulus gave people ‘cold’, ‘smooth’ and ‘hard’ impressions and an image of something ‘artificial’. The metal stimulus caused a stress response in human cerebral blood flow although its evaluation in terms of ‘pleasant or unpleasant’ was neutral. There were no remarkable differences between the stimuli of natural and artificial pothos compared with other types of stimulus psychologically. However, only the natural pothos stimulus showed a sense of physiological calm in the same appearance as the fabric stimulus.

Conclusions

This study shows that people experience an unconscious calming reaction to touching a plant. It is to be concluded that plants are an indispensable element of the human environment.     

Perceived Stress and Coping Strategies in Relation to Body Mass Index: Cross-Sectional Study of 12,045 Japanese Men and Women

BackgroundAccumulated evidence suggests a weak positive relationship between psychosocial stress and body mass index (BMI), but little is known about stress coping strategies and BMI.ObjectiveWe aimed to examine if perceived stress and coping strategies are related to BMI, with any of their mutual interactions on BMI.MethodsThis cross-sectional study included 5,063 men and 6,982 women aged 40-69 years. A self-administered questionnaire ascertained perceived stress and 5 items of coping strategies (emotion expression, emotional support seeking, positive reappraisal, problem solving, and disengagement). Analyses were performed by gender with adjustment for age, socioeconomic status, and lifestyle factors.ResultsNo significant associations were detected between perceived stress and BMI in either men (P_trend = 0.09) or women (P_trend = 0.58). In men, however, ‘disengagement’ showed an inverse association with BMI (P_trend < 0.001), and ‘positive reappraisal’ and ‘problem solving’ revealed a positive association with BMI (P_trend = 0.04 and 0.007, respectively) even after controlling for perceived stress. A possible interaction between perceived stress and ‘disengagement’ on BMI was found in men (P_interaction = 0.027); the inverse association between ‘disengagement’ and BMI was more evident in higher levels of stress (β = −0.13, P_trend = 0.21 in low; β = −0.22, P_trend = 0.01 in medium; and β = −0.24, P_trend = 0.06 in high). In men, ‘disengagement’ was inversely associated with overweight/obesity (odds ratio 0.79, 95% confidential interval 0.67-0.95), and “positive reappraisal” was positively associated with it (1.25, 1.02-1.54).ConclusionsCoping strategies may have an important role in developing overweight/obesity, particularly in men.     

The Characteristics of Heterozygous Protein Truncating Variants in the Human Genome

Sequencing projects have identified large numbers of rare stop-gain and frameshift variants in the human genome. As most of these are observed in the heterozygous state, they test a gene’s tolerance to haploinsufficiency and dominant loss of function. We analyzed the distribution of truncating variants across 16,260 autosomal protein coding genes in 11,546 individuals. We observed 39,893 truncating variants affecting 12,062 genes, which significantly differed from an expectation of 12,916 genes under a model of neutral de novo mutation (p<10⁻⁴). Extrapolating this to increasing numbers of sequenced individuals, we estimate that 10.8% of human genes do not tolerate heterozygous truncating variants. An additional 10 to 15% of truncated genes may be rescued by incomplete penetrance or compensatory mutations, or because the truncating variants are of limited functional impact. The study of protein truncating variants delineates the essential genome and, more generally, identifies rare heterozygous variants as an unexplored source of diversity of phenotypic traits and diseases.     

Jack-of-all-trades: phenotypic plasticity facilitates the invasion of an alien slug species

Invasive alien species might benefit from phenotypic plasticity by being able to (i) maintain fitness in stressful environments (‘robust’), (ii) increase fitness in favourable environments (‘opportunistic’), or (iii) combine both abilities (‘robust and opportunistic’). Here, we applied this framework, for the first time, to an animal, the invasive slug, Arion lusitanicus, and tested (i) whether it has a more adaptive phenotypic plasticity compared with a congeneric native slug, Arion fuscus, and (ii) whether it is robust, opportunistic or both. During one year, we exposed specimens of both species to a range of temperatures along an altitudinal gradient (700–2400 m a.s.l.) and to high and low food levels, and we compared the responsiveness of two fitness traits: survival and egg production. During summer, the invasive species had a more adaptive phenotypic plasticity, and at high temperatures and low food levels, it survived better and produced more eggs than A. fuscus, representing the robust phenotype. During winter, A. lusitanicus displayed a less adaptive phenotype than A. fuscus. We show that the framework developed for plants is also very useful for a better mechanistic understanding of animal invasions. Warmer summers and milder winters might lead to an expansion of this invasive species to higher altitudes and enhance its spread in the lowlands, supporting the concern that global climate change will increase biological invasions.     

