Browsing by Subject "R PACKAGE"

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  • Heino, Jani; Soininen, Janne; Alahuhta, Janne; Lappalainen, Jyrki; Virtanen, Risto (2015)
    Most metacommunity studies have taken a direct mechanistic approach, aiming to model the effects of local and regional processes on local communities within a metacommunity. An alternative approach is to focus on emergent patterns at the metacommunity level through applying the elements of metacommunity structure (EMS; Oikos, 97, 2002, 237) analysis. The EMS approach has very rarely been applied in the context of a comparative analysis of metacommunity types of main microbial, plant, and animal groups. Furthermore, to our knowledge, no study has associated metacommunity types with their potential ecological correlates in the freshwater realm. We assembled data for 45 freshwater metacommunities, incorporating biologically highly disparate organismal groups (i.e., bacteria, algae, macrophytes, invertebrates, and fish). We first examined ecological correlates (e.g., matrix properties, beta diversity, and average characteristics of a metacommunity, including body size, trophic group, ecosystem type, life form, and dispersal mode) of the three elements of metacommunity structure (i.e., coherence, turnover, and boundary clumping). Second, based on those three elements, we determined which metacommunity types prevailed in freshwater systems and which ecological correlates best discriminated among the observed metacommunity types. We found that the three elements of metacommunity structure were not strongly related to the ecological correlates, except that turnover was positively related to beta diversity. We observed six metacommunity types. The most common were Clementsian and quasi-nested metacommunity types, whereas Random, quasi-Clementsian, Gleasonian, and quasi-Gleasonian types were less common. These six metacommunity types were best discriminated by beta diversity and the first axis of metacommunity ecological traits, ranging from metacommunities of producer organisms occurring in streams to those of large predatory organisms occurring in lakes. Our results showed that focusing on the emergent properties of multiple metacommunities provides information additional to that obtained in studies examining variation in local community structure within a metacommunity.
  • Syrjälä, Essi; Nevalainen, Jaakko; Peltonen, Jaakko; Takkinen, Hanna-Mari; Hakola, Leena; Åkerlund, Mari; Veijola, Riitta; Ilonen, Jorma; Toppari, Jorma; Knip, Mikael; Virtanen, Suvi M. (2019)
    Several dietary factors have been suspected to play a role in the development of advanced islet autoimmunity (IA) and/or type 1 diabetes (T1D), but the evidence is fragmentary. A prospective population-based cohort of 6081 Finnish newborn infants with HLA-DQB1-conferred susceptibility to T1D was followed up to 15 years of age. Diabetes-associated autoantibodies and diet were assessed at 3-to 12-month intervals. We aimed to study the association between consumption of selected foods and the development of advanced IA longitudinally with Cox regression models (CRM), basic joint models (JM) and joint latent class mixed models (JLCMM). The associations of these foods to T1D risk were also studied to investigate consistency between alternative endpoints. The JM showed a marginal association between meat consumption and advanced IA: the hazard ratio adjusted for selected confounding factors was 1.06 (95% CI: 1.00, 1.12). The JLCMM identified two classes in the consumption trajectories of fish and a marginal protective association for high consumers compared to low consumers: the adjusted hazard ratio was 0.68 (0.44, 1.05). Similar findings were obtained for T1D risk with adjusted hazard ratios of 1.13 (1.02, 1.24) for meat and 0.45 (0.23, 0.86) for fish consumption. Estimates from the CRMs were closer to unity and CIs were narrower compared to the JMs. Findings indicate that intake of meat might be directly and fish inversely associated with the development of advanced IA and T1D, and that disease hazards in longitudinal nutritional epidemiology are more appropriately modeled by joint models than with naive approaches.
