Coupling bacterioplankton populations and environment to community function in coastal temperate waters

DEFF Research Database (Denmark)

Traving, S. J.; Bentzon-Tilia, Mikkel; Knudsen-Leerbeck, H.

2016-01-01

drivers of bacterioplankton community functions, taking into account the variability in community composition and environmental conditions over seasons, in two contrasting coastal systems. A Least Absolute Shrinkage and Selection Operator (LASSO) analysis of the biological and chemical data obtained from...... surface waters over a full year indicated that specific bacterial populations were linked to measured functions. Namely, Synechococcus (Cyanobacteria) was strongly correlated with protease activity. Both function and community composition showed seasonal variation. However, the pattern of substrate...... of common drivers of bacterioplankton community functions in two different systems indicates that the drivers may be of broader relevance in coastal temperate waters....

Prokaryotic Phylogenies Inferred from Whole-Genome Sequence and Annotation Data

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Wei Du

2013-01-01

Full Text Available Phylogenetic trees are used to represent the evolutionary relationship among various groups of species. In this paper, a novel method for inferring prokaryotic phylogenies using multiple genomic information is proposed. The method is called CGCPhy and based on the distance matrix of orthologous gene clusters between whole-genome pairs. CGCPhy comprises four main steps. First, orthologous genes are determined by sequence similarity, genomic function, and genomic structure information. Second, genes involving potential HGT events are eliminated, since such genes are considered to be the highly conserved genes across different species and the genes located on fragments with abnormal genome barcode. Third, we calculate the distance of the orthologous gene clusters between each genome pair in terms of the number of orthologous genes in conserved clusters. Finally, the neighbor-joining method is employed to construct phylogenetic trees across different species. CGCPhy has been examined on different datasets from 617 complete single-chromosome prokaryotic genomes and achieved applicative accuracies on different species sets in agreement with Bergey's taxonomy in quartet topologies. Simulation results show that CGCPhy achieves high average accuracy and has a low standard deviation on different datasets, so it has an applicative potential for phylogenetic analysis.

Phylogenetic comparisons of a coastal bacterioplankton community with its counterparts in open ocean and freshwater systems.

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Rappé; Vergin; Giovannoni

2000-09-01

In order to extend previous comparisons between coastal marine bacterioplankton communities and their open ocean and freshwater counterparts, here we summarize and provide new data on a clone library of 105 SSU rRNA genes recovered from seawater collected over the western continental shelf of the USA in the Pacific Ocean. Comparisons to previously published data revealed that this coastal bacterioplankton clone library was dominated by SSU rRNA gene phylotypes originally described from surface waters of the open ocean, but also revealed unique SSU rRNA gene lineages of beta Proteobacteria related to those found in clone libraries from freshwater habitats. beta Proteobacteria lineages common to coastal and freshwater samples included members of a clade of obligately methylotrophic bacteria, SSU rRNA genes affiliated with Xylophilus ampelinus, and a clade related to the genus Duganella. In addition, SSU rRNA genes were recovered from such previously recognized marine bacterioplankton SSU rRNA gene clone clusters as the SAR86, SAR11, and SAR116 clusters within the class Proteobacteria, the Roseobacter clade of the alpha subclass of the Proteobacteria, the marine group A/SAR406 cluster, and the marine Actinobacteria clade. Overall, these results support and extend previous observations concerning the global distribution of several marine planktonic prokaryote SSU rRNA gene phylotypes, but also show that coastal bacterioplankton communities contain SSU rRNA gene lineages (and presumably bacterioplankton) shown previously to be prevalent in freshwater habitats.

BPhyOG: An interactive server for genome-wide inference of bacterial phylogenies based on overlapping genes

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Lin Kui

2007-07-01

Full Text Available Abstract Background Overlapping genes (OGs in bacterial genomes are pairs of adjacent genes of which the coding sequences overlap partly or entirely. With the rapid accumulation of sequence data, many OGs in bacterial genomes have now been identified. Indeed, these might prove a consistent feature across all microbial genomes. Our previous work suggests that OGs can be considered as robust markers at the whole genome level for the construction of phylogenies. An online, interactive web server for inferring phylogenies is needed for biologists to analyze phylogenetic relationships among a set of bacterial genomes of interest. Description BPhyOG is an online interactive server for reconstructing the phylogenies of completely sequenced bacterial genomes on the basis of their shared overlapping genes. It provides two tree-reconstruction methods: Neighbor Joining (NJ and Unweighted Pair-Group Method using Arithmetic averages (UPGMA. Users can apply the desired method to generate phylogenetic trees, which are based on an evolutionary distance matrix for the selected genomes. The distance between two genomes is defined by the normalized number of their shared OG pairs. BPhyOG also allows users to browse the OGs that were used to infer the phylogenetic relationships. It provides detailed annotation for each OG pair and the features of the component genes through hyperlinks. Users can also retrieve each of the homologous OG pairs that have been determined among 177 genomes. It is a useful tool for analyzing the tree of life and overlapping genes from a genomic standpoint. Conclusion BPhyOG is a useful interactive web server for genome-wide inference of any potential evolutionary relationship among the genomes selected by users. It currently includes 177 completely sequenced bacterial genomes containing 79,855 OG pairs, the annotation and homologous OG pairs of which are integrated comprehensively. The reliability of phylogenies complemented by

Covariance of bacterioplankton composition and environmental variables in a temperate delta system

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Stepanauskas, R.; Moran, M.A.; Bergamaschi, B.A.; Hollibaugh, J.T.

2003-01-01

We examined seasonal and spatial variation in bacterioplankton composition in the Sacramento-San Joaquin River Delta (CA) using terminal restriction fragment length polymorphism (T-RFLP) analysis. Cloned 16S rRNA genes from this system were used for putative identification of taxa dominating the T-RFLP profiles. Both cloning and T-RFLP analysis indicated that Actinobacteria, Verrucomicrobia, Cytophaga-Flavobacterium and Proteobacteria were the most abundant bacterioplankton groups in the Delta. Despite the broad variety of sampled habitats (deep water channels, lakes, marshes, agricultural drains, freshwater and brackish areas), and the spatial and temporal differences in hydrology, temperature and water chemistry among the sampling campaigns, T-RFLP electropherograms from all samples were similar, indicating that the same bacterioplankton phylotypes dominated in the various habitats of the Delta throughout the year. However, principal component analysis (PCA) and partial least-squares regression (PLS) of T-RFLP profiles revealed consistent grouping of samples on a seasonal, but not a spatial, basis. ??-Proteobacteria related to Ralstonia, Actinobacteria related to Microthrix, and ??-Proteobacteria identical to the environmental Clone LD12 had the highest relative abundance in summer/fall T-RFLP profiles and were associated with low river flow, high pH, and a number of optical and chemical characteristics of dissolved organic carbon (DOC) indicative of an increased proportion of phytoplankton-produced organic material as opposed to allochthonous, terrestrially derived organic material. On the other hand, Geobacter-related ??-Proteobacteria showed a relative increase in abundance in T-RFLP analysis during winter/spring, and probably were washed out from watershed soils or sediment. Various phylotypes associated with the same phylogenetic division, based on tentative identification of T-RFLP fragments, exhibited diverse seasonal patterns, suggesting that ecological

Regulation of bacterioplankton density and biomass in tropical shallow coastal lagoons

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Fabiana MacCord

Full Text Available AIM: Estimating bacterioplankton density and biomass and their regulating factors is important in order to evaluate aquatic systems' carrying capacity, regarding bacterial growth and the stock of matter in the bacterial community, which can be consumed by higher trophic levels. We aim to evaluate the limnological factors which regulate - in space and time - the bacterioplankton dynamics (abundance and biomass in five tropical coastal lagoons in the state of Rio de Janeiro, Brazil. METHOD: The current study was carried out at the following lagoons: Imboassica, Cabiúnas, Comprida, Carapebus and Garças. They differ in morphology and in their main limnological factors. The limnological variables as well as bacterioplankton abundance and biomass were monthly sampled for 14 months. Model selection analyses were performed in order to evaluate the main variables regulating the bacterioplankton's dynamics in these lagoons. RESULT: The salt concentration and the "space" factor (i.e. different lagoons explained great part of the bacterial density and biomass variance in the studied tropical coastal lagoons. When the lagoons were analyzed separately, salinity still explained great part of the variation of bacterial density and biomass in the Imboassica and Garças lagoons. On the other hand, phosphorus concentration was the main factor explaining the variance of bacterial density and biomass in the distrophic Cabiúnas, Comprida and Carapebus lagoons. There was a strong correlation between bacterial density and biomass (r² = 0.70, p < 0.05, indicating that bacterial biomass variations are highly dependent on bacterial density variations. CONCLUSION: (i Different limnological variables regulate the bacterial density and biomass in the studied coastal lagoons, (ii salt and phosphorus concentrations greatly explained the variation of bacterial density and biomass in the saline and distrophic lagoons, respectively, and (iii N-nitrate and chlorophyll

Insights into bacterioplankton community structure from Sundarbans mangrove ecoregion using Sanger and Illumina MiSeq sequencing approaches: A comparative analysis

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Anwesha Ghosh

2017-03-01

Full Text Available Next generation sequencing using platforms such as Illumina MiSeq provides a deeper insight into the structure and function of bacterioplankton communities in coastal ecosystems compared to traditional molecular techniques such as clone library approach which incorporates Sanger sequencing. In this study, structure of bacterioplankton communities was investigated from two stations of Sundarbans mangrove ecoregion using both Sanger and Illumina MiSeq sequencing approaches. The Illumina MiSeq data is available under the BioProject ID PRJNA35180 and Sanger sequencing data under accession numbers KX014101-KX014140 (Stn1 and KX014372-KX014410 (Stn3. Proteobacteria-, Firmicutes- and Bacteroidetes-like sequences retrieved from both approaches appeared to be abundant in the studied ecosystem. The Illumina MiSeq data (2.1 GB provided a deeper insight into the structure of bacterioplankton communities and revealed the presence of bacterial phyla such as Actinobacteria, Cyanobacteria, Tenericutes, Verrucomicrobia which were not recovered based on Sanger sequencing. A comparative analysis of bacterioplankton communities from both stations highlighted the presence of genera that appear in both stations and genera that occur exclusively in either station. However, both the Sanger sequencing and Illumina MiSeq data were coherent at broader taxonomic levels. Pseudomonas, Devosia, Hyphomonas and Erythrobacter-like sequences were the abundant bacterial genera found in the studied ecosystem. Both the sequencing methods showed broad coherence although as expected the Illumina MiSeq data helped identify rarer bacterioplankton groups and also showed the presence of unassigned OTUs indicating possible presence of novel bacterioplankton from the studied mangrove ecosystem.

Distribution, Community Composition, and Potential Metabolic Activity of Bacterioplankton in an Urbanized Mediterranean Sea Coastal Zone.

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Richa, Kumari; Balestra, Cecilia; Piredda, Roberta; Benes, Vladimir; Borra, Marco; Passarelli, Augusto; Margiotta, Francesca; Saggiomo, Maria; Biffali, Elio; Sanges, Remo; Scanlan, David J; Casotti, Raffaella

2017-09-01

Bacterioplankton are fundamental components of marine ecosystems and influence the entire biosphere by contributing to the global biogeochemical cycles of key elements. Yet, there is a significant gap in knowledge about their diversity and specific activities, as well as environmental factors that shape their community composition and function. Here, the distribution and diversity of surface bacterioplankton along the coastline of the Gulf of Naples (GON; Italy) were investigated using flow cytometry coupled with high-throughput sequencing of the 16S rRNA gene. Heterotrophic bacteria numerically dominated the bacterioplankton and comprised mainly Alphaproteobacteria , Gammaproteobacteria , and Bacteroidetes Distinct communities occupied river-influenced, coastal, and offshore sites, as indicated by Bray-Curtis dissimilarity, distance metric (UniFrac), linear discriminant analysis effect size (LEfSe), and multivariate analyses. The heterogeneity in diversity and community composition was mainly due to salinity and changes in environmental conditions across sites, as defined by nutrient and chlorophyll a concentrations. Bacterioplankton communities were composed of a few dominant taxa and a large proportion (92%) of rare taxa (here defined as operational taxonomic units [OTUs] accounting for coastal zones is of critical importance, considering that these areas are highly productive and anthropogenically impacted. Their richness and evenness, as well as their potential activity, are very important to assess ecosystem health and functioning. Here, we investigated bacterial distribution, community composition, and potential metabolic activity in the GON, which is an ideal test site due to its heterogeneous environment characterized by a complex hydrodynamics and terrestrial inputs of varied quantities and quality. Our study demonstrates that bacterioplankton communities in this region are highly diverse and strongly regulated by a combination of different environmental

Benchmarking Relatedness Inference Methods with Genome-Wide Data from Thousands of Relatives.

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Ramstetter, Monica D; Dyer, Thomas D; Lehman, Donna M; Curran, Joanne E; Duggirala, Ravindranath; Blangero, John; Mezey, Jason G; Williams, Amy L

2017-09-01

Inferring relatedness from genomic data is an essential component of genetic association studies, population genetics, forensics, and genealogy. While numerous methods exist for inferring relatedness, thorough evaluation of these approaches in real data has been lacking. Here, we report an assessment of 12 state-of-the-art pairwise relatedness inference methods using a data set with 2485 individuals contained in several large pedigrees that span up to six generations. We find that all methods have high accuracy (92-99%) when detecting first- and second-degree relationships, but their accuracy dwindles to 76% of relative pairs. Overall, the most accurate methods are Estimation of Recent Shared Ancestry (ERSA) and approaches that compute total IBD sharing using the output from GERMLINE and Refined IBD to infer relatedness. Combining information from the most accurate methods provides little accuracy improvement, indicating that novel approaches, such as new methods that leverage relatedness signals from multiple samples, are needed to achieve a sizeable jump in performance. Copyright © 2017 Ramstetter et al.

The aggregate site frequency spectrum for comparative population genomic inference.

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Xue, Alexander T; Hickerson, Michael J

2015-12-01

Understanding how assemblages of species responded to past climate change is a central goal of comparative phylogeography and comparative population genomics, an endeavour that has increasing potential to integrate with community ecology. New sequencing technology now provides the potential to perform complex demographic inference at unprecedented resolution across assemblages of nonmodel species. To this end, we introduce the aggregate site frequency spectrum (aSFS), an expansion of the site frequency spectrum to use single nucleotide polymorphism (SNP) data sets collected from multiple, co-distributed species for assemblage-level demographic inference. We describe how the aSFS is constructed over an arbitrary number of independent population samples and then demonstrate how the aSFS can differentiate various multispecies demographic histories under a wide range of sampling configurations while allowing effective population sizes and expansion magnitudes to vary independently. We subsequently couple the aSFS with a hierarchical approximate Bayesian computation (hABC) framework to estimate degree of temporal synchronicity in expansion times across taxa, including an empirical demonstration with a data set consisting of five populations of the threespine stickleback (Gasterosteus aculeatus). Corroborating what is generally understood about the recent postglacial origins of these populations, the joint aSFS/hABC analysis strongly suggests that the stickleback data are most consistent with synchronous expansion after the Last Glacial Maximum (posterior probability = 0.99). The aSFS will have general application for multilevel statistical frameworks to test models involving assemblages and/or communities, and as large-scale SNP data from nonmodel species become routine, the aSFS expands the potential for powerful next-generation comparative population genomic inference. © 2015 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

Genomic inference accurately predicts the timing and severity of a recent bottleneck in a non-model insect population

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McCoy, Rajiv C.; Garud, Nandita R.; Kelley, Joanna L.; Boggs, Carol L.; Petrov, Dmitri A.

2015-01-01

The analysis of molecular data from natural populations has allowed researchers to answer diverse ecological questions that were previously intractable. In particular, ecologists are often interested in the demographic history of populations, information that is rarely available from historical records. Methods have been developed to infer demographic parameters from genomic data, but it is not well understood how inferred parameters compare to true population history or depend on aspects of experimental design. Here we present and evaluate a method of SNP discovery using RNA-sequencing and demographic inference using the program δaδi, which uses a diffusion approximation to the allele frequency spectrum to fit demographic models. We test these methods in a population of the checkerspot butterfly Euphydryas gillettii. This population was intentionally introduced to Gothic, Colorado in 1977 and has since experienced extreme fluctuations including bottlenecks of fewer than 25 adults, as documented by nearly annual field surveys. Using RNA-sequencing of eight individuals from Colorado and eight individuals from a native population in Wyoming, we generate the first genomic resources for this system. While demographic inference is commonly used to examine ancient demography, our study demonstrates that our inexpensive, all-in-one approach to marker discovery and genotyping provides sufficient data to accurately infer the timing of a recent bottleneck. This demographic scenario is relevant for many species of conservation concern, few of which have sequenced genomes. Our results are remarkably insensitive to sample size or number of genomic markers, which has important implications for applying this method to other non-model systems. PMID:24237665

Basin-scale seasonal changes in marine free-living bacterioplankton community in the Ofunato Bay

KAUST Repository

Reza, Md. Shaheed

2018-04-26

The Ofunato Bay in the northeastern Pacific Ocean area of Japan possesses the highest biodiversity of marine organisms in the world and has attracted much attention due to its economic and environmental importance. We report here a shotgun metagenomic analysis of the year-round variation in free-living bacterioplankton collected across the entire length of the bay. Phylogenetic differences among spring, summer, autumn and winter bacterioplankton suggested that members of Proteobacteria tended to decrease at high water temperatures and increase at low temperatures. It was revealed that Candidatus Pelagibacter varied seasonally, reaching as much as 60% of all sequences at the genus level in the surface waters during winter. This increase was more evident in the deeper waters, where they reached up to 75%. The relative abundance of Planktomarina also rose during winter and fell during summer. A significant component of the winter bacterioplankton community was Archaea (mainly represented by Nitrosopumilus), as their relative abundance was very low during spring and summer but high during winter. In contrast, Actinobacteria and Cyanobacteria appeared to be higher in abundance during high-temperature periods. It was also revealed that Bacteroidetes constituted a significant component of the summer bacterioplankton community, being the second largest bacterial phylum detected in the Ofunato Bay. Its members, notably Polaribacter and Flavobacterium, were found to be high in abundance during spring and summer, particularly in the surface waters. Principal component analysis and hierarchal clustering analyses showed that the bacterial communities in the Ofunato Bay changed seasonally, likely caused by the levels of organic matter, which would be deeply mixed with surface runoff in the winter.

Habitat filtering of bacterioplankton communities above polymetallic nodule fields and sediments in the Clarion-Clipperton zone of the Pacific Ocean.

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Lindh, Markus V; Maillot, Brianne M; Smith, Craig R; Church, Matthew J

2018-04-01

Deep-sea mining of commercially valuable polymetallic nodule fields will generate a seabed sediment plume into the water column. Yet, the response of bacterioplankton communities, critical in regulating energy and matter fluxes in marine ecosystems, to such disturbances is unknown. Metacommunity theory, traditionally used in general ecology for macroorganisms, offers mechanistic understanding on the relative role of spatial differences compared with local environmental conditions (habitat filtering) for community assembly. We examined bacterioplankton metacommunities using 16S rRNA amplicons from the Clarion-Clipperton Zone (CCZ) in the eastern Pacific Ocean and in global ocean transect samples to determine sensitivity of these assemblages to environmental perturbations. Habitat filtering was the main assembly mechanism of bacterioplankton community composition in the epi- and mesopelagic waters of the CCZ and the Tara Oceans transect. Bathy- and abyssopelagic bacterioplankton assemblages were mainly assembled by undetermined metacommunity types or neutral and dispersal-driven patch-dynamics for the CCZ and the Malaspina transect. Environmental disturbances may alter the structure of upper-ocean microbial assemblages, with potentially even more substantial, yet unknown, impact on deep-sea communities. Predicting such responses in bacterioplankton assemblage dynamics can improve our understanding of microbially-mediated regulation of ecosystem services in the abyssal seabed likely to be exploited by future deep-sea mining operations. © 2018 Society for Applied Microbiology and John Wiley & Sons Ltd.

Genomic inferences of domestication events are corroborated by written records in Brassica rapa.

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Qi, Xinshuai; An, Hong; Ragsdale, Aaron P; Hall, Tara E; Gutenkunst, Ryan N; Chris Pires, J; Barker, Michael S

2017-07-01

Demographic modelling is often used with population genomic data to infer the relationships and ages among populations. However, relatively few analyses are able to validate these inferences with independent data. Here, we leverage written records that describe distinct Brassica rapa crops to corroborate demographic models of domestication. Brassica rapa crops are renowned for their outstanding morphological diversity, but the relationships and order of domestication remain unclear. We generated genomewide SNPs from 126 accessions collected globally using high-throughput transcriptome data. Analyses of more than 31,000 SNPs across the B. rapa genome revealed evidence for five distinct genetic groups and supported a European-Central Asian origin of B. rapa crops. Our results supported the traditionally recognized South Asian and East Asian B. rapa groups with evidence that pak choi, Chinese cabbage and yellow sarson are likely monophyletic groups. In contrast, the oil-type B. rapa subsp. oleifera and brown sarson were polyphyletic. We also found no evidence to support the contention that rapini is the wild type or the earliest domesticated subspecies of B. rapa. Demographic analyses suggested that B. rapa was introduced to Asia 2,400-4,100 years ago, and that Chinese cabbage originated 1,200-2,100 years ago via admixture of pak choi and European-Central Asian B. rapa. We also inferred significantly different levels of founder effect among the B. rapa subspecies. Written records from antiquity that document these crops are consistent with these inferences. The concordance between our age estimates of domestication events with historical records provides unique support for our demographic inferences. © 2017 John Wiley & Sons Ltd.

Submerged macrophytes shape the abundance and diversity of bacterial denitrifiers in bacterioplankton and epiphyton in the Shallow Fresh Lake Taihu, China.

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Fan, Zhou; Han, Rui-Ming; Ma, Jie; Wang, Guo-Xiang

2016-07-01

nirK and nirS genes are important functional genes involved in the denitrification pathway. Recent studies about these two denitrifying genes are focusing on sediment and wastewater microbe. In this study, we conducted a comparative analysis of the abundance and diversity of denitrifiers in the epiphyton of submerged macrophytes Potamogeton malaianus and Ceratophyllum demersum as well as in bacterioplankton in the shallow fresh lake Taihu, China. Results showed that nirK and nirS genes had significant different niches in epiphyton and bacterioplankton. Bacterioplankton showed greater abundance of nirK gene in terms of copy numbers and lower abundance of nirS gene. Significant difference in the abundance of nirK and nirS genes also existed between the epiphyton from different submerged macrophytes. Similar community diversity yet different community abundance was observed between epiphytic bacteria and bacterioplankton. No apparent seasonal variation was found either in epiphytic bacteria or bacterioplankton; however, environmental parameters seemed to have direct relevancy with nirK and nirS genes. Our study suggested that submerged macrophytes have greater influence than seasonal parameters in shaping the presence and abundance of bacterial denitrifiers. Further investigation needs to focus on the potential contact and relative contribution between denitrifiers and environmental factors.

Spatially uniform but temporally variable bacterioplankton in a semi-enclosed coastal area.

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Meziti, Alexandra; Kormas, Konstantinos A; Moustaka-Gouni, Maria; Karayanni, Hera

2015-07-01

Studies focusing on the temporal and spatial dynamics of bacterioplankton communities within littoral areas undergoing direct influences from the coast are quite limited. In addition, they are more complicated to resolve compared to communities in the open ocean. In order to elucidate the effects of spatial vs. temporal variability on bacterial communities in a highly land-influenced semi-enclosed gulf, surface bacterioplankton communities from five coastal sites in Igoumenitsa Gulf (Ionian Sea, Greece) were analyzed over a nine-month period using 16S rDNA 454-pyrosequencing. Temporal differences were more pronounced than spatial ones, with lower diversity indices observed during the summer months. During winter and early spring, bacterial communities were dominated by SAR11 representatives, while this pattern changed in May when they were abruptly replaced by members of Flavobacteriales, Pseudomonadales, and Alteromonadales. Additionally, correlation analysis showed high negative correlations between the presence of SAR11 OTUs in relation to temperature and sunlight that might have driven, directly or indirectly, the disappearance of these OTUs in the summer months. The dominance of SAR11 during the winter months further supported the global distribution of the clade, not only in the open-sea, but also in coastal systems. This study revealed that specific bacteria exhibited distinct succession patterns in an anthropogenic-impacted coastal system. The major bacterioplankton component was represented by commonly found marine bacteria exhibiting seasonal dynamics, while freshwater and terrestrial-related phylotypes were absent. Copyright © 2015 Elsevier GmbH. All rights reserved.

Inferring causal genomic alterations in breast cancer using gene expression data

Science.gov (United States)

2011-01-01

Background One of the primary objectives in cancer research is to identify causal genomic alterations, such as somatic copy number variation (CNV) and somatic mutations, during tumor development. Many valuable studies lack genomic data to detect CNV; therefore, methods that are able to infer CNVs from gene expression data would help maximize the value of these studies. Results We developed a framework for identifying recurrent regions of CNV and distinguishing the cancer driver genes from the passenger genes in the regions. By inferring CNV regions across many datasets we were able to identify 109 recurrent amplified/deleted CNV regions. Many of these regions are enriched for genes involved in many important processes associated with tumorigenesis and cancer progression. Genes in these recurrent CNV regions were then examined in the context of gene regulatory networks to prioritize putative cancer driver genes. The cancer driver genes uncovered by the framework include not only well-known oncogenes but also a number of novel cancer susceptibility genes validated via siRNA experiments. Conclusions To our knowledge, this is the first effort to systematically identify and validate drivers for expression based CNV regions in breast cancer. The framework where the wavelet analysis of copy number alteration based on expression coupled with the gene regulatory network analysis, provides a blueprint for leveraging genomic data to identify key regulatory components and gene targets. This integrative approach can be applied to many other large-scale gene expression studies and other novel types of cancer data such as next-generation sequencing based expression (RNA-Seq) as well as CNV data. PMID:21806811

Inferring network structure in non-normal and mixed discrete-continuous genomic data.

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Bhadra, Anindya; Rao, Arvind; Baladandayuthapani, Veerabhadran

2018-03-01

Inferring dependence structure through undirected graphs is crucial for uncovering the major modes of multivariate interaction among high-dimensional genomic markers that are potentially associated with cancer. Traditionally, conditional independence has been studied using sparse Gaussian graphical models for continuous data and sparse Ising models for discrete data. However, there are two clear situations when these approaches are inadequate. The first occurs when the data are continuous but display non-normal marginal behavior such as heavy tails or skewness, rendering an assumption of normality inappropriate. The second occurs when a part of the data is ordinal or discrete (e.g., presence or absence of a mutation) and the other part is continuous (e.g., expression levels of genes or proteins). In this case, the existing Bayesian approaches typically employ a latent variable framework for the discrete part that precludes inferring conditional independence among the data that are actually observed. The current article overcomes these two challenges in a unified framework using Gaussian scale mixtures. Our framework is able to handle continuous data that are not normal and data that are of mixed continuous and discrete nature, while still being able to infer a sparse conditional sign independence structure among the observed data. Extensive performance comparison in simulations with alternative techniques and an analysis of a real cancer genomics data set demonstrate the effectiveness of the proposed approach. © 2017, The International Biometric Society.

Latitudinal patterns in the abundance of major marine bacterioplankton groups

DEFF Research Database (Denmark)

Wietz, Matthias; Gram, Lone; Jørgensen, Bo

2010-01-01

relative abundance 37%, average absolute abundance 3.7×105 cells mL-1) including SAR11 (30%/3×105), Gammaproteobacteria (14%/1.2×105), and Bacteroidetes (12%/1.3×105) globally dominated the bacterioplankton. The SAR86 clade (4.6%/4.1×104) and Actinobacteria (4.5%/4×104) were detected ubiquitously, whereas...

Compositional and mutational rate heterogeneity in mitochondrial genomes and its effect on the phylogenetic inferences of Cimicomorpha (Hemiptera: Heteroptera).

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Yang, Huanhuan; Li, Teng; Dang, Kai; Bu, Wenjun

2018-04-18

Mitochondrial genome (mt-genome) data can potentially return artefactual relationships in the higher-level phylogenetic inference of insects due to the biases of accelerated substitution rates and compositional heterogeneity. Previous studies based on mt-genome data alone showed a paraphyly of Cimicomorpha (Insecta, Hemiptera) due to the positions of the families Tingidae and Reduviidae rather than the monophyly that was supported based on morphological characters, morphological and molecular combined data and large scale molecular datasets. Various strategies have been proposed to ameliorate the effects of potential mt-genome biases, including dense taxon sampling, removal of third codon positions or purine-pyrimidine coding and the use of site-heterogeneous models. In this study, we sequenced the mt-genomes of five additional Tingidae species and discussed the compositional and mutational rate heterogeneity in mt-genomes and its effect on the phylogenetic inferences of Cimicomorpha by implementing the bias-reduction strategies mentioned above. Heterogeneity in nucleotide composition and mutational biases were found in mt protein-coding genes, and the third codon exhibited high levels of saturation. Dense taxon sampling of Tingidae and Reduviidae and the other common strategies mentioned above were insufficient to recover the monophyly of the well-established group Cimicomorpha. When the sites with weak phylogenetic signals in the dataset were removed, the remaining dataset of mt-genomes can support the monophyly of Cimicomorpha; this support demonstrates that mt-genomes possess strong phylogenetic signals for the inference of higher-level phylogeny of this group. Comparison of the ratio of the removal of amino acids for each PCG showed that ATP8 has the highest ratio while CO1 has the lowest. This pattern is largely congruent with the evolutionary rate of 13 PCGs that ATP8 represents the highest evolutionary rate, whereas CO1 appears to be the lowest. Notably

Bacterial phylogenetic reconstruction from whole genomes is robust to recombination but demographic inference is not.

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Hedge, Jessica; Wilson, Daniel J

2014-11-25

Phylogenetic inference in bacterial genomics is fundamental to understanding problems such as population history, antimicrobial resistance, and transmission dynamics. The field has been plagued by an apparent state of contradiction since the distorting effects of recombination on phylogeny were discovered more than a decade ago. Researchers persist with detailed phylogenetic analyses while simultaneously acknowledging that recombination seriously misleads inference of population dynamics and selection. Here we resolve this paradox by showing that phylogenetic tree topologies based on whole genomes robustly reconstruct the clonal frame topology but that branch lengths are badly skewed. Surprisingly, removing recombining sites can exacerbate branch length distortion caused by recombination. Phylogenetic tree reconstruction is a popular approach for understanding the relatedness of bacteria in a population from differences in their genome sequences. However, bacteria frequently exchange regions of their genomes by a process called homologous recombination, which violates a fundamental assumption of phylogenetic methods. Since many researchers continue to use phylogenetics for recombining bacteria, it is important to understand how recombination affects the conclusions drawn from these analyses. We find that whole-genome sequences afford great accuracy in reconstructing evolutionary relationships despite concerns surrounding the presence of recombination, but the branch lengths of the phylogenetic tree are indeed badly distorted. Surprisingly, methods to reduce the impact of recombination on branch lengths can exacerbate the problem. Copyright © 2014 Hedge and Wilson.

Bacterioplankton features and its relations with doc characteristics and other limnological variables in Paraná river floodplain environments (PR/MS-Brazil).

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Teixeira, Mariana Carolina; Santana, Natália Fernanda; de Azevedo, Júlio César Rodrigues; Pagioro, Thomaz Aurélio

2011-07-01

Since the introduction of the Microbial Loop concept, many studies aimed to explain the role of bacterioplankton and dissolved organic carbon (DOC) in aquatic ecosystems. Paraná River floodplain system is a very complex environment where these subjects were little explored. The aim of this work was to characterize bacterial community in terms of density, biomass and biovolume in some water bodies of this floodplain and to verify its temporal variation and its relation with some limnological variables, including some indicators of DOC quality, obtained through Ultraviolet-visible (UV-VIS) and fluorescence spectroscopic analysis. Bacterial density, biomass and biovolume are similar to those from other freshwater environments and both density and biomass were higher in the period with less rain. The limnological and spectroscopic features that showed any relation with bacterioplankton were the concentrations of N-NH4 and P-PO4, water transparency, and some indicators of DOC quality and origin. The analysis of these relations showed a possible competition between bacterioplankton and phytoplankton for inorganic nutrients and that the DOC used by bacterioplankton is labile and probably from aquatic macrophytes.

Bacterioplankton diversity and community composition in the Southern Lagoon of Venice.

Science.gov (United States)

Simonato, Francesca; Gómez-Pereira, Paola R; Fuchs, Bernhard M; Amann, Rudolf

2010-04-01

The Lagoon of Venice is a large water basin that exchanges water with the Northern Adriatic Sea through three large inlets. In this study, the 16S rRNA approach was used to investigate the bacterial diversity and community composition within the southern basin of the Lagoon of Venice and at one inlet in October 2007 and June 2008. Comparative sequence analysis of 645 mostly partial 16S rRNA gene sequences indicated high diversity and dominance of Alphaproteobacteria, Gammaproteobacteria and Bacteroidetes at the lagoon as well as at the inlet station, therefore pointing to significant mixing. Many of these sequences were close to the 16S rRNA of marine, often coastal, bacterioplankton, such as the Roseobacter clade, the family Vibrionaceae, and class Flavobacteria. Sequences of Actinobacteria were indicators of a freshwater input. The composition of the bacterioplankton was quantified by catalyzed reporter deposition fluorescence in situ hybridization (CARD-FISH) with a set of rRNA-targeted oligonucleotide probes. CARD-FISH counts corroborated the dominance of members of the phyla Alphaproteobacteria, Gammaproteobacteria and Bacteroidetes. When assessed by a probe set for the quantification of selected clades within Alphaproteobacteria and Gammaproteobacteria, bacterioplankton composition differed between October 2007 and June 2008, and also between the inlet and the lagoon. In particular, members of the readily culturable copiotrophic gammaproteobacterial genera Vibrio, Alteromonas and Pseudoalteromonas were enriched in the southern basin of the Lagoon of Venice. Interestingly, the alphaproteobacterial SAR11 clade and related clusters were also present in high abundances at the inlet and within the lagoon, which was indicative of inflow of water from the open sea.

Impact of Sample Type and DNA Isolation Procedure on Genomic Inference of Microbiome Composition

DEFF Research Database (Denmark)

Knudsen, Berith Elkær; Bergmark, Lasse; Munk, Patrick

2016-01-01

that in standard protocols. Based on this insight, we designed an improved DNA isolation procedure optimized for microbiome genomics that can be used for the three examined specimen types and potentially also for other biological specimens. A standard operating procedure is available from https://dx.doi.org/10......Explorations of complex microbiomes using genomics greatly enhance our understanding about their diversity, biogeography, and function. The isolation of DNA from microbiome specimens is a key prerequisite for such examinations, but challenges remain in obtaining sufficient DNA quantities required...... for certain sequencing approaches, achieving accurate genomic inference of microbiome composition, and facilitating comparability of findings across specimen types and sequencing projects. These aspects are particularly relevant for the genomics-based global surveillance of infectious agents and antimicrobial...

Inference of population splits and mixtures from genome-wide allele frequency data.

Directory of Open Access Journals (Sweden)

Joseph K Pickrell

Full Text Available Many aspects of the historical relationships between populations in a species are reflected in genetic data. Inferring these relationships from genetic data, however, remains a challenging task. In this paper, we present a statistical model for inferring the patterns of population splits and mixtures in multiple populations. In our model, the sampled populations in a species are related to their common ancestor through a graph of ancestral populations. Using genome-wide allele frequency data and a Gaussian approximation to genetic drift, we infer the structure of this graph. We applied this method to a set of 55 human populations and a set of 82 dog breeds and wild canids. In both species, we show that a simple bifurcating tree does not fully describe the data; in contrast, we infer many migration events. While some of the migration events that we find have been detected previously, many have not. For example, in the human data, we infer that Cambodians trace approximately 16% of their ancestry to a population ancestral to other extant East Asian populations. In the dog data, we infer that both the boxer and basenji trace a considerable fraction of their ancestry (9% and 25%, respectively to wolves subsequent to domestication and that East Asian toy breeds (the Shih Tzu and the Pekingese result from admixture between modern toy breeds and "ancient" Asian breeds. Software implementing the model described here, called TreeMix, is available at http://treemix.googlecode.com.

Metabolic Roles of Uncultivated Bacterioplankton Lineages in the Northern Gulf of Mexico "Dead Zone".

