The applicability of recurrent neural networks for biological sequence analysis

Selection of machine learning techniques requires a certain sensitivity to the requirements of the problem. In particular, the problem can be made more tractable by deliberately using algorithms that are biased toward solutions of the requisite kind. In this paper, we argue that recurrent neural networks have a natural bias toward a problem domain of which biological sequence analysis tasks are a subset. We use experiments with synthetic data to illustrate this bias. We then demonstrate that this bias can be exploitable using a data set of protein sequences containing several classes of subcellular localization targeting peptides. The results show that, compared with feed forward, recurrent neural networks will generally perform better on sequence analysis tasks. Furthermore, as the patterns within the sequence become more ambiguous, the choice of specific recurrent architecture becomes more critical.

Human threats to sandy beaches: a meta-analysis of ghost crabs illustrates global anthropogenic impacts

Beach and coastal dune systems are increasingly subjected to a broad range of anthropogenic pressures that on many shorelines require significant conservation and mitigation interventions. But these interventions require reliable data on the severity and frequency of adverse ecological impacts. Such evidence is often obtained by measuring the response of 'indicator species'.Ghost crabs are the largest invertebrates inhabiting tropical and subtropical sandy shores and are frequently used to assess human impacts on ocean beaches. Here we present the first global meta-analysis of these impacts, and analyse the design properties and metrics of studies using ghost-crabs in their assessment. This was complemented by a gap analysis to identify thematic areas of anthropogenic pressures on sandy beach ecosystems that are under-represented in the published literature.Our meta-analysis demonstrates a broad geographic reach, encompassing studies on shores of the Pacific, Indian, and Atlantic Oceans, as well as the South China Sea. It also reveals what are, arguably, two major limitations: i) the near-universal use of proxies (i.e. burrow counts to estimate abundance) at the cost of directly measuring biological traits and bio-markers in the organism itself; and ii) descriptive or correlative study designs that rarely extend beyond a simple 'compare and contrast approach', and hence fail to identify the mechanistic cause(s) of observed contrasts.Evidence for a historically narrow range of assessed pressures (i.e., chiefly urbanisation, vehicles, beach nourishment, and recreation) is juxtaposed with rich opportunities for the broader integration of ghost crabs as a model taxon in studies of disturbance and impact assessments on ocean beaches. Tangible advances will most likely occur where ghost crabs provide foci for experiments that test specific hypotheses associated with effects of chemical, light and acoustic pollution, as well as the consequences of climate change (e.g. species range shifts).

Effect of sublethal doses of the insecticide imidacloprid on adaptive traits of Drosophila melanogaster: Response to treatment over and after 15 consecutive generations

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Mice behaviorally selected for high Pavlovian fear memory exhibit fear generalization, HPA-axis alterations and increased basal activity in cortico-limbic circuits

Biological factors underlying individual variability in fearfulness and anxiety have important implications for stress-related psychiatric illness including PTSD and major depression. Using an advanced intercross line (AIL) derived from C57BL/6 and DBA/2J mouse strains and behavioral selection over 3 generations, we established two lines exhibiting High or Low fear behavior after fear conditioning. Across the selection generations, the two lines showed clear differences in training and tests for contextual and conditioned fear. Before fear conditioning training, there were no differences between lines in baseline freezing to a novel context. However, after fear conditioning High line mice demonstrated pronounced freezing in a new context suggestive of poor context discrimination. Fear generalization was not restricted to contextual fear. High fear mice froze to a novel acoustic stimulus while freezing in the Low line did not increase over baseline. Enhanced fear learning and generalization are consistent with transgenic and pharmacological disruption of the hypothalamic-pituitary-adrenal axis (HPA-axis) (Brinks, 2009, Thompson, 2004, Kaouane, 2012). To determine whether there were differences in HPA-axis regulation between the lines, morning urine samples were collected to measure basal corticosterone. Levels of secreted corticosterone in the circadian trough were analyzed by corticosterone ELISA. High fear mice were found to have higher basal corticosterone levels than low line animals. Examination of hormonal stress response components by qPCR revealed increased expression of CRH mRNA and decreased mRNA for MR and CRHR1 in hypothalamus of high fear mice. These alterations may contribute to both the behavioral phenotype and higher basal corticosterone in High fear mice. To determine basal brain activity in vivo in High and Low fear mice we used manganese-enhanced magnetic resonance imaging (MEMRI). Analysis revealed a pattern of basal brain activity made up of amygdala, cortical and hippocampal circuits that was elevated in the High line. Ongoing studies also seek to determine the relative balance of excitatory and inhibitory tone in the amygdala and hippocampus and the neuronal structure of its neurons. While these heterogeneous lines are selected on fear memory expression, HPA-axis alterations and differences in hippocampal activity segregate with the behavioral phenotypes. These differences are detectable in a basal state strongly suggesting these are biological traits underlying the behavioral phenotype (Johnson et al, 2011).