  • Kess, Tony; Bentzen, Paul; Lehnert, Sarah J.; Sylvester, Emma V.A.; Lien, Sigbjorn; Kent, Matthew P.; Sinclair-Waters, Marion; Morris, Corey J.; Regular, Paul; Fairweather, Robert; Bradbury, Ian R. (2019)
    Chromosome structural variation may underpin ecologically important intraspecific diversity by reducing recombination within supergenes containing linked, coadapted alleles. Here, we confirm that an ancient chromosomal rearrangement is strongly associated with migratory phenotype and individual genetic structure in Atlantic cod (Gadus morhua) across the Northwest Atlantic. We reconstruct trends in effective population size over the last century and reveal declines in effective population size matching onset of industrialized harvest (after 1950). We find different demographic trajectories between individuals homozygous for the chromosomal rearrangement relative to heterozygous or homozygous individuals for the noninverted haplotype, suggesting different selective histories across the past 150 years. These results illustrate how chromosomal structural diversity can mediate fine-scale genetic, phenotypic, and demographic variation in a highly connected marine species and show how overfishing may have led to loss of biocomplexity within Northern cod stock.
  • Mäklin, Tommi; Kallonen, Teemu; Alanko, Jarno; Samuelsen, Ørjan; Hegstad, Kristin; Mäkinen, Veli; Corander, Jukka; Heinz, Eva; Honkela, Antti (2021)
    Genomic epidemiology is a tool for tracing transmission of pathogens based on whole-genome sequencing. We introduce the mGEMS pipeline for genomic epidemiology with plate sweeps representing mixed samples of a target pathogen, opening the possibility to sequence all colonies on selective plates with a single DNA extraction and sequencing step. The pipeline includes the novel mGEMS read binner for probabilistic assignments of sequencing reads, and the scalable pseudoaligner Themisto. We demonstrate the effectiveness of our approach using closely related samples in a nosocomial setting, obtaining results that are comparable to those based on single-colony picks. Our results lend firm support to more widespread consideration of genomic epidemiology with mixed infection samples.
  • White, Brian S.; Khan, Suleiman A.; Mason, Mike J.; Ammad-ud-din, Muhammad; Potdar, Swapnil; Malani, Disha; Kuusanmäki, Heikki; Druker, Brian J.; Heckman, Caroline; Kallioniemi, Olli; Kurtz, Stephen E.; Porkka, Kimmo; Tognon, Cristina E.; Tyner, Jeffrey W.; Aittokallio, Tero; Wennerberg, Krister; Guinney, Justin (2021)
    The FDA recently approved eight targeted therapies for acute myeloid leukemia (AML), including the BCL-2 inhibitor venetoclax. Maximizing efficacy of these treatments requires refining patient selection. To this end, we analyzed two recent AML studies profiling the gene expression and ex vivo drug response of primary patient samples. We find that ex vivo samples often exhibit a general sensitivity to (any) drug exposure, independent of drug target. We observe that this "general response across drugs" (GRD) is associated with FLT3-ITD mutations, clinical response to standard induction chemotherapy, and overall survival. Further, incorporating GRD into expression-based regression models trained on one of the studies improved their performance in predicting ex vivo response in the second study, thus signifying its relevance to precision oncology efforts. We find that venetoclax response is independent of GRD but instead show that it is linked to expression of monocyte-associated genes by developing and applying a multi-source Bayesian regression approach. The method shares information across studies to robustly identify biomarkers of drug response and is broadly applicable in integrative analyses.
  • Mammola, Stefano; Carmona, Carlos P.; Guillerme, Thomas; Cardoso, Pedro (2021)
    The use of functional diversity analyses in ecology has grown exponentially over the past two decades, broadening our understanding of biological diversity and its change across space and time. Virtually all ecological sub-disciplines recognise the critical value of looking at species and communities from a functional perspective, and this has led to a proliferation of methods for estimating contrasting dimensions of functional diversity. Differences between these methods and their development generated terminological inconsistencies and confusion about the selection of the most appropriate approach for addressing any particular ecological question, hampering the potential for comparative studies, simulation exercises and meta-analyses. Two general mathematical frameworks for estimating functional diversity are prevailing: those based on dissimilarity matrices (e.g. Rao entropy, functional dendrograms) and those relying on multidimensional spaces, constructed as either convex hulls or probabilistic hypervolumes. We review these frameworks, discuss their strengths and weaknesses and provide an overview of the main R packages performing these calculations. In parallel, we propose a way for organising functional diversity metrics in a unified scheme to quantify the richness, divergence and regularity of species or individuals under each framework. This overview offers a roadmap for confidently approaching functional diversity analyses both theoretically and practically.