Science.gov (United States)

Thrash, J Cameron; Seitz, Kiley W; Baker, Brett J; Temperton, Ben; Gillies, Lauren E; Rabalais, Nancy N; Henrissat, Bernard; Mason, Olivia U

2017-09-12

Marine regions that have seasonal to long-term low dissolved oxygen (DO) concentrations, sometimes called "dead zones," are increasing in number and severity around the globe with deleterious effects on ecology and economics. One of the largest of these coastal dead zones occurs on the continental shelf of the northern Gulf of Mexico (nGOM), which results from eutrophication-enhanced bacterioplankton respiration and strong seasonal stratification. Previous research in this dead zone revealed the presence of multiple cosmopolitan bacterioplankton lineages that have eluded cultivation, and thus their metabolic roles in this ecosystem remain unknown. We used a coupled shotgun metagenomic and metatranscriptomic approach to determine the metabolic potential of Marine Group II Euryarchaeota , SAR406, and SAR202. We recovered multiple high-quality, nearly complete genomes from all three groups as well as candidate phyla usually associated with anoxic environments- Parcubacteria (OD1) and Peregrinibacteria Two additional groups with putative assignments to ACD39 and PAUC34f supplement the metabolic contributions by uncultivated taxa. Our results indicate active metabolism in all groups, including prevalent aerobic respiration, with concurrent expression of genes for nitrate reduction in SAR406 and SAR202, and dissimilatory nitrite reduction to ammonia and sulfur reduction by SAR406. We also report a variety of active heterotrophic carbon processing mechanisms, including degradation of complex carbohydrate compounds by SAR406, SAR202, ACD39, and PAUC34f. Together, these data help constrain the metabolic contributions from uncultivated groups in the nGOM during periods of low DO and suggest roles for these organisms in the breakdown of complex organic matter. IMPORTANCE Dead zones receive their name primarily from the reduction of eukaryotic macrobiota (demersal fish, shrimp, etc.) that are also key coastal fisheries. Excess nutrients contributed from anthropogenic activity

Extensive error in the number of genes inferred from draft genome assemblies.

Directory of Open Access Journals (Sweden)

James F Denton

2014-12-01

Full Text Available Current sequencing methods produce large amounts of data, but genome assemblies based on these data are often woefully incomplete. These incomplete and error-filled assemblies result in many annotation errors, especially in the number of genes present in a genome. In this paper we investigate the magnitude of the problem, both in terms of total gene number and the number of copies of genes in specific families. To do this, we compare multiple draft assemblies against higher-quality versions of the same genomes, using several new assemblies of the chicken genome based on both traditional and next-generation sequencing technologies, as well as published draft assemblies of chimpanzee. We find that upwards of 40% of all gene families are inferred to have the wrong number of genes in draft assemblies, and that these incorrect assemblies both add and subtract genes. Using simulated genome assemblies of Drosophila melanogaster, we find that the major cause of increased gene numbers in draft genomes is the fragmentation of genes onto multiple individual contigs. Finally, we demonstrate the usefulness of RNA-Seq in improving the gene annotation of draft assemblies, largely by connecting genes that have been fragmented in the assembly process.

SWPhylo - A Novel Tool for Phylogenomic Inferences by Comparison of Oligonucleotide Patterns and Integration of Genome-Based and Gene-Based Phylogenetic Trees.

Science.gov (United States)

Yu, Xiaoyu; Reva, Oleg N

2018-01-01

Modern phylogenetic studies may benefit from the analysis of complete genome sequences of various microorganisms. Evolutionary inferences based on genome-scale analysis are believed to be more accurate than the gene-based alternative. However, the computational complexity of current phylogenomic procedures, inappropriateness of standard phylogenetic tools to process genome-wide data, and lack of reliable substitution models which correlates with alignment-free phylogenomic approaches deter microbiologists from using these opportunities. For example, the super-matrix and super-tree approaches of phylogenomics use multiple integrated genomic loci or individual gene-based trees to infer an overall consensus tree. However, these approaches potentially multiply errors of gene annotation and sequence alignment not mentioning the computational complexity and laboriousness of the methods. In this article, we demonstrate that the annotation- and alignment-free comparison of genome-wide tetranucleotide frequencies, termed oligonucleotide usage patterns (OUPs), allowed a fast and reliable inference of phylogenetic trees. These were congruent to the corresponding whole genome super-matrix trees in terms of tree topology when compared with other known approaches including 16S ribosomal RNA and GyrA protein sequence comparison, complete genome-based MAUVE, and CVTree methods. A Web-based program to perform the alignment-free OUP-based phylogenomic inferences was implemented at http://swphylo.bi.up.ac.za/. Applicability of the tool was tested on different taxa from subspecies to intergeneric levels. Distinguishing between closely related taxonomic units may be enforced by providing the program with alignments of marker protein sequences, eg, GyrA.

Bacterioplankton features and its relations with doc characteristics and other limnological variables in Paraná river floodplain environments (PR/MS-Brazil

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Mariana Carolina Teixeira

2011-09-01

Full Text Available Since the introduction of the Microbial Loop concept, many studies aimed to explain the role of bacterioplankton and dissolved organic carbon (DOC in aquatic ecosystems. Paraná River floodplain system is a very complex environment where these subjects were little explored. The aim of this work was to characterize bacterial community in terms of density, biomass and biovolume in some water bodies of this floodplain and to verify its temporal variation and its relation with some limnological variables, including some indicators of DOC quality, obtained through Ultraviolet-visible (UV-VIS and fluorescence spectroscopic analysis. Bacterial density, biomass and biovolume are similar to those from other freshwater environments and both density and biomass were higher in the period with less rain. The limnological and spectroscopic features that showed any relation with bacterioplankton were the concentrations of N-NH4 and P-PO4, water transparency, and some indicators of DOC quality and origin. The analysis of these relations showed a possible competition between bacterioplankton and phytoplankton for inorganic nutrients and that the DOC used by bacterioplankton is labile and probably from aquatic macrophytes.

Nearly a decade-long repeatable seasonal diversity patterns of bacterioplankton communities in the eutrophic Lake Donghu (Wuhan, China)

Energy Technology Data Exchange (ETDEWEB)

Yan, Qingyun [Environmental Microbiome Research Center and the School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou China; Key Laboratory of Aquatic Biodiversity and Conservation of Chinese Academy of Sciences, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan China; Stegen, James C. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA USA; Yu, Yuhe [Key Laboratory of Aquatic Biodiversity and Conservation of Chinese Academy of Sciences, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan China; Deng, Ye [CAS Key Laboratory of Environmental Biotechnology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing China; Li, Xinghao [Key Laboratory of Aquatic Biodiversity and Conservation of Chinese Academy of Sciences, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan China; Wu, Shu [Key Laboratory of Aquatic Biodiversity and Conservation of Chinese Academy of Sciences, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan China; Dai, Lili [Key Laboratory of Aquatic Biodiversity and Conservation of Chinese Academy of Sciences, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan China; Zhang, Xiang [Key Laboratory of Aquatic Biodiversity and Conservation of Chinese Academy of Sciences, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan China; Li, Jinjin [Key Laboratory of Aquatic Biodiversity and Conservation of Chinese Academy of Sciences, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan China; Wang, Chun [Key Laboratory of Aquatic Biodiversity and Conservation of Chinese Academy of Sciences, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan China; Ni, Jiajia [Key Laboratory of Aquatic Biodiversity and Conservation of Chinese Academy of Sciences, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan China; Li, Xuemei [Key Laboratory of Aquatic Biodiversity and Conservation of Chinese Academy of Sciences, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan China; Hu, Hongjuan [Key Laboratory of Aquatic Biodiversity and Conservation of Chinese Academy of Sciences, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan China; Xiao, Fanshu [Environmental Microbiome Research Center and the School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou China; Feng, Weisong [Key Laboratory of Aquatic Biodiversity and Conservation of Chinese Academy of Sciences, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan China; Ning, Daliang [Department of Microbiology and Plant Biology, Institute for Environmental Genomics, University of Oklahoma, Norman OK USA; He, Zhili [Environmental Microbiome Research Center and the School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou China; Department of Microbiology and Plant Biology, Institute for Environmental Genomics, University of Oklahoma, Norman OK USA; Van Nostrand, Joy D. [Department of Microbiology and Plant Biology, Institute for Environmental Genomics, University of Oklahoma, Norman OK USA; Wu, Liyou [Department of Microbiology and Plant Biology, Institute for Environmental Genomics, University of Oklahoma, Norman OK USA; Zhou, Jizhong [Department of Microbiology and Plant Biology, Institute for Environmental Genomics, University of Oklahoma, Norman OK USA; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing China; Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley CA USA

2017-05-21

Uncovering which environmental factors have the greatest influence on community diversity patterns and how ecological processes govern community turnover are key questions related to understanding community assembly mechanisms. Although we have good understanding of plant and animal community assembly, the mechanisms regulating diversity patterns of aquatic bacterial communities in lake ecosystems remains poorly understood. Here we present nearly a decade-long time-series study of bacterioplankton communities from the eutrophic Lake Donghu (Wuhan, China) using 16S rRNA gene amplicon sequencing. We found strong repeatable seasonal patterns for the overall community, common (detected in more than 50% samples) and dominant bacterial taxa (relative abundance > 1%). Moreover, community composition tracked the seasonal temperature gradient, indicating that temperature is an important environmental factor controlling observed diversity patterns. Total phosphorus also contributed significantly to the seasonal shifts in bacterioplankton composition. However, any spatial pattern across the main lake areas was overwhelmed by temporal variability in this eutrophic lake system. Phylogenetic analysis further indicated that 75%-82% of community turnover was governed by homogeneous selection, suggesting that the bacterioplankton communities are mainly controlled by niche-based processes. However, dominant niches available within seasons might be occupied by similar combinations of bacterial taxa with modest dispersal rates throughout this lake system. This study gives us important insights into community assembly and seasonal turnover of lake bacterioplankton, it may be also useful to predict temporal patterns of other planktonic communities.

SWPhylo – A Novel Tool for Phylogenomic Inferences by Comparison of Oligonucleotide Patterns and Integration of Genome-Based and Gene-Based Phylogenetic Trees

Science.gov (United States)

Yu, Xiaoyu; Reva, Oleg N

2018-01-01

Modern phylogenetic studies may benefit from the analysis of complete genome sequences of various microorganisms. Evolutionary inferences based on genome-scale analysis are believed to be more accurate than the gene-based alternative. However, the computational complexity of current phylogenomic procedures, inappropriateness of standard phylogenetic tools to process genome-wide data, and lack of reliable substitution models which correlates with alignment-free phylogenomic approaches deter microbiologists from using these opportunities. For example, the super-matrix and super-tree approaches of phylogenomics use multiple integrated genomic loci or individual gene-based trees to infer an overall consensus tree. However, these approaches potentially multiply errors of gene annotation and sequence alignment not mentioning the computational complexity and laboriousness of the methods. In this article, we demonstrate that the annotation- and alignment-free comparison of genome-wide tetranucleotide frequencies, termed oligonucleotide usage patterns (OUPs), allowed a fast and reliable inference of phylogenetic trees. These were congruent to the corresponding whole genome super-matrix trees in terms of tree topology when compared with other known approaches including 16S ribosomal RNA and GyrA protein sequence comparison, complete genome-based MAUVE, and CVTree methods. A Web-based program to perform the alignment-free OUP-based phylogenomic inferences was implemented at http://swphylo.bi.up.ac.za/. Applicability of the tool was tested on different taxa from subspecies to intergeneric levels. Distinguishing between closely related taxonomic units may be enforced by providing the program with alignments of marker protein sequences, eg, GyrA. PMID:29511354

INFLUENCE OF LIGHT ON BACTERIOPLANKTON PRODUCTION AND RESPIRATION IN A SUBTROPICAL CORAL REEF

Science.gov (United States)

The influence of sunlight on bacterioplankton production (14C-leucine (Leu) and 3H-thymidine (TdR) incorporation; changes in cell abundances) and O2 consumption was investigated in a shallow subtropical coral reef located near Key Largo, Florida. Quartz (light) and opaque (dark) ...

Strong variability in bacterioplankton abundance and production in central and western Bay of Bengal

Digital Repository Service at National Institute of Oceanography (India)

Fernandes, V.; Ramaiah, N.; Paul, J.T.; Sardessai, S.; Jyothibabu, R.; Gauns, M.

to low or no nutrient injections into the surface, primary production in Bay of Bengal is reportedly low. As a consequence, the Bay of Bengal is considered as a region of low biological productivity. Along with many biological parameters, bacterioplankton...

RegPredict: an integrated system for regulon inference in prokaryotes by comparative genomics approach

Energy Technology Data Exchange (ETDEWEB)

Novichkov, Pavel S.; Rodionov, Dmitry A.; Stavrovskaya, Elena D.; Novichkova, Elena S.; Kazakov, Alexey E.; Gelfand, Mikhail S.; Arkin, Adam P.; Mironov, Andrey A.; Dubchak, Inna

2010-05-26

RegPredict web server is designed to provide comparative genomics tools for reconstruction and analysis of microbial regulons using comparative genomics approach. The server allows the user to rapidly generate reference sets of regulons and regulatory motif profiles in a group of prokaryotic genomes. The new concept of a cluster of co-regulated orthologous operons allows the user to distribute the analysis of large regulons and to perform the comparative analysis of multiple clusters independently. Two major workflows currently implemented in RegPredict are: (i) regulon reconstruction for a known regulatory motif and (ii) ab initio inference of a novel regulon using several scenarios for the generation of starting gene sets. RegPredict provides a comprehensive collection of manually curated positional weight matrices of regulatory motifs. It is based on genomic sequences, ortholog and operon predictions from the MicrobesOnline. An interactive web interface of RegPredict integrates and presents diverse genomic and functional information about the candidate regulon members from several web resources. RegPredict is freely accessible at http://regpredict.lbl.gov.

Inferring genome-wide patterns of admixture in Qataris using fifty-five ancestral populations

Directory of Open Access Journals (Sweden)

Omberg Larsson

2012-06-01

Full Text Available Abstract Background Populations of the Arabian Peninsula have a complex genetic structure that reflects waves of migrations including the earliest human migrations from Africa and eastern Asia, migrations along ancient civilization trading routes and colonization history of recent centuries. Results Here, we present a study of genome-wide admixture in this region, using 156 genotyped individuals from Qatar, a country located at the crossroads of these migration patterns. Since haplotypes of these individuals could have originated from many different populations across the world, we have developed a machine learning method "SupportMix" to infer loci-specific genomic ancestry when simultaneously analyzing many possible ancestral populations. Simulations show that SupportMix is not only more accurate than other popular admixture discovery tools but is the first admixture inference method that can efficiently scale for simultaneous analysis of 50-100 putative ancestral populations while being independent of prior demographic information. Conclusions By simultaneously using the 55 world populations from the Human Genome Diversity Panel, SupportMix was able to extract the fine-scale ancestry of the Qatar population, providing many new observations concerning the ancestry of the region. For example, as well as recapitulating the three major sub-populations in Qatar, composed of mainly Arabic, Persian, and African ancestry, SupportMix additionally identifies the specific ancestry of the Persian group to populations sampled in Greater Persia rather than from China and the ancestry of the African group to sub-Saharan origin and not Southern African Bantu origin as previously thought.

Response of bacterioplankton community structure to an artificial gradient of pCO2 in the Arctic Ocean

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R. Zhang

2013-06-01

Full Text Available In order to test the influences of ocean acidification on the ocean pelagic ecosystem, so far the largest CO2 manipulation mesocosm study (European Project on Ocean Acidification, EPOCA was performed in Kings Bay (Kongsfjorden, Spitsbergen. During a 30 day incubation, bacterial diversity was investigated using DNA fingerprinting and clone library analysis of bacterioplankton samples. Terminal restriction fragment length polymorphism (T-RFLP analysis of the PCR amplicons of the 16S rRNA genes revealed that general bacterial diversity, taxonomic richness and community structure were influenced by the variation of productivity during the time of incubation, but not the degree of ocean acidification. A BIOENV analysis suggested a complex control of bacterial community structure by various biological and chemical environmental parameters. The maximum apparent diversity of bacterioplankton (i.e., the number of T-RFs in high and low pCO2 treatments differed significantly. A negative relationship between the relative abundance of Bacteroidetes and pCO2 levels was observed for samples at the end of the experiment by the combination of T-RFLP and clone library analysis. Our study suggests that ocean acidification affects the development of bacterial assemblages and potentially impacts the ecological function of the bacterioplankton in the marine ecosystem.

Response of bacterioplankton community structure to an artificial gradient of pCO2 in the Arctic Ocean

Science.gov (United States)

Zhang, R.; Xia, X.; Lau, S. C. K.; Motegi, C.; Weinbauer, M. G.; Jiao, N.

2013-06-01

In order to test the influences of ocean acidification on the ocean pelagic ecosystem, so far the largest CO2 manipulation mesocosm study (European Project on Ocean Acidification, EPOCA) was performed in Kings Bay (Kongsfjorden), Spitsbergen. During a 30 day incubation, bacterial diversity was investigated using DNA fingerprinting and clone library analysis of bacterioplankton samples. Terminal restriction fragment length polymorphism (T-RFLP) analysis of the PCR amplicons of the 16S rRNA genes revealed that general bacterial diversity, taxonomic richness and community structure were influenced by the variation of productivity during the time of incubation, but not the degree of ocean acidification. A BIOENV analysis suggested a complex control of bacterial community structure by various biological and chemical environmental parameters. The maximum apparent diversity of bacterioplankton (i.e., the number of T-RFs) in high and low pCO2 treatments differed significantly. A negative relationship between the relative abundance of Bacteroidetes and pCO2 levels was observed for samples at the end of the experiment by the combination of T-RFLP and clone library analysis. Our study suggests that ocean acidification affects the development of bacterial assemblages and potentially impacts the ecological function of the bacterioplankton in the marine ecosystem.

Hybrid Origins of Citrus Varieties Inferred from DNA Marker Analysis of Nuclear and Organelle Genomes

Science.gov (United States)

Kitajima, Akira; Nonaka, Keisuke; Yoshioka, Terutaka; Ohta, Satoshi; Goto, Shingo; Toyoda, Atsushi; Fujiyama, Asao; Mochizuki, Takako; Nagasaki, Hideki; Kaminuma, Eli; Nakamura, Yasukazu

2016-01-01

Most indigenous citrus varieties are assumed to be natural hybrids, but their parentage has so far been determined in only a few cases because of their wide genetic diversity and the low transferability of DNA markers. Here we infer the parentage of indigenous citrus varieties using simple sequence repeat and indel markers developed from various citrus genome sequence resources. Parentage tests with 122 known hybrids using the selected DNA markers certify their transferability among those hybrids. Identity tests confirm that most variant strains are selected mutants, but we find four types of kunenbo (Citrus nobilis) and three types of tachibana (Citrus tachibana) for which we suggest different origins. Structure analysis with DNA markers that are in Hardy–Weinberg equilibrium deduce three basic taxa coinciding with the current understanding of citrus ancestors. Genotyping analysis of 101 indigenous citrus varieties with 123 selected DNA markers infers the parentages of 22 indigenous citrus varieties including Satsuma, Temple, and iyo, and single parents of 45 indigenous citrus varieties, including kunenbo, C. ichangensis, and Ichang lemon by allele-sharing and parentage tests. Genotyping analysis of chloroplast and mitochondrial genomes using 11 DNA markers classifies their cytoplasmic genotypes into 18 categories and deduces the combination of seed and pollen parents. Likelihood ratio analysis verifies the inferred parentages with significant scores. The reconstructed genealogy identifies 12 types of varieties consisting of Kishu, kunenbo, yuzu, koji, sour orange, dancy, kobeni mikan, sweet orange, tachibana, Cleopatra, willowleaf mandarin, and pummelo, which have played pivotal roles in the occurrence of these indigenous varieties. The inferred parentage of the indigenous varieties confirms their hybrid origins, as found by recent studies. PMID:27902727

Inference of haplotypic phase and missing genotypes in polyploid organisms and variable copy number genomic regions

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Balding David J

2008-12-01

Full Text Available Abstract Background The power of haplotype-based methods for association studies, identification of regions under selection, and ancestral inference, is well-established for diploid organisms. For polyploids, however, the difficulty of determining phase has limited such approaches. Polyploidy is common in plants and is also observed in animals. Partial polyploidy is sometimes observed in humans (e.g. trisomy 21; Down's syndrome, and it arises more frequently in some human tissues. Local changes in ploidy, known as copy number variations (CNV, arise throughout the genome. Here we present a method, implemented in the software polyHap, for the inference of haplotype phase and missing observations from polyploid genotypes. PolyHap allows each individual to have a different ploidy, but ploidy cannot vary over the genomic region analysed. It employs a hidden Markov model (HMM and a sampling algorithm to infer haplotypes jointly in multiple individuals and to obtain a measure of uncertainty in its inferences. Results In the simulation study, we combine real haplotype data to create artificial diploid, triploid, and tetraploid genotypes, and use these to demonstrate that polyHap performs well, in terms of both switch error rate in recovering phase and imputation error rate for missing genotypes. To our knowledge, there is no comparable software for phasing a large, densely genotyped region of chromosome from triploids and tetraploids, while for diploids we found polyHap to be more accurate than fastPhase. We also compare the results of polyHap to SATlotyper on an experimentally haplotyped tetraploid dataset of 12 SNPs, and show that polyHap is more accurate. Conclusion With the availability of large SNP data in polyploids and CNV regions, we believe that polyHap, our proposed method for inferring haplotypic phase from genotype data, will be useful in enabling researchers analysing such data to exploit the power of haplotype-based analyses.

The Diversity of the Limnohabitans Genus, an Important Group of Freshwater Bacterioplankton, by Characterization of 35 Isolated Strains

Science.gov (United States)

Kasalický, Vojtěch; Jezbera, Jan; Hahn, Martin W.; Šimek, Karel

2013-01-01

Bacteria of the genus Limnohabitans, more precisely the R-BT lineage, have a prominent role in freshwater bacterioplankton communities due to their high rates of substrate uptake and growth, growth on algal-derived substrates and high mortality rates from bacterivory. Moreover, due to their generally larger mean cell volume, compared to typical bacterioplankton cells, they contribute over-proportionally to total bacterioplankton biomass. Here we present genetic, morphological and ecophysiological properties of 35 bacterial strains affiliated with the Limnohabitans genus newly isolated from 11 non-acidic European freshwater habitats. The low genetic diversity indicated by the previous studies using the ribosomal SSU gene highly contrasted with the surprisingly rich morphologies and different patterns in substrate utilization of isolated strains. Therefore, the intergenic spacer between 16S and 23S rRNA genes was successfully tested as a fine-scale marker to delineate individual lineages and even genotypes. For further studies, we propose the division of the Limnohabitans genus into five lineages (provisionally named as LimA, LimB, LimC, LimD and LimE) and also additional sublineages within the most diversified lineage LimC. Such a delineation is supported by the morphology of isolated strains which predetermine large differences in their ecology. PMID:23505469

Copy-number analysis and inference of subclonal populations in cancer genomes using Sclust.

Science.gov (United States)

Cun, Yupeng; Yang, Tsun-Po; Achter, Viktor; Lang, Ulrich; Peifer, Martin

2018-06-01

The genomes of cancer cells constantly change during pathogenesis. This evolutionary process can lead to the emergence of drug-resistant mutations in subclonal populations, which can hinder therapeutic intervention in patients. Data derived from massively parallel sequencing can be used to infer these subclonal populations using tumor-specific point mutations. The accurate determination of copy-number changes and tumor impurity is necessary to reliably infer subclonal populations by mutational clustering. This protocol describes how to use Sclust, a copy-number analysis method with a recently developed mutational clustering approach. In a series of simulations and comparisons with alternative methods, we have previously shown that Sclust accurately determines copy-number states and subclonal populations. Performance tests show that the method is computationally efficient, with copy-number analysis and mutational clustering taking Linux/Unix command-line syntax should be able to carry out analyses of subclonal populations.

Seasonality Affects the Diversity and Composition of Bacterioplankton Communities in Dongjiang River, a Drinking Water Source of Hong Kong

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Wei Sun

2017-08-01

Full Text Available Water quality ranks the most vital criterion for rivers serving as drinking water sources, which periodically changes over seasons. Such fluctuation is believed associated with the state shifts of bacterial community within. To date, seasonality effects on bacterioplankton community patterns in large rivers serving as drinking water sources however, are still poorly understood. Here we investigated the intra-annual bacterial community structure in the Dongjiang River, a drinking water source of Hong Kong, using high-throughput pyrosequencing in concert with geochemical property measurements during dry, and wet seasons. Our results showed that Proteobacteria, Actinobacteria, and Bacteroidetes were the dominant phyla of bacterioplankton communities, which varied in composition, and distribution from dry to wet seasons, and exhibited profound seasonal changes. Actinobacteria, Bacteroidetes, and Cyanobacteria seemed to be more associated with seasonality that the relative abundances of Actinobacteria, and Bacteroidetes were significantly higher in the dry season than those in the wet season (p < 0.01, while the relative abundance of Cyanobacteria was about 10-fold higher in the wet season than in the dry season. Temperature and NO3--N concentration represented key contributing factors to the observed seasonal variations. These findings help understand the roles of various bacterioplankton and their interactions with the biogeochemical processes in the river ecosystem.

Efficient inference of population size histories and locus-specific mutation rates from large-sample genomic variation data.

Science.gov (United States)

Bhaskar, Anand; Wang, Y X Rachel; Song, Yun S

2015-02-01

With the recent increase in study sample sizes in human genetics, there has been growing interest in inferring historical population demography from genomic variation data. Here, we present an efficient inference method that can scale up to very large samples, with tens or hundreds of thousands of individuals. Specifically, by utilizing analytic results on the expected frequency spectrum under the coalescent and by leveraging the technique of automatic differentiation, which allows us to compute gradients exactly, we develop a very efficient algorithm to infer piecewise-exponential models of the historical effective population size from the distribution of sample allele frequencies. Our method is orders of magnitude faster than previous demographic inference methods based on the frequency spectrum. In addition to inferring demography, our method can also accurately estimate locus-specific mutation rates. We perform extensive validation of our method on simulated data and show that it can accurately infer multiple recent epochs of rapid exponential growth, a signal that is difficult to pick up with small sample sizes. Lastly, we use our method to analyze data from recent sequencing studies, including a large-sample exome-sequencing data set of tens of thousands of individuals assayed at a few hundred genic regions. © 2015 Bhaskar et al.; Published by Cold Spring Harbor Laboratory Press.

LASSIM-A network inference toolbox for genome-wide mechanistic modeling.

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Rasmus Magnusson

2017-06-01

with truly systems-level data. We demonstrate the power of this approach by inferring a mechanistically motivated, genome-wide model of the Th2 transcription regulatory system, which plays an important role in several immune related diseases.

Depth distributions of DNA damage in Antarctic marine phyto- and bacterioplankton exposed to summertime UV radiation

NARCIS (Netherlands)

Buma, A.G.J.; de Boer, M.K.; Boelen, P.

During a survey from January to March 1998, the occurrence of W-B radiation (UVBR)-induced DNA damage in Antarctic marine phytoplankton and bacterioplankton was investigated, Sampling was done in Ryder Bay, off the British base Rothera Station, 67 degreesS, 68 degreesW (British Antarctic Survey).

Effects of UV radiation on DNA photodamage and production in bacterioplankton in the coastal Caribbean Sea

NARCIS (Netherlands)

Visser, P.M; Snelder, E; Kop, A.J; Boelen, P.; Buma, A.G.J.; van Duyl, F.C

1999-01-01

This study focuses on the effects of ultraviolet radiation (UVR) on bacterioplankton. The effect of different parts of the sunlight spectrum on the leucine and thymidine incorporation and on the induction of DNA damage in natural bacterial populations in the coastal Caribbean Sea off Curacao were

Deep Learning for Population Genetic Inference.

Science.gov (United States)

Sheehan, Sara; Song, Yun S

2016-03-01

Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme.

.i.Candidatus./i. Planktophila limnetica, an actinobacterium representing one of the most numerically important taxa in freshwater bacterioplankton

Czech Academy of Sciences Publication Activity Database

Jezbera, Jan; Sharma, A. K.; Brandt, U.; Doolittle, W.F.; Hahn, M.W.

2009-01-01

Roč. 59, č. 11 (2009), s. 2864-2869 ISSN 1466-5026 Institutional research plan: CEZ:AV0Z60170517 Keywords : Actinobacteria * Planktophila * freshwater * bacterioplankton Subject RIV: EE - Microbiology, Virology Impact factor: 2.113, year: 2009

Macrophytes and periphyton carbon subsidies to bacterioplankton and zooplankton in a shallow eutrophic lake in tropical China

NARCIS (Netherlands)

de Kluijver, A.; Ning, J.; Liu, Z.; Jeppesen, E.; Gulati, R.D.; Middelburg, J.J.

The subsidy of carbon derived from macrophytes and associated periphyton to bacterioplankton and zooplankton in subtropical shallow eutrophic Huizhou West Lake in China was analyzed using carbon stable isotope signatures. A restored part of the lake dominated by macrophytes was compared with an

Macrophytes and periphyton carbon subsidies to bacterioplankton and zooplankton in a shallow eutrophic lake in tropical China

NARCIS (Netherlands)

de Kluijver, A.; Ning, J.; Liu, Z.; Jeppesen, E.; Gulati, R.D.; Middelburg, J.J.

2015-01-01

The subsidy of carbon derived from macrophytes and associated periphyton to bacterioplankton and zooplankton in subtropical shallow eutrophic Huizhou West Lake in China was analyzed using carbon stable isotope signatures. A restored part of the lake dominated by macrophytes was compared with an

Bootstrapping phylogenies inferred from rearrangement data

Directory of Open Access Journals (Sweden)

Lin Yu

2012-08-01

Full Text Available Abstract Background Large-scale sequencing of genomes has enabled the inference of phylogenies based on the evolution of genomic architecture, under such events as rearrangements, duplications, and losses. Many evolutionary models and associated algorithms have been designed over the last few years and have found use in comparative genomics and phylogenetic inference. However, the assessment of phylogenies built from such data has not been properly addressed to date. The standard method used in sequence-based phylogenetic inference is the bootstrap, but it relies on a large number of homologous characters that can be resampled; yet in the case of rearrangements, the entire genome is a single character. Alternatives such as the jackknife suffer from the same problem, while likelihood tests cannot be applied in the absence of well established probabilistic models. Results We present a new approach to the assessment of distance-based phylogenetic inference from whole-genome data; our approach combines features of the jackknife and the bootstrap and remains nonparametric. For each feature of our method, we give an equivalent feature in the sequence-based framework; we also present the results of extensive experimental testing, in both sequence-based and genome-based frameworks. Through the feature-by-feature comparison and the experimental results, we show that our bootstrapping approach is on par with the classic phylogenetic bootstrap used in sequence-based reconstruction, and we establish the clear superiority of the classic bootstrap for sequence data and of our corresponding new approach for rearrangement data over proposed variants. Finally, we test our approach on a small dataset of mammalian genomes, verifying that the support values match current thinking about the respective branches. Conclusions Our method is the first to provide a standard of assessment to match that of the classic phylogenetic bootstrap for aligned sequences. Its

Bootstrapping phylogenies inferred from rearrangement data.

Science.gov (United States)

Lin, Yu; Rajan, Vaibhav; Moret, Bernard Me

2012-08-29

Large-scale sequencing of genomes has enabled the inference of phylogenies based on the evolution of genomic architecture, under such events as rearrangements, duplications, and losses. Many evolutionary models and associated algorithms have been designed over the last few years and have found use in comparative genomics and phylogenetic inference. However, the assessment of phylogenies built from such data has not been properly addressed to date. The standard method used in sequence-based phylogenetic inference is the bootstrap, but it relies on a large number of homologous characters that can be resampled; yet in the case of rearrangements, the entire genome is a single character. Alternatives such as the jackknife suffer from the same problem, while likelihood tests cannot be applied in the absence of well established probabilistic models. We present a new approach to the assessment of distance-based phylogenetic inference from whole-genome data; our approach combines features of the jackknife and the bootstrap and remains nonparametric. For each feature of our method, we give an equivalent feature in the sequence-based framework; we also present the results of extensive experimental testing, in both sequence-based and genome-based frameworks. Through the feature-by-feature comparison and the experimental results, we show that our bootstrapping approach is on par with the classic phylogenetic bootstrap used in sequence-based reconstruction, and we establish the clear superiority of the classic bootstrap for sequence data and of our corresponding new approach for rearrangement data over proposed variants. Finally, we test our approach on a small dataset of mammalian genomes, verifying that the support values match current thinking about the respective branches. Our method is the first to provide a standard of assessment to match that of the classic phylogenetic bootstrap for aligned sequences. Its support values follow a similar scale and its receiver

Dispersal timing and drought history influence the response of bacterioplankton to drying-rewetting stress.

Science.gov (United States)

Székely, Anna J; Langenheder, Silke

2017-08-01

The extent and frequency of drought episodes is expected to increase in the following decades making it a crucial stress factor for smaller water bodies. However, very little is known about how bacterioplankton is affected by increased evaporation and how these communities reassemble after rewetting. Here, we present results from a microcosm experiment that assessed the effect of drying-rewetting stress on bacterioplankton in the light of the stress history and the rate and timing of dispersal after the rewetting. We found that the drying phase resulted mainly in a change of function, whereas the complete desiccation and rewetting processes strongly affected both composition and function, which were, however, influenced by the initial conditions and stress history of the communities. Effects of dispersal were generally stronger when it occurred at an early stage after the rewetting. At this stage, selective establishment of dispersed bacteria coupled with enhanced compositional and functional recovery was found, whereas effects of dispersal were neutral, that is, predictable by dispersal rates, at later stages. Our studies therefore show that both the stress history and the timing of dispersal are important factors that influence the response of bacterial communities to environmental change and stress events.

Deep Learning for Population Genetic Inference.

Directory of Open Access Journals (Sweden)

Sara Sheehan

2016-03-01

Full Text Available Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data to the output (e.g., population genetic parameters of interest. We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history. Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme.

Deep Learning for Population Genetic Inference

Science.gov (United States)

Sheehan, Sara; Song, Yun S.

2016-01-01

Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme. PMID:27018908

Diversity in UV sensitivity and recovery potential among bacterioneuston and bacterioplankton isolates.

Science.gov (United States)

Santos, A L; Lopes, S; Baptista, I; Henriques, I; Gomes, N C M; Almeida, A; Correia, A; Cunha, A

2011-04-01

To assess the variability in UV-B (280-320 nm) sensitivity of selected bacterial isolates from the surface microlayer and underlying water of the Ria de Aveiro (Portugal) estuary and their ability to recover from previous UV-induced stress. Bacterial suspensions were exposed to UV-B radiation (3·3 W m⁻²). Effects on culturability and activity were assessed from colony counts and (3) H-leucine incorporation rates, respectively. Among the tested isolates, wide variability in UV-B-induced inhibition of culturability (37·4-99·3%) and activity (36·0-98·0%) was observed. Incubation of UV-B-irradiated suspensions under reactivating regimes (UV-A, 3·65 W m⁻²; photosynthetic active radiation, 40 W m⁻²; dark) also revealed diversity in the extent of recovery from UV-B stress. Trends of enhanced resistance of culturability (up to 15·0%) and enhanced recovery in activity (up to 52·0%) were observed in bacterioneuston isolates. Bacterioneuston isolates were less sensitive and recovered more rapidly from UV-B stress than bacterioplankton isolates, showing enhanced reduction in their metabolism during the irradiation period and decreased culturability during the recovery process compared to bacterioplankton. UV exposure can affect the diversity and activity of microbial communities by selecting UV-resistant strains and alter their metabolic activity towards protective strategies. © 2011 The Authors. Letters in Applied Microbiology © 2011 The Society for Applied Microbiology.

Bacterioplankton community composition along a salinity gradient of sixteen high-mountain lakes located on the Tibetan Plateau, China

NARCIS (Netherlands)

Wu, Q.L.; Zwart, G.; Schauer, M.; Kamst-van Agterveld, M.P.; Hahn, M.W.

2006-01-01

The influence of altitude and salinity on bacterioplankton community composition (BCC) in 16 high-mountain lakes located at altitudes of 2,817 to 5,134 m on the Eastern Qinghai-Xizang (Tibetan) Plateau, China, spanning a salinity gradient from 0.02% (freshwater) to 22.3% (hypersaline), was

Seasonality in molecular and cytometric diversity of marine bacterioplankton: the reshuffling of bacterial taxa by vertical mixing

KAUST Repository

García, Francisca C.

