Identification of Differential Aberrations in Multiple‐Sample Array CGH Studies

Summary Most existing methods for identifying aberrant regions with array CGH data are confined to a single target sample. Focusing on the comparison of multiple samples from two different groups, we develop a new penalized regression approach with a fused adaptive lasso penalty to accommodate the spatial dependence of the clones. The nonrandom aberrant genomic segments are determined by assessing the significance of the differences between neighboring clones and neighboring segments. The algorithm proposed in this article is a first attempt to simultaneously detect the common aberrant regions within each group, and the regions where the two groups differ in copy number changes. The simulation study suggests that the proposed procedure outperforms the commonly used single‐sample aberration detection methods for segmentation in terms of both false positives and false negatives. To further assess the value of the proposed method, we analyze a data set from a study that identified the aberrant genomic regions associated with grade subgroups of breast cancer tumors.     

Genome‐based estimates of fungal rDNA copy number variation across phylogenetic scales and ecological lifestyles

Ribosomal DNA (rDNA) copy number variation (CNV) has major physiological implications for all organisms, but how it varies for fungi, an ecologically ubiquitous and important group of microorganisms, has yet to be systemically investigated. Here, we examine rDNA CNV using an in silico read depth approach for 91 fungal taxa with sequenced genomes and assess copy number conservation across phylogenetic scales and ecological lifestyles. rDNA copy number varied considerably across fungi, ranging from an estimated 14 to 1,442 copies (mean = 113, median = 82), and copy number similarity was inversely correlated with phylogenetic distance. No correlations were found between rDNA CNV and fungal trophic mode, ecological guild or genome size. Taken together, these results show that like other microorganisms, fungi exhibit substantial variation in rDNA copy number, which is linked to their phylogeny in a scale‐dependent manner.     

Empirical‐likelihood‐based criteria for model selection on marginal analysis of longitudinal data with dropout missingness

Longitudinal data are common in clinical trials and observational studies, where missing outcomes due to dropouts are always encountered. Under such context with the assumption of missing at random, the weighted generalized estimating equation (WGEE) approach is widely adopted for marginal analysis. Model selection on marginal mean regression is a crucial aspect of data analysis, and identifying an appropriate correlation structure for model fitting may also be of interest and importance. However, the existing information criteria for model selection in WGEE have limitations, such as separate criteria for the selection of marginal mean and correlation structures, unsatisfactory selection performance in small‐sample setups, and so forth. In particular, there are few studies to develop joint information criteria for selection of both marginal mean and correlation structures. In this work, by embedding empirical likelihood into the WGEE framework, we propose two innovative information criteria named a joint empirical Akaike information criterion and a joint empirical Bayesian information criterion, which can simultaneously select the variables for marginal mean regression and also correlation structure. Through extensive simulation studies, these empirical‐likelihood‐based criteria exhibit robustness, flexibility, and outperformance compared to the other criteria including the weighted quasi‐likelihood under the independence model criterion, the missing longitudinal information criterion, and the joint longitudinal information criterion. In addition, we provide a theoretical justification of our proposed criteria, and present two real data examples in practice for further illustration.     

An efficient method for measuring copy number variation applied to improvement of nematode resistance in soybean

Copy number variation (CNV) is implicated in important traits in multiple crop plants, but can be challenging to genotype using conventional methods. The Rhg1 locus of soybean, which confers resistance to soybean cyst nematode (SCN), is a CNV of multiple 31.2‐kb genomic units each containing four genes. Reliable, high‐throughput methods to quantify Rhg1 and other CNVs for selective breeding were developed. The CNV genotyping assay described here uses a homeologous gene copy within the paleopolyploid soybean genome to provide the internal control for a single‐tube TaqMan copy number assay. Using this assay, CNV in breeding populations can be tracked with high precision. We also show that extensive CNV exists within Fayette, a released, inbred SCN‐resistant soybean cultivar with a high copy number at Rhg1 derived from a single donor parent. Copy number at Rhg1 is therefore unstable within a released variety over a relatively small number of generations. Using this assay to select for individuals with altered copy number, plants were obtained with both increased copy number and increased SCN resistance relative to control plants. Thus, CNV genotyping technologies can be used as a new type of marker‐assisted selection to select for desirable traits in breeding populations, and to control for undesirable variation within cultivars.     