  • Kautt, Andreas F.; Kratochwil, Claudius F.; Nater, Alexander; Machado-Schiaffino, Gonzalo; Olave, Melisa; Henning, Frederico; Torres-Dowdall, Julian; Härer, Andreas; Hulsey, C. Darrin; Franchini, Paolo; Pippel, Martin; Myers, Eugene W.; Meyer, Axel (2020)
    Population genomic analyses of Midas cichlid fishes in young Nicaraguan crater lakes suggest that sympatric speciation is promoted by polygenic architectures. The transition from 'well-marked varieties' of a single species into 'well-defined species'-especially in the absence of geographic barriers to gene flow (sympatric speciation)-has puzzled evolutionary biologists ever since Darwin(1,2). Gene flow counteracts the buildup of genome-wide differentiation, which is a hallmark of speciation and increases the likelihood of the evolution of irreversible reproductive barriers (incompatibilities) that complete the speciation process(3). Theory predicts that the genetic architecture of divergently selected traits can influence whether sympatric speciation occurs(4), but empirical tests of this theory are scant because comprehensive data are difficult to collect and synthesize across species, owing to their unique biologies and evolutionary histories(5). Here, within a young species complex of neotropical cichlid fishes (Amphilophus spp.), we analysed genomic divergence among populations and species. By generating a new genome assembly and re-sequencing 453 genomes, we uncovered the genetic architecture of traits that have been suggested to be important for divergence. Species that differ in monogenic or oligogenic traits that affect ecological performance and/or mate choice show remarkably localized genomic differentiation. By contrast, differentiation among species that have diverged in polygenic traits is genomically widespread and much higher overall, consistent with the evolution of effective and stable genome-wide barriers to gene flow. Thus, we conclude that simple trait architectures are not always as conducive to speciation with gene flow as previously suggested, whereas polygenic architectures can promote rapid and stable speciation in sympatry.
  • Liao, Ziyan; Chen, Youhua; Pan, Kaiwen; Dakhil, Mohammed A.; Lin, Kexin; Tian, Xianglin; Zhang, Fengying; Wu, Xiaogang; Pandey, Bikram; Wang, Bin; Zimmermann, Niklaus E.; Zhang, Lin; Nobis, Michael P. (2022)
    Background: We aimed to characterise the geographical distribution of Sorensen-based multi-site dissimilarity (beta(sor)) and its underlying true turnover (beta(sim)) and nestedness (beta(sne)) components for Chinese Lauraceae and to analyse their relationships to current climate and past climate change. Methods: We used ensembles of small models (ESMs) to map the current distributions of 353 Lauraceae species in China and calculated beta(sor) and its beta(sim) and beta(sne) components. We tested the relationship between beta(sor), beta s(ne) and beta(sim) with current climate and past climate change related predictors using a series of simultaneous autoregressive (SAR(err)) models. Results: Spatial distribution of beta(sor) of Lauraceae is positively correlated with latitude, showing an inverse relationship to the latitudinal alpha-diversity (species richness) gradient. High beta(sor) occurs at the boundaries of the warm temperate and subtropical zones and at the Qinghai-Tibet Plateau due to high beta(sne). The optimized SAR(err) model explains beta(sor) and beta(sne) well, but not beta(sim). Current mean annual temperature determines beta(sor) and beta(sne) of Lauraceae more than anomalies and velocities of temperature or precipitation since the Last Glacial Maximum. Conclusions: Current low temperatures and high climatic heterogeneity are the main factors explaining the high multi-site beta-diversity of Lauraceae. In contrast to analyses of the beta-diversity of entire species assemblages, studies of single plant families can provide complementary insights into the drivers of beta-diversity of evolutionarily more narrowly defined entities.