2015-07-17

The ’cytometric diversity’ of phytoplankton communities has been studied based on single-cell properties, but the applicability of this method to characterize bacterioplankton has been unexplored. Here, we analysed seasonal changes in cytometric diversity of marine bacterioplankton along a decadal time-series at three coastal stations in the Southern Bay of Biscay. Shannon-Weaver diversity estimates and Bray-Curtis similarities obtained by cytometric and molecular (16S rRNA tag sequencing) methods were significantly correlated in samples from a 3.5-year monthly time-series. Both methods showed a consistent cyclical pattern in the diversity of surface bacterial communities with maximal values in winter. The analysis of the highly resolved flow cytometry time-series across the vertical profile showed that water column mixing was a key factor explaining the seasonal changes in bacterial composition and the winter increase in bacterial diversity in coastal surface waters. Due to its low cost and short processing time as compared to genetic methods, the cytometric diversity approach represents a useful complementary tool in the macroecology of aquatic microbes.

Diurnal variations in depth profiles of UV-induced DNA damage and inhibition of bacterioplankton production in tropical coastal waters

NARCIS (Netherlands)

Visser, PM; Poos, JJ; Scheper, BB; Boelen, P; van Duyl, FC

2002-01-01

In this study, diurnal changes in bacterial production and DNA damage in bacterio-plankton (measured as cyclobutane pyrimidine dimers, CPDs) incubated in bags at different depths in tropical coastal waters were investigated. The DNA damage and inhibition of the bacterial production was highest at

The evolutionary history of termites as inferred from 66 mitochondrial genomes.

Science.gov (United States)

Bourguignon, Thomas; Lo, Nathan; Cameron, Stephen L; Šobotník, Jan; Hayashi, Yoshinobu; Shigenobu, Shuji; Watanabe, Dai; Roisin, Yves; Miura, Toru; Evans, Theodore A

2015-02-01

Termites have colonized many habitats and are among the most abundant animals in tropical ecosystems, which they modify considerably through their actions. The timing of their rise in abundance and of the dispersal events that gave rise to modern termite lineages is not well understood. To shed light on termite origins and diversification, we sequenced the mitochondrial genome of 48 termite species and combined them with 18 previously sequenced termite mitochondrial genomes for phylogenetic and molecular clock analyses using multiple fossil calibrations. The 66 genomes represent most major clades of termites. Unlike previous phylogenetic studies based on fewer molecular data, our phylogenetic tree is fully resolved for the lower termites. The phylogenetic positions of Macrotermitinae and Apicotermitinae are also resolved as the basal groups in the higher termites, but in the crown termitid groups, including Termitinae + Syntermitinae + Nasutitermitinae + Cubitermitinae, the position of some nodes remains uncertain. Our molecular clock tree indicates that the lineages leading to termites and Cryptocercus roaches diverged 170 Ma (153-196 Ma 95% confidence interval [CI]), that modern Termitidae arose 54 Ma (46-66 Ma 95% CI), and that the crown termitid group arose 40 Ma (35-49 Ma 95% CI). This indicates that the distribution of basal termite clades was influenced by the final stages of the breakup of Pangaea. Our inference of ancestral geographic ranges shows that the Termitidae, which includes more than 75% of extant termite species, most likely originated in Africa or Asia, and acquired their pantropical distribution after a series of dispersal and subsequent diversification events. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Metagenomic identification of bacterioplankton taxa and pathways involved in microcystin degradation in lake erie.

Directory of Open Access Journals (Sweden)

Xiaozhen Mou

Full Text Available Cyanobacterial harmful blooms (CyanoHABs that produce microcystins are appearing in an increasing number of freshwater ecosystems worldwide, damaging quality of water for use by human and aquatic life. Heterotrophic bacteria assemblages are thought to be important in transforming and detoxifying microcystins in natural environments. However, little is known about their taxonomic composition or pathways involved in the process. To address this knowledge gap, we compared the metagenomes of Lake Erie free-living bacterioplankton assemblages in laboratory microcosms amended with microcystins relative to unamended controls. A diverse array of bacterial phyla were responsive to elevated supply of microcystins, including Acidobacteria, Actinobacteria, Bacteroidetes, Planctomycetes, Proteobacteria of the alpha, beta, gamma, delta and epsilon subdivisions and Verrucomicrobia. At more detailed taxonomic levels, Methylophilales (mainly in genus Methylotenera and Burkholderiales (mainly in genera Bordetella, Burkholderia, Cupriavidus, Polaromonas, Ralstonia, Polynucleobacter and Variovorax of Betaproteobacteria were suggested to be more important in microcystin degradation than Sphingomonadales of Alphaproteobacteria. The latter taxa were previously thought to be major microcystin degraders. Homologs to known microcystin-degrading genes (mlr were not overrepresented in microcystin-amended metagenomes, indicating that Lake Erie bacterioplankton might employ alternative genes and/or pathways in microcystin degradation. Genes for xenobiotic metabolism were overrepresented in microcystin-amended microcosms, suggesting they are important in bacterial degradation of microcystin, a phenomenon that has been identified previously only in eukaryotic systems.

Relation between presence-absence of a visible nucleoid and metabolic activity in bacterioplankton cells

Energy Technology Data Exchange (ETDEWEB)

Choi, Joon, W.; Sherr, E.B.; Sherr, B.F. [Oregon State Univ., Corvallis, OR (United States)

1996-09-01

We investigated the report of Zweifel and Hagstroem that only a portion of marine bacteria contain nucleoids--the DNA-containing regions of procaryotic cells-- and that such bacteria correspond to the active or viable fraction of bacterioplankton. In Oregon coastal waters, 21-64% of bacteria had visible nucleoids; number of nucleoid-visible (NV) bacteria were greater than numbers of metabolically active bacteria, based on cells with active electron transport systems (ETS) and intact cell membranes. During log growth of a marine isolate, proportions of NV and ETS-active cells approached 100%. In stationary growth phase, the fraction of ETS-active cells decreased rapidly, while that of NV cells remained high for 7 d. When starved cells of the isolate were resupplied with nutrient (50 mg liter{sup -1} peptone), total cell number did not increase during the initial 6 h, but the proportion of NV cells increased from 27 to 100%, and that of ETS-active cells from 6 to 75%. In an analogous experiment with a bacterioplankton assemblage, a similar trend was observed: the number of NV cells double during the initial 6 h prior to an increase in total cell counts. These results show that some bacteria without visible nucleoids are capable of becoming NV cells, and thus have DNa in a nucleoid region not detectable with the method used here. 18 refs., 4 figs., 1 tab.

Biogeography and environmental genomics of the Roseobacter-affiliated pelagic CHAB-I-5 lineage

DEFF Research Database (Denmark)

Billerbeck, Sara; Wemheuer, Bernd; Voget, Sonja

2016-01-01

The identification and functional characterization of microbial communities remains a prevailing topic in microbial oceanography as information on environmentally relevant pelagic prokaryotes is still limited. The Roseobacter group, an abundant lineage of marine Alphaproteobacteria, can constitute...... large proportions of the bacterioplankton. Roseobacters also occur associated with eukaryotic organisms and possess streamlined as well as larger genomes from 2.2 to >5 Mpb. Here, we show that one pelagic cluster of this group, CHAB-I-5, occurs globally from tropical to polar regions and accounts for up...

The Recombination Landscape in Wild House Mice Inferred Using Population Genomic Data.

Science.gov (United States)

Booker, Tom R; Ness, Rob W; Keightley, Peter D

2017-09-01

Characterizing variation in the rate of recombination across the genome is important for understanding several evolutionary processes. Previous analysis of the recombination landscape in laboratory mice has revealed that the different subspecies have different suites of recombination hotspots. It is unknown, however, whether hotspots identified in laboratory strains reflect the hotspot diversity of natural populations or whether broad-scale variation in the rate of recombination is conserved between subspecies. In this study, we constructed fine-scale recombination rate maps for a natural population of the Eastern house mouse, Mus musculus castaneus We performed simulations to assess the accuracy of recombination rate inference in the presence of phase errors, and we used a novel approach to quantify phase error. The spatial distribution of recombination events is strongly positively correlated between our castaneus map, and a map constructed using inbred lines derived predominantly from M. m. domesticus Recombination hotspots in wild castaneus show little overlap, however, with the locations of double-strand breaks in wild-derived house mouse strains. Finally, we also find that genetic diversity in M. m. castaneus is positively correlated with the rate of recombination, consistent with pervasive natural selection operating in the genome. Our study suggests that recombination rate variation is conserved at broad scales between house mouse subspecies, but it is not strongly conserved at fine scales. Copyright © 2017 by the Genetics Society of America.

A new isolation with migration model along complete genomes infers very different divergence processes among closely related great ape species.

Directory of Open Access Journals (Sweden)

Thomas Mailund

Full Text Available We present a hidden Markov model (HMM for inferring gradual isolation between two populations during speciation, modelled as a time interval with restricted gene flow. The HMM describes the history of adjacent nucleotides in two genomic sequences, such that the nucleotides can be separated by recombination, can migrate between populations, or can coalesce at variable time points, all dependent on the parameters of the model, which are the effective population sizes, splitting times, recombination rate, and migration rate. We show by extensive simulations that the HMM can accurately infer all parameters except the recombination rate, which is biased downwards. Inference is robust to variation in the mutation rate and the recombination rate over the sequence and also robust to unknown phase of genomes unless they are very closely related. We provide a test for whether divergence is gradual or instantaneous, and we apply the model to three key divergence processes in great apes: (a the bonobo and common chimpanzee, (b the eastern and western gorilla, and (c the Sumatran and Bornean orang-utan. We find that the bonobo and chimpanzee appear to have undergone a clear split, whereas the divergence processes of the gorilla and orang-utan species occurred over several hundred thousands years with gene flow stopping quite recently. We also apply the model to the Homo/Pan speciation event and find that the most likely scenario involves an extended period of gene flow during speciation.

Short-term dynamics of North Sea bacterioplankton-dissolved organic matter coherence on molecular level

Directory of Open Access Journals (Sweden)

Judith eLucas

2016-03-01

Full Text Available Remineralisation and transformation of dissolved organic matter (DOM by marine microbes shape the DOM composition and thus, have large impact on global carbon and nutrient cycling. However, information on bacterioplankton-DOM interactions on a molecular level is limited. We examined the variation of bacterial community composition at Helgoland Roads (North Sea in relation to variation of molecular DOM composition and various environmental parameters on short-time scales. Surface water samples were taken daily over a period of twenty days. Bacterial community and molecular DOM composition were assessed via 16S rRNA gene tag sequencing and ultrahigh resolution Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS, respectively. Environmental conditions were driven by a coastal water influx during the first half of the sampling period and the onset of a summer phytoplankton bloom towards the end of the sampling period. These phenomena led to a distinct grouping of bacterial communities and DOM composition which was particularly influenced by total dissolved nitrogen concentration, temperature and salinity, as revealed by distance-based linear regression analyses. Bacterioplankton-DOM interaction was demonstrated in strong correlations between specific bacterial taxa and particular DOM molecules, thus, suggesting potential specialization on particular substrates. We propose that a combination of high resolution techniques, as used in this study, may provide substantial information on substrate generalists and specialists and thus, contribute to prediction of bacterial community composition variation.

Inferences from Genomic Models in Stratified Populations

DEFF Research Database (Denmark)

Janss, Luc; de los Campos, Gustavo; Sheehan, Nuala

2012-01-01

Unaccounted population stratification can lead to spurious associations in genome-wide association studies (GWAS) and in this context several methods have been proposed to deal with this problem. An alternative line of research uses whole-genome random regression (WGRR) models that fit all marker...

Integration of Multiple Genomic and Phenotype Data to Infer Novel miRNA-Disease Associations.

Science.gov (United States)

Shi, Hongbo; Zhang, Guangde; Zhou, Meng; Cheng, Liang; Yang, Haixiu; Wang, Jing; Sun, Jie; Wang, Zhenzhen

2016-01-01

MicroRNAs (miRNAs) play an important role in the development and progression of human diseases. The identification of disease-associated miRNAs will be helpful for understanding the molecular mechanisms of diseases at the post-transcriptional level. Based on different types of genomic data sources, computational methods for miRNA-disease association prediction have been proposed. However, individual source of genomic data tends to be incomplete and noisy; therefore, the integration of various types of genomic data for inferring reliable miRNA-disease associations is urgently needed. In this study, we present a computational framework, CHNmiRD, for identifying miRNA-disease associations by integrating multiple genomic and phenotype data, including protein-protein interaction data, gene ontology data, experimentally verified miRNA-target relationships, disease phenotype information and known miRNA-disease connections. The performance of CHNmiRD was evaluated by experimentally verified miRNA-disease associations, which achieved an area under the ROC curve (AUC) of 0.834 for 5-fold cross-validation. In particular, CHNmiRD displayed excellent performance for diseases without any known related miRNAs. The results of case studies for three human diseases (glioblastoma, myocardial infarction and type 1 diabetes) showed that all of the top 10 ranked miRNAs having no known associations with these three diseases in existing miRNA-disease databases were directly or indirectly confirmed by our latest literature mining. All these results demonstrated the reliability and efficiency of CHNmiRD, and it is anticipated that CHNmiRD will serve as a powerful bioinformatics method for mining novel disease-related miRNAs and providing a new perspective into molecular mechanisms underlying human diseases at the post-transcriptional level. CHNmiRD is freely available at http://www.bio-bigdata.com/CHNmiRD.

Integration of Multiple Genomic and Phenotype Data to Infer Novel miRNA-Disease Associations.

Directory of Open Access Journals (Sweden)

Hongbo Shi

Full Text Available MicroRNAs (miRNAs play an important role in the development and progression of human diseases. The identification of disease-associated miRNAs will be helpful for understanding the molecular mechanisms of diseases at the post-transcriptional level. Based on different types of genomic data sources, computational methods for miRNA-disease association prediction have been proposed. However, individual source of genomic data tends to be incomplete and noisy; therefore, the integration of various types of genomic data for inferring reliable miRNA-disease associations is urgently needed. In this study, we present a computational framework, CHNmiRD, for identifying miRNA-disease associations by integrating multiple genomic and phenotype data, including protein-protein interaction data, gene ontology data, experimentally verified miRNA-target relationships, disease phenotype information and known miRNA-disease connections. The performance of CHNmiRD was evaluated by experimentally verified miRNA-disease associations, which achieved an area under the ROC curve (AUC of 0.834 for 5-fold cross-validation. In particular, CHNmiRD displayed excellent performance for diseases without any known related miRNAs. The results of case studies for three human diseases (glioblastoma, myocardial infarction and type 1 diabetes showed that all of the top 10 ranked miRNAs having no known associations with these three diseases in existing miRNA-disease databases were directly or indirectly confirmed by our latest literature mining. All these results demonstrated the reliability and efficiency of CHNmiRD, and it is anticipated that CHNmiRD will serve as a powerful bioinformatics method for mining novel disease-related miRNAs and providing a new perspective into molecular mechanisms underlying human diseases at the post-transcriptional level. CHNmiRD is freely available at http://www.bio-bigdata.com/CHNmiRD.

Inference of the ancestral vertebrate phenotype through vestiges of the whole-genome duplications.

Science.gov (United States)

Onimaru, Koh; Kuraku, Shigehiro

2018-03-16

Inferring the phenotype of the last common ancestor of living vertebrates is a challenging problem because of several unresolvable factors. They include the lack of reliable out-groups of living vertebrates, poor information about less fossilizable organs and specialized traits of phylogenetically important species, such as lampreys and hagfishes (e.g. secondary loss of vertebrae in adult hagfishes). These factors undermine the reliability of ancestral reconstruction by traditional character mapping approaches based on maximum parsimony. In this article, we formulate an approach to hypothesizing ancestral vertebrate phenotypes using information from the phylogenetic and functional properties of genes duplicated by genome expansions in early vertebrate evolution. We named the conjecture as 'chronological reconstruction of ohnolog functions (CHROF)'. This CHROF conjecture raises the possibility that the last common ancestor of living vertebrates may have had more complex traits than currently thought.

Population-based statistical inference for temporal sequence of somatic mutations in cancer genomes.

Science.gov (United States)

Rhee, Je-Keun; Kim, Tae-Min

2018-04-20

It is well recognized that accumulation of somatic mutations in cancer genomes plays a role in carcinogenesis; however, the temporal sequence and evolutionary relationship of somatic mutations remain largely unknown. In this study, we built a population-based statistical framework to infer the temporal sequence of acquisition of somatic mutations. Using the model, we analyzed the mutation profiles of 1954 tumor specimens across eight tumor types. As a result, we identified tumor type-specific directed networks composed of 2-15 cancer-related genes (nodes) and their mutational orders (edges). The most common ancestors identified in pairwise comparison of somatic mutations were TP53 mutations in breast, head/neck, and lung cancers. The known relationship of KRAS to TP53 mutations in colorectal cancers was identified, as well as potential ancestors of TP53 mutation such as NOTCH1, EGFR, and PTEN mutations in head/neck, lung and endometrial cancers, respectively. We also identified apoptosis-related genes enriched with ancestor mutations in lung cancers and a relationship between APC hotspot mutations and TP53 mutations in colorectal cancers. While evolutionary analysis of cancers has focused on clonal versus subclonal mutations identified in individual genomes, our analysis aims to further discriminate ancestor versus descendant mutations in population-scale mutation profiles that may help select cancer drivers with clinical relevance.

Covariance Between Genotypic Effects and its Use for Genomic Inference in Half-Sib Families

Science.gov (United States)

Wittenburg, Dörte; Teuscher, Friedrich; Klosa, Jan; Reinsch, Norbert

2016-01-01

In livestock, current statistical approaches utilize extensive molecular data, e.g., single nucleotide polymorphisms (SNPs), to improve the genetic evaluation of individuals. The number of model parameters increases with the number of SNPs, so the multicollinearity between covariates can affect the results obtained using whole genome regression methods. In this study, dependencies between SNPs due to linkage and linkage disequilibrium among the chromosome segments were explicitly considered in methods used to estimate the effects of SNPs. The population structure affects the extent of such dependencies, so the covariance among SNP genotypes was derived for half-sib families, which are typical in livestock populations. Conditional on the SNP haplotypes of the common parent (sire), the theoretical covariance was determined using the haplotype frequencies of the population from which the individual parent (dam) was derived. The resulting covariance matrix was included in a statistical model for a trait of interest, and this covariance matrix was then used to specify prior assumptions for SNP effects in a Bayesian framework. The approach was applied to one family in simulated scenarios (few and many quantitative trait loci) and using semireal data obtained from dairy cattle to identify genome segments that affect performance traits, as well as to investigate the impact on predictive ability. Compared with a method that does not explicitly consider any of the relationship among predictor variables, the accuracy of genetic value prediction was improved by 10–22%. The results show that the inclusion of dependence is particularly important for genomic inference based on small sample sizes. PMID:27402363

Nonparametric Bayesian inference in biostatistics

CERN Document Server

Müller, Peter

2015-01-01

As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters c...

Inferring patterns of folktale diffusion using genomic data

Science.gov (United States)

Bortolini, Eugenio; Pagani, Luca; Sarno, Stefania; Boattini, Alessio; Sazzini, Marco; da Silva, Sara Graça; Martini, Gessica; Metspalu, Mait; Pettener, Davide; Luiselli, Donata; Tehrani, Jamshid J.

2017-01-01

Observable patterns of cultural variation are consistently intertwined with demic movements, cultural diffusion, and adaptation to different ecological contexts [Cavalli-Sforza and Feldman (1981) Cultural Transmission and Evolution: A Quantitative Approach; Boyd and Richerson (1985) Culture and the Evolutionary Process]. The quantitative study of gene–culture coevolution has focused in particular on the mechanisms responsible for change in frequency and attributes of cultural traits, the spread of cultural information through demic and cultural diffusion, and detecting relationships between genetic and cultural lineages. Here, we make use of worldwide whole-genome sequences [Pagani et al. (2016) Nature 538:238–242] to assess the impact of processes involving population movement and replacement on cultural diversity, focusing on the variability observed in folktale traditions (n = 596) [Uther (2004) The Types of International Folktales: A Classification and Bibliography. Based on the System of Antti Aarne and Stith Thompson] in Eurasia. We find that a model of cultural diffusion predicted by isolation-by-distance alone is not sufficient to explain the observed patterns, especially at small spatial scales (up to ∼4,000 km). We also provide an empirical approach to infer presence and impact of ethnolinguistic barriers preventing the unbiased transmission of both genetic and cultural information. After correcting for the effect of ethnolinguistic boundaries, we show that, of the alternative models that we propose, the one entailing cultural diffusion biased by linguistic differences is the most plausible. Additionally, we identify 15 tales that are more likely to be predominantly transmitted through population movement and replacement and locate putative focal areas for a set of tales that are spread worldwide. PMID:28784786

Effects of decreased resource availability, protozoan grazing and viral impact on a structure of bacterioplankton assemblage in a canyon-shaped reservoir

Czech Academy of Sciences Publication Activity Database

Horňák, Karel; Mašín, Michal; Jezbera, Jan; Bettarel, Y.; Nedoma, Jiří; Sime-Ngando, T.; Šimek, Karel

2005-01-01

Roč. 52, č. 3 (2005), s. 315-327 ISSN 0168-6496 R&D Projects: GA ČR(CZ) GA206/02/0003 Grant - others:PICS(FR) project 1111 Institutional research plan: CEZ:AV0Z60170517 Keywords : bacterioplankton * protozoan grazing * viral lysis Subject RIV: EH - Ecology, Behaviour Impact factor: 2.787, year: 2005

Flow cytometric monitoring of bacterioplankton phenotypic diversity predicts high population-specific feeding rates by invasive dreissenid mussels.

Science.gov (United States)

Props, Ruben; Schmidt, Marian L; Heyse, Jasmine; Vanderploeg, Henry A; Boon, Nico; Denef, Vincent J

2018-02-01

Species invasion is an important disturbance to ecosystems worldwide, yet knowledge about the impacts of invasive species on bacterial communities remains sparse. Using a novel approach, we simultaneously detected phenotypic and derived taxonomic change in a natural bacterioplankton community when subjected to feeding pressure by quagga mussels, a widespread aquatic invasive species. We detected a significant decrease in diversity within 1 h of feeding and a total diversity loss of 11.6 ± 4.1% after 3 h. This loss of microbial diversity was caused by the selective removal of high nucleic acid populations (29 ± 5% after 3 h). We were able to track the community diversity at high temporal resolution by calculating phenotypic diversity estimates from flow cytometry (FCM) data of minute amounts of sample. Through parallel FCM and 16S rRNA gene amplicon sequencing analysis of environments spanning a broad diversity range, we showed that the two approaches resulted in highly correlated diversity measures and captured the same seasonal and lake-specific patterns in community composition. Based on our results, we predict that selective feeding by invasive dreissenid mussels directly impacts the microbial component of the carbon cycle, as it may drive bacterioplankton communities toward less diverse and potentially less productive states. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

The diversity of the Limnohabitans genus, an important group of freshwater bacterioplankton, by characterization of 35 isolated strains

Czech Academy of Sciences Publication Activity Database

Kasalický, Vojtěch; Jezbera, Jan; Hahn, M.W.; Šimek, Karel

2013-01-01

Roč. 8, č. 3 (2013), e58209 E-ISSN 1932-6203 R&D Projects: GA ČR(CZ) GA206/08/0015; GA ČR(CZ) GAP504/10/0566; GA MŠk(CZ) MEB060702; GA MŠk(CZ) MEB060901 Institutional research plan: CEZ:AV0Z60170517 Institutional support: RVO:60077344 Keywords : bacterial microdiversity * aquatic * Limnohabitans * freshwater * bacterioplankton Subject RIV: EE - Microbiology, Virology Impact factor: 3.534, year: 2013

Exploring the Ecological Coherence between the Spatial and Temporal Patterns of Bacterioplankton in Boreal Lakes

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Juan Pablo Niño-García

2017-04-01

Full Text Available One of the major contemporary challenges in microbial ecology has been to discriminate the reactive core from the random, unreactive components of bacterial communities. In previous work we used the spatial abundance distributions of bacterioplankton across boreal lakes of Québec to group taxa into four distinct categories that reflect either hydrology-mediated dispersal along the aquatic network or environmental selection mechanisms within lakes. Here, we test whether this categorization derived from the spatial distribution of taxa is maintained over time, by analyzing the temporal dynamics of the operational taxonomic units (OTUs within those spatially derived categories along an annual cycle in the oligotrophic lake Croche (Québec, Canada, and assessing the coherence in the patterns of abundance, occurrence, and environmental range of these OTUs over space and time. We report that the temporal dynamics of most taxa within a single lake are largely coherent with those derived from their spatial distribution over large spatial scales, suggesting that these properties must be intrinsic of particular taxa. We also identified a set of rare taxa cataloged as having a random occupancy based on their spatial distribution, but which showed clear seasonality and abundance peaks along the year, yet these comprised a very small fraction of the total rare OTUs. We conclude that the presence of most rare bacterioplankton taxa in boreal lakes is random, since both their temporal and spatial dynamics suggest links to passive downstream transport and persistence in freshwater networks, rather than environmental selection.

A core phylogeny of Dictyostelia inferred from genomes representative of the eight major and minor taxonomic divisions of the group.

Science.gov (United States)

Singh, Reema; Schilde, Christina; Schaap, Pauline

2016-11-17

Dictyostelia are a well-studied group of organisms with colonial multicellularity, which are members of the mostly unicellular Amoebozoa. A phylogeny based on SSU rDNA data subdivided all Dictyostelia into four major groups, but left the position of the root and of six group-intermediate taxa unresolved. Recent phylogenies inferred from 30 or 213 proteins from sequenced genomes, positioned the root between two branches, each containing two major groups, but lacked data to position the group-intermediate taxa. Since the positions of these early diverging taxa are crucial for understanding the evolution of phenotypic complexity in Dictyostelia, we sequenced six representative genomes of early diverging taxa. We retrieved orthologs of 47 housekeeping proteins with an average size of 890 amino acids from six newly sequenced and eight published genomes of Dictyostelia and unicellular Amoebozoa and inferred phylogenies from single and concatenated protein sequence alignments. Concatenated alignments of all 47 proteins, and four out of five subsets of nine concatenated proteins all produced the same consensus phylogeny with 100% statistical support. Trees inferred from just two out of the 47 proteins, individually reproduced the consensus phylogeny, highlighting that single gene phylogenies will rarely reflect correct species relationships. However, sets of two or three concatenated proteins again reproduced the consensus phylogeny, indicating that a small selection of genes suffices for low cost classification of as yet unincorporated or newly discovered dictyostelid and amoebozoan taxa by gene amplification. The multi-locus consensus phylogeny shows that groups 1 and 2 are sister clades in branch I, with the group-intermediate taxon D. polycarpum positioned as outgroup to group 2. Branch II consists of groups 3 and 4, with the group-intermediate taxon Polysphondylium violaceum positioned as sister to group 4, and the group-intermediate taxon Dictyostelium polycephalum

Evolutionary Inference across Eukaryotes Identifies Specific Pressures Favoring Mitochondrial Gene Retention.

Science.gov (United States)

Johnston, Iain G; Williams, Ben P

2016-02-24

Since their endosymbiotic origin, mitochondria have lost most of their genes. Although many selective mechanisms underlying the evolution of mitochondrial genomes have been proposed, a data-driven exploration of these hypotheses is lacking, and a quantitatively supported consensus remains absent. We developed HyperTraPS, a methodology coupling stochastic modeling with Bayesian inference, to identify the ordering of evolutionary events and suggest their causes. Using 2015 complete mitochondrial genomes, we inferred evolutionary trajectories of mtDNA gene loss across the eukaryotic tree of life. We find that proteins comprising the structural cores of the electron transport chain are preferentially encoded within mitochondrial genomes across eukaryotes. A combination of high GC content and high protein hydrophobicity is required to explain patterns of mtDNA gene retention; a model that accounts for these selective pressures can also predict the success of artificial gene transfer experiments in vivo. This work provides a general method for data-driven inference of the ordering of evolutionary and progressive events, here identifying the distinct features shaping mitochondrial genomes of present-day species. Copyright © 2016 Elsevier Inc. All rights reserved.

Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach.

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Simon Boitard

2016-03-01

Full Text Available Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey, PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.

Inference of gene-phenotype associations via protein-protein interaction and orthology.

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Panwen Wang

Full Text Available One of the fundamental goals of genetics is to understand gene functions and their associated phenotypes. To achieve this goal, in this study we developed a computational algorithm that uses orthology and protein-protein interaction information to infer gene-phenotype associations for multiple species. Furthermore, we developed a web server that provides genome-wide phenotype inference for six species: fly, human, mouse, worm, yeast, and zebrafish. We evaluated our inference method by comparing the inferred results with known gene-phenotype associations. The high Area Under the Curve values suggest a significant performance of our method. By applying our method to two human representative diseases, Type 2 Diabetes and Breast Cancer, we demonstrated that our method is able to identify related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The web server can be used to infer functions and putative phenotypes of a gene along with the candidate genes of a phenotype, and thus aids in disease candidate gene discovery. Our web server is available at http://jjwanglab.org/PhenoPPIOrth.

Grazer and virus-induced mortality of bacterioplankton accelerates development of .i.Flectobacillus./i. populations in a freshwater community

Czech Academy of Sciences Publication Activity Database

Šimek, Karel; Weinbauer, M.G.; Horňák, Karel; Jezbera, Jan; Nedoma, Jiří; Dolan, J. R.

2007-01-01

Roč. 9, č. 3 (2007), s. 789-800 ISSN 1462-2912 R&D Projects: GA ČR(CZ) GA206/05/0007; GA AV ČR(CZ) 1QS600170504 Grant - others:MŠMT(CZ) Barrande 2004-004-2 Institutional research plan: CEZ:AV0Z60170517 Source of funding: V - iné verejné zdroje Keywords : bacterioplankton community composition * virus lysis * flagellate bacterivory * reservoir * FISH analysis of food vacuoles * microautoradiography Subject RIV: EE - Microbiology, Virology Impact factor: 4.929, year: 2007

The passive yet successful way of planktonic life: genomic and experimental analysis of the ecology of a free-living polynucleobacter population.

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Martin W Hahn

Full Text Available The bacterial taxon Polynucleobacter necessarius subspecies asymbioticus represents a group of planktonic freshwater bacteria with cosmopolitan and ubiquitous distribution in standing freshwater habitats. These bacteria comprise <1% to 70% (on average about 20% of total bacterioplankton cells in various freshwater habitats. The ubiquity of this taxon was recently explained by intra-taxon ecological diversification, i.e. specialization of lineages to specific environmental conditions; however, details on specific adaptations are not known. Here we investigated by means of genomic and experimental analyses the ecological adaptation of a persistent population dwelling in a small acidic pond.The investigated population (F10 lineage contributed on average 11% to total bacterioplankton in the pond during the vegetation periods (ice-free period, usually May to November. Only a low degree of genetic diversification of the population could be revealed. These bacteria are characterized by a small genome size (2.1 Mb, a relatively small number of genes involved in transduction of environmental signals, and the lack of motility and quorum sensing. Experiments indicated that these bacteria live as chemoorganotrophs by mainly utilizing low-molecular-weight substrates derived from photooxidation of humic substances.Evolutionary genome streamlining resulted in a highly passive lifestyle so far only known among free-living bacteria from pelagic marine taxa dwelling in environmentally stable nutrient-poor off-shore systems. Surprisingly, such a lifestyle is also successful in a highly dynamic and nutrient-richer environment such as the water column of the investigated pond, which was undergoing complete mixis and pronounced stratification in diurnal cycles. Obviously, metabolic and ecological versatility is not a prerequisite for long-lasting establishment of abundant bacterial populations under highly dynamic environmental conditions. Caution should be exercised

Alkane Hydroxylase Gene (alkB Phylotype Composition and Diversity in Northern Gulf of Mexico Bacterioplankton

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Conor Blake Smith

2013-12-01

Full Text Available Natural and anthropogenic activities introduce alkanes into marine systems where they are degraded by alkane hydroxylases expressed by phylogenetically diverse bacteria. Partial sequences for alkB, one of the structural genes of alkane hydroxylase, have been used to assess the composition of alkane-degrading communities, and to determine their responses to hydrocarbon inputs. We present here the first spatially extensive analysis of alkB in bacterioplankton of the northern Gulf of Mexico (nGoM, a region that experiences numerous hydrocarbon inputs. We have analyzed 401 partial alkB gene sequences amplified from genomic extracts collected during March 2010 from 17 water column samples that included surface waters and bathypelagic depths. Previous analyses of 16S rRNA gene sequences for these and related samples have shown that nGoM bacterial community composition and structure stratify strongly with depth, with distinctly different communities above and below 100 m. Although we hypothesized that alkB gene sequences would exhibit a similar pattern, PCA analyses of operational protein units (OPU indicated that community composition did not vary consistently with depth or other major physical-chemical variables. We observed 22 distinct OPUs, one of which was ubiquitous and accounted for 57% of all sequences. This OPU clustered with alkB sequences from known hydrocarbon oxidizers (e.g., Alcanivorax and Marinobacter. Some OPUs could not be associated with known alkane degraders, however, and perhaps represent novel hydrocarbon-oxidizing populations or genes. These results indicate that the capacity for alkane hydrolysis occurs widely in the nGoM, but that alkane degrader diversity varies substantially among sites and responds differently than bulk communities to physical-chemical variables.

The phylogenomic position of the grey nurse shark Carcharias taurus Rafinesque, 1810 (Lamniformes, Odontaspididae) inferred from the mitochondrial genome.

Science.gov (United States)

Bowden, Deborah L; Vargas-Caro, Carolina; Ovenden, Jennifer R; Bennett, Michael B; Bustamante, Carlos

2016-11-01

The complete mitochondrial genome of the grey nurse shark Carcharias taurus is described from 25 963 828 sequences obtained using Illumina NGS technology. Total length of the mitogenome is 16 715 bp, consisting of 2 rRNAs, 13 protein-coding regions, 22 tRNA and 2 non-coding regions thus updating the previously published mitogenome for this species. The phylogenomic reconstruction inferred from the mitogenome of 15 species of Lamniform and Carcharhiniform sharks supports the inclusion of C. taurus in a clade with the Lamnidae and Cetorhinidae. This complete mitogenome contributes to ongoing investigation into the monophyly of the Family Odontaspididae.

Maximum growth rates and possible life strategies of different bacterioplankton groups in relation to phosphorus availability in a freshwater reservoir

Czech Academy of Sciences Publication Activity Database

Šimek, Karel; Horňák, Karel; Jezbera, Jan; Nedoma, Jiří; Vrba, Jaroslav; Straškrábová, Viera; Macek, Miroslav; Dolan, J. R.; Hahn, M.W.

2006-01-01

Roč. 8, č. 9 (2006), s. 1613-1624 ISSN 1462-2912 R&D Projects: GA ČR(CZ) GA206/05/0007; GA AV ČR(CZ) 1QS600170504 Grant - others:MŠM(CZ) 60076658/01 Institutional research plan: CEZ:AV0Z60170517 Keywords : bacterioplankton community composition * growth of bacteria and flagellates * phosphorus availability * reservoir * top-down and bottom-up control Subject RIV: EE - Microbiology, Virology Impact factor: 4.630, year: 2006

Bacterioplankton communities of Crater Lake, OR: Dynamic changes with euphotic zone food web structure and stable deep water populations

Science.gov (United States)

Urbach, E.; Vergin, K.L.; Larson, G.L.; Giovannoni, S.J.

2007-01-01

The distribution of bacterial and archaeal species in Crater Lake plankton varies dramatically over depth and with time, as assessed by hybridization of group-specific oligonucleotides to RNA extracted from lakewater. Nonmetric, multidimensional scaling (MDS) analysis of relative bacterial phylotype densities revealed complex relationships among assemblages sampled from depth profiles in July, August and September of 1997 through 1999. CL500-11 green nonsulfur bacteria (Phylum Chloroflexi) and marine Group I crenarchaeota are consistently dominant groups in the oxygenated deep waters at 300 and 500 m. Other phylotypes found in the deep waters are similar to surface and mid-depth populations and vary with time. Euphotic zone assemblages are dominated either by ??-proteobacteria or CL120-10 verrucomicrobia, and ACK4 actinomycetes. MDS analyses of euphotic zone populations in relation to environmental variables and phytoplankton and zooplankton population structures reveal apparent links between Daphnia pulicaria zooplankton population densities and microbial community structure. These patterns may reflect food web interactions that link kokanee salmon population densities to community structure of the bacterioplankton, via fish predation on Daphnia with cascading consequences to Daphnia bacterivory and predation on bacterivorous protists. These results demonstrate a stable bottom-water microbial community. They also extend previous observations of food web-driven changes in euphotic zone bacterioplankton community structure to an oligotrophic setting. ?? 2007 Springer Science+Business Media B.V.