Copy number variation associates with mortality in long‐lived individuals: a genome‐wide assessment

Copy number variants (CNVs) represent a significant source of genetic variation in the human genome and have been implicated in numerous diseases and complex traits. To date, only a few studies have investigated the role of CNVs in human lifespan. To investigate the impact of CNVs on prospective mortality at the extreme end of life, where the genetic component of lifespan appears most profound, we analyzed genomewide CNV data in 603 Danish nonagenarians and centenarians (mean age 96.9 years, range 90.0–102.5 years). Replication was performed in 500 long‐lived individuals from the Leiden Longevity Study (mean age 93.2 years, range 88.9–103.4 years). First, we assessed the association between the CNV burden of each individual (the number of CNVs, the average CNV length, and the total CNV length) and mortality and found a significant increase in mortality per 10 kb increase in the average CNV length, both for all CNVs (hazard ratio (HR) = 1.024, P = 0.002) and for duplications (HR = 1.011, P = 0.005), as well as per 100 kb increase in the total length of deletions (HR = 1.009, P = 0.0005). Next, we assessed the relation between specific deletions and duplications and mortality. Although no genome–wide significant associations were discovered, we identified six deletions and one duplication that showed consistent association with mortality in both or either of the sexes across both study populations. These results indicate that the genome–wide CNV burden, specifically the average CNV length and the total CNV length, associates with higher mortality in long‐lived individuals.     

Ultra‐deep Illumina sequencing accurately identifies MHC class IIb alleles and provides evidence for copy number variation in the guppy (Poecilia reticulata)

We address the bioinformatic issue of accurately separating amplified genes of the major histocompatibility complex (MHC) from artefacts generated during high‐throughput sequencing workflows. We fit observed ultra‐deep sequencing depths (hundreds to thousands of sequences per amplicon) of allelic variants to expectations from genetic models of copy number variation (CNV). We provide a simple, accurate and repeatable method for genotyping multigene families, evaluating our method via analyses of 209 b of MHC class IIb exon 2 in guppies (Poecilia reticulata). Genotype repeatability for resequenced individuals (N = 49) was high (100%) within the same sequencing run. However, repeatability dropped to 83.7% between independent runs, either because of lower mean amplicon sequencing depth in the initial run or random PCR effects. This highlights the importance of fully independent replicates. Significant improvements in genotyping accuracy were made by greatly reducing type I genotyping error (i.e. accepting an artefact as a true allele), which may occur when using low‐depth allele validation thresholds used by previous methods. Only a small amount (4.9%) of type II error (i.e. rejecting a genuine allele as an artefact) was detected through fully independent sequencing runs. We observed 1–6 alleles per individual, and evidence of sharing of alleles across loci. Variation in the total number of MHC class II loci among individuals, both among and within populations was also observed, and some genotypes appeared to be partially hemizygous; total allelic dosage added up to an odd number of allelic copies. Collectively, observations provide evidence of MHC CNV and its complex basis in natural populations.     

Accounting for uncertainty in the tree topology has little effect on the decision-theoretic approach to model selection in phylogeny estimation

Currently available methods for model selection used in phylogenetic analysis are based on an initial fixed-tree topology. Once a model is picked based on this topology, a rigorous search of the tree space is run under that model to find the maximum-likelihood estimate of the tree (topology and branch lengths) and the maximum-likelihood estimates of the model parameters. In this paper, we propose two extensions to the decision-theoretic (DT) approach that relax the fixed-topology restriction. We also relax the fixed-topology restriction for the Bayesian information criterion (BIC) and the Akaike information criterion (AIC) methods. We compare the performance of the different methods (the relaxed, restricted, and the likelihood-ratio test [LRT]) using simulated data. This comparison is done by evaluating the relative complexity of the models resulting from each method and by comparing the performance of the chosen models in estimating the true tree. We also compare the methods relative to one another by measuring the closeness of the estimated trees corresponding to the different chosen models under these methods. We show that varying the topology does not have a major impact on model choice. We also show that the outcome of the two proposed extensions is identical and is comparable to that of the BIC, Extended-BIC, and DT. Hence, using the simpler methods in choosing a model for analyzing the data is more computationally feasible, with results comparable to the more computationally intensive methods. Another outcome of this study is that earlier conclusions about the DT approach are reinforced. That is, LRT, Extended-AIC, and AIC result in more complicated models that do not contribute to the performance of the phylogenetic inference, yet cause a significant increase in the time required for data analysis.     