  • Parravicini, Valeriano; Casey, Jordan M.; Schiettekatte, Nina M. D.; Brandl, Simon J.; Pozas-Schacre, Chloe; Carlot, Jeremy; Edgar, Graham J.; Graham, Nicholas A. J.; Harmelin-Vivien, Mireille; Kulbicki, Michel; Strona, Giovanni; Stuart-Smith, Rick D. (2020)
    Understanding species' roles in food webs requires an accurate assessment of their trophic niche. However, it is challenging to delineate potential trophic interactions across an ecosystem, and a paucity of empirical information often leads to inconsistent definitions of trophic guilds based on expert opinion, especially when applied to hyperdiverse ecosystems. Using coral reef fishes as a model group, we show that experts disagree on the assignment of broad trophic guilds for more than 20% of species, which hampers comparability across studies. Here, we propose a quantitative, unbiased, and reproducible approach to define trophic guilds and apply recent advances in machine learning to predict probabilities of pairwise trophic interactions with high accuracy. We synthesize data from community-wide gut content analyses of tropical coral reef fishes worldwide, resulting in diet information from 13,961 individuals belonging to 615 reef fish. We then use network analysis to identify 8 trophic guilds and Bayesian phylogenetic modeling to show that trophic guilds can be predicted based on phylogeny and maximum body size. Finally, we use machine learning to test whether pairwise trophic interactions can be predicted with accuracy. Our models achieved a misclassification error of less than 5%, indicating that our approach results in a quantitative and reproducible trophic categorization scheme, as well as high-resolution probabilities of trophic interactions. By applying our framework to the most diverse vertebrate consumer group, we show that it can be applied to other organismal groups to advance reproducibility in trait-based ecology. Our work thus provides a viable approach to account for the complexity of predator-prey interactions in highly diverse ecosystems.
  • Mauri, Achille; Girardello, Marco; Strona, Giovanni; Beck, Pieter S. A.; Forzieri, Giovanni; Caudullo, Giovanni; Manca, Federica; Cescatti, Alessandro (2022)
    We present "EU-Trees4F", a dataset of current and future potential distributions of 67 tree species in Europe at 10 km spatial resolution. We provide both climatically suitable future areas of occupancy and the future distribution expected under a scenario of natural dispersal for two emission scenarios (RCP 4.5 and RCP 8.5) and three time steps (2035, 2065, and 2095). Also, we provide a version of the dataset where tree ranges are limited by future land use. These data-driven projections were made using an ensemble species distribution model calibrated using EU-Forest, a comprehensive dataset of tree species occurrences for Europe, and driven by seven bioclimatic parameters derived from EURO-CORDEX regional climate model simulations, and two soil parameters. "EU-Trees4F", can benefit various research fields, including forestry, biodiversity, ecosystem services, and bio-economy. Possible applications include the calibration or benchmarking of dynamic vegetation models, or informing forest adaptation strategies based on assisted tree migration. Given the multiple European policy initiatives related to forests, this dataset represents a timely and valuable resource to support policymaking.