Inferring Variation in Copy Number Using High Throughput Sequencing Data in R.

Science.gov (United States)

Knaus, Brian J; Grünwald, Niklaus J

2018-01-01

Inference of copy number variation presents a technical challenge because variant callers typically require the copy number of a genome or genomic region to be known a priori . Here we present a method to infer copy number that uses variant call format (VCF) data as input and is implemented in the R package vcfR . This method is based on the relative frequency of each allele (in both genic and non-genic regions) sequenced at heterozygous positions throughout a genome. These heterozygous positions are summarized by using arbitrarily sized windows of heterozygous positions, binning the allele frequencies, and selecting the bin with the greatest abundance of positions. This provides a non-parametric summary of the frequency that alleles were sequenced at. The method is applicable to organisms that have reference genomes that consist of full chromosomes or sub-chromosomal contigs. In contrast to other software designed to detect copy number variation, our method does not rely on an assumption of base ploidy, but instead infers it. We validated these approaches with the model system of Saccharomyces cerevisiae and applied it to the oomycete Phytophthora infestans , both known to vary in copy number. This functionality has been incorporated into the current release of the R package vcfR to provide modular and flexible methods to investigate copy number variation in genomic projects.

Quantification of carbon and phosphorus co-limitation in bacterioplankton: new insights on an old topic.

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Irene Dorado-García

Full Text Available Because the nature of the main resource that limits bacterioplankton (e.g. organic carbon [C] or phosphorus [P] has biogeochemical implications concerning organic C accumulation in freshwater ecosystems, empirical knowledge is needed concerning how bacteria respond to these two resources, available alone or together. We performed field experiments of resource manipulation (2×2 factorial design, with the addition of C, P, or both combined in two Mediterranean freshwater ecosystems with contrasting trophic states (oligotrophy vs. eutrophy and trophic natures (autotrophy vs. heterotrophy, measured as gross primary production:respiration ratio. Overall, the two resources synergistically co-limited bacterioplankton, i.e. the magnitude of the response of bacterial production and abundance to the two resources combined was higher than the additive response in both ecosystems. However, bacteria also responded positively to single P and C additions in the eutrophic ecosystem, but not to single C in the oligotrophic one, consistent with the value of the ratio between bacterial C demand and algal C supply. Accordingly, the trophic nature rather than the trophic state of the ecosystems proves to be a key feature determining the expected types of resource co-limitation of bacteria, as summarized in a proposed theoretical framework. The actual types of co-limitation shifted over time and partially deviated (a lesser degree of synergism from the theoretical expectations, particularly in the eutrophic ecosystem. These deviations may be explained by extrinsic ecological forces to physiological limitations of bacteria, such as predation, whose role in our experiments is supported by the relationship between the dynamics of bacteria and bacterivores tested by SEMs (structural equation models. Our study, in line with the increasingly recognized role of freshwater ecosystems in the global C cycle, suggests that further attention should be focussed on the biotic

Progression inference for somatic mutations in cancer

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Leif E. Peterson

2017-04-01

Full Text Available Computational methods were employed to determine progression inference of genomic alterations in commonly occurring cancers. Using cross-sectional TCGA data, we computed evolutionary trajectories involving selectivity relationships among pairs of gene-specific genomic alterations such as somatic mutations, deletions, amplifications, downregulation, and upregulation among the top 20 driver genes associated with each cancer. Results indicate that the majority of hierarchies involved TP53, PIK3CA, ERBB2, APC, KRAS, EGFR, IDH1, VHL, etc. Research into the order and accumulation of genomic alterations among cancer driver genes will ever-increase as the costs of nextgen sequencing subside, and personalized/precision medicine incorporates whole-genome scans into the diagnosis and treatment of cancer. Keywords: Oncology, Cancer research, Genetics, Computational biology

Phytozome Comparative Plant Genomics Portal

Energy Technology Data Exchange (ETDEWEB)

Goodstein, David; Batra, Sajeev; Carlson, Joseph; Hayes, Richard; Phillips, Jeremy; Shu, Shengqiang; Schmutz, Jeremy; Rokhsar, Daniel

2014-09-09

The Dept. of Energy Joint Genome Institute is a genomics user facility supporting DOE mission science in the areas of Bioenergy, Carbon Cycling, and Biogeochemistry. The Plant Program at the JGI applies genomic, analytical, computational and informatics platforms and methods to: 1. Understand and accelerate the improvement (domestication) of bioenergy crops 2. Characterize and moderate plant response to climate change 3. Use comparative genomics to identify constrained elements and infer gene function 4. Build high quality genomic resource platforms of JGI Plant Flagship genomes for functional and experimental work 5. Expand functional genomic resources for Plant Flagship genomes

Evolution of genes and genomes on the Drosophila phylogeny

DEFF Research Database (Denmark)

Clark, Andrew G; Eisen, Michael B; Smith, Douglas R

2007-01-01

Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the ......Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here...... tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila...

Genome-wide survey in African Americans demonstrates potential epistasis of fitness in the human genome.

Science.gov (United States)

Wang, Heming; Choi, Yoonha; Tayo, Bamidele; Wang, Xuefeng; Morris, Nathan; Zhang, Xiang; Broeckel, Uli; Hanis, Craig; Kardia, Sharon; Redline, Susan; Cooper, Richard S; Tang, Hua; Zhu, Xiaofeng

2017-02-01

The role played by epistasis between alleles at unlinked loci in shaping population fitness has been debated for many years and the existing evidence has been mainly accumulated from model organisms. In model organisms, fitness epistasis can be systematically inferred by detecting nonindependence of genotypic values between loci in a population and confirmed through examining the number of offspring produced in two-locus genotype groups. No systematic study has been conducted to detect epistasis of fitness in humans owing to experimental constraints. In this study, we developed a novel method to detect fitness epistasis by testing the correlation between local ancestries on different chromosomes in an admixed population. We inferred local ancestry across the genome in 16,252 unrelated African Americans and systematically examined the pairwise correlations between the genomic regions on different chromosomes. Our analysis revealed a pair of genomic regions on chromosomes 4 and 6 that show significant local ancestry correlation (P-value = 4.01 × 10 -8 ) that can be potentially attributed to fitness epistasis. However, we also observed substantial local ancestry correlation that cannot be explained by systemic ancestry inference bias. To our knowledge, this study is the first to systematically examine evidence of fitness epistasis across the human genome. © 2016 WILEY PERIODICALS, INC.

Revealing less derived nature of cartilaginous fish genomes with their evolutionary time scale inferred with nuclear genes.

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Adina J Renz

Full Text Available Cartilaginous fishes, divided into Holocephali (chimaeras and Elasmoblanchii (sharks, rays and skates, occupy a key phylogenetic position among extant vertebrates in reconstructing their evolutionary processes. Their accurate evolutionary time scale is indispensable for better understanding of the relationship between phenotypic and molecular evolution of cartilaginous fishes. However, our current knowledge on the time scale of cartilaginous fish evolution largely relies on estimates using mitochondrial DNA sequences. In this study, making the best use of the still partial, but large-scale sequencing data of cartilaginous fish species, we estimate the divergence times between the major cartilaginous fish lineages employing nuclear genes. By rigorous orthology assessment based on available genomic and transcriptomic sequence resources for cartilaginous fishes, we selected 20 protein-coding genes in the nuclear genome, spanning 2973 amino acid residues. Our analysis based on the Bayesian inference resulted in the mean divergence time of 421 Ma, the late Silurian, for the Holocephali-Elasmobranchii split, and 306 Ma, the late Carboniferous, for the split between sharks and rays/skates. By applying these results and other documented divergence times, we measured the relative evolutionary rate of the Hox A cluster sequences in the cartilaginous fish lineages, which resulted in a lower substitution rate with a factor of at least 2.4 in comparison to tetrapod lineages. The obtained time scale enables mapping phenotypic and molecular changes in a quantitative framework. It is of great interest to corroborate the less derived nature of cartilaginous fish at the molecular level as a genome-wide phenomenon.

The reach of the genome signature in prokaryotes

NARCIS (Netherlands)

van Passel, M.W.J.; Kuramae, E.E.; Luyf, A.C.M.; Bart, A.; Boekhout, T.

2006-01-01

Background: With the increased availability of sequenced genomes there have been several initiatives to infer evolutionary relationships by whole genome characteristics. One of these studies suggested good congruence between genome synteny, shared gene content, 16S ribosomal DNA identity, codon

Genome-Wide SNP Discovery, Genotyping and Their Preliminary Applications for Population Genetic Inference in Spotted Sea Bass (Lateolabrax maculatus.

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Juan Wang

Full Text Available Next-generation sequencing and the collection of genome-wide single-nucleotide polymorphisms (SNPs allow identifying fine-scale population genetic structure and genomic regions under selection. The spotted sea bass (Lateolabrax maculatus is a non-model species of ecological and commercial importance and widely distributed in northwestern Pacific. A total of 22 648 SNPs was discovered across the genome of L. maculatus by paired-end sequencing of restriction-site associated DNA (RAD-PE for 30 individuals from two populations. The nucleotide diversity (π for each population was 0.0028±0.0001 in Dandong and 0.0018±0.0001 in Beihai, respectively. Shallow but significant genetic differentiation was detected between the two populations analyzed by using both the whole data set (FST = 0.0550, P < 0.001 and the putatively neutral SNPs (FST = 0.0347, P < 0.001. However, the two populations were highly differentiated based on the putatively adaptive SNPs (FST = 0.6929, P < 0.001. Moreover, a total of 356 SNPs representing 298 unique loci were detected as outliers putatively under divergent selection by FST-based outlier tests as implemented in BAYESCAN and LOSITAN. Functional annotation of the contigs containing putatively adaptive SNPs yielded hits for 22 of 55 (40% significant BLASTX matches. Candidate genes for local selection constituted a wide array of functions, including binding, catalytic and metabolic activities, etc. The analyses with the SNPs developed in the present study highlighted the importance of genome-wide genetic variation for inference of population structure and local adaptation in L. maculatus.

Energetic differences between bacterioplankton trophic groups and coral reef resistance.

Science.gov (United States)

McDole Somera, Tracey; Bailey, Barbara; Barott, Katie; Grasis, Juris; Hatay, Mark; Hilton, Brett J; Hisakawa, Nao; Nosrat, Bahador; Nulton, James; Silveira, Cynthia B; Sullivan, Chris; Brainard, Russell E; Rohwer, Forest

2016-04-27

Coral reefs are among the most productive and diverse marine ecosystems on the Earth. They are also particularly sensitive to changing energetic requirements by different trophic levels. Microbialization specifically refers to the increase in the energetic metabolic demands of microbes relative to macrobes and is significantly correlated with increasing human influence on coral reefs. In this study, metabolic theory of ecology is used to quantify the relative contributions of two broad bacterioplankton groups, autotrophs and heterotrophs, to energy flux on 27 Pacific coral reef ecosystems experiencing human impact to varying degrees. The effective activation energy required for photosynthesis is lower than the average energy of activation for the biochemical reactions of the Krebs cycle, and changes in the proportional abundance of these two groups can greatly affect rates of energy and materials cycling. We show that reef-water communities with a higher proportional abundance of microbial autotrophs expend more metabolic energy per gram of microbial biomass. Increased energy and materials flux through fast energy channels (i.e. water-column associated microbial autotrophs) may dampen the detrimental effects of increased heterotrophic loads (e.g. coral disease) on coral reef systems experiencing anthropogenic disturbance. © 2016 The Author(s).

Prosecutor: parameter-free inference of gene function for prokaryotes using DNA microarray data, genomic context and multiple gene annotation sources

Directory of Open Access Journals (Sweden)

van Hijum Sacha AFT

2008-10-01

Full Text Available Abstract Background Despite a plethora of functional genomic efforts, the function of many genes in sequenced genomes remains unknown. The increasing amount of microarray data for many species allows employing the guilt-by-association principle to predict function on a large scale: genes exhibiting similar expression patterns are more likely to participate in shared biological processes. Results We developed Prosecutor, an application that enables researchers to rapidly infer gene function based on available gene expression data and functional annotations. Our parameter-free functional prediction method uses a sensitive algorithm to achieve a high association rate of linking genes with unknown function to annotated genes. Furthermore, Prosecutor utilizes additional biological information such as genomic context and known regulatory mechanisms that are specific for prokaryotes. We analyzed publicly available transcriptome data sets and used literature sources to validate putative functions suggested by Prosecutor. We supply the complete results of our analysis for 11 prokaryotic organisms on a dedicated website. Conclusion The Prosecutor software and supplementary datasets available at http://www.prosecutor.nl allow researchers working on any of the analyzed organisms to quickly identify the putative functions of their genes of interest. A de novo analysis allows new organisms to be studied.

Impacts of combined overfishing and oil spills on the plankton trophodynamics of the West Florida shelf over the last half century of 1965-2011: A two-dimensional simulation analysis of biotic state transitions, from a zooplankton- to a bacterioplankton-modulated ecosystem.

Science.gov (United States)

Walsh, J. J.; Lenes, J. M.; Darrow, B.; Parks, A.; Weisberg, R. H.

2016-03-01

Over 50 years of multiple anthropogenic perturbations, Florida zooplankton stocks of the northeastern Gulf of Mexico declined ten-fold, with increments of mainly dominant toxic dinoflagellate harmful algal blooms (HABs), rather than diatoms, and a shift in loci of nutrient remineralization and oxygen depletion by bacterioplankton, from the sea floor to near surface waters. Yet, lytic bacterial biomass and associated ammonification only increased at most five-fold over the same time period, with consequently little indication of new, expanded "dead zones" of diatom-induced hypoxia. After bacterial lysis of intact cells of these increased HABs, the remaining residues of zooplankton biomass decrements evidently instead exited the water column as malign aerosolized HAB asthma triggers, correlated by co-traveling mercury aerosols, within wind-borne sea sprays. To unravel the causal mechanisms of these inferred decadal food web transitions, a 36-state variable plankton model of algal, bacterial, protozoan, and copepod component communities replicated daily time series of each plankton group's representatives on the West Florida shelf (WFS) during 1965-2011. At the lower phytoplankton trophic levels, 52% of the ungrazed HAB increments, between 1965-1967 and 2001-2002 before recent oil spills, remained in the water column to kill fishes and fuel bacterioplankton. But, another 48% of the WFS primary production then left the ocean's surface as a harbinger of increased public health hazards during continuing sea spray exports of salts, HAB toxins, and Hg poisons. Following the Deepwater Horizon petroleum releases in 2010, little additional change of element partition among the altered importance of WFS food web components of the trophic pyramid then pertained between 2001-2002 and 2010-2011, despite when anomalous upwelled nutrient supplies instead favored retrograde benign, oil-tolerant diatoms over the HABs during 2010. Indeed, by 2011 HABs were back, with biomass

Capturing single cell genomes of active polysaccharide degraders: an unexpected contribution of Verrucomicrobia.

Directory of Open Access Journals (Sweden)

Manuel Martinez-Garcia

Full Text Available Microbial hydrolysis of polysaccharides is critical to ecosystem functioning and is of great interest in diverse biotechnological applications, such as biofuel production and bioremediation. Here we demonstrate the use of a new, efficient approach to recover genomes of active polysaccharide degraders from natural, complex microbial assemblages, using a combination of fluorescently labeled substrates, fluorescence-activated cell sorting, and single cell genomics. We employed this approach to analyze freshwater and coastal bacterioplankton for degraders of laminarin and xylan, two of the most abundant storage and structural polysaccharides in nature. Our results suggest that a few phylotypes of Verrucomicrobia make a considerable contribution to polysaccharide degradation, although they constituted only a minor fraction of the total microbial community. Genomic sequencing of five cells, representing the most predominant, polysaccharide-active Verrucomicrobia phylotype, revealed significant enrichment in genes encoding a wide spectrum of glycoside hydrolases, sulfatases, peptidases, carbohydrate lyases and esterases, confirming that these organisms were well equipped for the hydrolysis of diverse polysaccharides. Remarkably, this enrichment was on average higher than in the sequenced representatives of Bacteroidetes, which are frequently regarded as highly efficient biopolymer degraders. These findings shed light on the ecological roles of uncultured Verrucomicrobia and suggest specific taxa as promising bioprospecting targets. The employed method offers a powerful tool to rapidly identify and recover discrete genomes of active players in polysaccharide degradation, without the need for cultivation.

MicroScope: a platform for microbial genome annotation and comparative genomics.

Science.gov (United States)

Vallenet, D; Engelen, S; Mornico, D; Cruveiller, S; Fleury, L; Lajus, A; Rouy, Z; Roche, D; Salvignol, G; Scarpelli, C; Médigue, C

2009-01-01

The initial outcome of genome sequencing is the creation of long text strings written in a four letter alphabet. The role of in silico sequence analysis is to assist biologists in the act of associating biological knowledge with these sequences, allowing investigators to make inferences and predictions that can be tested experimentally. A wide variety of software is available to the scientific community, and can be used to identify genomic objects, before predicting their biological functions. However, only a limited number of biologically interesting features can be revealed from an isolated sequence. Comparative genomics tools, on the other hand, by bringing together the information contained in numerous genomes simultaneously, allow annotators to make inferences based on the idea that evolution and natural selection are central to the definition of all biological processes. We have developed the MicroScope platform in order to offer a web-based framework for the systematic and efficient revision of microbial genome annotation and comparative analysis (http://www.genoscope.cns.fr/agc/microscope). Starting with the description of the flow chart of the annotation processes implemented in the MicroScope pipeline, and the development of traditional and novel microbial annotation and comparative analysis tools, this article emphasizes the essential role of expert annotation as a complement of automatic annotation. Several examples illustrate the use of implemented tools for the review and curation of annotations of both new and publicly available microbial genomes within MicroScope's rich integrated genome framework. The platform is used as a viewer in order to browse updated annotation information of available microbial genomes (more than 440 organisms to date), and in the context of new annotation projects (117 bacterial genomes). The human expertise gathered in the MicroScope database (about 280,000 independent annotations) contributes to improve the quality of

Insights into archaeal evolution and symbiosis from the genomes of a nanoarchaeon and its inferred crenarchaeal host from Obsidian Pool, Yellowstone National Park.

Science.gov (United States)

Podar, Mircea; Makarova, Kira S; Graham, David E; Wolf, Yuri I; Koonin, Eugene V; Reysenbach, Anna-Louise

2013-04-22

A single cultured marine organism, Nanoarchaeum equitans, represents the Nanoarchaeota branch of symbiotic Archaea, with a highly reduced genome and unusual features such as multiple split genes. The first terrestrial hyperthermophilic member of the Nanoarchaeota was collected from Obsidian Pool, a thermal feature in Yellowstone National Park, separated by single cell isolation, and sequenced together with its putative host, a Sulfolobales archaeon. Both the new Nanoarchaeota (Nst1) and N. equitans lack most biosynthetic capabilities, and phylogenetic analysis of ribosomal RNA and protein sequences indicates that the two form a deep-branching archaeal lineage. However, the Nst1 genome is more than 20% larger, and encodes a complete gluconeogenesis pathway as well as the full complement of archaeal flagellum proteins. With a larger genome, a smaller repertoire of split protein encoding genes and no split non-contiguous tRNAs, Nst1 appears to have experienced less severe genome reduction than N. equitans. These findings imply that, rather than representing ancestral characters, the extremely compact genomes and multiple split genes of Nanoarchaeota are derived characters associated with their symbiotic or parasitic lifestyle. The inferred host of Nst1 is potentially autotrophic, with a streamlined genome and simplified central and energetic metabolism as compared to other Sulfolobales. Comparison of the N. equitans and Nst1 genomes suggests that the marine and terrestrial lineages of Nanoarchaeota share a common ancestor that was already a symbiont of another archaeon. The two distinct Nanoarchaeota-host genomic data sets offer novel insights into the evolution of archaeal symbiosis and parasitism, enabling further studies of the cellular and molecular mechanisms of these relationships. This article was reviewed by Patrick Forterre, Bettina Siebers (nominated by Michael Galperin) and Purification Lopez-Garcia.

Modulated modularity clustering as an exploratory tool for functional genomic inference.

Directory of Open Access Journals (Sweden)

Eric A Stone

2009-05-01

Full Text Available In recent years, the advent of high-throughput assays, coupled with their diminishing cost, has facilitated a systems approach to biology. As a consequence, massive amounts of data are currently being generated, requiring efficient methodology aimed at the reduction of scale. Whole-genome transcriptional profiling is a standard component of systems-level analyses, and to reduce scale and improve inference clustering genes is common. Since clustering is often the first step toward generating hypotheses, cluster quality is critical. Conversely, because the validation of cluster-driven hypotheses is indirect, it is critical that quality clusters not be obtained by subjective means. In this paper, we present a new objective-based clustering method and demonstrate that it yields high-quality results. Our method, modulated modularity clustering (MMC, seeks community structure in graphical data. MMC modulates the connection strengths of edges in a weighted graph to maximize an objective function (called modularity that quantifies community structure. The result of this maximization is a clustering through which tightly-connected groups of vertices emerge. Our application is to systems genetics, and we quantitatively compare MMC both to the hierarchical clustering method most commonly employed and to three popular spectral clustering approaches. We further validate MMC through analyses of human and Drosophila melanogaster expression data, demonstrating that the clusters we obtain are biologically meaningful. We show MMC to be effective and suitable to applications of large scale. In light of these features, we advocate MMC as a standard tool for exploration and hypothesis generation.

An Assessment of Different Genomic Approaches for Inferring Phylogeny of Listeria monocytogenes

DEFF Research Database (Denmark)

Henri, Clementine; Leekitcharoenphon, Pimlapas; Carleton, Heather A.

2017-01-01

Background/objectives: Whole genome sequencing (WGS) has proven to be a powerful subtyping tool for foodborne pathogenic bacteria like L. monocytogenes. The interests of genome-scale analysis for national surveillance, outbreak detection or source tracking has been largely documented. The genomic......MLPPST) or pan genome (wgMLPPST). Currently, there are little comparisons studies of these different analytical approaches. Our objective was to assess and compare different genomic methods that can be implemented in order to cluster isolates of L monocytogenes.Methods: The clustering methods were evaluated...... on a collection of 207 L. monocytogenes genomes of food origin representative of the genetic diversity of the Anses collection. The trees were then compared using robust statistical analyses.Results: The backward comparability between conventional typing methods and genomic methods revealed a near...

Allele coding in genomic evaluation

Directory of Open Access Journals (Sweden)

Christensen Ole F

2011-06-01

Full Text Available Abstract Background Genomic data are used in animal breeding to assist genetic evaluation. Several models to estimate genomic breeding values have been studied. In general, two approaches have been used. One approach estimates the marker effects first and then, genomic breeding values are obtained by summing marker effects. In the second approach, genomic breeding values are estimated directly using an equivalent model with a genomic relationship matrix. Allele coding is the method chosen to assign values to the regression coefficients in the statistical model. A common allele coding is zero for the homozygous genotype of the first allele, one for the heterozygote, and two for the homozygous genotype for the other allele. Another common allele coding changes these regression coefficients by subtracting a value from each marker such that the mean of regression coefficients is zero within each marker. We call this centered allele coding. This study considered effects of different allele coding methods on inference. Both marker-based and equivalent models were considered, and restricted maximum likelihood and Bayesian methods were used in inference. Results Theoretical derivations showed that parameter estimates and estimated marker effects in marker-based models are the same irrespective of the allele coding, provided that the model has a fixed general mean. For the equivalent models, the same results hold, even though different allele coding methods lead to different genomic relationship matrices. Calculated genomic breeding values are independent of allele coding when the estimate of the general mean is included into the values. Reliabilities of estimated genomic breeding values calculated using elements of the inverse of the coefficient matrix depend on the allele coding because different allele coding methods imply different models. Finally, allele coding affects the mixing of Markov chain Monte Carlo algorithms, with the centered coding being

Genomics and the challenging translation into conservation practice

Science.gov (United States)

Aaron B. A. Shafer; Jochen B. W. Wolf; Paulo C. Alves; Linnea Bergstrom; Michael W. Bruford; Ioana Brannstrom; Guy Colling; Love Dalen; Luc De Meester; Robert Ekblom; Katie D. Fawcett; Simone Fior; Mehrdad Hajibabaei; Jason A. Hill; A. Rus Hoezel; Jacob Hoglund; Evelyn L. Jensen; Johannes Krause; Torsten N. Kristensen; Michael Krutzen; John K. McKay; Anita J. Norman; Rob Ogden; E. Martin Osterling; N. Joop Ouborg; John Piccolo; Danijela Popovic; Craig R. Primmer; Floyd A. Reed; Marie Roumet; Jordi Salmona; Tamara Schenekar; Michael K. Schwartz; Gernot Segelbacher; Helen Senn; Jens Thaulow; Mia Valtonen; Andrew Veale; Philippine Vergeer; Nagarjun Vijay; Carles Vila; Matthias Weissensteiner; Lovisa Wennerstrom; Christopher W. Wheat; Piotr Zielinski

2015-01-01

The global loss of biodiversity continues at an alarming rate. Genomic approaches have been suggested as a promising tool for conservation practice as scaling up to genome-wide data can improve traditional conservation genetic inferences and provide qualitatively novel insights. However, the generation of genomic data and subsequent analyses and interpretations remain...

REGEN: Ancestral Genome Reconstruction for Bacteria

OpenAIRE

Yang, Kuan; Heath, Lenwood S.; Setubal, João C.

2012-01-01

Ancestral genome reconstruction can be understood as a phylogenetic study with more details than a traditional phylogenetic tree reconstruction. We present a new computational system called REGEN for ancestral bacterial genome reconstruction at both the gene and replicon levels. REGEN reconstructs gene content, contiguous gene runs, and replicon structure for each ancestral genome. Along each branch of the phylogenetic tree, REGEN infers evolutionary events, including gene creation and deleti...

Effective Normalization for Copy Number Variation Detection from Whole Genome Sequencing

NARCIS (Netherlands)

Janevski, A.; Varadan, V.; Kamalakaran, S.; Banerjee, N.; Dimitrova, D.

2012-01-01

Background Whole genome sequencing enables a high resolution view ofthe human genome and provides unique insights into genome structureat an unprecedented scale. There have been a number of tools to infer copy number variation in the genome. These tools while validatedalso include a number of

Euphotic zone bacterioplankton sources major sedimentary bacteriohopanepolyols in the Holocene Black Sea

Science.gov (United States)

Blumenberg, Martin; Seifert, Richard; Kasten, Sabine; Bahlmann, Enno; Michaelis, Walter

2009-02-01

Bacteriohopanepolyols (BHPs) are lipid constituents of many bacterial groups. Geohopanoids, the diagenetic products, are therefore ubiquitous in organic matter of the geosphere. To examine the potential of BHPs as environmental markers in marine sediments, we investigated a Holocene sediment core from the Black Sea. The concentrations of BHPs mirror the environmental shift from a well-mixed lake to a stratified marine environment by a strong and gradual increase from low values (˜30 μg g -1 TOC) in the oldest sediments to ˜170 μg g -1 TOC in sediments representing the onset of a permanently anoxic water body at about 7500 years before present (BP). This increase in BHP concentrations was most likely caused by a strong increase in bacterioplanktonic paleoproductivity brought about by several ingressions of Mediterranean Sea waters at the end of the lacustrine stage (˜9500 years BP). δ 15N values coevally decreasing with increasing BHP concentrations may indicate a shift from a phosphorus- to a nitrogen-limited setting supporting growth of N 2-fixing, BHP-producing bacteria. In sediments of the last ˜3000 years BHP concentrations have remained relatively stable at about 50 μg g -1 TOC. The distributions of major BHPs did not change significantly during the shift from lacustrine (or oligohaline) to marine conditions. Tetrafunctionalized BHPs prevailed throughout the entire sediment core, with the common bacteriohopanetetrol and 35-aminobacteriohopanetriol and the rare 35-aminobacteriohopenetriol, so far only known from a purple non-sulfur α-proteobacterium, being the main components. Other BHPs specific to cyanobacteria and pelagic methanotrophic bacteria were also found but only in much smaller amounts. Our results demonstrate that BHPs from microorganisms living in deeper biogeochemical zones of marine water columns are underrepresented or even absent in the sediment compared to the BHPs of bacteria present in the euphotic zone. Obviously, the assemblage of

An Assessment of Different Genomic Approaches for Inferring Phylogeny of Listeria monocytogenes

Directory of Open Access Journals (Sweden)

Clémentine Henri

2017-11-01

Full Text Available Background/objectives: Whole genome sequencing (WGS has proven to be a powerful subtyping tool for foodborne pathogenic bacteria like L. monocytogenes. The interests of genome-scale analysis for national surveillance, outbreak detection or source tracking has been largely documented. The genomic data however can be exploited with many different bioinformatics methods like single nucleotide polymorphism (SNP, core-genome multi locus sequence typing (cgMLST, whole-genome multi locus sequence typing (wgMLST or multi locus predicted protein sequence typing (MLPPST on either core-genome (cgMLPPST or pan-genome (wgMLPPST. Currently, there are little comparisons studies of these different analytical approaches. Our objective was to assess and compare different genomic methods that can be implemented in order to cluster isolates of L. monocytogenes.Methods: The clustering methods were evaluated on a collection of 207 L. monocytogenes genomes of food origin representative of the genetic diversity of the Anses collection. The trees were then compared using robust statistical analyses.Results: The backward comparability between conventional typing methods and genomic methods revealed a near-perfect concordance. The importance of selecting a proper reference when calling SNPs was highlighted, although distances between strains remained identical. The analysis also revealed that the topology of the phylogenetic trees between wgMLST and cgMLST were remarkably similar. The comparison between SNP and cgMLST or SNP and wgMLST approaches showed that the topologies of phylogenic trees were statistically similar with an almost equivalent clustering.Conclusion: Our study revealed high concordance between wgMLST, cgMLST, and SNP approaches which are all suitable for typing of L. monocytogenes. The comparable clustering is an important observation considering that the two approaches have been variously implemented among reference laboratories.

Comparative inference of duplicated genes produced by polyploidization in soybean genome.

Science.gov (United States)

Yang, Yanmei; Wang, Jinpeng; Di, Jianyong

2013-01-01

Soybean (Glycine max) is one of the most important crop plants for providing protein and oil. It is important to investigate soybean genome for its economic and scientific value. Polyploidy is a widespread and recursive phenomenon during plant evolution, and it could generate massive duplicated genes which is an important resource for genetic innovation. Improved sequence alignment criteria and statistical analysis are used to identify and characterize duplicated genes produced by polyploidization in soybean. Based on the collinearity method, duplicated genes by whole genome duplication account for 70.3% in soybean. From the statistical analysis of the molecular distances between duplicated genes, our study indicates that the whole genome duplication event occurred more than once in the genome evolution of soybean, which is often distributed near the ends of chromosomes.

My sister's keeper?: genomic research and the identifiability of siblings

Directory of Open Access Journals (Sweden)

Kohane Isaac S

2008-07-01

Full Text Available Abstract Background Genomic sequencing of SNPs is increasingly prevalent, though the amount of familial information these data contain has not been quantified. Methods We provide a framework for measuring the risk to siblings of a patient's SNP genotype disclosure, and demonstrate that sibling SNP genotypes can be inferred with substantial accuracy. Results Extending this inference technique, we determine that a very low number of matches at commonly varying SNPs is sufficient to confirm sib-ship, demonstrating that published sequence data can reliably be used to derive sibling identities. Using HapMap trio data, at SNPs where one child is homozygotic major, with a minor allele frequency ≤ 0.20, (N = 452684, 65.1% we achieve 91.9% inference accuracy for sibling genotypes. Conclusion These findings demonstrate that substantial discrimination and privacy risks arise from use of inferred familial genomic data.

The genomic organization of plant pathogenicity in Fusarium species

NARCIS (Netherlands)

Rep, M.; Kistler, H.C.

2010-01-01

Comparative genomics is a powerful tool to infer the molecular basis of fungal pathogenicity and its evolution by identifying differences in gene content and genomic organization between fungi with different hosts or modes of infection. Through comparative analysis, pathogenicity-related chromosomes

The ecology of pelagic freshwater methylotrophs assessed by a high-resolution monitoring and isolation campaign

Czech Academy of Sciences Publication Activity Database

Salcher, Michaela M.; Neuenschwander, S. M.; Posch, T.; Pernthaler, J.

2015-01-01

Roč. 9, č. 11 (2015), s. 2442-2453 ISSN 1751-7362 Institutional support: RVO:60077344 Keywords : in-situ hybridization * genome sequence * bacterioplankton populations Subject RIV: EE - Microbiology, Virology Impact factor: 9.328, year: 2015

fastBMA: scalable network inference and transitive reduction.

Science.gov (United States)

Hung, Ling-Hong; Shi, Kaiyuan; Wu, Migao; Young, William Chad; Raftery, Adrian E; Yeung, Ka Yee

2017-10-01

Inferring genetic networks from genome-wide expression data is extremely demanding computationally. We have developed fastBMA, a distributed, parallel, and scalable implementation of Bayesian model averaging (BMA) for this purpose. fastBMA also includes a computationally efficient module for eliminating redundant indirect edges in the network by mapping the transitive reduction to an easily solved shortest-path problem. We evaluated the performance of fastBMA on synthetic data and experimental genome-wide time series yeast and human datasets. When using a single CPU core, fastBMA is up to 100 times faster than the next fastest method, LASSO, with increased accuracy. It is a memory-efficient, parallel, and distributed application that scales to human genome-wide expression data. A 10 000-gene regulation network can be obtained in a matter of hours using a 32-core cloud cluster (2 nodes of 16 cores). fastBMA is a significant improvement over its predecessor ScanBMA. It is more accurate and orders of magnitude faster than other fast network inference methods such as the 1 based on LASSO. The improved scalability allows it to calculate networks from genome scale data in a reasonable time frame. The transitive reduction method can improve accuracy in denser networks. fastBMA is available as code (M.I.T. license) from GitHub (https://github.com/lhhunghimself/fastBMA), as part of the updated networkBMA Bioconductor package (https://www.bioconductor.org/packages/release/bioc/html/networkBMA.html) and as ready-to-deploy Docker images (https://hub.docker.com/r/biodepot/fastbma/). © The Authors 2017. Published by Oxford University Press.

Real-Time Pathogen Detection in the Era of Whole-Genome Sequencing and Big Data: Comparison of k-mer and Site-Based Methods for Inferring the Genetic Distances among Tens of Thousands of Salmonella Samples.

Science.gov (United States)

Pettengill, James B; Pightling, Arthur W; Baugher, Joseph D; Rand, Hugh; Strain, Errol

2016-01-01

The adoption of whole-genome sequencing within the public health realm for molecular characterization of bacterial pathogens has been followed by an increased emphasis on real-time detection of emerging outbreaks (e.g., food-borne Salmonellosis). In turn, large databases of whole-genome sequence data are being populated. These databases currently contain tens of thousands of samples and are expected to grow to hundreds of thousands within a few years. For these databases to be of optimal use one must be able to quickly interrogate them to accurately determine the genetic distances among a set of samples. Being able to do so is challenging due to both biological (evolutionary diverse samples) and computational (petabytes of sequence data) issues. We evaluated seven measures of genetic distance, which were estimated from either k-mer profiles (Jaccard, Euclidean, Manhattan, Mash Jaccard, and Mash distances) or nucleotide sites (NUCmer and an extended multi-locus sequence typing (MLST) scheme). When analyzing empirical data (whole-genome sequence data from 18,997 Salmonella isolates) there are features (e.g., genomic, assembly, and contamination) that cause distances inferred from k-mer profiles, which treat absent data as informative, to fail to accurately capture the distance between samples when compared to distances inferred from differences in nucleotide sites. Thus, site-based distances, like NUCmer and extended MLST, are superior in performance, but accessing the computing resources necessary to perform them may be challenging when analyzing large databases.

Real-Time Pathogen Detection in the Era of Whole-Genome Sequencing and Big Data: Comparison of k-mer and Site-Based Methods for Inferring the Genetic Distances among Tens of Thousands of Salmonella Samples.

