Maximum-likelihood model averaging to profile clustering of site types across discrete linear sequences

Lineage-specific genes are clustered with HET-domain genes and respond to environmental and genetic manipulations regulating reproduction in Neurospora

Lineage-specific genes (LSGs) have long been postulated to play roles in the establishment of genetic barriers to intercrossing and speciation. In the genome of Neurospora crassa, most of the 670 Neurospora LSGs that are aggregated adjacent to the telomeres are clustered with 61% of the HET-domain genes, some of which regulate self-recognition and define vegetative incompatibility groups. In contrast, the LSG-encoding proteins possess few to no domains that would help to identify potential functional roles. Possible functional roles of LSGs were further assessed by performing transcriptomic profiling in genetic mutants and in response to environmental alterations, as well as examining gene knockouts for phenotypes. Among the 342 LSGs that are dynamically expressed during both asexual and sexual phases, 64% were detectable on unusual carbon sources such as furfural, a wildfire-produced chemical that is a strong inducer of sexual development, and the structurally-related furan 5-hydroxymethyl furfural (HMF). Expression of a significant portion of the LSGs was sensitive to light and temperature, factors that also regulate the switch from asexual to sexual reproduction. Furthermore, expression of the LSGs was significantly affected in the knockouts of adv-1 and pp-1 that regulate hyphal communication, and expression of more than one quarter of the LSGs was affected by perturbation of the mating locus. These observations encouraged further investigation of the roles of clustered lineage-specific and HET-domain genes in ecology and reproduction regulation in Neurospora, especially the regulation of the switch from the asexual growth to sexual reproduction, in response to dramatic environmental conditions changes.

Comparison and multi-model inference of excess risks models for radiation-related solid cancer

In assessments of detrimental health risks from exposures to ionising radiation, many forms of risk to dose-response models are available in the literature. The usual practice is to base risk assessment on one specific model and ignore model uncertainty. The analysis illustrated here considers model uncertainty for the outcome all solid cancer incidence, when modelled as a function of colon organ dose, using the most recent publicly available data from the Life Span Study on atomic bomb survivors of Japan. Seven recent publications reporting all solid cancer risk models currently deemed plausible by the scientific community have been included in a model averaging procedure so that the main conclusions do not depend on just one type of model. The models have been estimated with different baselines and presented for males and females at various attained ages and ages at exposure, to obtain specially computed model-averaged Excess Relative Risks (ERR) and Excess Absolute Risks (EAR). Monte Carlo simulated estimation of uncertainty on excess risks was accounted for by applying realisations including correlations in the risk model parameters. Three models were found to weight the model-averaged risks most strongly depending on the baseline and information criteria used for the weighting. Fitting all excess risk models with the same baseline, one model dominates for both information criteria considered in this study. Based on the analysis presented here, it is generally recommended to take model uncertainty into account in future risk analyses.

Multigenerational experimental simulation of climate change on an economically important insect pest

Long-term multigenerational experimental simulations of climate change on insect pests of economically and socially important crops are crucial to anticipate challenges for feeding humanity in the not-so-far future. Mexican bean weevil Zabrotes subfasciatus, is a worldwide pest that attacks the common bean Phaseolus vulgaris seeds, in crops and storage. We designed a long term (i.e., over 10 generations), experimental simulation of climate change by increasing temperature and CO2 air concentration in controlled conditions according to model predictions for 2100. Higher temperature and CO2 concentrations favored pest's egg-to-adult development survival, even at high female fecundity. It also induced a reduction of fat storage and increase of protein content but did not alter body size. After 10 generations of simulation, genetic adaptation was detected for total lipid content only, however, other traits showed signs of such process. Future experimental designs and methods similar to ours, are key for studying long-term effects of climate change through multigenerational experimental designs.