  • Marques, Francine Z.; Prestes, Priscilla R.; Byars, Sean G.; Ritchie, Scott C.; Wurtz, Peter; Patel, Sheila K.; Booth, Scott A.; Rana, Indrajeetsinh; Minoda, Yosuke; Berzins, Stuart P.; Curl, Claire L.; Bell, James R.; Wai, Bryan; Srivastava, Piyush M.; Kangas, Antti J.; Soininen, Pasi; Ruohonen, Saku; Kahonen, Mika; Lehtimaki, Terho; Raitoharju, Emma; Havulinna, Aki; Perola, Markus; Raitakari, Olli; Salomaa, Veikko; Ala-Korpela, Mika; Kettunen, Johannes; McGlynn, Maree; Kelly, Jason; Wlodek, Mary E.; Lewandowski, Paul A.; Delbridge, Lea M.; Burrell, Louise M.; Inouye, Michael; Harrap, Stephen B.; Charchar, Fadi J. (2017)
    Background-Cardiac hypertrophy increases the risk of developing heart failure and cardiovascular death. The neutrophil inflammatory protein, lipocalin-2 (LCN2/NGAL), is elevated in certain forms of cardiac hypertrophy and acute heart failure. However, a specific role for LCN2 in predisposition and etiology of hypertrophy and the relevant genetic determinants are unclear. Here, we defined the role of LCN2 in concentric cardiac hypertrophy in terms of pathophysiology, inflammatory expression networks, and genomic determinants. Methods and Results-We used 3 experimental models: a polygenic model of cardiac hypertrophy and heart failure, a model of intrauterine growth restriction and Lcn2-knockout mouse; cultured cardiomyocytes; and 2 human cohorts: 114 type 2 diabetes mellitus patients and 2064 healthy subjects of the YFS (Young Finns Study). In hypertrophic heart rats, cardiac and circulating Lcn2 was significantly overexpressed before, during, and after development of cardiac hypertrophy and heart failure. Lcn2 expression was increased in hypertrophic hearts in a model of intrauterine growth restriction, whereas Lcn2-knockout mice had smaller hearts. In cultured cardiomyocytes, Lcn2 activated molecular hypertrophic pathways and increased cell size, but reduced proliferation and cell numbers. Increased LCN2 was associated with cardiac hypertrophy and diastolic dysfunction in diabetes mellitus. In the YFS, LCN2 expression was associated with body mass index and cardiac mass and with levels of inflammatory markers. The single-nucleotide polymorphism, rs13297295, located near LCN2 defined a significant cis-eQTL for LCN2 expression. Conclusions-Direct effects of LCN2 on cardiomyocyte size and number and the consistent associations in experimental and human analyses reveal a central role for LCN2 in the ontogeny of cardiac hypertrophy and heart failure.
  • Scala, Giovanni; Serra, Angela; Marwah, Veer Singh; Saarimaki, Laura Aliisa; Greco, Dario (2019)
    BackgroundFunctional annotation of genes is an essential step in omics data analysis. Multiple databases and methods are currently available to summarize the functions of sets of genes into higher level representations, such as ontologies and molecular pathways. Annotating results from omics experiments into functional categories is essential not only to understand the underlying regulatory dynamics but also to compare multiple experimental conditions at a higher level of abstraction. Several tools are already available to the community to represent and compare functional profiles of omics experiments. However, when the number of experiments and/or enriched functional terms is high, it becomes difficult to interpret the results even when graphically represented. Therefore, there is currently a need for interactive and user-friendly tools to graphically navigate and further summarize annotations in order to facilitate results interpretation also when the dimensionality is high.ResultsWe developed an approach that exploits the intrinsic hierarchical structure of several functional annotations to summarize the results obtained through enrichment analyses to higher levels of interpretation and to map gene related information at each summarized level. We built a user-friendly graphical interface that allows to visualize the functional annotations of one or multiple experiments at once. The tool is implemented as a R-Shiny application called FunMappOne and is available at https://github.com/grecolab/FunMappOne.ConclusionFunMappOne is a R-shiny graphical tool that takes in input multiple lists of human or mouse genes, optionally along with their related modification magnitudes, computes the enriched annotations from Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, or Reactome databases, and reports interactive maps of functional terms and pathways organized in rational groups. FunMappOne allows a fast and convenient comparison of multiple experiments and an easy way to interpret results.
  • Marwah, Veer Singh; Kinare, Pia Anneli Sofia; Serra, Angela; Scala, Giovanni; Lauerma, Antti; Fortino, Vittorio; Grecot, Dario (2018)
    The Summary: Detecting and interpreting responsive modules from gene expression data by using network-based approaches is a common but laborious task. It often requires the application of several computational methods implemented in different software packages, forcing biologists to compile complex analytical pipelines. Here we introduce INfORM (Inference of NetwOrk Response Modules), an R shiny application that enables non-expert users to detect, evaluate and select gene modules with high statistical and biological significance. INfORM is a comprehensive tool for the identification of biologically meaningful response modules from consensus gene networks inferred by using multiple algorithms. It is accessible through an intuitive graphical user interface allowing for a level of abstraction from the computational steps.