Directory of Open Access Journals (Sweden)

James B Pettengill

Full Text Available The adoption of whole-genome sequencing within the public health realm for molecular characterization of bacterial pathogens has been followed by an increased emphasis on real-time detection of emerging outbreaks (e.g., food-borne Salmonellosis. In turn, large databases of whole-genome sequence data are being populated. These databases currently contain tens of thousands of samples and are expected to grow to hundreds of thousands within a few years. For these databases to be of optimal use one must be able to quickly interrogate them to accurately determine the genetic distances among a set of samples. Being able to do so is challenging due to both biological (evolutionary diverse samples and computational (petabytes of sequence data issues. We evaluated seven measures of genetic distance, which were estimated from either k-mer profiles (Jaccard, Euclidean, Manhattan, Mash Jaccard, and Mash distances or nucleotide sites (NUCmer and an extended multi-locus sequence typing (MLST scheme. When analyzing empirical data (whole-genome sequence data from 18,997 Salmonella isolates there are features (e.g., genomic, assembly, and contamination that cause distances inferred from k-mer profiles, which treat absent data as informative, to fail to accurately capture the distance between samples when compared to distances inferred from differences in nucleotide sites. Thus, site-based distances, like NUCmer and extended MLST, are superior in performance, but accessing the computing resources necessary to perform them may be challenging when analyzing large databases.

seXY: a tool for sex inference from genotype arrays.

Science.gov (United States)

Qian, David C; Busam, Jonathan A; Xiao, Xiangjun; O'Mara, Tracy A; Eeles, Rosalind A; Schumacher, Frederick R; Phelan, Catherine M; Amos, Christopher I

2017-02-15

Checking concordance between reported sex and genotype-inferred sex is a crucial quality control measure in genome-wide association studies (GWAS). However, limited insights exist regarding the true accuracy of software that infer sex from genotype array data. We present seXY, a logistic regression model trained on both X chromosome heterozygosity and Y chromosome missingness, that consistently demonstrated >99.5% sex inference accuracy in cross-validation for 889 males and 5,361 females enrolled in prostate cancer and ovarian cancer GWAS. Compared to PLINK, one of the most popular tools for sex inference in GWAS that assesses only X chromosome heterozygosity, seXY achieved marginally better male classification and 3% more accurate female classification. https://github.com/Christopher-Amos-Lab/seXY. Christopher.I.Amos@dartmouth.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

On the Relationship between Pollen Size and Genome Size

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Charles A. Knight

2010-01-01

Full Text Available Here we test whether genome size is a predictor of pollen size. If it were, inferences of ancient genome size would be possible using the abundant paleo-palynolgical record. We performed regression analyses across 464 species of pollen width and genome size. We found a significant positive trend. However, regression analysis using phylogentically independent contrasts did not support the correlated evolution of these traits. Instead, a large split between angiosperms and gymnosperms for both pollen width and genome size was revealed. Sister taxa were not more likely to show a positive contrast when compared to deeper nodes. However, significantly more congeneric species had a positive trend than expected by chance. These results may reflect the strong selection pressure for pollen to be small. Also, because pollen grains are not metabolically active when measured, their biology is different than other cells which have been shown to be strongly related to genome size, such as guard cells. Our findings contrast with previously published research. It was our hope that pollen size could be used as a proxy for inferring the genome size of ancient species. However, our results suggest pollen is not a good candidate for such endeavors.

The hidden seasonality of the rare biosphere in coastal marine bacterioplankton

KAUST Repository

Alonso-Sáez, Laura

2015-04-08

Summary: Rare microbial taxa are increasingly recognized to play key ecological roles, but knowledge of their spatio-temporal dynamics is lacking. In a time-series study in coastal waters, we detected 83 bacterial lineages with significant seasonality, including environmentally relevant taxa where little ecological information was available. For example, Verrucomicrobia had recurrent maxima in summer, while the Flavobacteria NS4, NS5 and NS2b clades had contrasting seasonal niches. Among the seasonal taxa, only 4 were abundant and persistent, 20 cycled between rare and abundant and, remarkably, most of them (59) were always rare (contributing <1% of total reads). We thus demonstrate that seasonal patterns in marine bacterioplankton are largely driven by lineages that never sustain abundant populations. A fewer number of rare taxa (20) also produced episodic \\'blooms\\', and these events were highly synchronized, mostly occurring on a single month. The recurrent seasonal growth and loss of rare bacteria opens new perspectives on the temporal dynamics of the rare biosphere, hitherto mainly characterized by dormancy and episodes of \\'boom and bust\\', as envisioned by the seed-bank hypothesis. The predictable patterns of seasonal reoccurrence are relevant for understanding the ecology of rare bacteria, which may include key players for the functioning of marine ecosystems. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.

De-anonymizing Genomic Databases Using Phenotypic Traits

Directory of Open Access Journals (Sweden)

Humbert Mathias

2015-06-01

Full Text Available People increasingly have their genomes sequenced and some of them share their genomic data online. They do so for various purposes, including to find relatives and to help advance genomic research. An individual’s genome carries very sensitive, private information such as its owner’s susceptibility to diseases, which could be used for discrimination. Therefore, genomic databases are often anonymized. However, an individual’s genotype is also linked to visible phenotypic traits, such as eye or hair color, which can be used to re-identify users in anonymized public genomic databases, thus raising severe privacy issues. For instance, an adversary can identify a target’s genome using known her phenotypic traits and subsequently infer her susceptibility to Alzheimer’s disease. In this paper, we quantify, based on various phenotypic traits, the extent of this threat in several scenarios by implementing de-anonymization attacks on a genomic database of OpenSNP users sequenced by 23andMe. Our experimental results show that the proportion of correct matches reaches 23% with a supervised approach in a database of 50 participants. Our approach outperforms the baseline by a factor of four, in terms of the proportion of correct matches, in most scenarios. We also evaluate the adversary’s ability to predict individuals’ predisposition to Alzheimer’s disease, and we observe that the inference error can be halved compared to the baseline. We also analyze the effect of the number of known phenotypic traits on the success rate of the attack. As progress is made in genomic research, especially for genotype-phenotype associations, the threat presented in this paper will become more serious.

Using Genetic Distance to Infer the Accuracy of Genomic Prediction.

Directory of Open Access Journals (Sweden)

Marco Scutari

2016-09-01

Full Text Available The prediction of phenotypic traits using high-density genomic data has many applications such as the selection of plants and animals of commercial interest; and it is expected to play an increasing role in medical diagnostics. Statistical models used for this task are usually tested using cross-validation, which implicitly assumes that new individuals (whose phenotypes we would like to predict originate from the same population the genomic prediction model is trained on. In this paper we propose an approach based on clustering and resampling to investigate the effect of increasing genetic distance between training and target populations when predicting quantitative traits. This is important for plant and animal genetics, where genomic selection programs rely on the precision of predictions in future rounds of breeding. Therefore, estimating how quickly predictive accuracy decays is important in deciding which training population to use and how often the model has to be recalibrated. We find that the correlation between true and predicted values decays approximately linearly with respect to either FST or mean kinship between the training and the target populations. We illustrate this relationship using simulations and a collection of data sets from mice, wheat and human genetics.

Rapid genome reshaping by multiple-gene loss after whole-genome duplication in teleost fish suggested by mathematical modeling

Science.gov (United States)

Sato, Yukuto; Tsukamoto, Katsumi; Nishida, Mutsumi

2015-01-01

Whole-genome duplication (WGD) is believed to be a significant source of major evolutionary innovation. Redundant genes resulting from WGD are thought to be lost or acquire new functions. However, the rates of gene loss and thus temporal process of genome reshaping after WGD remain unclear. The WGD shared by all teleost fish, one-half of all jawed vertebrates, was more recent than the two ancient WGDs that occurred before the origin of jawed vertebrates, and thus lends itself to analysis of gene loss and genome reshaping. Using a newly developed orthology identification pipeline, we inferred the post–teleost-specific WGD evolutionary histories of 6,892 protein-coding genes from nine phylogenetically representative teleost genomes on a time-calibrated tree. We found that rapid gene loss did occur in the first 60 My, with a loss of more than 70–80% of duplicated genes, and produced similar genomic gene arrangements within teleosts in that relatively short time. Mathematical modeling suggests that rapid gene loss occurred mainly by events involving simultaneous loss of multiple genes. We found that the subsequent 250 My were characterized by slow and steady loss of individual genes. Our pipeline also identified about 1,100 shared single-copy genes that are inferred to have become singletons before the divergence of clupeocephalan teleosts. Therefore, our comparative genome analysis suggests that rapid gene loss just after the WGD reshaped teleost genomes before the major divergence, and provides a useful set of marker genes for future phylogenetic analysis. PMID:26578810

Genomic Heritability: What Is It?

DEFF Research Database (Denmark)

de los Campos, Gustavo; Sorensen, Daniel; Gianola, Daniel

2015-01-01

Whole-genome regression methods are being increasingly used for the analysis and prediction of complex traits and diseases. In human genetics, these methods are commonly used for inferences about genetic parameters, such as the amount of genetic variance among individuals or the proportion of phe...

msCentipede: Modeling Heterogeneity across Genomic Sites and Replicates Improves Accuracy in the Inference of Transcription Factor Binding.

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Anil Raj

Full Text Available Understanding global gene regulation depends critically on accurate annotation of regulatory elements that are functional in a given cell type. CENTIPEDE, a powerful, probabilistic framework for identifying transcription factor binding sites from tissue-specific DNase I cleavage patterns and genomic sequence content, leverages the hypersensitivity of factor-bound chromatin and the information in the DNase I spatial cleavage profile characteristic of each DNA binding protein to accurately infer functional factor binding sites. However, the model for the spatial profile in this framework fails to account for the substantial variation in the DNase I cleavage profiles across different binding sites. Neither does it account for variation in the profiles at the same binding site across multiple replicate DNase I experiments, which are increasingly available. In this work, we introduce new methods, based on multi-scale models for inhomogeneous Poisson processes, to account for such variation in DNase I cleavage patterns both within and across binding sites. These models account for the spatial structure in the heterogeneity in DNase I cleavage patterns for each factor. Using DNase-seq measurements assayed in a lymphoblastoid cell line, we demonstrate the improved performance of this model for several transcription factors by comparing against the Chip-seq peaks for those factors. Finally, we explore the effects of DNase I sequence bias on inference of factor binding using a simple extension to our framework that allows for a more flexible background model. The proposed model can also be easily applied to paired-end ATAC-seq and DNase-seq data. msCentipede, a Python implementation of our algorithm, is available at http://rajanil.github.io/msCentipede.

msCentipede: Modeling Heterogeneity across Genomic Sites and Replicates Improves Accuracy in the Inference of Transcription Factor Binding.

Science.gov (United States)

Raj, Anil; Shim, Heejung; Gilad, Yoav; Pritchard, Jonathan K; Stephens, Matthew

2015-01-01

Understanding global gene regulation depends critically on accurate annotation of regulatory elements that are functional in a given cell type. CENTIPEDE, a powerful, probabilistic framework for identifying transcription factor binding sites from tissue-specific DNase I cleavage patterns and genomic sequence content, leverages the hypersensitivity of factor-bound chromatin and the information in the DNase I spatial cleavage profile characteristic of each DNA binding protein to accurately infer functional factor binding sites. However, the model for the spatial profile in this framework fails to account for the substantial variation in the DNase I cleavage profiles across different binding sites. Neither does it account for variation in the profiles at the same binding site across multiple replicate DNase I experiments, which are increasingly available. In this work, we introduce new methods, based on multi-scale models for inhomogeneous Poisson processes, to account for such variation in DNase I cleavage patterns both within and across binding sites. These models account for the spatial structure in the heterogeneity in DNase I cleavage patterns for each factor. Using DNase-seq measurements assayed in a lymphoblastoid cell line, we demonstrate the improved performance of this model for several transcription factors by comparing against the Chip-seq peaks for those factors. Finally, we explore the effects of DNase I sequence bias on inference of factor binding using a simple extension to our framework that allows for a more flexible background model. The proposed model can also be easily applied to paired-end ATAC-seq and DNase-seq data. msCentipede, a Python implementation of our algorithm, is available at http://rajanil.github.io/msCentipede.

REGEN: Ancestral Genome Reconstruction for Bacteria.

Science.gov (United States)

Yang, Kuan; Heath, Lenwood S; Setubal, João C

2012-07-18

Ancestral genome reconstruction can be understood as a phylogenetic study with more details than a traditional phylogenetic tree reconstruction. We present a new computational system called REGEN for ancestral bacterial genome reconstruction at both the gene and replicon levels. REGEN reconstructs gene content, contiguous gene runs, and replicon structure for each ancestral genome. Along each branch of the phylogenetic tree, REGEN infers evolutionary events, including gene creation and deletion and replicon fission and fusion. The reconstruction can be performed by either a maximum parsimony or a maximum likelihood method. Gene content reconstruction is based on the concept of neighboring gene pairs. REGEN was designed to be used with any set of genomes that are sufficiently related, which will usually be the case for bacteria within the same taxonomic order. We evaluated REGEN using simulated genomes and genomes in the Rhizobiales order.

Comparative analyses of plastid genomes from fourteen Cornales species: inferences for phylogenetic relationships and genome evolution.

Science.gov (United States)

Fu, Chao-Nan; Li, Hong-Tao; Milne, Richard; Zhang, Ting; Ma, Peng-Fei; Yang, Jing; Li, De-Zhu; Gao, Lian-Ming

2017-12-08

The Cornales is the basal lineage of the asterids, the largest angiosperm clade. Phylogenetic relationships within the order were previously not fully resolved. Fifteen plastid genomes representing 14 species, ten genera and seven families of Cornales were newly sequenced for comparative analyses of genome features, evolution, and phylogenomics based on different partitioning schemes and filtering strategies. All plastomes of the 14 Cornales species had the typical quadripartite structure with a genome size ranging from 156,567 bp to 158,715 bp, which included two inverted repeats (25,859-26,451 bp) separated by a large single-copy region (86,089-87,835 bp) and a small single-copy region (18,250-18,856 bp) region. These plastomes encoded the same set of 114 unique genes including 31 transfer RNA, 4 ribosomal RNA and 79 coding genes, with an identical gene order across all examined Cornales species. Two genes (rpl22 and ycf15) contained premature stop codons in seven and five species respectively. The phylogenetic relationships among all sampled species were fully resolved with maximum support. Different filtering strategies (none, light and strict) of sequence alignment did not have an effect on these relationships. The topology recovered from coding and noncoding data sets was the same as for the whole plastome, regardless of filtering strategy. Moreover, mutational hotspots and highly informative regions were identified. Phylogenetic relationships among families and intergeneric relationships within family of Cornales were well resolved. Different filtering strategies and partitioning schemes do not influence the relationships. Plastid genomes have great potential to resolve deep phylogenetic relationships of plants.

Combining genetical genomics and bulked segregant analysis differential expression: an approach to gene localization

NARCIS (Netherlands)

Chen, Xinwei; Hedley, P.E.; Morris, J.; Liu, Hui; Niks, R.E.; Waugh, R.

2011-01-01

Positional gene isolation in unsequenced species generally requires either a reference genome sequence or an inference of gene content based on conservation of synteny with a genomic model. In the large unsequenced genomes of the Triticeae cereals the latter, i.e. conservation of synteny with the

Characterization and functional inferences of a genome-wide DNA methylation profile in the loin ( muscle of swine

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Woonsu Kim

2018-01-01

Full Text Available Objective DNA methylation plays a major role in regulating the expression of genes related to traits of economic interest (e.g., weight gain in livestock animals. This study characterized and investigated the functional inferences of genome-wide DNA methylome in the loin (longissimus dorsi muscle (LDM of swine. Methods A total of 8.99 Gb methylated DNA immunoprecipitation sequence data were obtained from LDM samples of eight Duroc pigs (four pairs of littermates. The reference pig genome was annotated with 78.5% of the raw reads. A total of 33,506 putative methylated regions (PMR were identified from methylated regions that overlapped at least two samples. Results Of these, only 3.1% were commonly observed in all eight samples. DNA methylation patterns between two littermates were as diverse as between unrelated individuals (p = 0.47, indicating that maternal genetic effects have little influence on the variation in DNA methylation of porcine LDM. The highest density of PMR was observed on chromosome 10. A major proportion (47.7% of PMR was present in the repeat regions, followed by introns (21.5%. The highest conservation of PMR was found in CpG islands (12.1%. These results show an important role for DNA methylation in species- and tissue-specific regulation of gene expression. PMR were also significantly related to muscular cell development, cell-cell communication, cellular integrity and transport, and nutrient metabolism. Conclusion This study indicated the biased distribution and functional role of DNA methylation in gene expression of porcine LDM. DNA methylation was related to cell development, cell-cell communication, cellular integrity and transport, and nutrient metabolism (e.g., insulin signaling pathways. Nutritional and environmental management may have a significant impact on the variation in DNA methylation of porcine LDM.

REGEN: Ancestral Genome Reconstruction for Bacteria

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João C. Setubal

2012-07-01

Full Text Available Ancestral genome reconstruction can be understood as a phylogenetic study with more details than a traditional phylogenetic tree reconstruction. We present a new computational system called REGEN for ancestral bacterial genome reconstruction at both the gene and replicon levels. REGEN reconstructs gene content, contiguous gene runs, and replicon structure for each ancestral genome. Along each branch of the phylogenetic tree, REGEN infers evolutionary events, including gene creation and deletion and replicon fission and fusion. The reconstruction can be performed by either a maximum parsimony or a maximum likelihood method. Gene content reconstruction is based on the concept of neighboring gene pairs. REGEN was designed to be used with any set of genomes that are sufficiently related, which will usually be the case for bacteria within the same taxonomic order. We evaluated REGEN using simulated genomes and genomes in the Rhizobiales order.

A new fast method for inferring multiple consensus trees using k-medoids.

Science.gov (United States)

Tahiri, Nadia; Willems, Matthieu; Makarenkov, Vladimir

2018-04-05

Gene trees carry important information about specific evolutionary patterns which characterize the evolution of the corresponding gene families. However, a reliable species consensus tree cannot be inferred from a multiple sequence alignment of a single gene family or from the concatenation of alignments corresponding to gene families having different evolutionary histories. These evolutionary histories can be quite different due to horizontal transfer events or to ancient gene duplications which cause the emergence of paralogs within a genome. Many methods have been proposed to infer a single consensus tree from a collection of gene trees. Still, the application of these tree merging methods can lead to the loss of specific evolutionary patterns which characterize some gene families or some groups of gene families. Thus, the problem of inferring multiple consensus trees from a given set of gene trees becomes relevant. We describe a new fast method for inferring multiple consensus trees from a given set of phylogenetic trees (i.e. additive trees or X-trees) defined on the same set of species (i.e. objects or taxa). The traditional consensus approach yields a single consensus tree. We use the popular k-medoids partitioning algorithm to divide a given set of trees into several clusters of trees. We propose novel versions of the well-known Silhouette and Caliński-Harabasz cluster validity indices that are adapted for tree clustering with k-medoids. The efficiency of the new method was assessed using both synthetic and real data, such as a well-known phylogenetic dataset consisting of 47 gene trees inferred for 14 archaeal organisms. The method described here allows inference of multiple consensus trees from a given set of gene trees. It can be used to identify groups of gene trees having similar intragroup and different intergroup evolutionary histories. The main advantage of our method is that it is much faster than the existing tree clustering approaches, while

Phylogenomic Analysis and Dynamic Evolution of Chloroplast Genomes in Salicaceae

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Yuan Huang

2017-06-01

Full Text Available Chloroplast genomes of plants are highly conserved in both gene order and gene content. Analysis of the whole chloroplast genome is known to provide much more informative DNA sites and thus generates high resolution for plant phylogenies. Here, we report the complete chloroplast genomes of three Salix species in family Salicaceae. Phylogeny of Salicaceae inferred from complete chloroplast genomes is generally consistent with previous studies but resolved with higher statistical support. Incongruences of phylogeny, however, are observed in genus Populus, which most likely results from homoplasy. By comparing three Salix chloroplast genomes with the published chloroplast genomes of other Salicaceae species, we demonstrate that the synteny and length of chloroplast genomes in Salicaceae are highly conserved but experienced dynamic evolution among species. We identify seven positively selected chloroplast genes in Salicaceae, which might be related to the adaptive evolution of Salicaceae species. Comparative chloroplast genome analysis within the family also indicates that some chloroplast genes are lost or became pseudogenes, infer that the chloroplast genes horizontally transferred to the nucleus genome. Based on the complete nucleus genome sequences from two Salicaceae species, we remarkably identify that the entire chloroplast genome is indeed transferred and integrated to the nucleus genome in the individual of the reference genome of P. trichocarpa at least once. This observation, along with presence of the large nuclear plastid DNA (NUPTs and NUPTs-containing multiple chloroplast genes in their original order in the chloroplast genome, favors the DNA-mediated hypothesis of organelle to nucleus DNA transfer. Overall, the phylogenomic analysis using chloroplast complete genomes clearly elucidates the phylogeny of Salicaceae. The identification of positively selected chloroplast genes and dynamic chloroplast-to-nucleus gene transfers in

Co-Inheritance Analysis within the Domains of Life Substantially Improves Network Inference by Phylogenetic Profiling.

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Junha Shin

Full Text Available Phylogenetic profiling, a network inference method based on gene inheritance profiles, has been widely used to construct functional gene networks in microbes. However, its utility for network inference in higher eukaryotes has been limited. An improved algorithm with an in-depth understanding of pathway evolution may overcome this limitation. In this study, we investigated the effects of taxonomic structures on co-inheritance analysis using 2,144 reference species in four query species: Escherichia coli, Saccharomyces cerevisiae, Arabidopsis thaliana, and Homo sapiens. We observed three clusters of reference species based on a principal component analysis of the phylogenetic profiles, which correspond to the three domains of life-Archaea, Bacteria, and Eukaryota-suggesting that pathways inherit primarily within specific domains or lower-ranked taxonomic groups during speciation. Hence, the co-inheritance pattern within a taxonomic group may be eroded by confounding inheritance patterns from irrelevant taxonomic groups. We demonstrated that co-inheritance analysis within domains substantially improved network inference not only in microbe species but also in the higher eukaryotes, including humans. Although we observed two sub-domain clusters of reference species within Eukaryota, co-inheritance analysis within these sub-domain taxonomic groups only marginally improved network inference. Therefore, we conclude that co-inheritance analysis within domains is the optimal approach to network inference with the given reference species. The construction of a series of human gene networks with increasing sample sizes of the reference species for each domain revealed that the size of the high-accuracy networks increased as additional reference species genomes were included, suggesting that within-domain co-inheritance analysis will continue to expand human gene networks as genomes of additional species are sequenced. Taken together, we propose that co

Diagnostic SNPs for inferring population structure in American mink (Neovison vison) identified through RAD sequencing

DEFF Research Database (Denmark)

2015-01-01

Data from: "Diagnostic SNPs for inferring population structure in American mink (Neovison vison) identified through RAD sequencing" in Genomic Resources Notes accepted 1 October 2014 to 30 November 2014....

From the Beauty of Genomic Landscapes to the Strength of Transcriptional Mechanisms.

Science.gov (United States)

Natoli, Gioacchino

2016-03-24

Genomic analyses are commonly used to infer trends and broad rules underlying transcriptional control. The innovative approach by Tong et al. to interrogate genomic datasets allows extracting mechanistic information on the specific regulation of individual genes. Copyright © 2016 Elsevier Inc. All rights reserved.

Recent and ongoing selection in the human genome

DEFF Research Database (Denmark)

Nielsen, Rasmus; Hellmann, Ines; Hubisz, Melissa

2007-01-01

The recent availability of genome-scale genotyping data has led to the identification of regions of the human genome that seem to have been targeted by selection. These findings have increased our understanding of the evolutionary forces that affect the human genome, have augmented our knowledge...... of gene function and promise to increase our understanding of the genetic basis of disease. However, inferences of selection are challenged by several confounding factors, especially the complex demographic history of human populations, and concordance between studies is variable. Although such studies...

Inferring species trees from incongruent multi-copy gene trees using the Robinson-Foulds distance

Science.gov (United States)

2013-01-01

Background Constructing species trees from multi-copy gene trees remains a challenging problem in phylogenetics. One difficulty is that the underlying genes can be incongruent due to evolutionary processes such as gene duplication and loss, deep coalescence, or lateral gene transfer. Gene tree estimation errors may further exacerbate the difficulties of species tree estimation. Results We present a new approach for inferring species trees from incongruent multi-copy gene trees that is based on a generalization of the Robinson-Foulds (RF) distance measure to multi-labeled trees (mul-trees). We prove that it is NP-hard to compute the RF distance between two mul-trees; however, it is easy to calculate this distance between a mul-tree and a singly-labeled species tree. Motivated by this, we formulate the RF problem for mul-trees (MulRF) as follows: Given a collection of multi-copy gene trees, find a singly-labeled species tree that minimizes the total RF distance from the input mul-trees. We develop and implement a fast SPR-based heuristic algorithm for the NP-hard MulRF problem. We compare the performance of the MulRF method (available at http://genome.cs.iastate.edu/CBL/MulRF/) with several gene tree parsimony approaches using gene tree simulations that incorporate gene tree error, gene duplications and losses, and/or lateral transfer. The MulRF method produces more accurate species trees than gene tree parsimony approaches. We also demonstrate that the MulRF method infers in minutes a credible plant species tree from a collection of nearly 2,000 gene trees. Conclusions Our new phylogenetic inference method, based on a generalized RF distance, makes it possible to quickly estimate species trees from large genomic data sets. Since the MulRF method, unlike gene tree parsimony, is based on a generic tree distance measure, it is appealing for analyses of genomic data sets, in which many processes such as deep coalescence, recombination, gene duplication and losses as

Molecular phylogeny of Systellognatha (Plecoptera: Arctoperlaria) inferred from mitochondrial genome sequences.

Science.gov (United States)

Chen, Zhi-Teng; Zhao, Meng-Yuan; Xu, Cheng; Du, Yu-Zhou

2018-05-01

The infraorder Systellognatha is the most species-rich clade in the insect order Plecoptera and includes six families in two superfamilies: Pteronarcyoidea (Pteronarcyidae, Peltoperlidae, and Styloperlidae) and Perloidea (Perlidae, Perlodidae, and Chloroperlidae). To resolve the debatable phylogeny of Systellognatha, we carried out the first mitochondrial phylogenetic analysis covering all the six families, including three newly sequenced mitogenomes from two families (Perlodidae and Peltoperlidae) and 15 published mitogenomes. The three newly reported mitogenomes share conserved mitogenomic features with other sequenced stoneflies. For phylogenetic analyses, we assembled five datasets with two inference methods to assess their influence on topology and nodal support within Systellognatha. The results indicated that inclusion of the third codon positions of PCGs, exclusion of rRNA genes, the use of nucleotide datasets and Bayesian inference could improve the phylogenetic reconstruction of Systellognatha. The monophyly of Perloidea was supported in the mitochondrial phylogeny, but Pteronarcyoidea was recovered as paraphyletic and remained controversial. In this mitochondrial phylogenetic study, the relationships within Systellognatha were recovered as (((Perlidae + (Perlodidae + Chloroperlidae)) + (Pteronarcyidae + Styloperlidae)) + Peltoperlidae). Copyright © 2018 Elsevier B.V. All rights reserved.

Using genomic data to unravel the root of the placental mammal phylogeny.

Science.gov (United States)

Murphy, William J; Pringle, Thomas H; Crider, Tess A; Springer, Mark S; Miller, Webb

2007-04-01

The phylogeny of placental mammals is a critical framework for choosing future genome sequencing targets and for resolving the ancestral mammalian genome at the nucleotide level. Despite considerable recent progress defining superordinal relationships, several branches remain poorly resolved, including the root of the placental tree. Here we analyzed the genome sequence assemblies of human, armadillo, elephant, and opossum to identify informative coding indels that would serve as rare genomic changes to infer early events in placental mammal phylogeny. We also expanded our species sampling by including sequence data from >30 ongoing genome projects, followed by PCR and sequencing validation of each indel in additional taxa. Our data provide support for a sister-group relationship between Afrotheria and Xenarthra (the Atlantogenata hypothesis), which is in turn the sister-taxon to Boreoeutheria. We failed to recover any indels in support of a basal position for Xenarthra (Epitheria), which is suggested by morphology and a recent retroposon analysis, or a hypothesis with Afrotheria basal (Exafricoplacentalia), which is favored by phylogenetic analysis of large nuclear gene data sets. In addition, we identified two retroposon insertions that also support Atlantogenata and none for the alternative hypotheses. A revised molecular timescale based on these phylogenetic inferences suggests Afrotheria and Xenarthra diverged from other placental mammals approximately 103 (95-114) million years ago. We discuss the impacts of this topology on earlier phylogenetic reconstructions and repeat-based inferences of phylogeny.

Permanent draft genomes of the Rhodopirellula maiorica strain SM1.

Science.gov (United States)

Richter, Michael; Richter-Heitmann, Tim; Klindworth, Anna; Wegner, Carl-Eric; Frank, Carsten S; Harder, Jens; Glöckner, Frank Oliver

2014-02-01

The genome of Rhodopirellula maiorica strain SM1 was sequenced as a permanent draft to complement the full genome sequence of the type strain Rhodopirellula baltica SH1(T). This isolate is part of a larger study to infer the biogeography of Rhodopirellula species in European marine waters, as well as to amend the genus description of R. baltica. This genomics resource article is the fifth of a series of five publications reporting in total eight new permanent daft genomes of Rhodopirellula species. Copyright © 2013 Elsevier B.V. All rights reserved.

Demographic inferences from large-scale NGS data

DEFF Research Database (Denmark)

Pedersen, Casper-Emil Tingskov

.g. human genetics. In this thesis, the three papers presented demonstrate the advantages of NGS data in the framework of population genetics for elucidating demographic inferences, important for understanding conservation efforts, selection and mutational burdens. In the first whole-genome study...... that the demographic history of the Inuit is the most extreme in terms of population size, of any human population. We identify a slight increase in the number of deleterious alleles because of this demographic history and support our results using simulations. We use this to show that the reduction in population size...

A Genome-Wide Landscape of Retrocopies in Primate Genomes.

Science.gov (United States)

Navarro, Fábio C P; Galante, Pedro A F

2015-07-29

Gene duplication is a key factor contributing to phenotype diversity across and within species. Although the availability of complete genomes has led to the extensive study of genomic duplications, the dynamics and variability of gene duplications mediated by retrotransposition are not well understood. Here, we predict mRNA retrotransposition and use comparative genomics to investigate their origin and variability across primates. Analyzing seven anthropoid primate genomes, we found a similar number of mRNA retrotranspositions (∼7,500 retrocopies) in Catarrhini (Old Word Monkeys, including humans), but a surprising large number of retrocopies (∼10,000) in Platyrrhini (New World Monkeys), which may be a by-product of higher long interspersed nuclear element 1 activity in these genomes. By inferring retrocopy orthology, we dated most of the primate retrocopy origins, and estimated a decrease in the fixation rate in recent primate history, implying a smaller number of species-specific retrocopies. Moreover, using RNA-Seq data, we identified approximately 3,600 expressed retrocopies. As expected, most of these retrocopies are located near or within known genes, present tissue-specific and even species-specific expression patterns, and no expression correlation to their parental genes. Taken together, our results provide further evidence that mRNA retrotransposition is an active mechanism in primate evolution and suggest that retrocopies may not only introduce great genetic variability between lineages but also create a large reservoir of potentially functional new genomic loci in primate genomes. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Genomics-informed isolation and characterization of a symbiotic Nanoarchaeota system from a terrestrial geothermal environment.

Science.gov (United States)

Wurch, Louie; Giannone, Richard J; Belisle, Bernard S; Swift, Carolyn; Utturkar, Sagar; Hettich, Robert L; Reysenbach, Anna-Louise; Podar, Mircea

2016-07-05

Biological features can be inferred, based on genomic data, for many microbial lineages that remain uncultured. However, cultivation is important for characterizing an organism's physiology and testing its genome-encoded potential. Here we use single-cell genomics to infer cultivation conditions for the isolation of an ectosymbiotic Nanoarchaeota ('Nanopusillus acidilobi') and its host (Acidilobus, a crenarchaeote) from a terrestrial geothermal environment. The cells of 'Nanopusillus' are among the smallest known cellular organisms (100-300 nm). They appear to have a complete genetic information processing machinery, but lack almost all primary biosynthetic functions as well as respiration and ATP synthesis. Genomic and proteomic comparison with its distant relative, the marine Nanoarchaeum equitans illustrate an ancient, common evolutionary history of adaptation of the Nanoarchaeota to ectosymbiosis, so far unique among the Archaea.

Directed partial correlation: inferring large-scale gene regulatory network through induced topology disruptions.

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Yinyin Yuan

Full Text Available Inferring regulatory relationships among many genes based on their temporal variation in transcript abundance has been a popular research topic. Due to the nature of microarray experiments, classical tools for time series analysis lose power since the number of variables far exceeds the number of the samples. In this paper, we describe some of the existing multivariate inference techniques that are applicable to hundreds of variables and show the potential challenges for small-sample, large-scale data. We propose a directed partial correlation (DPC method as an efficient and effective solution to regulatory network inference using these data. Specifically for genomic data, the proposed method is designed to deal with large-scale datasets. It combines the efficiency of partial correlation for setting up network topology by testing conditional independence, and the concept of Granger causality to assess topology change with induced interruptions. The idea is that when a transcription factor is induced artificially within a gene network, the disruption of the network by the induction signifies a genes role in transcriptional regulation. The benchmarking results using GeneNetWeaver, the simulator for the DREAM challenges, provide strong evidence of the outstanding performance of the proposed DPC method. When applied to real biological data, the inferred starch metabolism network in Arabidopsis reveals many biologically meaningful network modules worthy of further investigation. These results collectively suggest DPC is a versatile tool for genomics research. The R package DPC is available for download (http://code.google.com/p/dpcnet/.

Genomic organization, annotation, and ligand-receptor inferences of chicken chemokines and chemokine receptor genes based on comparative genomics

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Sze Sing-Hoi

2005-03-01

Full Text Available Abstract Background Chemokines and their receptors play important roles in host defense, organogenesis, hematopoiesis, and neuronal communication. Forty-two chemokines and 19 cognate receptors have been found in the human genome. Prior to this report, only 11 chicken chemokines and 7 receptors had been reported. The objectives of this study were to systematically identify chicken chemokines and their cognate receptor genes in the chicken genome and to annotate these genes and ligand-receptor binding by a comparative genomics approach. Results Twenty-three chemokine and 14 chemokine receptor genes were identified in the chicken genome. All of the chicken chemokines contained a conserved CC, CXC, CX3C, or XC motif, whereas all the chemokine receptors had seven conserved transmembrane helices, four extracellular domains with a conserved cysteine, and a conserved DRYLAIV sequence in the second intracellular domain. The number of coding exons in these genes and the syntenies are highly conserved between human, mouse, and chicken although the amino acid sequence homologies are generally low between mammalian and chicken chemokines. Chicken genes were named with the systematic nomenclature used in humans and mice based on phylogeny, synteny, and sequence homology. Conclusion The independent nomenclature of chicken chemokines and chemokine receptors suggests that the chicken may have ligand-receptor pairings similar to mammals. All identified chicken chemokines and their cognate receptors were identified in the chicken genome except CCR9, whose ligand was not identified in this study. The organization of these genes suggests that there were a substantial number of these genes present before divergence between aves and mammals and more gene duplications of CC, CXC, CCR, and CXCR subfamilies in mammals than in aves after the divergence.

Intercoalescence time distribution of incomplete gene genealogies in temporally varying populations, and applications in population genetic inference.

Science.gov (United States)

Chen, Hua

2013-03-01

Tracing back to a specific time T in the past, the genealogy of a sample of haplotypes may not have reached their common ancestor and may leave m lineages extant. For such an incomplete genealogy truncated at a specific time T in the past, the distribution and expectation of the intercoalescence times conditional on T are derived in an exact form in this paper for populations of deterministically time-varying sizes, specifically, for populations growing exponentially. The derived intercoalescence time distribution can be integrated to the coalescent-based joint allele frequency spectrum (JAFS) theory, and is useful for population genetic inference from large-scale genomic data, without relying on computationally intensive approaches, such as importance sampling and Markov Chain Monte Carlo (MCMC) methods. The inference of several important parameters relying on this derived conditional distribution is demonstrated: quantifying population growth rate and onset time, and estimating the number of ancestral lineages at a specific ancient time. Simulation studies confirm validity of the derivation and statistical efficiency of the methods using the derived intercoalescence time distribution. Two examples of real data are given to show the inference of the population growth rate of a European sample from the NIEHS Environmental Genome Project, and the number of ancient lineages of 31 mitochondrial genomes from Tibetan populations. © 2013 Blackwell Publishing Ltd/University College London.