Comparative and functional genome analysis of fungi for development of the protein production host Trichoderma reesei

Filamentous fungi of the subphylum Pezizomycotina are well known as protein and secondary metabolite producers. Various industries take advantage of these capabilities. However, the molecular biology of yeasts, i.e. Saccharomycotina and especially that of Saccharomyces cerevisiae, the baker's yeast, is much better known. In an effort to explain fungal phenotypes through their genotypes we have compared protein coding gene contents of Pezizomycotina and Saccharomycotina. Only biomass degradation and secondary metabolism related protein families seem to have expanded recently in Pezizomycotina. Of the protein families clearly diverged between Pezizomycotina and Saccharomycotina, those related to mitochondrial functions emerge as the most prominent. However, the primary metabolism as described in S. cerevisiae is largely conserved in all fungi. Apart from the known secondary metabolism, Pezizomycotina have pathways that could link secondary metabolism to primary metabolism and a wealth of undescribed enzymes. Previous studies of individual Pezizomycotina genomes have shown that regardless of the difference in production efficiency and diversity of secreted proteins, the content of the known secretion machinery genes in Pezizomycotina and Saccharomycotina appears very similar. Genome wide analysis of gene products is therefore needed to better understand the efficient secretion of Pezizomycotina. We have developed methods applicable to transcriptome analysis of non-sequenced organisms. TRAC (Transcriptional profiling with the aid of affinity capture) has been previously developed at VTT for fast, focused transcription analysis. We introduce a version of TRAC that allows more powerful signal amplification and multiplexing. We also present computational optimisations of transcriptome analysis of non-sequenced organism and TRAC analysis in general. Trichoderma reesei is one of the most commonly used Pezizomycotina in the protein production industry. In order to understand its secretion system better and find clues for improvement of its industrial performance, we have analysed its transcriptomic response to protein secretion stress conditions. In comparison to S. cerevisiae, the response of T. reesei appears different, but still impacts on the same cellular functions. We also discovered in T. reesei interesting similarities to mammalian protein secretion stress response. Together these findings highlight targets for more detailed studies.

Quantifying forage specialisation in polyphagic insects: the polylectic and rare solitary bee, Colletes floralis (Hymenoptera: Colletidae)

Many insect species vary in their degree of foraging specialisation, with many bee species considered polyphagic (polylectic). Wild, non-managed bee species vary in their conservation status, and species-specific biological traits such as foraging specialisation may play an important role in determining variance in population declines. Current agri-environment schemes (AESs) prescribe the introduction of flower seed mixes for agricultural systems to aid the conservation of wild bees. However, the extent to which flower combinations adequately meet bee foraging requirements is poorly known. We quantitatively assessed pollen use and selectivity using two statistical approaches: Bailey's Intervals and Compositional Analysis, in an examplar species, a purportedly polylectic and rare bee, Colletes floralis, across 7 sites through detailed analysis of bee scopal pollen loads and flower abundance. Both approaches provided good congruence, but Compositional Analysis was more robust to small sample sizes. We advocate its use for the quantitative determination of foraging behaviour and dietary preference. Although C. floralis is polylectic, it showed a clear dietary preference for plants within the family Apiaceae. Where Apiaceae was uncommon, the species exploited alternative resources. Other plant families, such as the Apiaceae, could be included, or have their proportion increased in AES seed mixes, to aid the management of C. floralis and potentially other wild solitary bees of conservation concern. © 2011 The Authors. Insect Conservation and Diversity © 2011 The Royal Entomological Society.