  • DiLeo, Michelle F.; Husby, Arild; Saastamoinen, Marjo (2018)
    There is now clear evidence that species across a broad range of taxa harbor extensive heritable variation in dispersal. While studies suggest that this variation can facilitate demographic outcomes such as range expansion and invasions, few have considered the consequences of intraspecific variation in dispersal for the maintenance and distribution of genetic variation across fragmented landscapes. Here, we examine how landscape characteristics and individual variation in dispersal combine to predict genetic structure using genomic and spatial data from the Glanville fritillary butterfly. We used linear and latent factor mixed models to identify the landscape features that best predict spatial sorting of alleles in the dispersal-related gene phosphoglucose isomerase (Pgi). We next used structural equation modeling to test if variation in Pgi mediated gene flow as measured by F-st at putatively neutral loci. In a year when the population was recovering following a large decline, individuals with a genotype associated with greater dispersal ability were found at significantly higher frequencies in populations isolated by water and forest, and these populations showed lower levels of genetic differentiation at neutral loci. These relationships disappeared in the next year when metapopulation density was high, suggesting that the effects of individual variation are context dependent. Together our results highlight that (1) more complex aspects of landscape structure beyond just the configuration of habitat can be important for maintaining spatial variation in dispersal traits and (2) that individual variation in dispersal plays a key role in maintaining genetic variation across fragmented landscapes.
  • Huang, Shan; Saarinen, Juha J.; Eyres, Alison; Eronen, Jussi T.; Fritz, Susanne A. (2022)
    Aim: Body size evolution has long been hypothesized to have been driven by factors linked to climate change, but the specific mechanisms are difficult to disentangle due to the wide range of functional traits that covary with body size. In this study, we investigated the impact of regional habitat changes as a potential indirect effect of climate change on body size evolution. Location: Europe and North America. Time period: The Neogene (similar to 23-2 million years ago). Major taxa: Five orders of terrestrial mammals: Artiodactyla, Carnivora, Perissodactyla, Proboscidea and Primates. Methods: We compared the two continental faunas, which have exceptional fossil records of terrestrial mammals and underwent different processes of habitat transition during the Neogene. Using Bayesian multilevel regression models, we assessed the variation in the temporal dynamics of body size diversity among ecographic groups, defined by their continent of occurrence and dietary preference. Results: Model comparisons unanimously supported a combined effect of diet and continent on all metrics of body size frequency distributions, rejecting the shared energetic advantage of larger bodies in colder climates as a dominant mechanism of body size evolution. Rather, the diet-specific dynamics on each continent pinpointed an indirect effect of climate change - change in habitat availability, and thus the resource landscape as a key driver of mammalian evolution. Main conclusions: Our study highlights dietary preference as a mechanistic link between mammalian evolution and habitat transition mediating an indirect climate-change effect and demonstrates the complexity of climatic influence on biodiversity. Our findings suggest that the intensified habitat modification today likely poses a bigger threat than climate change in itself to living mammals, and perhaps all endotherms.
  • Morita, Wataru; Morimoto, Naoki; Jernvall, Jukka (2020)
    A major challenge in evolutionary developmental biology is to understand how genetic mutations underlie phenotypic changes. In principle, selective pressures on the phenotype screen the gene pool of the population. Teeth are an excellent model for understanding evolutionary changes in the genotype-phenotype relationship since they exist throughout vertebrates. Genetically modified mice (mutants) with abnormalities in teeth have been used to explore tooth development. The relationship between signaling pathways and molar shape, however, remains elusive due to the high intrinsic complexity of tooth crowns. This hampers our understanding of the extent to which developmental factors explored in mutants explain developmental and phenotypic variation in natural species that represent the consequence of natural selection. Here we combine a novel morphometric method with two kinds of data mining techniques to extract data sets from the three-dimensional surface models of lower first molars: i) machine learning to maximize classification accuracy of 22 mutants, and ii) phylogenetic signal for 31 Murinae species. Major shape variation among mutants is explained by the number of cusps and cusp distribution on a tooth crown. The distribution of mutant mice in morphospace suggests a nonlinear relationship between the signaling pathways and molar shape variation. Comparative analysis of mutants and wild murines reveals that mutant variation overlaps naturally occurring diversity, including more ancestral and derived morphologies. However, taxa with transverse lophs are not fully covered by mutant variation, suggesting experimentally unexplored developmental factors in the evolutionary radiation of Murines. Author summary Teeth are found in almost all vertebrates, and they show many different morphologies. In mammals, especially the cheek teeth or molars are highly diverse in shape, reflecting a vast range of dietary habits and efficiency of occlusion. As teeth are the most durable part of the body, they preserve well in the fossil record. The diversity of molar fossils has been useful in reconstructing the diet and phylogeny of extinct mammals. Genetically modified mice (mutants) show diverse modifications of their molar morphology, but we lack computational tools to test to what extent mutant morphologies account for the natural diversity found in the wild. We developed data mining using machine learning and phylogeny-based methods to analyze three-dimensional molar shapes in mouse mutants and natural species. Although many mutants and species have comparable features, most of the mutant molar variation covers the more evolutionarily ancestral than the more evolutionary derived shapes. Yet to be explored developmental factors may underly the more extreme shapes.