Genomic analyses inform on migration events during the peopling of Eurasia

OpenAIRE

Pagani, L; Lawson, DJ; Jagoda, E; Mörseburg, A; Eriksson, A; Mitt, M; Clemente, F; Hudjashov, G; Degiorgio, M; Saag, L; Wall, JD; Cardona, A; Mägi, R; Sayres, MAW; Kaewert, S

2016-01-01

© 2016 Macmillan Publishers Limited, part of Springer Nature. High-Coverage whole-genome sequence studies have so far focused on a limited number of geographically restricted populations, or been targeted at specific diseases, such as cancer. Nevertheless, the availability of high-resolution genomic data has led to the development of new methodologies for inferring population history and refuelled the debate on the mutation rate in humans. Here we present the Estonian Biocentre Human Genome D...

Structure, expression profile and phylogenetic inference of chalcone isomerase-like genes from the narrow-leafed lupin (Lupinus angustifolius L. genome

Directory of Open Access Journals (Sweden)

Łucja ePrzysiecka

2015-04-01

Full Text Available Lupins, like other legumes, have a unique biosynthesis scheme of 5-deoxy-type flavonoids and isoflavonoids. A key enzyme in this pathway is chalcone isomerase (CHI, a member of CHI-fold protein family, encompassing subfamilies of CHI1, CHI2, CHI-like (CHIL, and fatty acid-binding (FAP proteins. Here, two Lupinus angustifolius (narrow-leafed lupin CHILs, LangCHIL1 and LangCHIL2, were identified and characterized using DNA fingerprinting, cytogenetic and linkage mapping, sequencing and expression profiling. Clones carrying CHIL sequences were assembled into two contigs. Full gene sequences were obtained from these contigs, and mapped in two L. angustifolius linkage groups by gene-specific markers. Bacterial artificial chromosome fluorescence in situ hybridization approach confirmed the localization of two LangCHIL genes in distinct chromosomes. The expression profiles of both LangCHIL isoforms were very similar. The highest level of transcription was in the roots of the third week of plant growth; thereafter, expression declined. The expression of both LangCHIL genes in leaves and stems was similar and low. Comparative mapping to reference legume genome sequences revealed strong syntenic links; however, LangCHIL2 contig had a much more conserved structure than LangCHIL1. LangCHIL2 is assumed to be an ancestor gene, whereas LangCHIL1 probably appeared as a result of duplication. As both copies are transcriptionally active, questions arise concerning their hypothetical functional divergence. Screening of the narrow-leafed lupin genome and transcriptome with CHI-fold protein sequences, followed by Bayesian inference of phylogeny and cross-genera synteny survey, identified representatives of all but one (CHI1 main subfamilies. They are as follows: two copies of CHI2, FAPa2 and CHIL, and single copies of FAPb and FAPa1. Duplicated genes are remnants of whole genome duplication which is assumed to have occurred after the divergence of Lupinus, Arachis

Inference of cancer-specific gene regulatory networks using soft computing rules.

Science.gov (United States)

Wang, Xiaosheng; Gotoh, Osamu

2010-03-24

Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer) using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

Evolutionary Genomics of Life in (and from) the Sea

Energy Technology Data Exchange (ETDEWEB)

Boore, Jeffrey L.; Dehal, Paramvir; Fuerstenberg, Susan I.

2006-01-09

High throughput genome sequencing centers that were originally built for the Human Genome Project (Lander et al., 2001; Venter et al., 2001) have now become an engine for comparative genomics. The six largest centers alone are now producing over 150 billion nucleotides per year, more than 50 times the amount of DNA in the human genome, and nearly all of this is directed at projects that promise great insights into the pattern and processes of evolution. Unfortunately, this data is being produced at a pace far exceeding the capacity of the scientific community to provide insightful analysis, and few scientists with training and experience in evolutionary biology have played prominent roles to date. One of the consequences is that poor quality analyses are typical; for example, orthology among genes is generally determined by simple measures of sequence similarity, when this has been discredited by molecular evolutionary biologists decades ago. Here we discuss the how genomes are chosen for sequencing and how the scientific community can have input. We describe the PhIGs database and web tools (Dehal and Boore 2005a; http://PhIGs.org), which provide phylogenetic analysis of all gene families for all completely sequenced genomes and the associated 'Synteny Viewer', which allows comparisons of the relative positions of orthologous genes. This is the best tool available for inferring gene function across multiple genomes. We also describe how we have used the PhIGs methods with the whole genome sequences of a tunicate, fish, mouse, and human to conclusively demonstrate that two rounds of whole genome duplication occurred at the base of vertebrates (Dehal and Boore 2005b). This evidence is found in the large scale structure of the positions of paralogous genes that arose from duplications inferred by evolutionary analysis to have occurred at the base of vertebrates.

CGBayesNets: conditional Gaussian Bayesian network learning and inference with mixed discrete and continuous data.

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McGeachie, Michael J; Chang, Hsun-Hsien; Weiss, Scott T

2014-06-01

Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com.

Lake Bacterial Assemblage Composition Is Sensitive to Biological Disturbance Caused by an Invasive Filter Feeder.

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Denef, Vincent J; Carrick, Hunter J; Cavaletto, Joann; Chiang, Edna; Johengen, Thomas H; Vanderploeg, Henry A

2017-01-01

One approach to improve forecasts of how global change will affect ecosystem processes is to better understand how anthropogenic disturbances alter bacterial assemblages that drive biogeochemical cycles. Species invasions are important contributors to global change, but their impacts on bacterial community ecology are rarely investigated. Here, we studied direct impacts of invasive dreissenid mussels (IDMs), one of many invasive filter feeders, on freshwater lake bacterioplankton. We demonstrated that direct effects of IDMs reduced bacterial abundance and altered assemblage composition by preferentially removing larger and particle-associated bacteria. While this increased the relative abundances of many free-living bacterial taxa, some were susceptible to filter feeding, in line with efficient removal of phytoplankton cells of <2 μm. This selective removal of particle-associated and larger bacteria by IDMs altered inferred bacterial functional group representation, defined by carbon and energy source utilization. Specifically, we inferred an increased relative abundance of chemoorganoheterotrophs predicted to be capable of rhodopsin-dependent energy generation. In contrast to the few previous studies that have focused on the longer-term combined direct and indirect effects of IDMs on bacterioplankton, our study showed that IDMs act directly as a biological disturbance to which freshwater bacterial assemblages are sensitive. The negative impacts on particle-associated bacteria, which have been shown to be more active than free-living bacteria, and the inferred shifts in functional group representation raise the possibility that IDMs may directly alter bacterially mediated ecosystem functions. IMPORTANCE Freshwater bacteria play fundamental roles in global elemental cycling and are an intrinsic part of local food webs. Human activities are altering freshwater environments, and much has been learned regarding the sensitivity of bacterial assemblages to a variety of

Inference of directional selection and mutation parameters assuming equilibrium.

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Vogl, Claus; Bergman, Juraj

2015-12-01

In a classical study, Wright (1931) proposed a model for the evolution of a biallelic locus under the influence of mutation, directional selection and drift. He derived the equilibrium distribution of the allelic proportion conditional on the scaled mutation rate, the mutation bias and the scaled strength of directional selection. The equilibrium distribution can be used for inference of these parameters with genome-wide datasets of "site frequency spectra" (SFS). Assuming that the scaled mutation rate is low, Wright's model can be approximated by a boundary-mutation model, where mutations are introduced into the population exclusively from sites fixed for the preferred or unpreferred allelic states. With the boundary-mutation model, inference can be partitioned: (i) the shape of the SFS distribution within the polymorphic region is determined by random drift and directional selection, but not by the mutation parameters, such that inference of the selection parameter relies exclusively on the polymorphic sites in the SFS; (ii) the mutation parameters can be inferred from the amount of polymorphic and monomorphic preferred and unpreferred alleles, conditional on the selection parameter. Herein, we derive maximum likelihood estimators for the mutation and selection parameters in equilibrium and apply the method to simulated SFS data as well as empirical data from a Madagascar population of Drosophila simulans. Copyright © 2015 Elsevier Inc. All rights reserved.

Genomic Signatures of Reinforcement

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Austin G. Garner

2018-04-01

Full Text Available Reinforcement is the process by which selection against hybridization increases reproductive isolation between taxa. Much research has focused on demonstrating the existence of reinforcement, yet relatively little is known about the genetic basis of reinforcement or the evolutionary conditions under which reinforcement can occur. Inspired by reinforcement’s characteristic phenotypic pattern of reproductive trait divergence in sympatry but not in allopatry, we discuss whether reinforcement also leaves a distinct genomic pattern. First, we describe three patterns of genetic variation we expect as a consequence of reinforcement. Then, we discuss a set of alternative processes and complicating factors that may make the identification of reinforcement at the genomic level difficult. Finally, we consider how genomic analyses can be leveraged to inform if and to what extent reinforcement evolved in the face of gene flow between sympatric lineages and between allopatric and sympatric populations of the same lineage. Our major goals are to understand if genome scans for particular patterns of genetic variation could identify reinforcement, isolate the genetic basis of reinforcement, or infer the conditions under which reinforcement evolved.

Genomic Signatures of Reinforcement

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Goulet, Benjamin E.

2018-01-01

Reinforcement is the process by which selection against hybridization increases reproductive isolation between taxa. Much research has focused on demonstrating the existence of reinforcement, yet relatively little is known about the genetic basis of reinforcement or the evolutionary conditions under which reinforcement can occur. Inspired by reinforcement’s characteristic phenotypic pattern of reproductive trait divergence in sympatry but not in allopatry, we discuss whether reinforcement also leaves a distinct genomic pattern. First, we describe three patterns of genetic variation we expect as a consequence of reinforcement. Then, we discuss a set of alternative processes and complicating factors that may make the identification of reinforcement at the genomic level difficult. Finally, we consider how genomic analyses can be leveraged to inform if and to what extent reinforcement evolved in the face of gene flow between sympatric lineages and between allopatric and sympatric populations of the same lineage. Our major goals are to understand if genome scans for particular patterns of genetic variation could identify reinforcement, isolate the genetic basis of reinforcement, or infer the conditions under which reinforcement evolved. PMID:29614048

Inference of expanded Lrp-like feast/famine transcription factor targets in a non-model organism using protein structure-based prediction.

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Ashworth, Justin; Plaisier, Christopher L; Lo, Fang Yin; Reiss, David J; Baliga, Nitin S

2014-01-01

Widespread microbial genome sequencing presents an opportunity to understand the gene regulatory networks of non-model organisms. This requires knowledge of the binding sites for transcription factors whose DNA-binding properties are unknown or difficult to infer. We adapted a protein structure-based method to predict the specificities and putative regulons of homologous transcription factors across diverse species. As a proof-of-concept we predicted the specificities and transcriptional target genes of divergent archaeal feast/famine regulatory proteins, several of which are encoded in the genome of Halobacterium salinarum. This was validated by comparison to experimentally determined specificities for transcription factors in distantly related extremophiles, chromatin immunoprecipitation experiments, and cis-regulatory sequence conservation across eighteen related species of halobacteria. Through this analysis we were able to infer that Halobacterium salinarum employs a divergent local trans-regulatory strategy to regulate genes (carA and carB) involved in arginine and pyrimidine metabolism, whereas Escherichia coli employs an operon. The prediction of gene regulatory binding sites using structure-based methods is useful for the inference of gene regulatory relationships in new species that are otherwise difficult to infer.

Distribution and evolution of repeated sequences in genomes of Triatominae (Hemiptera-Reduviidae inferred from genomic in situ hybridization.

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Sebastian Pita

Full Text Available The subfamily Triatominae, vectors of Chagas disease, comprises 140 species characterized by a highly homogeneous chromosome number. We analyzed the chromosomal distribution and evolution of repeated sequences in Triatominae genomes by Genomic in situ Hybridization using Triatoma delpontei and Triatoma infestans genomic DNAs as probes. Hybridizations were performed on their own chromosomes and on nine species included in six genera from the two main tribes: Triatomini and Rhodniini. Genomic probes clearly generate two different hybridization patterns, dispersed or accumulated in specific regions or chromosomes. The three used probes generate the same hybridization pattern in each species. However, these patterns are species-specific. In closely related species, the probes strongly hybridized in the autosomal heterochromatic regions, resembling C-banding and DAPI patterns. However, in more distant species these co-localizations are not observed. The heterochromatic Y chromosome is constituted by highly repeated sequences, which is conserved among 10 species of Triatomini tribe suggesting be an ancestral character for this group. However, the Y chromosome in Rhodniini tribe is markedly different, supporting the early evolutionary dichotomy between both tribes. In some species, sex chromosomes and autosomes shared repeated sequences, suggesting meiotic chromatin exchanges among these heterologous chromosomes. Our GISH analyses enabled us to acquire not only reliable information about autosomal repeated sequences distribution but also an insight into sex chromosome evolution in Triatominae. Furthermore, the differentiation obtained by GISH might be a valuable marker to establish phylogenetic relationships and to test the controversial origin of the Triatominae subfamily.

Sequencing and comparing whole mitochondrial genomes ofanimals

Energy Technology Data Exchange (ETDEWEB)

Boore, Jeffrey L.; Macey, J. Robert; Medina, Monica

2005-04-22

Comparing complete animal mitochondrial genome sequences is becoming increasingly common for phylogenetic reconstruction and as a model for genome evolution. Not only are they much more informative than shorter sequences of individual genes for inferring evolutionary relatedness, but these data also provide sets of genome-level characters, such as the relative arrangements of genes, that can be especially powerful. We describe here the protocols commonly used for physically isolating mtDNA, for amplifying these by PCR or RCA, for cloning,sequencing, assembly, validation, and gene annotation, and for comparing both sequences and gene arrangements. On several topics, we offer general observations based on our experiences to date with determining and comparing complete mtDNA sequences.

Genomic analyses inform on migration events during the peopling of Eurasia

OpenAIRE

Pagani, L.; Lawson, D. J.; Jagoda, E.; Moerseburg, A.; Eriksson, A.; Mitt, M.; Clemente, F.; Hudjashov, G.; DeGiorgio, M.; Saag, L.; Wall, J. D.; Cardona, A.; Maegi, R.; Sayres, M. A. W.; Kaewert, S.

2016-01-01

High-coverage whole-genome sequence studies have so far focused on a limited number1 of geographically restricted populations2, 3, 4, 5, or been targeted at specific diseases, such as cancer6. Nevertheless, the availability of high-resolution genomic data has led to the development of new methodologies for inferring population history7, 8, 9 and refuelled the debate on the mutation rate in humans10. Here we present the Estonian Biocentre Human Genome Diversity Panel (EGDP), a dataset of 483 h...

Estimating demographic parameters from large-scale population genomic data using Approximate Bayesian Computation

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Li Sen

2012-03-01

Full Text Available Abstract Background The Approximate Bayesian Computation (ABC approach has been used to infer demographic parameters for numerous species, including humans. However, most applications of ABC still use limited amounts of data, from a small number of loci, compared to the large amount of genome-wide population-genetic data which have become available in the last few years. Results We evaluated the performance of the ABC approach for three 'population divergence' models - similar to the 'isolation with migration' model - when the data consists of several hundred thousand SNPs typed for multiple individuals by simulating data from known demographic models. The ABC approach was used to infer demographic parameters of interest and we compared the inferred values to the true parameter values that was used to generate hypothetical "observed" data. For all three case models, the ABC approach inferred most demographic parameters quite well with narrow credible intervals, for example, population divergence times and past population sizes, but some parameters were more difficult to infer, such as population sizes at present and migration rates. We compared the ability of different summary statistics to infer demographic parameters, including haplotype and LD based statistics, and found that the accuracy of the parameter estimates can be improved by combining summary statistics that capture different parts of information in the data. Furthermore, our results suggest that poor choices of prior distributions can in some circumstances be detected using ABC. Finally, increasing the amount of data beyond some hundred loci will substantially improve the accuracy of many parameter estimates using ABC. Conclusions We conclude that the ABC approach can accommodate realistic genome-wide population genetic data, which may be difficult to analyze with full likelihood approaches, and that the ABC can provide accurate and precise inference of demographic parameters from

Additions, losses, and rearrangements on the evolutionary route from a reconstructed ancestor to the modern Saccharomyces cerevisiae genome.

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Jonathan L Gordon

2009-05-01

Full Text Available Comparative genomics can be used to infer the history of genomic rearrangements that occurred during the evolution of a species. We used the principle of parsimony, applied to aligned synteny blocks from 11 yeast species, to infer the gene content and gene order that existed in the genome of an extinct ancestral yeast about 100 Mya, immediately before it underwent whole-genome duplication (WGD. The reconstructed ancestral genome contains 4,703 ordered loci on eight chromosomes. The reconstruction is complete except for the subtelomeric regions. We then inferred the series of rearrangement steps that led from this ancestor to the current Saccharomyces cerevisiae genome; relative to the ancestral genome we observe 73 inversions, 66 reciprocal translocations, and five translocations involving telomeres. Some fragile chromosomal sites were reused as evolutionary breakpoints multiple times. We identified 124 genes that have been gained by S. cerevisiae in the time since the WGD, including one that is derived from a hAT family transposon, and 88 ancestral loci at which S. cerevisiae did not retain either of the gene copies that were formed by WGD. Sites of gene gain and evolutionary breakpoints both tend to be associated with tRNA genes and, to a lesser extent, with origins of replication. Many of the gained genes in S. cerevisiae have functions associated with ethanol production, growth in hypoxic environments, or the uptake of alternative nutrient sources.

Evolutionary inference across eukaryotes identifies specific pressures favoring mitochondrial gene retention

OpenAIRE

Williams, Ben; Johnston, Iain

2016-01-01

Since their endosymbiotic origin, mitochondria have lost most of their genes. Although many selective mechanisms underlying the evolution of mitochondrial genomes have been proposed, a data-driven exploration of these hypotheses is lacking, and a quantitatively supported consensus remains absent. We developed HyperTraPS, a methodology coupling stochastic modelling with Bayesian inference, to identify the ordering of evolutionary events and suggest their causes. Using 2015 complete mitochondri...

Comparative genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus

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Kovaleva Galina

2011-06-01

Full Text Available Abstract Background Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in bacteria is one of the critical tasks of modern genomics. The Shewanella genus is comprised of metabolically versatile gamma-proteobacteria, whose lifestyles and natural environments are substantially different from Escherichia coli and other model bacterial species. The comparative genomics approaches and computational identification of regulatory sites are useful for the in silico reconstruction of transcriptional regulatory networks in bacteria. Results To explore conservation and variations in the Shewanella transcriptional networks we analyzed the repertoire of transcription factors and performed genomics-based reconstruction and comparative analysis of regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors and their DNA binding sites, 8 riboswitches and 6 translational attenuators. Forty five regulons were newly inferred from the genome context analysis, whereas others were propagated from previously characterized regulons in the Enterobacteria and Pseudomonas spp.. Multiple variations in regulatory strategies between the Shewanella spp. and E. coli include regulon contraction and expansion (as in the case of PdhR, HexR, FadR, numerous cases of recruiting non-orthologous regulators to control equivalent pathways (e.g. PsrA for fatty acid degradation and, conversely, orthologous regulators to control distinct pathways (e.g. TyrR, ArgR, Crp. Conclusions We tentatively defined the first reference collection of ~100 transcriptional regulons in 16 Shewanella genomes. The resulting regulatory network contains ~600 regulated genes per genome that are mostly involved in metabolism of carbohydrates, amino acids, fatty acids, vitamins, metals, and stress responses. Several reconstructed regulons including NagR for N-acetylglucosamine catabolism were experimentally validated in S

Inferring the demographic history of European Ficedula flycatcher populations

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Backström Niclas

2013-01-01

Full Text Available Abstract Background Inference of population and species histories and population stratification using genetic data is important for discriminating between different speciation scenarios and for correct interpretation of genome scans for signs of adaptive evolution and trait association. Here we use data from 24 intronic loci re-sequenced in population samples of two closely related species, the pied flycatcher and the collared flycatcher. Results We applied Isolation-Migration models, assignment analyses and estimated the genetic differentiation and diversity between species and between populations within species. The data indicate a divergence time between the species of Conclusions Our results provide further evidence for a divergence process where different genomic regions may be at different stages of speciation. We also conclude that forthcoming analyses of genotype-phenotype relations in these ecological model species should be designed to take population stratification into account.

Sparse representation and Bayesian detection of genome copy number alterations from microarray data.

Science.gov (United States)

Pique-Regi, Roger; Monso-Varona, Jordi; Ortega, Antonio; Seeger, Robert C; Triche, Timothy J; Asgharzadeh, Shahab

2008-02-01

Genomic instability in cancer leads to abnormal genome copy number alterations (CNA) that are associated with the development and behavior of tumors. Advances in microarray technology have allowed for greater resolution in detection of DNA copy number changes (amplifications or deletions) across the genome. However, the increase in number of measured signals and accompanying noise from the array probes present a challenge in accurate and fast identification of breakpoints that define CNA. This article proposes a novel detection technique that exploits the use of piece wise constant (PWC) vectors to represent genome copy number and sparse Bayesian learning (SBL) to detect CNA breakpoints. First, a compact linear algebra representation for the genome copy number is developed from normalized probe intensities. Second, SBL is applied and optimized to infer locations where copy number changes occur. Third, a backward elimination (BE) procedure is used to rank the inferred breakpoints; and a cut-off point can be efficiently adjusted in this procedure to control for the false discovery rate (FDR). The performance of our algorithm is evaluated using simulated and real genome datasets and compared to other existing techniques. Our approach achieves the highest accuracy and lowest FDR while improving computational speed by several orders of magnitude. The proposed algorithm has been developed into a free standing software application (GADA, Genome Alteration Detection Algorithm). http://biron.usc.edu/~piquereg/GADA

Genomic analyses inform on migration events during the peopling of Eurasia

OpenAIRE

Pagani, Luca; Lawson, Daniel John; Jagoda, Evelyn; M?rseburg, Alexander; Eriksson, Anders; Mitt, Mario; Clemente, Florian; Hudjashov, Georgi; DeGiorgio, Michael; Saag, Lauri; Wall, Jeffrey D.; Cardona, Alexia; M?gi, Reedik; Wilson Sayres, Melissa A.; Kaewert, Sarah

2016-01-01

High-coverage whole-genome sequence studies have so far focused\\ud on a limited number1 of geographically restricted populations2–5,\\ud or been targeted at specific diseases, such as cancer6. Nevertheless,\\ud the availability of high-resolution genomic data has led to the\\ud development of new methodologies for inferring population\\ud history7–9 and refuelled the debate on the mutation rate in humans10.\\ud Here we present the Estonian Biocentre Human Genome Diversity\\ud Panel (EGDP), a datase...

Divergence times in Caenorhabditis and Drosophila inferred from direct estimates of the neutral mutation rate.

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Cutter, Asher D

2008-04-01

Accurate inference of the dates of common ancestry among species forms a central problem in understanding the evolutionary history of organisms. Molecular estimates of divergence time rely on the molecular evolutionary prediction that neutral mutations and substitutions occur at the same constant rate in genomes of related species. This underlies the notion of a molecular clock. Most implementations of this idea depend on paleontological calibration to infer dates of common ancestry, but taxa with poor fossil records must rely on external, potentially inappropriate, calibration with distantly related species. The classic biological models Caenorhabditis and Drosophila are examples of such problem taxa. Here, I illustrate internal calibration in these groups with direct estimates of the mutation rate from contemporary populations that are corrected for interfering effects of selection on the assumption of neutrality of substitutions. Divergence times are inferred among 6 species each of Caenorhabditis and Drosophila, based on thousands of orthologous groups of genes. I propose that the 2 closest known species of Caenorhabditis shared a common ancestor <24 MYA (Caenorhabditis briggsae and Caenorhabditis sp. 5) and that Caenorhabditis elegans diverged from its closest known relatives <30 MYA, assuming that these species pass through at least 6 generations per year; these estimates are much more recent than reported previously with molecular clock calibrations from non-nematode phyla. Dates inferred for the common ancestor of Drosophila melanogaster and Drosophila simulans are roughly concordant with previous studies. These revised dates have important implications for rates of genome evolution and the origin of self-fertilization in Caenorhabditis.

Carnivore-specific SINEs (Can-SINEs): distribution, evolution, and genomic impact.

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Walters-Conte, Kathryn B; Johnson, Diana L E; Allard, Marc W; Pecon-Slattery, Jill

2011-01-01

Short interspersed nuclear elements (SINEs) are a type of class 1 transposable element (retrotransposon) with features that allow investigators to resolve evolutionary relationships between populations and species while providing insight into genome composition and function. Characterization of a Carnivora-specific SINE family, Can-SINEs, has, has aided comparative genomic studies by providing rare genomic changes, and neutral sequence variants often needed to resolve difficult evolutionary questions. In addition, Can-SINEs constitute a significant source of functional diversity with Carnivora. Publication of the whole-genome sequence of domestic dog, domestic cat, and giant panda serves as a valuable resource in comparative genomic inferences gleaned from Can-SINEs. In anticipation of forthcoming studies bolstered by new genomic data, this review describes the discovery and characterization of Can-SINE motifs as well as describes composition, distribution, and effect on genome function. As the contribution of noncoding sequences to genomic diversity becomes more apparent, SINEs and other transposable elements will play an increasingly large role in mammalian comparative genomics.

Estimating variation within the genes and inferring the phylogeny of 186 sequenced diverse Escherichia coli genomes

DEFF Research Database (Denmark)

Kaas, Rolf Sommer; Rundsten, Carsten Friis; Ussery, David

2012-01-01

Background Escherichia coli exists in commensal and pathogenic forms. By measuring the variation of individual genes across more than a hundred sequenced genomes, gene variation can be studied in detail, including the number of mutations found for any given gene. This knowledge will be useful...... for creating better phylogenies, for determination of molecular clocks and for improved typing techniques. Results We find 3,051 gene clusters/families present in at least 95% of the genomes and 1,702 gene clusters present in 100% of the genomes. The former 'soft core' of about 3,000 gene families is perhaps...... more biologically relevant, especially considering that many of these genome sequences are draft quality. The E. coli pan-genome for this set of isolates contains 16,373 gene clusters. A core-gene tree, based on alignment and a pan-genome tree based on gene presence/absence, maps the relatedness...

Diversity of bacterioplankton in the surface seawaters of Drake Passage near the Chinese Antarctic station.

Science.gov (United States)

Xing, Mengxin; Li, Zhao; Wang, Wei; Sun, Mi

2015-07-01

The determination of relative abundances and distribution of different bacterial groups is a critical step toward understanding the functions of various bacteria and its surrounding environment. Few studies focus on the taxonomic composition and functional diversity of microbial communities in Drake Passage. In this study, marine bacterioplankton communities from surface seawaters at five locations in Drake Passage were examined by 16S rRNA gene sequence analyses. The results indicated that psychrophilic bacteria were the most abundant group in Drake Passage, and mainly made up of Bacillus, Aeromonas, Psychrobacter, Pseudomonas and Halomonas. Diversity analysis showed that surface seawater communities had no significant correlation with latitudinal gradient. Additionally, a clear difference among five surface seawater communities was evident, with 1.8% OTUs (only two) belonged to Bacillus consistent across five locations and 71% OTUs (80) existed in only one location. However, the few cosmopolitans had the largest population sizes. Our results support the hypothesis that the dominant bacterial groups appear to be analogous between geographical sites, but significant differences may be detected among rare bacterial groups. The microbial diversity of surface seawaters would be liable to be affected by environmental factors. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Inference of Cancer-specific Gene Regulatory Networks Using Soft Computing Rules

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Xiaosheng Wang

2010-03-01

Full Text Available Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

Inferring regulatory networks from expression data using tree-based methods.

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Vân Anh Huynh-Thu

2010-09-01

Full Text Available One of the pressing open problems of computational systems biology is the elucidation of the topology of genetic regulatory networks (GRNs using high throughput genomic data, in particular microarray gene expression data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM challenge aims to evaluate the success of GRN inference algorithms on benchmarks of simulated data. In this article, we present GENIE3, a new algorithm for the inference of GRNs that was best performer in the DREAM4 In Silico Multifactorial challenge. GENIE3 decomposes the prediction of a regulatory network between p genes into p different regression problems. In each of the regression problems, the expression pattern of one of the genes (target gene is predicted from the expression patterns of all the other genes (input genes, using tree-based ensemble methods Random Forests or Extra-Trees. The importance of an input gene in the prediction of the target gene expression pattern is taken as an indication of a putative regulatory link. Putative regulatory links are then aggregated over all genes to provide a ranking of interactions from which the whole network is reconstructed. In addition to performing well on the DREAM4 In Silico Multifactorial challenge simulated data, we show that GENIE3 compares favorably with existing algorithms to decipher the genetic regulatory network of Escherichia coli. It doesn't make any assumption about the nature of gene regulation, can deal with combinatorial and non-linear interactions, produces directed GRNs, and is fast and scalable. In conclusion, we propose a new algorithm for GRN inference that performs well on both synthetic and real gene expression data. The algorithm, based on feature selection with tree-based ensemble methods, is simple and generic, making it adaptable to other types of genomic data and interactions.

Macrophyte Species Drive the Variation of Bacterioplankton Community Composition in a Shallow Freshwater Lake

Science.gov (United States)

Zeng, Jin; Bian, Yuanqi; Xing, Peng

2012-01-01

Macrophytes play an important role in structuring aquatic ecosystems. In this study, we explored whether macrophyte species are involved in determining the bacterioplankton community composition (BCC) in shallow freshwater lakes. The BCC in field areas dominated by different macrophyte species in Taihu Lake, a large, shallow freshwater lake, was investigated over a 1-year period. Subsequently, microcosm experiments were conducted to determine if single species of different types of macrophytes in an isolated environment would alter the BCC. Denaturing gradient gel electrophoresis (DGGE), followed by cloning and sequence analysis of selected samples, was employed to analyze the BCC. The DGGE results of the field investigations indicated that the BCC changed significantly from season to season and that the presence of different macrophyte species resulted in lower BCC similarities in the summer and fall. LIBSHUFF analysis of selected clone libraries from the summer demonstrated different BCCs in the water column surrounding different macrophytes. Relative to the field observations, the microcosm studies indicated that the BCC differed more pronouncedly when associated with different species of macrophytes, which was also supported by LIBSHUFF analysis of the selected clone libraries. Overall, this study suggested that macrophyte species might be an important factor in determining the composition of bacterial communities in this shallow freshwater lake and that the species-specific influence of macrophytes on BCC is variable with the season and distance. PMID:22038598

Limitations of a metabolic network-based reverse ecology method for inferring host-pathogen interactions.

Science.gov (United States)

Takemoto, Kazuhiro; Aie, Kazuki

2017-05-25

Host-pathogen interactions are important in a wide range of research fields. Given the importance of metabolic crosstalk between hosts and pathogens, a metabolic network-based reverse ecology method was proposed to infer these interactions. However, the validity of this method remains unclear because of the various explanations presented and the influence of potentially confounding factors that have thus far been neglected. We re-evaluated the importance of the reverse ecology method for evaluating host-pathogen interactions while statistically controlling for confounding effects using oxygen requirement, genome, metabolic network, and phylogeny data. Our data analyses showed that host-pathogen interactions were more strongly influenced by genome size, primary network parameters (e.g., number of edges), oxygen requirement, and phylogeny than the reserve ecology-based measures. These results indicate the limitations of the reverse ecology method; however, they do not discount the importance of adopting reverse ecology approaches altogether. Rather, we highlight the need for developing more suitable methods for inferring host-pathogen interactions and conducting more careful examinations of the relationships between metabolic networks and host-pathogen interactions.

Analyses of charophyte chloroplast genomes help characterize the ancestral chloroplast genome of land plants.

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Civaň, Peter; Foster, Peter G; Embley, Martin T; Séneca, Ana; Cox, Cymon J

2014-04-01

Despite the significance of the relationships between embryophytes and their charophyte algal ancestors in deciphering the origin and evolutionary success of land plants, few chloroplast genomes of the charophyte algae have been reconstructed to date. Here, we present new data for three chloroplast genomes of the freshwater charophytes Klebsormidium flaccidum (Klebsormidiophyceae), Mesotaenium endlicherianum (Zygnematophyceae), and Roya anglica (Zygnematophyceae). The chloroplast genome of Klebsormidium has a quadripartite organization with exceptionally large inverted repeat (IR) regions and, uniquely among streptophytes, has lost the rrn5 and rrn4.5 genes from the ribosomal RNA (rRNA) gene cluster operon. The chloroplast genome of Roya differs from other zygnematophycean chloroplasts, including the newly sequenced Mesotaenium, by having a quadripartite structure that is typical of other streptophytes. On the basis of the improbability of the novel gain of IR regions, we infer that the quadripartite structure has likely been lost independently in at least three zygnematophycean lineages, although the absence of the usual rRNA operonic synteny in the IR regions of Roya may indicate their de novo origin. Significantly, all zygnematophycean chloroplast genomes have undergone substantial genomic rearrangement, which may be the result of ancient retroelement activity evidenced by the presence of integrase-like and reverse transcriptase-like elements in the Roya chloroplast genome. Our results corroborate the close phylogenetic relationship between Zygnematophyceae and land plants and identify 89 protein-coding genes and 22 introns present in the chloroplast genome at the time of the evolutionary transition of plants to land, all of which can be found in the chloroplast genomes of extant charophytes.

Adaptation, Ecology, and Evolution of the Halophilic Stromatolite Archaeon Halococcus hamelinensis Inferred through Genome Analyses

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Reema K. Gudhka

2015-01-01

Full Text Available Halococcus hamelinensis was the first archaeon isolated from stromatolites. These geomicrobial ecosystems are thought to be some of the earliest known on Earth, yet, despite their evolutionary significance, the role of Archaea in these systems is still not well understood. Detailed here is the genome sequencing and analysis of an archaeon isolated from stromatolites. The genome of H. hamelinensis consisted of 3,133,046 base pairs with an average G+C content of 60.08% and contained 3,150 predicted coding sequences or ORFs, 2,196 (68.67% of which were protein-coding genes with functional assignments and 954 (29.83% of which were of unknown function. Codon usage of the H. hamelinensis genome was consistent with a highly acidic proteome, a major adaptive mechanism towards high salinity. Amino acid transport and metabolism, inorganic ion transport and metabolism, energy production and conversion, ribosomal structure, and unknown function COG genes were overrepresented. The genome of H. hamelinensis also revealed characteristics reflecting its survival in its extreme environment, including putative genes/pathways involved in osmoprotection, oxidative stress response, and UV damage repair. Finally, genome analyses indicated the presence of putative transposases as well as positive matches of genes of H. hamelinensis against various genomes of Bacteria, Archaea, and viruses, suggesting the potential for horizontal gene transfer.

Statistical Methods for Population Genetic Inference Based on Low-Depth Sequencing Data from Modern and Ancient DNA

DEFF Research Database (Denmark)

Korneliussen, Thorfinn Sand

Due to the recent advances in DNA sequencing technology genomic data are being generated at an unprecedented rate and we are gaining access to entire genomes at population level. The technology does, however, not give direct access to the genetic variation and the many levels of preprocessing...... that is required before being able to make inferences from the data introduces multiple levels of uncertainty, especially for low-depth data. Therefore methods that take into account the inherent uncertainty are needed for being able to make robust inferences in the downstream analysis of such data. This poses...... a problem for a range of key summary statistics within populations genetics where existing methods are based on the assumption that the true genotypes are known. Motivated by this I present: 1) a new method for the estimation of relatedness between pairs of individuals, 2) a new method for estimating...

Signatures of selection in the Iberian honey bee: a genome wide approach using single nucleotide polymorphisms (SNPs)

OpenAIRE

Chavez-Galarza, Julio; Johnston, J. Spencer; Azevedo, João; Muñoz, Irene; De la Rúa, Pilar; Patton, John C.; Pinto, M. Alice

2011-01-01

Dissecting genome-wide (expansions, contractions, admixture) from genome-specific effects (selection) is a goal of central importance in evolutionary biology because it leads to more robust inferences of demographic history and to identification of adaptive divergence. The publication of the honey bee genome and the development of high-density SNPs genotyping, provide us with powerful tools, allowing us to identify signatures of selection in the honey bee genome. These signatur...

RegPrecise 3.0--a resource for genome-scale exploration of transcriptional regulation in bacteria.