Macroinvertebrate traits as biomonitoring tools in agricultural scenarios

Os ecossistemas de água doce – responsáveis por funções ambientais importantes e pelo fornecimento de bens e serviços insubstituíveis – têm vindo a ser severamente afectados por perturbações antropogénicas. A conversão de floresta em terreno agrícola afecta os sistemas aquáticos através de uma série de mecanismos: sedimentação; excesso de nutrientes; contaminação; alterações hidrológicas; e remoção de vegetação ripícola. As comunidades de macroinvertebrados de água doce – devido à sua diversidade, ubiquidade e sensibilidade às perturbações ambientais – revelam-se como particularmente adequadas para estudos de avaliação da integridade ecológica destes sistemas expostos simultaneamente a múltiplos factores de impacto. O uso sistemático de respostas biológicas para avaliação de mudanças ambientais – ou biomonitorização – pode ser levado a cabo através de diversas metodologias, que, de uma forma geral, não consideram aspectos funcionais das comunidades biológicas e têm aplicabilidade geograficamente restrita. A biomonitorização através de atributos biológicos (características que reflectem a adaptação das espécies ao seu meio ambiente) revela-se como uma ferramenta promissora na resolução dos problemas referidos, apresentando vantagens adicionais: relações causa-efeito directas; melhoria na diferenciação de impactos; e integração da variabilidade natural. O presente estudo apresenta uma revisão critica do estado-da-arte actual na área do uso de atributos biológicos em biomonitorização. Até à data de publicação, não estava disponível nenhum outro trabalho com a base conceptual do uso de atributos de macroinvertebrados enquanto descritores de comunidades e para efeitos de biomonitorização e gestão de sistemas de água doce. Descrevem-se as teorias ecológicas de suporte destas metodologias (conceitos de habitat-molde e de filtros paisagísticos) e os estudos que aplicaram estas teorias em cenários reais, tendo-se chamado a atenção para questões técnicas e possíveis soluções. As necessidades futuras nesta área englobam: o desenvolvimento de uma só ferramenta de biomonitorização de aplicação alargada; uma maior compreensão da variabilidade natural nas comunidades biológicas; diminuição dos efeitos de soluções de compromisso biológico e sindromas; realização de estudos autoecológicos adicionais; e detecção de impactos específicos em cenários de impacto complexos. Um dos objectivos deste estudo foi contribuir para a melhoria das técnicas de biomonitorização através de atributos, focalizando em comunidades de macroinvertebrados ribeirinhas em diferentes regiões biogeográficas (as bacias hidrográficas dos rios: Little e Salmon em New Brunswick, Canadá; Anllóns na Galiza, Espanha; Reventazón em Cartago, Costa Rica). Em cada região, foram estudados gradientes de uso agrícola de solo, incluindo desde bacias hidrográficas quase exclusivamente cobertas por floresta até bacias sob a influência maioritária de actividades agrícolas intensivas. Em cada gradiente de uso de solo, a caracterização da comunidade biológica (por amostragem de macroinvertebrados em troços de rápidos) foi acompanhada pela caracterização do habitat circundante (incluindo propriedades da bacia hidrográfica, análise química das águas e outras propriedades à escala local). A comunidade de macroinvertebrados foi caracterizada através de informação taxonómica, métricas estruturais, índices de diversidade, métricas de tolerância, índices bióticos e através da compilação de atributos biológicos e fisiológicos gerais, de história de vida e de resistência a perturbações. Análises estatísticas univariadas e multivariadas foram usadas para evidenciar os gradientes biológicos e físico-químicos, confirmar a sua co-variação, testar a significância da discriminação de níveis de impacto e estabelecer comparações inter-regionais. A estrutura de comunidades revelou os complexos gradientes de impacto, que por sua vez co-variaram significativamente com os gradientes de uso de solo. Os gradientes de impacto relacionaram-se sobretudo com entrada de nutrientes e sedimentação. Os gradientes biológicos definidos pelas medidas estruturais seleccionadas co-variaram com os gradientes de impacto estudados, muito embora apenas algumas variáveis estruturais tenham individualmente discriminado as categorias de uso de solo definidas a priori. Não foi detectada consistência nas respostas das medidas estruturais entre regiões biogeográficas, tendo-se confirmadado que as interpretações puramente taxonómicas de impactos são difíceis de extrapolar entre regiões. Os gradientes biológicos definidos através dos atributos seleccionados também co-variaram com os gradientes de perturbação, tendo sido possível obter uma melhor discriminação de categorias de uso de solo. Nas diferentes regiões, a discriminação de locais mais impactados foi feita com base num conjunto similar de atributos, que inclui tamanho, voltinismo, técnicas reproductivas, microhabitat, preferências de corrente e substrato, hábitos alimentares e formas de resistência. Este conjunto poderá vir a ser usado para avaliar de forma predictiva os efeitos das modificações severas de uso de solo impostas pela actividade agrícola. Quando analisadas simultaneamente através dos atributos, as comunidades das três regiões permitiram uma moderada mas significativa discriminação de níveis de impacto. Estas análises corroboram as evidências de que as mudanças nas comunidades de macroinvertebrados aquáticos em locais sob a influência de agricultura intensiva podem seguir uma trajectória convergente no espaço multidimensional, independentemente de factores geográficos. Foram fornecidas pistas para a identificação de parâmetros específicos que deverão ser tidos em conta no planeamento de novos programas de biomonitorização com comunidades de macroinvertebrados bentónicos, para aplicação numa gestão fluvial verdadeiramente ecológica, nestas e noutras regiões. Foram ainda sugeridas possíveis linhas futuras de investigação.