  • Shu, Le; Zhao, Yuqi; Kurt, Zeyneb; Byars, Sean Geoffrey; Tukiainen, Taru; Kettunen, Johannes; Orozco, Luz D.; Pellegrini, Matteo; Lusis, Aldons J.; Ripatti, Samuli; Zhang, Bin; Inouye, Michael; Makinen, Ville-Petteri; Yang, Xia (2016)
    Background: Complex diseases are characterized by multiple subtle perturbations to biological processes. New omics platforms can detect these perturbations, but translating the diverse molecular and statistical information into testable mechanistic hypotheses is challenging. Therefore, we set out to create a public tool that integrates these data across multiple datasets, platforms, study designs and species in order to detect the most promising targets for further mechanistic studies. Results: We developed Mergeomics, a computational pipeline consisting of independent modules that 1) leverage multi-omics association data to identify biological processes that are perturbed in disease, and 2) overlay the disease-associated processes onto molecular interaction networks to pinpoint hubs as potential key regulators. Unlike existing tools that are mostly dedicated to specific data type or settings, the Mergeomics pipeline accepts and integrates datasets across platforms, data types and species. We optimized and evaluated the performance of Mergeomics using simulation and multiple independent datasets, and benchmarked the results against alternative methods. We also demonstrate the versatility of Mergeomics in two case studies that include genome-wide, epigenome-wide and transcriptome-wide datasets from human and mouse studies of total cholesterol and fasting glucose. In both cases, the Mergeomics pipeline provided statistical and contextual evidence to prioritize further investigations in the wet lab. The software implementation of Mergeomics is freely available as a Bioconductor R package. Conclusion: Mergeomics is a flexible and robust computational pipeline for multidimensional data integration. It outperforms existing tools, and is easily applicable to datasets from different studies, species and omics data types for the study of complex traits.
  • Kess, Tony; Bentzen, Paul; Lehnert, Sarah J.; Sylvester, Emma V.A.; Lien, Sigbjørn; Kent, Matthew P.; Sinclair-Waters, Marion; Morris, Corey J.; Wringe, Brendan; Fairweather, Robert; Bradbury, Ian R. (2020)
    Genomic architecture and standing variation can play a key role in ecological adaptation and contribute to the predictability of evolution. In Atlantic cod (Gadus morhua), four large chromosomal rearrangements have been associated with ecological gradients and migratory behavior in regional analyses. However, the degree of parallelism, the extent of independent inheritance, and functional distinctiveness of these rearrangements remain poorly understood. Here, we use a 12K single nucleotide polymorphism (SNP) array to demonstrate extensive individual variation in rearrangement genotype within populations across the species range, suggesting that local adaptation to fine-scale ecological variation is enabled by rearrangements with independent inheritance. Our results demonstrate significant association of rearrangements with migration phenotype and environmental gradients across the species range. Individual rearrangements exhibit functional modularity, but also contain loci showing multiple environmental associations. Clustering in genetic distance trees and reduced differentiation within rearrangements across the species range are consistent with shared variation as a source of contemporary adaptive diversity in Atlantic cod. Conversely, we also find that haplotypes in the LG12 and LG1 rearranged region have diverged across the Atlantic, despite consistent environmental associations. Exchange of these structurally variable genomic regions, as well as local selective pressures, has likely facilitated individual diversity within Atlantic cod stocks. Our results highlight the importance of genomic architecture and standing variation in enabling fine-scale adaptation in marine species.