Estimating Improved Partitioning Schemes for Ultraconserved Elements

Ultraconserved (UCEs) are popular markers for phylogenomic studies. They are relatively simple to collect from distantly-related organisms, and contain sufficient information to infer relationships at almost all taxonomic levels. Most studies of UCEs use partitioning to account for variation in rates and patterns of molecular evolution among sites, for example by estimating an independent model of molecular evolution for each UCE. However, rates and patterns of molecular evolution vary substantially within as well as between UCEs, suggesting that there may be opportunities to improve how UCEs are partitioned for phylogenetic inference. We propose and evaluate new partitioning methods for phylogenomic studies of UCEs: Sliding-Window Site Characteristics (SWSC), and UCE Site Position (UCESP). The first method uses site characteristics such as entropy, multinomial likelihood, and GC content to generate partitions that account for heterogeneity in rates and patterns of molecular evolution within each UCE. The second method groups together nucleotides that are found in similar physical locations within the UCEs. We examined the new methods with seven published data sets from a variety of taxa. We demonstrate the UCESP method generates partitions that are worse than other strategies used to partition UCE data sets (e.g., one partition per UCE). The SWSC method, particularly when based on site entropies, generates partitions that account for within-UCE heterogeneity and leads to large increases in the model fit. All of the methods, code, and data used in this study, are available from https://github.com/Tagliacollo/PartitionUCE. Simplified code for implementing the best method, the SWSC-EN, is available from https://github.com/Tagliacollo/PFinderUCE-SWSC-EN.

Detection of Regional Variation in Selection Intensity within Protein-Coding Genes Using DNA Sequence Polymorphism and Divergence

Numerous approaches have been developed to infer natural selection based on the comparison of polymorphism within species and divergence between species. These methods are especially powerful for the detection of uniform selection operating across a gene. However, empirical analyses have demonstrated that regions of protein-coding genes exhibiting clusters of amino acid substitutions are subject to different levels of selection relative to other regions of the same gene. To quantify this heterogeneity of selection within coding sequences, we developed Model Averaged Site Selection via Poisson Random Field (MASS-PRF). MASS-PRF identifies an ensemble of intragenic clustering models for polymorphic and divergent sites. This ensemble of models is used within the Poisson Random Field framework to estimate selection intensity on a site-by-site basis. Using simulations, we demonstrate that MASS-PRF has high power to detect clusters of amino acid variants in small genic regions, can reliably estimate the probability of a variant occurring at each nucleotide site in sequence data and is robust to historical demographic trends and recombination. We applied MASS-PRF to human gene polymorphism derived from the 1,000 Genomes Project and divergence data from the common chimpanzee. On the basis of this analysis, we discovered striking regional variation in selection intensity, indicative of positive or negative selection, in well-defined domains of genes that have previously been associated with neurological processing, immunity, and reproduction. We suggest that amino acid-altering substitutions within these regions likely are or have been selectively advantageous in the human lineage, playing important roles in protein function.

Genome Hotspots for Nucleotide Substitutions and the Evolution of Influenza A (H1N1) Human Strains

In recent years a number of studies have brought attention to the role of positive selection during the evolution of antigenic escape by influenza strains. Particularly, the identification of positively selected sites within antigenic domains of viral surface proteins has been used to suggest that the evolution of viral–host receptor binding specificity is driven by selection. Here we show that, following the 1918 outbreak, the antigenic sites of the hemagglutinin (HA) viral surface protein and the stalk region of neuraminidase became substitution hotspots. The hotspots show similar patterns of nucleotide substitution bias at synonymous and nonsynonymous sites. Such bias imposes directionality in amino acid replacements that can influence signals of selection at antigenic sites. Our results suggest that the high accumulation of substitutions within the antigenic sites of HA can explain not only cases of antigenic escape by antigenic drift but also lead to occasional episodes of viral extinction.