Geographic variation in sardine population traits: implications for stock assessment

Tese dout., Ciências e Tecnologias das Pescas, Universidade do Algarve, 2007

Near infrared reflectance spectroscopy (NIRS) to predict biological parameters of maize silage: effects of particle comminution, oven drying temperature and the presence of residual moisture

Maize silage nutritive quality is routinely determined by near infrared reflectance spectroscopy (NIRS). However, little is known about the impact of sample preparation on the accuracy of the calibration to predict biological traits. A sample population of 48 maize silages representing a wide range of physiological maturities was used in a study to determine the impact of different sample preparation procedures (i.e., drying regimes; the presence or absence of residual moisture; the degree of particle comminution) on resultant NIR prediction statistics. All silages were scanned using a total of 12 combinations of sample pre-treatments. Each sample preparation combination was subjected to three multivariate regression techniques to give a total of 36 predictions per biological trait. Increased sample preparations procedure, relative to scanning the unprocessed whole plant (WP) material, always resulted in a numerical minimisation of model statistics. However, the ability of each of the treatments to significantly minimise the model statistics differed. Particle comminution was the most important factor, oven-drying regime was intermediate, and residual moisture presence was the least important. Models to predict various biological parameters of maize silage will be improved if material is subjected to a high degree of particle comminution (i.e., having been passed through a 1 mm screen) and developed on plant material previously dried at 60 degrees C. The extra effort in terms of time and cost required to remove sample residual moisture cannot be justified. (c) 2005 Elsevier B.V. All rights reserved.

Similarities in butterfly emergence dates among populations suggest local adaptation to climate

Phenology shifts are the most widely cited examples of the biological impact of climate change, yet there are few assessments of potential effects on the fitness of individual organisms or the persistence of populations. Despite extensive evidence of climate-driven advances in phenological events over recent decades, comparable patterns across species' geographic ranges have seldom been described. Even fewer studies have quantified concurrent spatial gradients and temporal trends between phenology and climate. Here we analyse a large data set (~129 000 phenology measures) over 37 years across the UK to provide the first phylogenetic comparative analysis of the relative roles of plasticity and local adaptation in generating spatial and temporal patterns in butterfly mean flight dates. Although populations of all species exhibit a plastic response to temperature, with adult emergence dates earlier in warmer years by an average of 6.4 days per °C, among-population differences are significantly lower on average, at 4.3 days per °C. Emergence dates of most species are more synchronised over their geographic range than is predicted by their relationship between mean flight date and temperature over time, suggesting local adaptation. Biological traits of species only weakly explained the variation in differences between space-temperature and time-temperature phenological responses, suggesting that multiple mechanisms may operate to maintain local adaptation. As niche models assume constant relationships between occurrence and environmental conditions across a species' entire range, an important implication of the temperature-mediated local adaptation detected here is that populations of insects are much more sensitive to future climate changes than current projections suggest.

Comparison of non-linear growth models to describe the growth curve in West African Dwarf sheep

The objectives of this study were to compare the goodness of fit of four non-linear growth models, i.e. Brody, Gompertz, Logistic and Von Bertalanffy, in West African Dwarf (WAD) sheep. A total of 5274 monthly weight records from birth up to 180 days of age from 889 lambs, collected during 2001 to 2004 in Betecoucou breeding farm in Benin were used. In the preliminary analysis, the General Linear Model Procedure of the Statistical Analysis Systems Institute was applied to the dataset to identify the significant effects of the sex of lamb (male and female), type of birth (single and twin), season of birth (rainy season and dry season), parity of dam (1, 2 and 3) and year of birth (2001, 2002, 2003 and 2004) on the observed birth weight and monthly weight up to 6 months of age. The models parameters (A, B and k), coefficient of determination (112), mean square error (MSE) were calculated using language of technical computing package Matlab(R), 2006. The mean values of A, B and k were substituted into each model to calculate the corresponding Akaike's Information Criterion (AIC). Among the four growth functions, the Brody model has been selected for its accuracy of fit according to the higher R(2), lower MSE and A/C Finally, the parameters A, B and k were adjusted in Matlab(R) 2006 for the sex of lamb, year of birth, season of birth, birth type and the parity of ewe, providing a specific slope of the Brody growth curve. The results of this study suggest that Brody model can be useful for WAD sheep breeding in Betecoucou farm conditions through growth monitoring.

Genetic correlations between mature cow weight and productive and reproductive traits in Nellore cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The roles of environmental conditions and spatial factors in controlling stream macroalgal communities

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Polymorphisms in TOX and NCOA2 genes and their associations with reproductive traits in cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)