  • Tseng, Kuan-Yin; Wu, Jui-Sheng; Chen, Yuan-Hao; Airavaara, Mikko; Cheng, Cheng-Yi; Ma, Kuo-Hsing (2022)
    Parkinson's disease (PD) is characterized by the loss of dopaminergic neurons in substantia nigra pars compacta, which leads to the motor control deficits. Recently, cell transplantation is a cutting-edge technique for the therapy of PD. Nevertheless, one key bottleneck to realizing such potential is allogenic immune reaction of tissue grafts by recipients. Cerebral dopamine neurotrophic factor (CDNF) was shown to possess immune-modulatory properties that benefit neurodegenerative diseases. We hypothesized that co-administration of CDNF with fetal ventral mesencephalic (VM) tissue can improve the success of VM replacement therapies by attenuating immune responses. Hemiparkinsonian rats were generated by injecting 6-hydroxydopamine (6-OHDA) into the right medial forebrain bundle of Sprague Dawley (SD) rats. The rats were then intrastriatally transplanted with VM tissue from rats, with/without CDNF administration. Recovery of dopaminergic function and survival of the grafts were evaluated using the apomorphine-induced rotation test and smallanimal positron emission tomography (PET) coupled with [F-18] DOPA or [F-18] FE-PE2I, respectively. In addition, transplantation-related inflammatory response was determined by uptake of [F-18] FEPPA in the grafted side of striatum. Immunohistochemistry (IHC) examination was used to determine the survival of the grated dopaminergic neurons in the striatum and to investigate immune-modulatory effects of CDNF. The modulation of inflammatory responses caused by CDNF might involve enhancing M2 subset polarization and increasing fractal dimensions of 6-OHDA-treated BV2 microglial cell line. Analysis of CDNF-induced changes to gene expressions of 6-OHDA-stimulated BV2 cells implies that these alternations of the biomarkers and microglial morphology are implicated in the upregulation of protein kinase B signaling as well as regulation of catalytic, transferase, and protein serine/threonine kinase activity. The effects of CDNF on 6-OHDA-induced alternation of the canonical pathway in BV2 microglial cells is highly associated with PI3K-mediated phagosome formation. Our results are the first to show that CDNF administration enhances the survival of the grafted dopaminergic neurons and improves functional recovery in PD animal model. Modulation of the polarization, morphological characteristics, and transcriptional profiles of 6-OHDA-stimualted microglia by CDNF may possess these properties in transplantation-based regenerative therapies.
  • Lafuma, Fabien; Corfe, Ian; Clavel, Julien; Di-Poi, Nicolas (2021)
    Teeth act as tools for acquiring and processing food, thus holding a prominent role in vertebrate evolution. In mammals, dental-dietary adaptations rely on tooth complexity variations controlled by cusp number and pattern. Complexity increase through cusp addition has dominated the diversification of mammals. However, studies of Mammalia alone cannot reveal patterns of tooth complexity conserved throughout vertebrate evolution. Here, we use morphometric and phylogenetic comparative methods across fossil and extant squamates to show they also repeatedly evolved increasingly complex teeth, but with more flexibility than mammals. Since the Late Jurassic, multiple-cusped teeth evolved over 20 times independently from a single-cusped common ancestor. Squamates frequently lost cusps and evolved varied multiple-cusped morphologies at heterogeneous rates. Tooth complexity evolved in correlation with changes in plant consumption, resulting in several major increases in speciation. Complex teeth played a critical role in vertebrate evolution outside Mammalia, with squamates exemplifying a more labile system of dental-dietary evolution.