Phylogenetic Gaussian process model for the inference of functionally important regions in protein tertiary structures

A critical question in biology is the identification of functionally important amino acid sites in proteins. Because functionally important sites are under stronger purifying selection, site-specific substitution rates tend to be lower than usual at these sites. A large number of phylogenetic models have been developed to estimate site-specific substitution rates in proteins and the extraordinarily low substitution rates have been used as evidence of function. Most of the existing tools, e.g. Rate4Site, assume that site-specific substitution rates are independent across sites. However, site-specific substitution rates may be strongly correlated in the protein tertiary structure, since functionally important sites tend to be clustered together to form functional patches. We have developed a new model, GP4Rate, which incorporates the Gaussian process model with the standard phylogenetic model to identify slowly evolved regions in protein tertiary structures. GP4Rate uses the Gaussian process to define a nonparametric prior distribution of site-specific substitution rates, which naturally captures the spatial correlation of substitution rates. Simulations suggest that GP4Rate can potentially estimate site-specific substitution rates with a much higher accuracy than Rate4Site and tends to report slowly evolved regions rather than individual sites. In addition, GP4Rate can estimate the strength of the spatial correlation of substitution rates from the data. By applying GP4Rate to a set of mammalian B7-1 genes, we found a highly conserved region which coincides with experimental evidence. GP4Rate may be a useful tool for the in silico prediction of functionally important regions in the proteins with known structures.

To understand how a protein functions, a critical step is to know which regions in its protein tertiary structure may be functionally important. Functionally important protein regions are typically more conserved than other regions because mutations in these regions are more likely to be deleterious. A number of phylogenetic models have been developed to identify conserved sites or regions in proteins by comparing protein sequences from multiple species. However, most of these methods treat amino acid sites independently and do not consider the spatial clustering of conserved sites in the protein tertiary structure. Therefore, their power of identifying functional protein regions is limited. We develop a new statistical model, GP4Rate, which combines the information from the protein sequences and the protein tertiary structure to infer conserved regions. We demonstrate that GP4Rate outperforms Rate4Site, the most widely used phylogenetic software for inferring functional amino acid sites, via simulations with a case study of B7-1 genes. GP4Rate is a potentially useful tool for guiding mutagenesis experiments or providing insights on the relationship between protein structures and functions.

Sex-linked transcriptional divergence in the hermaphrodite fungus Neurospora tetrasperma

In the filamentous ascomycete Neurospora tetrasperma, a large (approx. 7 Mbp) region of suppressed recombination surrounds the mating-type (mat) locus. While the remainder of the genome is largely homoallelic, this region of recombinational suppression, extending over 1500 genes, is associated with sequence divergence. Here, we used microarrays to examine how the molecular phenotype of gene expression level is linked to this divergent region, and thus to the mating type. Culturing N. tetrasperma on agar media that induce sexual/female or vegetative/male tissue, we found 196 genes significantly differentially expressed between mat A and mat a mating types. Our data show that the genes exhibiting mat-linked expression are enriched in the region genetically linked to mating type, and sequence and expression divergence are positively correlated. Our results indicate that the phenotype of mat A strains is optimized for traits promoting sexual/female development and the phenotype of mat a strains for vegetative/male development. This discovery of differentially expressed genes associated with mating type provides a link between genotypic and phenotypic divergence in this taxon and illustrates a fungal analogue to sexual dimorphism found among animals and plants.

Genome-wide comparative analysis of pogo-like transposable elements in different Fusarium species