Science.gov (United States)

Novichkov, Pavel S; Kazakov, Alexey E; Ravcheev, Dmitry A; Leyn, Semen A; Kovaleva, Galina Y; Sutormin, Roman A; Kazanov, Marat D; Riehl, William; Arkin, Adam P; Dubchak, Inna; Rodionov, Dmitry A

2013-11-01

Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in prokaryotes is one of the critical tasks of modern genomics. Bacteria from different taxonomic groups, whose lifestyles and natural environments are substantially different, possess highly diverged transcriptional regulatory networks. The comparative genomics approaches are useful for in silico reconstruction of bacterial regulons and networks operated by both transcription factors (TFs) and RNA regulatory elements (riboswitches). RegPrecise (http://regprecise.lbl.gov) is a web resource for collection, visualization and analysis of transcriptional regulons reconstructed by comparative genomics. We significantly expanded a reference collection of manually curated regulons we introduced earlier. RegPrecise 3.0 provides access to inferred regulatory interactions organized by phylogenetic, structural and functional properties. Taxonomy-specific collections include 781 TF regulogs inferred in more than 160 genomes representing 14 taxonomic groups of Bacteria. TF-specific collections include regulogs for a selected subset of 40 TFs reconstructed across more than 30 taxonomic lineages. Novel collections of regulons operated by RNA regulatory elements (riboswitches) include near 400 regulogs inferred in 24 bacterial lineages. RegPrecise 3.0 provides four classifications of the reference regulons implemented as controlled vocabularies: 55 TF protein families; 43 RNA motif families; ~150 biological processes or metabolic pathways; and ~200 effectors or environmental signals. Genome-wide visualization of regulatory networks and metabolic pathways covered by the reference regulons are available for all studied genomes. A separate section of RegPrecise 3.0 contains draft regulatory networks in 640 genomes obtained by an conservative propagation of the reference regulons to closely related genomes. RegPrecise 3.0 gives access to the transcriptional regulons reconstructed in

A Genomic Map of the Effects of Linked Selection in Drosophila.

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Eyal Elyashiv

2016-08-01

Full Text Available Natural selection at one site shapes patterns of genetic variation at linked sites. Quantifying the effects of "linked selection" on levels of genetic diversity is key to making reliable inference about demography, building a null model in scans for targets of adaptation, and learning about the dynamics of natural selection. Here, we introduce the first method that jointly infers parameters of distinct modes of linked selection, notably background selection and selective sweeps, from genome-wide diversity data, functional annotations and genetic maps. The central idea is to calculate the probability that a neutral site is polymorphic given local annotations, substitution patterns, and recombination rates. Information is then combined across sites and samples using composite likelihood in order to estimate genome-wide parameters of distinct modes of selection. In addition to parameter estimation, this approach yields a map of the expected neutral diversity levels along the genome. To illustrate the utility of our approach, we apply it to genome-wide resequencing data from 125 lines in Drosophila melanogaster and reliably predict diversity levels at the 1Mb scale. Our results corroborate estimates of a high fraction of beneficial substitutions in proteins and untranslated regions (UTR. They allow us to distinguish between the contribution of sweeps and other modes of selection around amino acid substitutions and to uncover evidence for pervasive sweeps in untranslated regions (UTRs. Our inference further suggests a substantial effect of other modes of linked selection and of adaptation in particular. More generally, we demonstrate that linked selection has had a larger effect in reducing diversity levels and increasing their variance in D. melanogaster than previously appreciated.

A Genomic Map of the Effects of Linked Selection in Drosophila.

Science.gov (United States)

Elyashiv, Eyal; Sattath, Shmuel; Hu, Tina T; Strutsovsky, Alon; McVicker, Graham; Andolfatto, Peter; Coop, Graham; Sella, Guy

2016-08-01

Natural selection at one site shapes patterns of genetic variation at linked sites. Quantifying the effects of "linked selection" on levels of genetic diversity is key to making reliable inference about demography, building a null model in scans for targets of adaptation, and learning about the dynamics of natural selection. Here, we introduce the first method that jointly infers parameters of distinct modes of linked selection, notably background selection and selective sweeps, from genome-wide diversity data, functional annotations and genetic maps. The central idea is to calculate the probability that a neutral site is polymorphic given local annotations, substitution patterns, and recombination rates. Information is then combined across sites and samples using composite likelihood in order to estimate genome-wide parameters of distinct modes of selection. In addition to parameter estimation, this approach yields a map of the expected neutral diversity levels along the genome. To illustrate the utility of our approach, we apply it to genome-wide resequencing data from 125 lines in Drosophila melanogaster and reliably predict diversity levels at the 1Mb scale. Our results corroborate estimates of a high fraction of beneficial substitutions in proteins and untranslated regions (UTR). They allow us to distinguish between the contribution of sweeps and other modes of selection around amino acid substitutions and to uncover evidence for pervasive sweeps in untranslated regions (UTRs). Our inference further suggests a substantial effect of other modes of linked selection and of adaptation in particular. More generally, we demonstrate that linked selection has had a larger effect in reducing diversity levels and increasing their variance in D. melanogaster than previously appreciated.

Permanent draft genomes of the two Rhodopirellula europaea strains 6C and SH398.

Science.gov (United States)

Richter-Heitmann, Tim; Richter, Michael; Klindworth, Anna; Wegner, Carl-Eric; Frank, Carsten S; Glöckner, Frank Oliver; Harder, Jens

2014-02-01

The genomes of two Rhodopirellula europaea strains were sequenced as permanent drafts to study the genomic diversity within this genus, especially in comparison with the closed genome of the type strain Rhodopirellula baltica SH1(T). The isolates are part of a larger study to infer the biogeography of Rhodopirellula species in European marine waters, as well as to amend the genus description of R. baltica. This genomics resource article is the second of a series of five publications describing a total of eight new permanent daft genomes of Rhodopirellula species. Copyright © 2013 Elsevier B.V. All rights reserved.

Simultaneous genome-wide inference of physical, genetic, regulatory, and functional pathway components.

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Christopher Y Park

2010-11-01

Full Text Available Biomolecular pathways are built from diverse types of pairwise interactions, ranging from physical protein-protein interactions and modifications to indirect regulatory relationships. One goal of systems biology is to bridge three aspects of this complexity: the growing body of high-throughput data assaying these interactions; the specific interactions in which individual genes participate; and the genome-wide patterns of interactions in a system of interest. Here, we describe methodology for simultaneously predicting specific types of biomolecular interactions using high-throughput genomic data. This results in a comprehensive compendium of whole-genome networks for yeast, derived from ∼3,500 experimental conditions and describing 30 interaction types, which range from general (e.g. physical or regulatory to specific (e.g. phosphorylation or transcriptional regulation. We used these networks to investigate molecular pathways in carbon metabolism and cellular transport, proposing a novel connection between glycogen breakdown and glucose utilization supported by recent publications. Additionally, 14 specific predicted interactions in DNA topological change and protein biosynthesis were experimentally validated. We analyzed the systems-level network features within all interactomes, verifying the presence of small-world properties and enrichment for recurring network motifs. This compendium of physical, synthetic, regulatory, and functional interaction networks has been made publicly available through an interactive web interface for investigators to utilize in future research at http://function.princeton.edu/bioweaver/.

Genomics and ecophysiology of heterotrophic nitrogen fixing bacteria isolated from estuarine surface water

DEFF Research Database (Denmark)

Bentzon-Tilia, Mikkel; Severin, Ina; Hansen, Lars H.

2015-01-01

The ability to reduce atmospheric nitrogen (N2) to ammonia, known as N2 fixation, is a widely distributed trait among prokaryotes that accounts for an essential input of new N to a multitude of environments. Nitrogenase reductase gene (nifH) composition suggests that putative N2-fixing heterotrop......The ability to reduce atmospheric nitrogen (N2) to ammonia, known as N2 fixation, is a widely distributed trait among prokaryotes that accounts for an essential input of new N to a multitude of environments. Nitrogenase reductase gene (nifH) composition suggests that putative N2-fixing...... heterotrophic organisms are widespread in marine bacterioplankton, but their autecology and ecological significance are unknown. Here, we report genomic and ecophysiology data in relation to N2 fixation by three environmentally relevant heterotrophic bacteria isolated from Baltic Sea surface water: Pseudomonas...... liter-1, presumably accommodated through aggregate formation. Glucose stimulated N2 fixation in general, and reactive N repressed N2 fixation, except that ammonium (NH4 ) stimulated N2 fixation in R. palustris BAL398, indicating the use of nitrogenase as an electron sink. The lack of correlations...

Use of the p-SINE1-r2 in inferring evolutionary relationships of Thai rice varieties with AA genome

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Preecha Prathepha

2006-01-01

Full Text Available In a previous study we described the prevalence and distribution in Thailand of the retroposon p- SINE1-r2, in the intron 10 of the waxy gene in cultivated and wild rice with the AA genome. In this study, additional varieties of rice were collected and sequencing was used to further characterize p-SINE1-r2. It was found that the length of the p-SINE1-r2 nucleotide sequences was about 125 bp, flanked by identical direct repeats of a 14 bp sequence. These sequences were compared and found to be similar to the sequences of p- SINE1-r2 found in Nipponbare, a rice strain discussed in a separate study. However, when compared the 48 DNA sequences identified in this study, much dissimilarity was found within the nucleotide sequences of p- SINE1-r2, in the form of base substitution mutations. Phylogenetic relationships inferred from the nucleotide sequences of these elements in cultivated rice (O. sativa and wild rice (O. nivara. It was found that rice accessions collected from the same geographical distribution have been placed in the same clade. The phylogenetic tree supports the origin and distribution of these rice strains.

Single-Genome Sequencing of Hepatitis C Virus in Donor-Recipient Pairs Distinguishes Modes and Models of Virus Transmission and Early Diversification.

Science.gov (United States)

Li, Hui; Stoddard, Mark B; Wang, Shuyi; Giorgi, Elena E; Blair, Lily M; Learn, Gerald H; Hahn, Beatrice H; Alter, Harvey J; Busch, Michael P; Fierer, Daniel S; Ribeiro, Ruy M; Perelson, Alan S; Bhattacharya, Tanmoy; Shaw, George M

2016-01-01

Despite the recent development of highly effective anti-hepatitis C virus (HCV) drugs, the global burden of this pathogen remains immense. Control or eradication of HCV will likely require the broad application of antiviral drugs and development of an effective vaccine. A precise molecular identification of transmitted/founder (T/F) HCV genomes that lead to productive clinical infection could play a critical role in vaccine research, as it has for HIV-1. However, the replication schema of these two RNA viruses differ substantially, as do viral responses to innate and adaptive host defenses. These differences raise questions as to the certainty of T/F HCV genome inferences, particularly in cases where multiple closely related sequence lineages have been observed. To clarify these issues and distinguish between competing models of early HCV diversification, we examined seven cases of acute HCV infection in humans and chimpanzees, including three examples of virus transmission between linked donors and recipients. Using single-genome sequencing (SGS) of plasma vRNA, we found that inferred T/F sequences in recipients were identical to viral sequences in their respective donors. Early in infection, HCV genomes generally evolved according to a simple model of random evolution where the coalescent corresponded to the T/F sequence. Closely related sequence lineages could be explained by high multiplicity infection from a donor whose viral sequences had undergone a pretransmission bottleneck due to treatment, immune selection, or recent infection. These findings validate SGS, together with mathematical modeling and phylogenetic analysis, as a novel strategy to infer T/F HCV genome sequences. Despite the recent development of highly effective, interferon-sparing anti-hepatitis C virus (HCV) drugs, the global burden of this pathogen remains immense. Control or eradication of HCV will likely require the broad application of antiviral drugs and the development of an effective

Conflicting Evolutionary Histories of the Mitochondrial and Nuclear Genomes in New World Myotis Bats.

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Platt, Roy N; Faircloth, Brant C; Sullivan, Kevin A M; Kieran, Troy J; Glenn, Travis C; Vandewege, Michael W; Lee, Thomas E; Baker, Robert J; Stevens, Richard D; Ray, David A

2018-03-01

The rapid diversification of Myotis bats into more than 100 species is one of the most extensive mammalian radiations available for study. Efforts to understand relationships within Myotis have primarily utilized mitochondrial markers and trees inferred from nuclear markers lacked resolution. Our current understanding of relationships within Myotis is therefore biased towards a set of phylogenetic markers that may not reflect the history of the nuclear genome. To resolve this, we sequenced the full mitochondrial genomes of 37 representative Myotis, primarily from the New World, in conjunction with targeted sequencing of 3648 ultraconserved elements (UCEs). We inferred the phylogeny and explored the effects of concatenation and summary phylogenetic methods, as well as combinations of markers based on informativeness or levels of missing data, on our results. Of the 294 phylogenies generated from the nuclear UCE data, all are significantly different from phylogenies inferred using mitochondrial genomes. Even within the nuclear data, quartet frequencies indicate that around half of all UCE loci conflict with the estimated species tree. Several factors can drive such conflict, including incomplete lineage sorting, introgressive hybridization, or even phylogenetic error. Despite the degree of discordance between nuclear UCE loci and the mitochondrial genome and among UCE loci themselves, the most common nuclear topology is recovered in one quarter of all analyses with strong nodal support. Based on these results, we re-examine the evolutionary history of Myotis to better understand the phenomena driving their unique nuclear, mitochondrial, and biogeographic histories.

Current development and application of soybean genomics

Institute of Scientific and Technical Information of China (English)

Lingli HE; Jing ZHAO; Man ZHAO; Chaoying HE

2011-01-01

Soybean (Glycine max),an important domesticated species originated in China,constitutes a major source of edible oils and high-quality plant proteins worldwide.In spite of its complex genome as a consequence of an ancient tetraploidilization,platforms for map-based genomics,sequence-based genomics,comparative genomics and functional genomics have been well developed in the last decade,thus rich repertoires of genomic tools and resources are available,which have been influencing the soybean genetic improvement.Here we mainly review the progresses of soybean (including its wild relative Glycine soja) genomics and its impetus for soybean breeding,and raise the major biological questions needing to be addressed.Genetic maps,physical maps,QTL and EST mapping have been so well achieved that the marker assisted selection and positional cloning in soybean is feasible and even routine.Whole genome sequencing and transcriptomic analyses provide a large collection of molecular markers and predicted genes,which are instrumental to comparative genomics and functional genomics.Comparative genomics has started to reveal the evolution of soybean genome and the molecular basis of soybean domestication process.Microarrays resources,mutagenesis and efficient transformation systems become essential components of soybean functional genomics.Furthermore,phenotypic functional genomics via both forward and reverse genetic approaches has inferred functions of many genes involved in plant and seed development,in response to abiotic stresses,functioning in plant-pathogenic microbe interactions,and controlling the oil and protein content of seed.These achievements have paved the way for generation of transgenic or genetically modified (GM) soybean crops.

Improving Microbial Genome Annotations in an Integrated Database Context

Science.gov (United States)

Chen, I-Min A.; Markowitz, Victor M.; Chu, Ken; Anderson, Iain; Mavromatis, Konstantinos; Kyrpides, Nikos C.; Ivanova, Natalia N.

2013-01-01

Effective comparative analysis of microbial genomes requires a consistent and complete view of biological data. Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that allow scientists to assess and improve the consistency and completeness of microbial genome annotations in the context of the Integrated Microbial Genomes (IMG) family of systems. All publicly available microbial genomes are characterized in IMG using different functional annotation and pathway resources, thus providing a comprehensive framework for identifying and resolving annotation discrepancies. A rule based system for predicting phenotypes in IMG provides a powerful mechanism for validating functional annotations, whereby the phenotypic traits of an organism are inferred based on the presence of certain metabolic reactions and pathways and compared to experimentally observed phenotypes. The IMG family of systems are available at http://img.jgi.doe.gov/. PMID:23424620

Improving microbial genome annotations in an integrated database context.

Directory of Open Access Journals (Sweden)

I-Min A Chen

Full Text Available Effective comparative analysis of microbial genomes requires a consistent and complete view of biological data. Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that allow scientists to assess and improve the consistency and completeness of microbial genome annotations in the context of the Integrated Microbial Genomes (IMG family of systems. All publicly available microbial genomes are characterized in IMG using different functional annotation and pathway resources, thus providing a comprehensive framework for identifying and resolving annotation discrepancies. A rule based system for predicting phenotypes in IMG provides a powerful mechanism for validating functional annotations, whereby the phenotypic traits of an organism are inferred based on the presence of certain metabolic reactions and pathways and compared to experimentally observed phenotypes. The IMG family of systems are available at http://img.jgi.doe.gov/.

ERC analysis: web-based inference of gene function via evolutionary rate covariation.

Science.gov (United States)

Wolfe, Nicholas W; Clark, Nathan L

2015-12-01

The recent explosion of comparative genomics data presents an unprecedented opportunity to construct gene networks via the evolutionary rate covariation (ERC) signature. ERC is used to identify genes that experienced similar evolutionary histories, and thereby draws functional associations between them. The ERC Analysis website allows researchers to exploit genome-wide datasets to infer novel genes in any biological function and to explore deep evolutionary connections between distinct pathways and complexes. The website provides five analytical methods, graphical output, statistical support and access to an increasing number of taxonomic groups. Analyses and data at http://csb.pitt.edu/erc_analysis/ nclark@pitt.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

MobilomeFINDER: web-based tools for in silico and experimental discovery of bacterial genomic islands

OpenAIRE

Ou, Hong-Yu; He, Xinyi; Harrison, Ewan M.; Kulasekara, Bridget R.; Thani, Ali Bin; Kadioglu, Aras; Lory, Stephen; Hinton, Jay C. D.; Barer, Michael R.; Deng, Zixin; Rajakumar, Kumar

2007-01-01

MobilomeFINDER (http://mml.sjtu.edu.cn/MobilomeFINDER) is an interactive online tool that facilitates bacterial genomic island or ‘mobile genome’ (mobilome) discovery; it integrates the ArrayOme and tRNAcc software packages. ArrayOme utilizes a microarray-derived comparative genomic hybridization input data set to generate ‘inferred contigs’ produced by merging adjacent genes classified as ‘present’. Collectively these ‘fragments’ represent a hypothetical ‘microarray-visualized genome (MVG)’....

Genome-association analysis of Korean Holstein milk traits using genomic estimated breeding value

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Donghyun Shin

2017-03-01

Full Text Available Objective Holsteins are known as the world’s highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein using Korean Holstein data. Methods This study was performed using single nucleotide polymorphism (SNP chip data (Illumina BovineSNP50 Beadchip of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased prediction (BLUP and ridge regression using BLUPF90 and R. We then performed a genome-wide association study and identified genetic regions related to milk traits. Results We identified 9, 6, and 17 significant genetic regions related to milk production, fat and protein, respectively. These genes are newly reported in the genetic association with milk traits of Holstein. Conclusion This study complements a recent Holstein genome-wide association studies that identified other SNPs and genes as the most significant variants. These results will help to expand the knowledge of the polygenic nature of milk production in Holsteins.

Inter-genomic DNA Exchanges and Homeologous Gene Silencing Shaped the Nascent Allopolyploid Coffee Genome (Coffea arabica L.

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Philippe Lashermes

2016-09-01

Full Text Available Allopolyploidization is a biological process that has played a major role in plant speciation and evolution. Genomic changes are common consequences of polyploidization, but their dynamics over time are still poorly understood. Coffea arabica, a recently formed allotetraploid, was chosen to study genetic changes that accompany allopolyploid formation. Both RNA-seq and DNA-seq data were generated from two genetically distant C. arabica accessions. Genomic structural variation was investigated using C. canephora, one of its diploid progenitors, as reference genome. The fate of 9047 duplicate homeologous genes was inferred and compared between the accessions. The pattern of SNP density along the reference genome was consistent with the allopolyploid structure. Large genomic duplications or deletions were not detected. Two homeologous copies were retained and expressed in 96% of the genes analyzed. Nevertheless, duplicated genes were found to be affected by various genomic changes leading to homeolog loss or silencing. Genetic and epigenetic changes were evidenced that could have played a major role in the stabilization of the unique ancestral allotetraploid and its subsequent diversification. While the early evolution of C. arabica mainly involved homeologous crossover exchanges, the later stage appears to have relied on more gradual evolution involving gene conversion and homeolog silencing.

Relationships between coastal bacterioplankton growth rates and biomass production: comparison of leucine and thymidine uptake with single-cell physiological characteristics.

Science.gov (United States)

Franco-Vidal, Leticia; Morán, Xosé Anxelu G

2011-02-01

Specific growth rates of heterotrophic bacterioplankton have been frequently estimated from in situ bacterial production (BP) to biomass (BB) ratios, using a series of assumptions that may result in serious discrepancies with values obtained from predator-free cultures. Here, we used both types of approaches together with a comprehensive assessment of single-cell physiological characteristics (membrane integrity, nucleic acid content, and active respiration) of coastal bacterioplankton during a complete annual cycle (February 2007-January 2008) in the southern Bay of Biscay off Xixón, Spain. Both leucine and thymidine incorporation rates were used in conjunction with empirical tracer to carbon or cells conversion factors (eCFs) to accurately derive BP. Leu and TdR incorporation rates covaried year-round, as did the corresponding eCFs at 0 and 50 m depth. eCFs peaked in autumn, with mean annual values close to the theoretical ones (3.4 kg C mol Leu(-1) and 2.0 × 10(18) cells mol TdR(-1)). Bacterial abundance (0.2-1.5 × 10(6) cells L(-1)) showed a bimodal distribution with maxima in May and October and minima in March. Live (membrane-intact) cells dominated year-round (79-97%), with high nucleic acid cells (42-88%) and actively respiring bacteria (CTC+, 1-16%) showing distinct surface maxima in April and July, respectively. BB (557-1,558 mg C m(-2)) and BP (7-139 mg C m(-2) day(-1)) presented two distinct peaks in spring and autumn, both of similar size due to a strong upwelling event observed in September. Specific growth rates (0.35-3.8 day(-1)) were one order of magnitude higher in predator-free incubations than bacterial turnover rates derived from integrated BP:BB ratios (0.01-0.16 and 0.01-0.09 day(-1), for Leu and TdR, respectively) and were not correlated, probably due to a significant contribution of low activity cells to total standing stocks. The Leu:TdR molar ratio averaged for the water column (6.6-25.5) decreased significantly with higher integrated

Development of genome- and transcriptome-derived microsatellites in related species of snapping shrimps with highly duplicated genomes.

Science.gov (United States)

Gaynor, Kaitlyn M; Solomon, Joseph W; Siller, Stefanie; Jessell, Linnet; Duffy, J Emmett; Rubenstein, Dustin R

2017-11-01

Molecular markers are powerful tools for studying patterns of relatedness and parentage within populations and for making inferences about social evolution. However, the development of molecular markers for simultaneous study of multiple species presents challenges, particularly when species exhibit genome duplication or polyploidy. We developed microsatellite markers for Synalpheus shrimp, a genus in which species exhibit not only great variation in social organization, but also interspecific variation in genome size and partial genome duplication. From the four primary clades within Synalpheus, we identified microsatellites in the genomes of four species and in the consensus transcriptome of two species. Ultimately, we designed and tested primers for 143 microsatellite markers across 25 species. Although the majority of markers were disomic, many markers were polysomic for certain species. Surprisingly, we found no relationship between genome size and the number of polysomic markers. As expected, markers developed for a given species amplified better for closely related species than for more distant relatives. Finally, the markers developed from the transcriptome were more likely to work successfully and to be disomic than those developed from the genome, suggesting that consensus transcriptomes are likely to be conserved across species. Our findings suggest that the transcriptome, particularly consensus sequences from multiple species, can be a valuable source of molecular markers for taxa with complex, duplicated genomes. © 2017 John Wiley & Sons Ltd.

Comprehensive genomic characterization of campylobacter genus reveals some underlying mechanisms for its genomic diversification.

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Yizhuang Zhou

Full Text Available Campylobacter species.are phenotypically diverse in many aspects including host habitats and pathogenicities, which demands comprehensive characterization of the entire Campylobacter genus to study their underlying genetic diversification. Up to now, 34 Campylobacter strains have been sequenced and published in public databases, providing good opportunity to systemically analyze their genomic diversities. In this study, we first conducted genomic characterization, which includes genome-wide alignments, pan-genome analysis, and phylogenetic identification, to depict the genetic diversity of Campylobacter genus. Afterward, we improved the tetranucleotide usage pattern-based naïve Bayesian classifier to identify the abnormal composition fragments (ACFs, fragments with significantly different tetranucleotide frequency profiles from its genomic tetranucleotide frequency profiles including horizontal gene transfers (HGTs to explore the mechanisms for the genetic diversity of this organism. Finally, we analyzed the HGTs transferred via bacteriophage transductions. To our knowledge, this study is the first to use single nucleotide polymorphism information to construct liable microevolution phylogeny of 21 Campylobacter jejuni strains. Combined with the phylogeny of all the collected Campylobacter species based on genome-wide core gene information, comprehensive phylogenetic inference of all 34 Campylobacter organisms was determined. It was found that C. jejuni harbors a high fraction of ACFs possibly through intraspecies recombination, whereas other Campylobacter members possess numerous ACFs possibly via intragenus recombination. Furthermore, some Campylobacter strains have undergone significant ancient viral integration during their evolution process. The improved method is a powerful tool for bacterial genomic analysis. Moreover, the findings would provide useful information for future research on Campylobacter genus.

A unified framework for haplotype inference in nuclear families.

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Iliadis, Alexandros; Anastassiou, Dimitris; Wang, Xiaodong

2012-07-01

Many large genome-wide association studies include nuclear families with more than one child (trio families), allowing for analysis of differences between siblings (sib pair analysis). Statistical power can be increased when haplotypes are used instead of genotypes. Currently, haplotype inference in families with more than one child can be performed either using the familial information or statistical information derived from the population samples but not both. Building on our recently proposed tree-based deterministic framework (TDS) for trio families, we augment its applicability to general nuclear families. We impose a minimum recombinant approach locally and independently on each multiple children family, while resorting to the population-derived information to solve the remaining ambiguities. Thus our framework incorporates all available information (familial and population) in a given study. We demonstrate that using all the constraints in our approach we can have gains in the accuracy as opposed to breaking the multiple children families to separate trios and resorting to a trio inference algorithm or phasing each family in isolation. We believe that our proposed framework could be the method of choice for haplotype inference in studies that include nuclear families with multiple children. Our software (tds2.0) is downloadable from www.ee.columbia.edu/∼anastas/tds. © 2012 The Authors Annals of Human Genetics © 2012 Blackwell Publishing Ltd/University College London.

Integrative Modeling and Inference in High Dimensional Genomic and Metabolic Data

DEFF Research Database (Denmark)

Brink-Jensen, Kasper

in Manuscript I preserves the attributes of the compounds found in LC–MS samples while identifying genes highly associated with these. The main obstacles that must be overcome with this approach are dimension reduction and variable selection, here done with PARAFAC and LASSO respectively. One important drawback...... of the LASSO has been the lack of inference, the variables selected could potentially just be the most important from a set of non–important variables. Manuscript II addresses this problem with a permutation based significance test for the variables chosen by the LASSO. Once a set of relevant variables has......, particularly it scales to many lists and it provides an intuitive interpretation of the measure....

Comparative Genomics of the Bacterial Genus Streptococcus Illuminates Evolutionary Implications of Species Groups

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Gao, Xiao-Yang; Zhi, Xiao-Yang; Li, Hong-Wei; Klenk, Hans-Peter; Li, Wen-Jun

2014-01-01

Members of the genus Streptococcus within the phylum Firmicutes are among the most diverse and significant zoonotic pathogens. This genus has gone through considerable taxonomic revision due to increasing improvements of chemotaxonomic approaches, DNA hybridization and 16S rRNA gene sequencing. It is proposed to place the majority of streptococci into “species groups”. However, the evolutionary implications of species groups are not clear presently. We use comparative genomic approaches to yield a better understanding of the evolution of Streptococcus through genome dynamics, population structure, phylogenies and virulence factor distribution of species groups. Genome dynamics analyses indicate that the pan-genome size increases with the addition of newly sequenced strains, while the core genome size decreases with sequential addition at the genus level and species group level. Population structure analysis reveals two distinct lineages, one including Pyogenic, Bovis, Mutans and Salivarius groups, and the other including Mitis, Anginosus and Unknown groups. Phylogenetic dendrograms show that species within the same species group cluster together, and infer two main clades in accordance with population structure analysis. Distribution of streptococcal virulence factors has no obvious patterns among the species groups; however, the evolution of some common virulence factors is congruous with the evolution of species groups, according to phylogenetic inference. We suggest that the proposed streptococcal species groups are reasonable from the viewpoints of comparative genomics; evolution of the genus is congruent with the individual evolutionary trajectories of different species groups. PMID:24977706

Species delimitation and interspecific relationships of the genus Orychophragmus (Brassicaceae inferred from whole chloroplast genomes

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Huan Hu

2016-12-01

Full Text Available IntroductionIt is rather difficult to delimit recently diverged species and construct their interspecific relationships because of insufficient informative variations of sampled DNA fragments (Schluter, 2000; Arnold, 2006. The genome-scale sequence variations were found to increase the phylogenetic resolutions of both high- and low-taxonomic groups (e.g., Yoder et al., 2013; Lamichhaney et al., 2015. It is still expensive to collect nuclear genome variations between species for most none-model genera without the reference genome. However, chloroplast genomes (plastome are relatively easy to be assembled to examine interspecific relationships for phylogenetic analyses, especially in addressing unresolved relationship at low taxonomic levels (Wu et al., 2010; Nock et al., 2011; Yang et al., 2013; Huang et al., 2014; Carbonell-Caballero et al., 2015. Plastomes are haploid with maternal inheritance in most angiosperms (Corriveau and Coleman, 1988; Zhang and Liu, 2003; Hagemann, 2004 and are highly conservative in gene order and genome structure with rare recombinations (Jansen et al., 2007; Moore et al., 2010. In this study, we aimed to examine species delimitation and interspecific relationships in Orychophragmus through assembling chloroplast genomes of multiple individuals of tentatively delimited species (Hu et al., 2015a. Orychophragmus is a small genus in the mustard family (Brassicaceae, Cruciferae distributed in northern, central, and southeastern China (Zhou et al., 2001. Its plants have been widely cultivated as ornamentals, vegetables, or source of seed oil (Sun et al., 2011. Despite controversial species delimitations in the genus (Zhou et al., 1987; Tan et al., 1998; Wu and Zhao, 2003; Al-Shehbaz and Yang, 2000; Zhou et al., 2001; Sun et al., 2012, our recent study based on nuclear (nr ITS sequence variations suggested the recognition of seven species (Hu et al., 2015a. Orychophragmus is sister to Sinalliaria, which is a genus endemic

An Improved Binary Differential Evolution Algorithm to Infer Tumor Phylogenetic Trees.

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Liang, Ying; Liao, Bo; Zhu, Wen

2017-01-01

Tumourigenesis is a mutation accumulation process, which is likely to start with a mutated founder cell. The evolutionary nature of tumor development makes phylogenetic models suitable for inferring tumor evolution through genetic variation data. Copy number variation (CNV) is the major genetic marker of the genome with more genes, disease loci, and functional elements involved. Fluorescence in situ hybridization (FISH) accurately measures multiple gene copy number of hundreds of single cells. We propose an improved binary differential evolution algorithm, BDEP, to infer tumor phylogenetic tree based on FISH platform. The topology analysis of tumor progression tree shows that the pathway of tumor subcell expansion varies greatly during different stages of tumor formation. And the classification experiment shows that tree-based features are better than data-based features in distinguishing tumor. The constructed phylogenetic trees have great performance in characterizing tumor development process, which outperforms other similar algorithms.

Impact of the choice of reference genome on the ability of the core genome SNV methodology to distinguish strains of Salmonella enterica serovar Heidelberg.

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Usongo, Valentine; Berry, Chrystal; Yousfi, Khadidja; Doualla-Bell, Florence; Labbé, Genevieve; Johnson, Roger; Fournier, Eric; Nadon, Celine; Goodridge, Lawrence; Bekal, Sadjia

2018-01-01

Salmonella enterica serovar Heidelberg (S. Heidelberg) is one of the top serovars causing human salmonellosis. The core genome single nucleotide variant pipeline (cgSNV) is one of several whole genome based sequence typing methods used for the laboratory investigation of foodborne pathogens. SNV detection using this method requires a reference genome. The purpose of this study was to investigate the impact of the choice of the reference genome on the cgSNV-informed phylogenetic clustering and inferred isolate relationships. We found that using a draft or closed genome of S. Heidelberg as reference did not impact the ability of the cgSNV methodology to differentiate among 145 S. Heidelberg isolates involved in foodborne outbreaks. We also found that using a distantly related genome such as S. Dublin as choice of reference led to a loss in resolution since some sporadic isolates were found to cluster together with outbreak isolates. In addition, the genetic distances between outbreak isolates as well as between outbreak and sporadic isolates were overall reduced when S. Dublin was used as the reference genome as opposed to S. Heidelberg.

Similar Ratios of Introns to Intergenic Sequence across Animal Genomes.

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Francis, Warren R; Wörheide, Gert

2017-06-01

One central goal of genome biology is to understand how the usage of the genome differs between organisms. Our knowledge of genome composition, needed for downstream inferences, is critically dependent on gene annotations, yet problems associated with gene annotation and assembly errors are usually ignored in comparative genomics. Here, we analyze the genomes of 68 species across 12 animal phyla and some single-cell eukaryotes for general trends in genome composition and transcription, taking into account problems of gene annotation. We show that, regardless of genome size, the ratio of introns to intergenic sequence is comparable across essentially all animals, with nearly all deviations dominated by increased intergenic sequence. Genomes of model organisms have ratios much closer to 1:1, suggesting that the majority of published genomes of nonmodel organisms are underannotated and consequently omit substantial numbers of genes, with likely negative impact on evolutionary interpretations. Finally, our results also indicate that most animals transcribe half or more of their genomes arguing against differences in genome usage between animal groups, and also suggesting that the transcribed portion is more dependent on genome size than previously thought. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

The complete mitochondrial genome of rabbit pinworm Passalurus ambiguus: genome characterization and phylogenetic analysis.

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Liu, Guo-Hua; Li, Sheng; Zou, Feng-Cai; Wang, Chun-Ren; Zhu, Xing-Quan

2016-01-01

Passalurus ambiguus (Nematda: Oxyuridae) is a common pinworm which parasitizes in the caecum and colon of rabbits. Despite its significance as a pathogen, the epidemiology, genetics, systematics, and biology of this pinworm remain poorly understood. In the present study, we sequenced the complete mitochondrial (mt) genome of P. ambiguus. The circular mt genome is 14,023 bp in size and encodes of 36 genes, including 12 protein-coding, two ribosomal RNA, and 22 transfer RNA genes. The mt gene order of P. ambiguus is the same as that of Wellcomia siamensis, but distinct from that of Enterobius vermicularis. Phylogenetic analyses based on concatenated amino acid sequences of 12 protein-coding genes by Bayesian inference (BI) showed that P. ambiguus was more closely related to W. siamensis than to E. vermicularis. This mt genome provides novel genetic markers for studying the molecular epidemiology, population genetics, systematics of pinworm of animals and humans, and should have implications for the diagnosis, prevention, and control of passaluriasis in rabbits and other animals.

Proteins Encoded in Genomic Regions Associated with Immune-Mediated Disease Physically Interact and Suggest Underlying Biology

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Rossin, Elizabeth J.; Hansen, Kasper Lage; Raychaudhuri, Soumya

2011-01-01

Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these r......Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed...... in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein-protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more...... that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non...

Quantitative measure of randomness and order for complete genomes

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Kong, Sing-Guan; Fan, Wen-Lang; Chen, Hong-Da; Wigger, Jan; Torda, Andrew E.; Lee, H. C.

2009-06-01

We propose an order index, ϕ , which gives a quantitative measure of randomness and order of complete genomic sequences. It maps genomes to a number from 0 (random and of infinite length) to 1 (fully ordered) and applies regardless of sequence length. The 786 complete genomic sequences in GenBank were found to have ϕ values in a very narrow range, ϕg=0.031-0.015+0.028 . We show this implies that genomes are halfway toward being completely random, or, at the “edge of chaos.” We further show that artificial “genomes” converted from literary classics have ϕ ’s that almost exactly coincide with ϕg , but sequences of low information content do not. We infer that ϕg represents a high information-capacity “fixed point” in sequence space, and that genomes are driven to it by the dynamics of a robust growth and evolution process. We show that a growth process characterized by random segmental duplication can robustly drive genomes to the fixed point.

The Capsaspora genome reveals a complex unicellular prehistory of animals.