Microarray karyotyping of maltose‐fermenting Saccharomyces yeasts with differing maltotriose utilization profiles reveals copy number variation in genes involved in maltose and maltotriose utilization

Aims: We performed an analysis of maltotriose utilization by 52 Saccharomyces yeast strains able to ferment maltose efficiently and correlated the observed phenotypes with differences in the copy number of genes possibly involved in maltotriose utilization by yeast cells. Methods and Results: The analysis of maltose and maltotriose utilization by laboratory and industrial strains of the species Saccharomyces cerevisiae and Saccharomyces pastorianus (a natural S. cerevisiae/Saccharomyces bayanus hybrid) was carried out using microscale liquid cultivation, as well as in aerobic batch cultures. All strains utilize maltose efficiently as a carbon source, but three different phenotypes were observed for maltotriose utilization: efficient growth, slow/delayed growth and no growth. Through microarray karyotyping and pulsed‐field gel electrophoresis blots, we analysed the copy number and localization of several maltose‐related genes in selected S. cerevisiae strains. While most strains lacked the MPH2 and MPH3 transporter genes, almost all strains analysed had the AGT1 gene and increased copy number of MALx1 permeases. Conclusions: Our results showed that S. pastorianus yeast strains utilized maltotriose more efficiently than S. cerevisiae strains and highlighted the importance of the AGT1 gene for efficient maltotriose utilization by S. cerevisiae yeasts. Significance and Impact of the Study: Our results revealed new maltotriose utilization phenotypes, contributing to a better understanding of the metabolism of this carbon source for improved fermentation by Saccharomyces yeasts.     

Intraspecific trait variation increases species diversity in a trait‐based grassland model

Intraspecific trait variation (ITV) is thought to play a significant role in community assembly, but the magnitude and direction of its influence are not well understood. Although it may be critical to better explain population persistence, species interactions, and therefore biodiversity patterns, manipulating ITV in experiments is challenging. We therefore incorporated ITV into a trait‐ and individual‐based model of grassland community assembly by adding variation to the plants’ functional traits, which then drive life‐history tradeoffs. Varying the amount of ITV in the simulation, we examine its influence on pairwise‐coexistence and then on the species diversity in communities of different initial sizes. We find that ITV increases the ability of the weakest species to invade most, but that this effect does not scale to the community level, where the primary effect of ITV is to increase the persistence and abundance of the competitively‐average species. Diversity of the initial community is also of critical importance in determining ITV's efficacy; above a threshold of interspecific diversity, ITV does not increase diversity further. For communities below this threshold, ITV mainly helps to increase diversity in those communities that would otherwise be low‐diversity. These findings suggest that ITV actively maintains diversity by helping the species on the margins of persistence, but mostly in habitats of relatively low alpha and beta diversity.     

Fragile X‐associated tremor/ataxia syndrome: Regional decrease of mitochondrial DNA copy number relates to clinical manifestations

Fragile X‐associated tremor/ataxia syndrome (FXTAS) is a late‐onset neurodegenerative disorder that appears in at least one‐third of adult carriers of a premutation (55‐200 CGG repeats) in the fragile X mental retardation 1 (FMR1) gene. Several studies have shown that mitochondrial dysfunction may play a central role in aging and also in neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, Huntington's disease as well as in FXTAS. It has been recently proposed that mtDNA copy number, measured by the number of mitochondrial genomes per nuclear genome (diploid), could be a useful biomarker of mitochondrial dysfunction. In order to elucidate the role of mtDNA variation in the pathogenesis of FXTAS, mtDNA copy number was quantified by digital droplet Polymerase chain reaction. In human brain samples, mtDNA levels were measured in the cerebellar vermis, dentate nucleus, parietal and temporal cortex, thalamus, caudate nucleus and hippocampus from a female FXTAS patient, a FMR1 premutation male carrier without FXTAS and from three male controls. The mtDNA copy number was further analyzed using this technology in dermal fibroblasts primary cultures derived from three FXTAS patients and three controls as well as in cortex and cerebellum of a CGG knock in FXTAS mice model. Finally, qPCR was carried out in human blood samples. Results indicate reduced mtDNA copy number in the specific brain region associated with disease progression in FXTAS patients, providing new insights into the role of mitochondrial dysfunction in the pathogenesis of FXTAS.     