The recent availability of genome sequences of four different Fusarium species offers the opportunity to perform extensive comparative analyses, in particular of repeated sequences. In a recent work, the overall content of such sequences in the genomes of three phylogenetically related Fusarium species, F. graminearum, F. verticillioides, and F. oxysporum f. sp. lycopersici has been estimated. In this study, we present an exhaustive characterization of pogo-like elements, named Fots, in four Fusarium genomes. Overall 10 Fot and two Fot-related miniature inverted-repeat transposable element families were identified, revealing a diversification of multiple lineages of pogo-like elements, some of which accompanied by a gain of introns. This analysis also showed that such elements are present in an unusual high proportion in the genomes of F. oxysporum f. sp. lycopersici and Nectria haematococca (anamorph F. solani f. sp. pisi) in contrast with most other fungal genomes in which retroelements are the most represented. Interestingly, our analysis showed that the most numerous Fot families all contain potentially active or mobilisable copies, thus conferring a mutagenic potential of these transposable elements and consequently a role in strain adaptation and genome evolution. This role is strongly reinforced when examining their genomic distribution which is clearly biased with a high proportion (more than 80%) located on strain- or species-specific regions enriched in genes involved in pathogenicity and/or adaptation. Finally, the different reproductive characteristics of the four Fusarium species allowed us to investigate the impact of the process of repeat-induced point mutations on the expansion and diversification of Fot elements.

Expression of biomass-degrading enzymes is a major event during conidium development in Trichoderma reesei

The conidium plays a critical role in the life cycle of many filamentous fungi, being the primary means for survival under unfavorable conditions. To investigate the transcriptional changes taking place during the transition from growing hyphae to conidia in Trichoderma reesei, microarray experiments were performed. A total of 900 distinct genes were classified as differentially expressed, relative to their expression at time zero of conidiation, at least at one of the time points analyzed. The main functional categories (FunCat) overrepresented among the upregulated genes were those involving solute transport, metabolism, transcriptional regulation, secondary metabolite synthesis, lipases, proteases, and, particularly, cellulases and hemicellulases. Categories overrepresented among the downregulated genes were especially those associated with ribosomal and mitochondrial functions. The upregulation of cellulase and hemicellulase genes was dependent on the function of the positive transcriptional regulator XYR1, but XYR1 exerted no influence on conidiation itself. At least 20% of the significantly regulated genes were nonrandomly distributed within the T. reesei genome, suggesting an epigenetic component in the regulation of conidiation. The significant upregulation of cellulases and hemicellulases during this process, and thus cellulase and hemicellulase content in the spores of T. reesei, contributes to the hypothesis that the ability to hydrolyze plant biomass is a major trait of this fungus enabling it to break dormancy and reinitiate vegetative growth after a period of facing unfavorable conditions.

Multi-model inference of adult and childhood leukaemia excess relative risks based on the Japanese A-bomb survivors mortality data (1950-2000)

Some relatively new issues that augment the usual practice of ignoring model uncertainty, when making inference about parameters of a specific model, are brought to the attention of the radiation protection community here. Nine recently published leukaemia risk models, developed with the Japanese A-bomb epidemiological mortality data, have been included in a model-averaging procedure so that the main conclusions do not depend on just one type of model or statistical test. The models have been centred here at various adult and young ages at exposure, for some short times since exposure, in order to obtain specially computed childhood Excess Relative Risks (ERR) with uncertainties that account for correlations in the fitted parameters associated with the ERR dose-response. The model-averaged ERR at 1 Sv was not found to be statistically significant for attained ages of 7 and 12 years but was statistically significant for attained ages of 17, 22 and 55 years. Consequently, such risks when applied to other situations, such as children in the vicinity of nuclear installations or in estimates of the proportion of childhood leukaemia incidence attributable to background radiation (i.e. low doses for young ages and short times since exposure), are only of very limited value, with uncertainty ranges that include zero risk. For example, assuming a total radiation dose to a 5-year-old child of 10 mSv and applying the model-averaged risk at 10 mSv for a 7-year-old exposed at 2 years of age would result in an ERR=0.33, 95% CI: -0.51 to 1.22. One model (United Nations scientific committee on the effects of atomic radiation report. Volume 1. Annex A: epidemiological studies of radiation and cancer, United Nations, New York, 2006) weighted model-averaged risks of leukaemia most strongly by half of the total unity weighting and is recommended for application in future leukaemia risk assessments that continue to ignore model uncertainty. However, on the basis of the analysis presented here, it is generally recommended to take model uncertainty into account in future risk analyses.