Large-scale pathway-based analysis of bladder cancer genome-wide association data from five studies of European background

Pathway analysis of genome-wide association studies (GWAS) offer a unique opportunity to collectively evaluate genetic variants with effects that are too small to be detected individually. We applied a pathway analysis to a bladder cancer GWAS containing data from 3,532 cases and 5,120 controls of European background (n = 5 studies). Thirteen hundred and ninety-nine pathways were drawn from five publicly available resources (Biocarta, Kegg, NCI-PID, HumanCyc, and Reactome), and we constructed 22 additional candidate pathways previously hypothesized to be related to bladder cancer. In total, 1421 pathways, 5647 genes and ∼90,000 SNPs were included in our study. Logistic regression model adjusting for age, sex, study, DNA source, and smoking status was used to assess the marginal trend effect of SNPs on bladder cancer risk. Two complementary pathway-based methods (gene-set enrichment analysis [GSEA], and adapted rank-truncated product [ARTP]) were used to assess the enrichment of association signals within each pathway. Eighteen pathways were detected by either GSEA or ARTP at P≤0.01. To minimize false positives, we used the I² statistic to identify SNPs displaying heterogeneous effects across the five studies. After removing these SNPs, seven pathways (‘Aromatic amine metabolism’ [P_GSEA = 0.0100, P_ARTP = 0.0020], ‘NAD biosynthesis’ [P_GSEA = 0.0018, P_ARTP = 0.0086], ‘NAD salvage’ [P_ARTP = 0.0068], ‘Clathrin derived vesicle budding’ [P_ARTP = 0.0018], ‘Lysosome vesicle biogenesis’ [P_GSEA = 0.0023, P_ARTP<0.00012], ’Retrograde neurotrophin signaling’ [P_GSEA = 0.00840], and ‘Mitotic metaphase/anaphase transition’ [P_GSEA = 0.0040]) remained. These pathways seem to belong to three fundamental cellular processes (metabolic detoxification, mitosis, and clathrin-mediated vesicles). Identification of the aromatic amine metabolism pathway provides support for the ability of this approach to identify pathways with established relevance to bladder carcinogenesis.     

Cryptic Biodiversity and the Origins of Pest Status Revealed in the Macrogenome of Simulium colombaschense (Diptera: Simuliidae), History’s Most Destructive Black Fly

The European black fly Simulium (Simulium) colombaschense (Scopoli), once responsible for as many as 22,000 livestock deaths per year, is chromosomally mapped, permitting its evolutionary relationships and pest drivers to be inferred. The species is 12 fixed inversions removed from the standard sequence of the subgenus Simulium. Three of these fixed inversions, 38 autosomal polymorphisms, and a complex set of 12 X and 6 Y chromosomes in 29 zygotic combinations uniquely characterize S. colombaschense and reveal 5 cytoforms: ‘A’ in the Danube watershed, ‘B’ in Italy’s Adige River, ‘C’ in the Aliakmonas River of Greece, ‘D’ in the Aoös drainage in Greece, and ‘E’ in the Belá River of Slovakia. ‘C’ and ‘D’ are reproductively isolated from one another, and ‘B’ is considered a cytotype of ‘A,’ the probable name bearer of colombaschense. The species status of ‘E’ cannot be determined without additional collections. Three derived polytene sequences, based on outgroup comparisons, place S. colombaschense in a clade of species composed of the S. jenningsi, S. malyschevi, and S. reptans species groups. Only cytoforms ‘A’ and ‘B’ are pests. Within the Simuliidae, pest status is reached through one of two principal pathways, both of which promote the production of large populations of blood-seeking flies: (1) colonization of the world’s largest rivers (habitat specialization) or (2) colonization of multiple habitat types (habitat generalization). Evolutionary acquisition of the ability to colonize large rivers by an ancestor of the S. jenningsi-malyschevi-reptans clade set the scene for the pest status of S. colombaschense and other big-river members of the clade. In an ironic twist, the macrogenome of S. colombaschense reveals that the name associated with history’s worst simuliid pest represents a complex of species, two or more of which are nonpests potentially vulnerable to loss of their limited habitat.