Contemporary evolution of resistance at the major insecticide target site gene Ace‐1 by mutation and copy number variation in the malaria mosquito Anopheles gambiae

Functionally constrained genes are ideal insecticide targets because disruption is often fatal, and resistance mutations are typically costly. Synaptic acetylcholinesterase (AChE) is an essential neurotransmission enzyme targeted by insecticides used increasingly in malaria control. In Anopheles and Culex mosquitoes, a glycine–serine substitution at codon 119 of the Ace‐1 gene confers both resistance and fitness costs, especially for 119S/S homozygotes. G119S in Anopheles gambiae from Accra (Ghana) is strongly associated with resistance, and, despite expectations of cost, resistant 119S alleles are increasing significantly in frequency. Sequencing of Accra females detected only a single Ace‐1 119S haplotype, whereas 119G diversity was high overall but very low at non‐synonymous sites, evidence of strong purifying selection driven by functional constraint. Flanking microsatellites showed reduced diversity, elevated linkage disequilibrium and high differentiation of 119S, relative to 119G homozygotes across up to two megabases of the genome. Yet these signals of selection were inconsistent and sometimes weak tens of kilobases from Ace‐1. This unexpected finding is attributable to apparently ubiquitous amplification of 119S alleles as part of a large copy number variant (CNV) far exceeding the size of the Ace‐1 gene, whereas 119G alleles were unduplicated. Ace‐1 CNV was detectable in archived samples collected when the 119S allele was rare in Ghana. Multicopy amplification of resistant alleles has not been observed previously and is likely to underpin the recent increase in 119S frequency. The large CNV compromised localization of the strong selective sweep around Ace‐1, emphasizing the need to integrate CNV analysis into genome scans for selection.     

A simple method to score single nucleotide polymorphisms based on allele‐specific PCR and primer‐induced fragment‐length variation

We describe a simple protocol to genotype single nucleotide polymorphisms (SNPs), which combines allele‐specific polymerase chain reaction (PCR) with fragment‐length analysis. Three primers are used in the PCR: two allele‐specific forward primers with a length‐difference and one reverse primer. The forward primers induce a length‐difference between the SNP‐variants, which can be assessed with standard fragment‐length analyses. We designed primers for 21 SNPs, and codominance was achieved for 76% of these SNPs. An inexpensive and flexible laser‐detection scoring protocol can be achieved with multiplex scoring and by incorporating the M13(‐21) genotyping method.     

A trans‐national monarch butterfly population model and implications for regional conservation priorities

1. The monarch has undergone considerable population declines over the past decade, and the governments of Mexico, Canada, and the United States have agreed to work together to conserve the species. 2. Given limited resources, understanding where to focus conservation action is key for widespread species like monarchs. To support planning for continental‐scale monarch habitat restoration, we address the question of where restoration efforts are likely to have the largest impacts on monarch butterfly (Danaus plexippus Linn.) population growth rates. 3. We present a spatially explicit demographic model simulating the multi‐generational annual cycle of the eastern monarch population, and use the model to examine management scenarios, some of which focus on particular regions of North America. 4. Improving the monarch habitat in the north central or southern parts of the monarch range yields a slightly greater increase in the population growth rate than restoration in other regions. However, combining restoration efforts across multiple regions yields population growth rates above 1 with smaller simulated improvements in habitat per region than single‐region strategies. 5. S ynthesis and applications: These findings suggest that conservation investment in projects across the full monarch range will be more effective than focusing on one or a few regions, and will require international cooperation across many land use categories.     

A joint individual‐based model coupling growth and mortality reveals that tree vigor is a key component of tropical forest dynamics

Tree vigor is often used as a covariate when tree mortality is predicted from tree growth in tropical forest dynamic models, but it is rarely explicitly accounted for in a coherent modeling framework. We quantify tree vigor at the individual tree level, based on the difference between expected and observed growth. The available methods to join nonlinear tree growth and mortality processes are not commonly used by forest ecologists so that we develop an inference methodology based on an MCMC approach, allowing us to sample the parameters of the growth and mortality model according to their posterior distribution using the joint model likelihood. We apply our framework to a set of data on the 20‐year dynamics of a forest in Paracou, French Guiana, taking advantage of functional trait‐based growth and mortality models already developed independently. Our results showed that growth and mortality are intimately linked and that the vigor estimator is an essential predictor of mortality, highlighting that trees growing more than expected have a far lower probability of dying. Our joint model methodology is sufficiently generic to be used to join two longitudinal and punctual linked processes and thus may be applied to a wide range of growth and mortality models. In the context of global changes, such joint models are urgently needed in tropical forests to analyze, and then predict, the effects of the ongoing changes on the tree dynamics in hyperdiverse tropical forests.     

Individual differences in behaviour explain variation in survival: a meta‐analysis

Research focusing on among‐individual differences in behaviour (‘animal personality’) has been blooming for over a decade. Central theories explaining the maintenance of such behavioural variation posits that individuals expressing greater “risky” behaviours should suffer higher mortality. Here, for the first time, we synthesize the existing empirical evidence for this key prediction. Our results did not support this prediction as there was no directional relationship between riskier behaviour and greater mortality; however there was a significant absolute relationship between behaviour and survival. In total, behaviour explained a significant, but small, portion (5.8%) of the variance in survival. We also found that risky (vs. “shy”) behavioural types live significantly longer in the wild, but not in the laboratory. This suggests that individuals expressing risky behaviours might be of overall higher quality but the lack of predation pressure and resource restrictions mask this effect in laboratory environments. Our work demonstrates that individual differences in behaviour explain important differences in survival but not in the direction predicted by theory. Importantly, this suggests that models predicting behaviour to be a mediator of reproduction‐survival trade‐offs may need revision and/or empiricists may need to reconsider their proxies of risky behaviours when testing such theory.     

Unifying ecology and macroevolution with individual‐based theory

A contemporary goal in both ecology and evolutionary biology is to develop theory that transcends the boundary between the two disciplines, to understand phenomena that cannot be explained by either field in isolation. This is challenging because macroevolution typically uses lineage‐based models, whereas ecology often focuses on individual organisms. Here, we develop a new parsimonious individual‐based theory by adding mild selection to the neutral theory of biodiversity. We show that this model generates realistic phylogenies showing a slowdown in diversification and also improves on the ecological predictions of neutral theory by explaining the occurrence of very common species. Moreover, we find the distribution of individual fitness changes over time, with average fitness increasing at a pace that depends positively on community size. Consequently, large communities tend to produce fitter species than smaller communities. These findings have broad implications beyond biodiversity theory, potentially impacting, for example, invasion biology and paleontology.     

Geographical variation in reproductive traits and trade‐offs between size and number of eggs in the king ratsnake,Elaphe carinata

We collected gravid king ratsnakes (Elaphe carinata) from three geographically separated populations in Chenzhou (CZ), Lishui (LS) and Dinghai (DH) of China to study the geographical variation in female reproductive traits and trade‐offs between the size and number of eggs. Not all reproductive traits varied among the three populations. Of the traits examined, five (egg‐laying date, post‐oviposition body mass, clutch size, egg mass and egg width) differed among the three populations. The egg‐laying date, ranging from late June to early August, varied among populations in a geographically continuous trend, with females at the most northern latitude (DH) laying eggs latest, and females at the most southern latitude (CZ) laying eggs earliest. Such a trend was less evident or even absent in the other traits that differed among the three populations. CZ and DH females, although separated by a distance of approximately 1100 km as the crow flies, were similar to each other in most traits examined. LS females were distinguished from CZ and DH females by the fact that they laid a greater number of eggs, but these were smaller. The egg size–number trade‐off was evident in each of the three populations and, at a given level of relative fecundity, egg mass was significantly greater in the DH population than in the LS population. © 2011 The Linnean Society of London, Biological Journal of the Linnean Society, 2011, 104 , 701–709.