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Suga, Hiroshi; Chen, Zehua; de Mendoza, Alex; Sebé-Pedrós, Arnau; Brown, Matthew W; Kramer, Eric; Carr, Martin; Kerner, Pierre; Vervoort, Michel; Sánchez-Pons, Núria; Torruella, Guifré; Derelle, Romain; Manning, Gerard; Lang, B Franz; Russ, Carsten; Haas, Brian J; Roger, Andrew J; Nusbaum, Chad; Ruiz-Trillo, Iñaki

2013-01-01

To reconstruct the evolutionary origin of multicellular animals from their unicellular ancestors, the genome sequences of diverse unicellular relatives are essential. However, only the genome of the choanoflagellate Monosiga brevicollis has been reported to date. Here we completely sequence the genome of the filasterean Capsaspora owczarzaki, the closest known unicellular relative of metazoans besides choanoflagellates. Analyses of this genome alter our understanding of the molecular complexity of metazoans' unicellular ancestors showing that they had a richer repertoire of proteins involved in cell adhesion and transcriptional regulation than previously inferred only with the choanoflagellate genome. Some of these proteins were secondarily lost in choanoflagellates. In contrast, most intercellular signalling systems controlling development evolved later concomitant with the emergence of the first metazoans. We propose that the acquisition of these metazoan-specific developmental systems and the co-option of pre-existing genes drove the evolutionary transition from unicellular protists to metazoans.

Rapid sequencing of the bamboo mitochondrial genome using Illumina technology and parallel episodic evolution of organelle genomes in grasses.

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Ma, Peng-Fei; Guo, Zhen-Hua; Li, De-Zhu

2012-01-01

Compared to their counterparts in animals, the mitochondrial (mt) genomes of angiosperms exhibit a number of unique features. However, unravelling their evolution is hindered by the few completed genomes, of which are essentially Sanger sequenced. While next-generation sequencing technologies have revolutionized chloroplast genome sequencing, they are just beginning to be applied to angiosperm mt genomes. Chloroplast genomes of grasses (Poaceae) have undergone episodic evolution and the evolutionary rate was suggested to be correlated between chloroplast and mt genomes in Poaceae. It is interesting to investigate whether correlated rate change also occurred in grass mt genomes as expected under lineage effects. A time-calibrated phylogenetic tree is needed to examine rate change. We determined a largely completed mt genome from a bamboo, Ferrocalamus rimosivaginus (Poaceae), through Illumina sequencing of total DNA. With combination of de novo and reference-guided assembly, 39.5-fold coverage Illumina reads were finally assembled into scaffolds totalling 432,839 bp. The assembled genome contains nearly the same genes as the completed mt genomes in Poaceae. For examining evolutionary rate in grass mt genomes, we reconstructed a phylogenetic tree including 22 taxa based on 31 mt genes. The topology of the well-resolved tree was almost identical to that inferred from chloroplast genome with only minor difference. The inconsistency possibly derived from long branch attraction in mtDNA tree. By calculating absolute substitution rates, we found significant rate change (∼4-fold) in mt genome before and after the diversification of Poaceae both in synonymous and nonsynonymous terms. Furthermore, the rate change was correlated with that of chloroplast genomes in grasses. Our result demonstrates that it is a rapid and efficient approach to obtain angiosperm mt genome sequences using Illumina sequencing technology. The parallel episodic evolution of mt and chloroplast

Utilizing genomics to study entomopathogenicity in the fungal phylum Entomophthoromycota

DEFF Research Database (Denmark)

de Fine Licht, Henrik Hjarvard; Hajek, Ann E.; Eilenberg, Jørgen

2016-01-01

primers, expressed sequence tag methodology or de novo transcriptome sequencing with molecular function inferred by homology analysis; and third, primarily forthcoming whole-genome sequencing data sets. Here we summarize the current genetic resources for Entomophthoromycota and identify research areas...

Collinearity analysis of Brassica A and C genomes based on an updated inferred unigene order

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Ian Bancroft

2015-06-01

Full Text Available This data article includes SNP scoring across lines of the Brassica napus TNDH population based on Illumina sequencing of mRNA, expanded to 75 lines. The 21, 323 mapped markers defined 887 recombination bins, representing an updated genetic linkage map for the species. Based on this new map, 5 genome sequence scaffolds were split and the order and orientation of scaffolds updated to establish a new pseudomolecule specification. The order of unigenes and SNP array probes within these pseudomolecules was determined. Unigenes were assessed for sequence similarity to the A and C genomes. The 57, 246 that mapped to both enabled the collinearity of the A and C genomes to be illustrated graphically. Although the great majority was in collinear positions, some were not. Analyses of 60 such instances are presented, suggesting that the breakdown in collinearity was largely due to either the absence of the homoeologue on one genome (resulting in sequence match to a paralogue or multiple similar sequences being present. The mRNAseq datasets for the TNDH lines are available from the SRA repository (ERA283648; the remaining datasets are supplied with this article.

KGCAK: a K-mer based database for genome-wide phylogeny and complexity evaluation.

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Wang, Dapeng; Xu, Jiayue; Yu, Jun

2015-09-16

The K-mer approach, treating genomic sequences as simple characters and counting the relative abundance of each string upon a fixed K, has been extensively applied to phylogeny inference for genome assembly, annotation, and comparison. To meet increasing demands for comparing large genome sequences and to promote the use of the K-mer approach, we develop a versatile database, KGCAK ( http://kgcak.big.ac.cn/KGCAK/ ), containing ~8,000 genomes that include genome sequences of diverse life forms (viruses, prokaryotes, protists, animals, and plants) and cellular organelles of eukaryotic lineages. It builds phylogeny based on genomic elements in an alignment-free fashion and provides in-depth data processing enabling users to compare the complexity of genome sequences based on K-mer distribution. We hope that KGCAK becomes a powerful tool for exploring relationship within and among groups of species in a tree of life based on genomic data.

Reconstructing relative genome size of vascular plants through geological time.

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Lomax, Barry H; Hilton, Jason; Bateman, Richard M; Upchurch, Garland R; Lake, Janice A; Leitch, Ilia J; Cromwell, Avery; Knight, Charles A

2014-01-01

The strong positive relationship evident between cell and genome size in both animals and plants forms the basis of using the size of stomatal guard cells as a proxy to track changes in plant genome size through geological time. We report for the first time a taxonomic fine-scale investigation into changes in stomatal guard-cell length and use these data to infer changes in genome size through the evolutionary history of land plants. Our data suggest that many of the earliest land plants had exceptionally large genome sizes and that a predicted overall trend of increasing genome size within individual lineages through geological time is not supported. However, maximum genome size steadily increases from the Mississippian (c. 360 million yr ago (Ma)) to the present. We hypothesise that the functional relationship between stomatal size, genome size and atmospheric CO2 may contribute to the dichotomy reported between preferential extinction of neopolyploids and the prevalence of palaeopolyploidy observed in DNA sequence data of extant vascular plants. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Permanent draft genomes of the three Rhodopirellula baltica strains SH28, SWK14 and WH47.

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Richter, Michael; Richter-Heitmann, Tim; Klindworth, Anna; Wegner, Carl-Eric; Frank, Carsten S; Harder, Jens; Glöckner, Frank Oliver

2014-02-01

The genomes of three Rhodopirellula baltica strains were sequenced as permanent drafts to complement the full genome sequence of the type strain R. baltica SH1(T). The isolates are part of a larger study to infer the biogeography of Rhodopirellula species in European marine waters, as well as to amend the genus description of R. baltica. This genomics resource article is the first of a series of five publications reporting in total eight new permanent daft genomes of Rhodopirellula species. Copyright © 2013 Elsevier B.V. All rights reserved.

The Amborella Genome and the Evolution of Flowering Plants

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Albert, Victor A.; Barbazuk, W. Bradley; dePamphilis, Claude W.

2013-01-01

Amborella trichopoda is strongly supported as the single living species of the sister lineage to all other extant flowering plants, providing a unique reference for inferring the genome content and structure of the most recent common ancestor (MRCA) of living angiosperms. Sequencing the Amborella...

Temporal and vertical distributions of bacterioplankton at the Gray's Reef National Marine Sanctuary.

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Lu, Xinxin; Sun, Shulei; Zhang, Yu-Qin; Hollibaugh, James T; Mou, Xiaozhen

2015-02-01

Large spatial scales and long-term shifts of bacterial community composition (BCC) in the open ocean can often be reliably predicted based on the dynamics of physical-chemical variables. The power of abiotic factors in shaping BCC on shorter time scales in shallow estuarine mixing zones is less clear. We examined the diurnal variation in BCC at different water depths in the spring and fall of 2011 at a station in the Gray's Reef National Marine Sanctuary (GRNMS). This site is located in the transition zone between the estuarine plume and continental shelf waters of the South Atlantic Bight. A total of 234,516 pyrotag sequences of bacterial 16S rRNA genes were recovered; they were taxonomically affiliated with >200 families of 23 bacterial phyla. Nonmetric multidimensional scaling analysis revealed significant differences in BCC between spring and fall samples, likely due to seasonality in the concentrations of dissolved organic carbon and nitrate plus nitrite. Within each diurnal sampling, BCC differed significantly by depth only in the spring and differed significantly between day and night only in the fall. The former variation largely tracked changes in light availability, while the latter was most correlated with concentrations of polyamines and chlorophyll a. Our results suggest that at the GRNMS, a coastal mixing zone, diurnal variation in BCC is attributable to the mixing of local and imported bacterioplankton rather than to bacterial growth in response to environmental changes. Our results also indicate that, like members of the Roseobacter clade, SAR11 bacteria may play an important role in processing dissolved organic material in coastal oceans. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Whole genome duplications and expansion of the vertebrate GATA transcription factor gene family

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Bowerman Bruce

2009-08-01

Full Text Available Abstract Background GATA transcription factors influence many developmental processes, including the specification of embryonic germ layers. The GATA gene family has significantly expanded in many animal lineages: whereas diverse cnidarians have only one GATA transcription factor, six GATA genes have been identified in many vertebrates, five in many insects, and eleven to thirteen in Caenorhabditis nematodes. All bilaterian animal genomes have at least one member each of two classes, GATA123 and GATA456. Results We have identified one GATA123 gene and one GATA456 gene from the genomic sequence of two invertebrate deuterostomes, a cephalochordate (Branchiostoma floridae and a hemichordate (Saccoglossus kowalevskii. We also have confirmed the presence of six GATA genes in all vertebrate genomes, as well as additional GATA genes in teleost fish. Analyses of conserved sequence motifs and of changes to the exon-intron structure, and molecular phylogenetic analyses of these deuterostome GATA genes support their origin from two ancestral deuterostome genes, one GATA 123 and one GATA456. Comparison of the conserved genomic organization across vertebrates identified eighteen paralogous gene families linked to multiple vertebrate GATA genes (GATA paralogons, providing the strongest evidence yet for expansion of vertebrate GATA gene families via genome duplication events. Conclusion From our analysis, we infer the evolutionary birth order and relationships among vertebrate GATA transcription factors, and define their expansion via multiple rounds of whole genome duplication events. As the genomes of four independent invertebrate deuterostome lineages contain single copy GATA123 and GATA456 genes, we infer that the 0R (pre-genome duplication invertebrate deuterostome ancestor also had two GATA genes, one of each class. Synteny analyses identify duplications of paralogous chromosomal regions (paralogons, from single ancestral vertebrate GATA123 and GATA456

Entropic Inference

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Caticha, Ariel

2011-03-01

In this tutorial we review the essential arguments behing entropic inference. We focus on the epistemological notion of information and its relation to the Bayesian beliefs of rational agents. The problem of updating from a prior to a posterior probability distribution is tackled through an eliminative induction process that singles out the logarithmic relative entropy as the unique tool for inference. The resulting method of Maximum relative Entropy (ME), includes as special cases both MaxEnt and Bayes' rule, and therefore unifies the two themes of these workshops—the Maximum Entropy and the Bayesian methods—into a single general inference scheme.

Extreme Recombination Frequencies Shape Genome Variation and Evolution in the Honeybee, Apis mellifera

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Wallberg, Andreas; Glémin, Sylvain; Webster, Matthew T.

2015-01-01

Meiotic recombination is a fundamental cellular process, with important consequences for evolution and genome integrity. However, we know little about how recombination rates vary across the genomes of most species and the molecular and evolutionary determinants of this variation. The honeybee, Apis mellifera, has extremely high rates of meiotic recombination, although the evolutionary causes and consequences of this are unclear. Here we use patterns of linkage disequilibrium in whole genome resequencing data from 30 diploid honeybees to construct a fine-scale map of rates of crossing over in the genome. We find that, in contrast to vertebrate genomes, the recombination landscape is not strongly punctate. Crossover rates strongly correlate with levels of genetic variation, but not divergence, which indicates a pervasive impact of selection on the genome. Germ-line methylated genes have reduced crossover rate, which could indicate a role of methylation in suppressing recombination. Controlling for the effects of methylation, we do not infer a strong association between gene expression patterns and recombination. The site frequency spectrum is strongly skewed from neutral expectations in honeybees: rare variants are dominated by AT-biased mutations, whereas GC-biased mutations are found at higher frequencies, indicative of a major influence of GC-biased gene conversion (gBGC), which we infer to generate an allele fixation bias 5 – 50 times the genomic average estimated in humans. We uncover further evidence that this repair bias specifically affects transitions and favours fixation of CpG sites. Recombination, via gBGC, therefore appears to have profound consequences on genome evolution in honeybees and interferes with the process of natural selection. These findings have important implications for our understanding of the forces driving molecular evolution. PMID:25902173

Genetic Competence Drives Genome Diversity in Bacillus subtilis

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Chevreux, Bastien; Serra, Cláudia R; Schyns, Ghislain; Henriques, Adriano O

2018-01-01

Abstract Prokaryote genomes are the result of a dynamic flux of genes, with increases achieved via horizontal gene transfer and reductions occurring through gene loss. The ecological and selective forces that drive this genomic flexibility vary across species. Bacillus subtilis is a naturally competent bacterium that occupies various environments, including plant-associated, soil, and marine niches, and the gut of both invertebrates and vertebrates. Here, we quantify the genomic diversity of B. subtilis and infer the genome dynamics that explain the high genetic and phenotypic diversity observed. Phylogenomic and comparative genomic analyses of 42 B. subtilis genomes uncover a remarkable genome diversity that translates into a core genome of 1,659 genes and an asymptotic pangenome growth rate of 57 new genes per new genome added. This diversity is due to a large proportion of low-frequency genes that are acquired from closely related species. We find no gene-loss bias among wild isolates, which explains why the cloud genome, 43% of the species pangenome, represents only a small proportion of each genome. We show that B. subtilis can acquire xenologous copies of core genes that propagate laterally among strains within a niche. While not excluding the contributions of other mechanisms, our results strongly suggest a process of gene acquisition that is largely driven by competence, where the long-term maintenance of acquired genes depends on local and global fitness effects. This competence-driven genomic diversity provides B. subtilis with its generalist character, enabling it to occupy a wide range of ecological niches and cycle through them. PMID:29272410

More than one kind of inference: re-examining what's learned in feature inference and classification.

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Sweller, Naomi; Hayes, Brett K

2010-08-01

Three studies examined how task demands that impact on attention to typical or atypical category features shape the category representations formed through classification learning and inference learning. During training categories were learned via exemplar classification or by inferring missing exemplar features. In the latter condition inferences were made about missing typical features alone (typical feature inference) or about both missing typical and atypical features (mixed feature inference). Classification and mixed feature inference led to the incorporation of typical and atypical features into category representations, with both kinds of features influencing inferences about familiar (Experiments 1 and 2) and novel (Experiment 3) test items. Those in the typical inference condition focused primarily on typical features. Together with formal modelling, these results challenge previous accounts that have characterized inference learning as producing a focus on typical category features. The results show that two different kinds of inference learning are possible and that these are subserved by different kinds of category representations.

Perceptual inference.

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Aggelopoulos, Nikolaos C

2015-08-01

Perceptual inference refers to the ability to infer sensory stimuli from predictions that result from internal neural representations built through prior experience. Methods of Bayesian statistical inference and decision theory model cognition adequately by using error sensing either in guiding action or in "generative" models that predict the sensory information. In this framework, perception can be seen as a process qualitatively distinct from sensation, a process of information evaluation using previously acquired and stored representations (memories) that is guided by sensory feedback. The stored representations can be utilised as internal models of sensory stimuli enabling long term associations, for example in operant conditioning. Evidence for perceptual inference is contributed by such phenomena as the cortical co-localisation of object perception with object memory, the response invariance in the responses of some neurons to variations in the stimulus, as well as from situations in which perception can be dissociated from sensation. In the context of perceptual inference, sensory areas of the cerebral cortex that have been facilitated by a priming signal may be regarded as comparators in a closed feedback loop, similar to the better known motor reflexes in the sensorimotor system. The adult cerebral cortex can be regarded as similar to a servomechanism, in using sensory feedback to correct internal models, producing predictions of the outside world on the basis of past experience. Copyright © 2015 Elsevier Ltd. All rights reserved.

SEMANTIC PATCH INFERENCE

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Andersen, Jesper

2009-01-01

Collateral evolution the problem of updating several library-using programs in response to API changes in the used library. In this dissertation we address the issue of understanding collateral evolutions by automatically inferring a high-level specification of the changes evident in a given set ...... specifications inferred by spdiff in Linux are shown. We find that the inferred specifications concisely capture the actual collateral evolution performed in the examples....

Inference of RNA polymerase II transcription dynamics from chromatin immunoprecipitation time course data.

Directory of Open Access Journals (Sweden)

Ciira wa Maina

2014-05-01

Full Text Available Gene transcription mediated by RNA polymerase II (pol-II is a key step in gene expression. The dynamics of pol-II moving along the transcribed region influence the rate and timing of gene expression. In this work, we present a probabilistic model of transcription dynamics which is fitted to pol-II occupancy time course data measured using ChIP-Seq. The model can be used to estimate transcription speed and to infer the temporal pol-II activity profile at the gene promoter. Model parameters are estimated using either maximum likelihood estimation or via Bayesian inference using Markov chain Monte Carlo sampling. The Bayesian approach provides confidence intervals for parameter estimates and allows the use of priors that capture domain knowledge, e.g. the expected range of transcription speeds, based on previous experiments. The model describes the movement of pol-II down the gene body and can be used to identify the time of induction for transcriptionally engaged genes. By clustering the inferred promoter activity time profiles, we are able to determine which genes respond quickly to stimuli and group genes that share activity profiles and may therefore be co-regulated. We apply our methodology to biological data obtained using ChIP-seq to measure pol-II occupancy genome-wide when MCF-7 human breast cancer cells are treated with estradiol (E2. The transcription speeds we obtain agree with those obtained previously for smaller numbers of genes with the advantage that our approach can be applied genome-wide. We validate the biological significance of the pol-II promoter activity clusters by investigating cluster-specific transcription factor binding patterns and determining canonical pathway enrichment. We find that rapidly induced genes are enriched for both estrogen receptor alpha (ERα and FOXA1 binding in their proximal promoter regions.

Genome-Wide Prediction and Analysis of 3D-Domain Swapped Proteins in the Human Genome from Sequence Information.

Science.gov (United States)

Upadhyay, Atul Kumar; Sowdhamini, Ramanathan

2016-01-01

3D-domain swapping is one of the mechanisms of protein oligomerization and the proteins exhibiting this phenomenon have many biological functions. These proteins, which undergo domain swapping, have acquired much attention owing to their involvement in human diseases, such as conformational diseases, amyloidosis, serpinopathies, proteionopathies etc. Early realisation of proteins in the whole human genome that retain tendency to domain swap will enable many aspects of disease control management. Predictive models were developed by using machine learning approaches with an average accuracy of 78% (85.6% of sensitivity, 87.5% of specificity and an MCC value of 0.72) to predict putative domain swapping in protein sequences. These models were applied to many complete genomes with special emphasis on the human genome. Nearly 44% of the protein sequences in the human genome were predicted positive for domain swapping. Enrichment analysis was performed on the positively predicted sequences from human genome for their domain distribution, disease association and functional importance based on Gene Ontology (GO). Enrichment analysis was also performed to infer a better understanding of the functional importance of these sequences. Finally, we developed hinge region prediction, in the given putative domain swapped sequence, by using important physicochemical properties of amino acids.

Multimodel inference and adaptive management

Science.gov (United States)

Rehme, S.E.; Powell, L.A.; Allen, Craig R.

2011-01-01

Ecology is an inherently complex science coping with correlated variables, nonlinear interactions and multiple scales of pattern and process, making it difficult for experiments to result in clear, strong inference. Natural resource managers, policy makers, and stakeholders rely on science to provide timely and accurate management recommendations. However, the time necessary to untangle the complexities of interactions within ecosystems is often far greater than the time available to make management decisions. One method of coping with this problem is multimodel inference. Multimodel inference assesses uncertainty by calculating likelihoods among multiple competing hypotheses, but multimodel inference results are often equivocal. Despite this, there may be pressure for ecologists to provide management recommendations regardless of the strength of their study’s inference. We reviewed papers in the Journal of Wildlife Management (JWM) and the journal Conservation Biology (CB) to quantify the prevalence of multimodel inference approaches, the resulting inference (weak versus strong), and how authors dealt with the uncertainty. Thirty-eight percent and 14%, respectively, of articles in the JWM and CB used multimodel inference approaches. Strong inference was rarely observed, with only 7% of JWM and 20% of CB articles resulting in strong inference. We found the majority of weak inference papers in both journals (59%) gave specific management recommendations. Model selection uncertainty was ignored in most recommendations for management. We suggest that adaptive management is an ideal method to resolve uncertainty when research results in weak inference.

RAD-seq derived genome-wide nuclear markers resolve the phylogeny of tunas

KAUST Repository

Díaz-Arce, Natalia

2016-06-07

Although species from the genus Thunnus include some of the most commercially important and most severely overexploited fishes, the phylogeny of this genus is still unresolved, hampering evolutionary and traceability studies that could help improve conservation and management strategies for these species. Previous attempts based on mitochondrial and nuclear markers were unsuccessful in inferring a congruent and reliable phylogeny, probably due to mitochondrial introgression events and lack of enough phylogenetically informative markers. Here we infer the first genome-wide nuclear marker-based phylogeny of tunas using restriction site associated DNA sequencing (RAD-seq) data. Our results, derived from phylogenomic inferences obtained from 128 nucleotide matrices constructed using alternative data assembly procedures, support a single Thunnus evolutionary history that challenges previous assumptions based on morphological and molecular data.

Seasonal and spatial distribution of Bacterioplankton in a fluvial-lagunar system of a tropical region: density, biomass, cellular volume and morphologic variation

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Magnólia Fernandes Florêncio de Araújo

2008-02-01

Full Text Available The temporal and spatial fluctuations of Bacterioplankton in a fluvial-lagunar system of a tropical region (Pitimbu River and Jiqui Lake, RN were studied during the dry and the rainy periods. The bacterial abundance varied from 2.67 to 5.1 Cells10(7mL-1 and did not show a typical temporal variation, presenting only small oscillations between the rainy and the dry periods. The bacterial biomass varied from 123 µgC L-1 to 269 µgC L-1 in the sampling sites and the average cellular volume varied from 0.12 to 0.54µm³, showing a predominance of the rods. The temperature showed a positive correlation with the cellular volume of the rods (R=0.55; p=0.02 and vibrio (R=0.53; p=0.03. Significant spatial differences of biomass (Mann Whitney: p=0.01 and cellular volume of the morphotypes (Mann Whitney: p=0.003 were found between the sampling sites. The strong positive correlations of the water temperature and oxygen with bacterioplankton showed a probable high bacterial activity in this system.A variação temporal e espacial do bacterioplâncton em um sistema fluvial-lagunar de região tropical foi estudada em períodos seco e chuvoso. As médias da abundância bacteriana variaram de 2,67 a 5,1 x 10(7 e não exibiram uma variação temporal marcante, tendo apresentado apenas pequenas oscilações entre os períodos chuvoso e seco. A biomassa bacteriana variou de 123 µg C L-1 a 269 µg C L-1 entre os locais de coleta e o volume celular médio de 0,12µm³ a 0,54µm³, ocorrendo predominância de bacilos. A temperatura mostrou correlação positiva com o volume celular de bacilos (R=0,55; p=0,02 e de vibriões (R=0,53; p=0,03. Foram encontradas diferenças espaciais significativas de biomassa (Mann Whitney: p=0,01 e volume celular dos morfotipos (Mann Whitney: p= 0,003, entre os locais de coleta. As fortes correlações positivas da temperatura da água e do oxigênio, com o bacterioplâncton, são sugestivas de uma provavelmente elevada atividade

Genome sequence data from 17 accessions of Ensete ventricosum, a staple food crop for millions in Ethiopia

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Zerihun Yemataw

2018-06-01

Full Text Available We present raw sequence reads and genome assemblies derived from 17 accessions of the Ethiopian orphan crop plant enset (Ensete ventricosum (Welw. Cheesman using the Illumina HiSeq and MiSeq platforms. Also presented is a catalogue of single-nucleotide polymorphisms inferred from the sequence data at an average density of approximately one per kilobase of genomic DNA.

Nannochloropsis genomes reveal evolution of microalgal oleaginous traits.

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Dongmei Wang

2014-01-01

Full Text Available Oleaginous microalgae are promising feedstock for biofuels, yet the genetic diversity, origin and evolution of oleaginous traits remain largely unknown. Here we present a detailed phylogenomic analysis of five oleaginous Nannochloropsis species (a total of six strains and one time-series transcriptome dataset for triacylglycerol (TAG synthesis on one representative strain. Despite small genome sizes, high coding potential and relative paucity of mobile elements, the genomes feature small cores of ca. 2,700 protein-coding genes and a large pan-genome of >38,000 genes. The six genomes share key oleaginous traits, such as the enrichment of selected lipid biosynthesis genes and certain glycoside hydrolase genes that potentially shift carbon flux from chrysolaminaran to TAG synthesis. The eleven type II diacylglycerol acyltransferase genes (DGAT-2 in every strain, each expressed during TAG synthesis, likely originated from three ancient genomes, including the secondary endosymbiosis host and the engulfed green and red algae. Horizontal gene transfers were inferred in most lipid synthesis nodes with expanded gene doses and many glycoside hydrolase genes. Thus multiple genome pooling and horizontal genetic exchange, together with selective inheritance of lipid synthesis genes and species-specific gene loss, have led to the enormous genetic apparatus for oleaginousness and the wide genomic divergence among present-day Nannochloropsis. These findings have important implications in the screening and genetic engineering of microalgae for biofuels.

Exploring Protein Function Using the Saccharomyces Genome Database.

Science.gov (United States)

Wong, Edith D

2017-01-01

Elucidating the function of individual proteins will help to create a comprehensive picture of cell biology, as well as shed light on human disease mechanisms, possible treatments, and cures. Due to its compact genome, and extensive history of experimentation and annotation, the budding yeast Saccharomyces cerevisiae is an ideal model organism in which to determine protein function. This information can then be leveraged to infer functions of human homologs. Despite the large amount of research and biological data about S. cerevisiae, many proteins' functions remain unknown. Here, we explore ways to use the Saccharomyces Genome Database (SGD; http://www.yeastgenome.org ) to predict the function of proteins and gain insight into their roles in various cellular processes.

Accuracy of Demographic Inferences from the Site Frequency Spectrum: The Case of the Yoruba Population.

Science.gov (United States)

Lapierre, Marguerite; Lambert, Amaury; Achaz, Guillaume

2017-05-01

Some methods for demographic inference based on the observed genetic diversity of current populations rely on the use of summary statistics such as the Site Frequency Spectrum (SFS). Demographic models can be either model-constrained with numerous parameters, such as growth rates, timing of demographic events, and migration rates, or model-flexible, with an unbounded collection of piecewise constant sizes. It is still debated whether demographic histories can be accurately inferred based on the SFS. Here, we illustrate this theoretical issue on an example of demographic inference for an African population. The SFS of the Yoruba population (data from the 1000 Genomes Project) is fit to a simple model of population growth described with a single parameter ( e.g. , founding time). We infer a time to the most recent common ancestor of 1.7 million years (MY) for this population. However, we show that the Yoruba SFS is not informative enough to discriminate between several different models of growth. We also show that for such simple demographies, the fit of one-parameter models outperforms the stairway plot, a recently developed model-flexible method. The use of this method on simulated data suggests that it is biased by the noise intrinsically present in the data. Copyright © 2017 by the Genetics Society of America.

Arthropod phylogenetics in light of three novel millipede (myriapoda: diplopoda mitochondrial genomes with comments on the appropriateness of mitochondrial genome sequence data for inferring deep level relationships.

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Michael S Brewer

Full Text Available BACKGROUND: Arthropods are the most diverse group of eukaryotic organisms, but their phylogenetic relationships are poorly understood. Herein, we describe three mitochondrial genomes representing orders of millipedes for which complete genomes had not been characterized. Newly sequenced genomes are combined with existing data to characterize the protein coding regions of myriapods and to attempt to reconstruct the evolutionary relationships within the Myriapoda and Arthropoda. RESULTS: The newly sequenced genomes are similar to previously characterized millipede sequences in terms of synteny and length. Unique translocations occurred within the newly sequenced taxa, including one half of the Appalachioria falcifera genome, which is inverted with respect to other millipede genomes. Across myriapods, amino acid conservation levels are highly dependent on the gene region. Additionally, individual loci varied in the level of amino acid conservation. Overall, most gene regions showed low levels of conservation at many sites. Attempts to reconstruct the evolutionary relationships suffered from questionable relationships and low support values. Analyses of phylogenetic informativeness show the lack of signal deep in the trees (i.e., genes evolve too quickly. As a result, the myriapod tree resembles previously published results but lacks convincing support, and, within the arthropod tree, well established groups were recovered as polyphyletic. CONCLUSIONS: The novel genome sequences described herein provide useful genomic information concerning millipede groups that had not been investigated. Taken together with existing sequences, the variety of compositions and evolution of myriapod mitochondrial genomes are shown to be more complex than previously thought. Unfortunately, the use of mitochondrial protein-coding regions in deep arthropod phylogenetics appears problematic, a result consistent with previously published studies. Lack of phylogenetic

Arthropod phylogenetics in light of three novel millipede (myriapoda: diplopoda) mitochondrial genomes with comments on the appropriateness of mitochondrial genome sequence data for inferring deep level relationships.

Science.gov (United States)

Brewer, Michael S; Swafford, Lynn; Spruill, Chad L; Bond, Jason E

2013-01-01

Arthropods are the most diverse group of eukaryotic organisms, but their phylogenetic relationships are poorly understood. Herein, we describe three mitochondrial genomes representing orders of millipedes for which complete genomes had not been characterized. Newly sequenced genomes are combined with existing data to characterize the protein coding regions of myriapods and to attempt to reconstruct the evolutionary relationships within the Myriapoda and Arthropoda. The newly sequenced genomes are similar to previously characterized millipede sequences in terms of synteny and length. Unique translocations occurred within the newly sequenced taxa, including one half of the Appalachioria falcifera genome, which is inverted with respect to other millipede genomes. Across myriapods, amino acid conservation levels are highly dependent on the gene region. Additionally, individual loci varied in the level of amino acid conservation. Overall, most gene regions showed low levels of conservation at many sites. Attempts to reconstruct the evolutionary relationships suffered from questionable relationships and low support values. Analyses of phylogenetic informativeness show the lack of signal deep in the trees (i.e., genes evolve too quickly). As a result, the myriapod tree resembles previously published results but lacks convincing support, and, within the arthropod tree, well established groups were recovered as polyphyletic. The novel genome sequences described herein provide useful genomic information concerning millipede groups that had not been investigated. Taken together with existing sequences, the variety of compositions and evolution of myriapod mitochondrial genomes are shown to be more complex than previously thought. Unfortunately, the use of mitochondrial protein-coding regions in deep arthropod phylogenetics appears problematic, a result consistent with previously published studies. Lack of phylogenetic signal renders the resulting tree topologies as suspect

Highly variable rates of genome rearrangements between hemiascomycetous yeast lineages.

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2006-03-01

Full Text Available Hemiascomycete yeasts cover an evolutionary span comparable to that of the entire phylum of chordates. Since this group currently contains the largest number of complete genome sequences it presents unique opportunities to understand the evolution of genome organization in eukaryotes. We inferred rates of genome instability on all branches of a phylogenetic tree for 11 species and calculated species-specific rates of genome rearrangements. We characterized all inversion events that occurred within synteny blocks between six representatives of the different lineages. We show that the rates of macro- and microrearrangements of gene order are correlated within individual lineages but are highly variable across different lineages. The most unstable genomes correspond to the pathogenic yeasts Candida albicans and Candida glabrata. Chromosomal maps have been intensively shuffled by numerous interchromosomal rearrangements, even between species that have retained a very high physical fraction of their genomes within small synteny blocks. Despite this intensive reshuffling of gene positions, essential genes, which cluster in low recombination regions in the genome of Saccharomyces cerevisiae, tend to remain syntenic during evolution. This work reveals that the high plasticity of eukaryotic genomes results from rearrangement rates that vary between lineages but also at different evolutionary times of a given lineage.

Estimating gene gain and loss rates in the presence of error in genome assembly and annotation using CAFE 3.

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Han, Mira V; Thomas, Gregg W C; Lugo-Martinez, Jose; Hahn, Matthew W

2013-08-01

Current sequencing methods produce large amounts of data, but genome assemblies constructed from these data are often fragmented and incomplete. Incomplete and error-filled assemblies result in many annotation errors, especially in the number of genes present in a genome. This means that methods attempting to estimate rates of gene duplication and loss often will be misled by such errors and that rates of gene family evolution will be consistently overestimated. Here, we present a method that takes these errors into account, allowing one to accurately infer rates of gene gain and loss among genomes even with low assembly and annotation quality. The method is implemented in the newest version of the software package CAFE, along with several other novel features. We demonstrate the accuracy of the method with extensive simulations and reanalyze several previously published data sets. Our results show that errors in genome annotation do lead to higher inferred rates of gene gain and loss but that CAFE 3 sufficiently accounts for these errors to provide accurate estimates of important evolutionary parameters.

Optimal inference with suboptimal models: Addiction and active Bayesian inference

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Schwartenbeck, Philipp; FitzGerald, Thomas H.B.; Mathys, Christoph; Dolan, Ray; Wurst, Friedrich; Kronbichler, Martin; Friston, Karl

2015-01-01

When casting behaviour as active (Bayesian) inference, optimal inference is defined with respect to an agent’s beliefs – based on its generative model of the world. This contrasts with normative accounts of choice behaviour, in which optimal actions are considered in relation to the true structure of the environment – as opposed to the agent’s beliefs about worldly states (or the task). This distinction shifts an understanding of suboptimal or pathological behaviour away from aberrant inference as such, to understanding the prior beliefs of a subject that cause them to behave less ‘optimally’ than our prior beliefs suggest they should behave. Put simply, suboptimal or pathological behaviour does not speak against understanding behaviour in terms of (Bayes optimal) inference, but rather calls for a more refined understanding of the subject’s generative model upon which their (optimal) Bayesian inference is based. Here, we discuss this fundamental distinction and its implications for understanding optimality, bounded rationality and pathological (choice) behaviour. We illustrate our argument using addictive choice behaviour in a recently described ‘limited offer’ task. Our simulations of pathological choices and addictive behaviour also generate some clear hypotheses, which we hope to pursue in ongoing empirical work. PMID:25561321

A Molecular Phylogeny of Hemiptera Inferred from Mitochondrial Genome Sequences

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Song, Nan; Liang, Ai-Ping; Bu, Cui-Ping

2012-01-01

Classically, Hemiptera is comprised of two suborders: Homoptera and Heteroptera. Homoptera includes Cicadomorpha, Fulgoromorpha and Sternorrhyncha. However, according to previous molecular phylogenetic studies based on 18S rDNA, Fulgoromorpha has a closer relationship to Heteroptera than to other hemipterans, leaving Homoptera as paraphyletic. Therefore, the position of Fulgoromorpha is important for studying phylogenetic structure of Hemiptera. We inferred the evolutionary affiliations of twenty-five superfamilies of Hemiptera using mitochondrial protein-coding genes and rRNAs. We sequenced three mitogenomes, from Pyrops candelaria, Lycorma delicatula and Ricania marginalis, representing two additional families in Fulgoromorpha. Pyrops and Lycorma are representatives of an additional major family Fulgoridae in Fulgoromorpha, whereas Ricania is a second representative of the highly derived clade Ricaniidae. The organization and size of these mitogenomes are similar to those of the sequenced fulgoroid species. Our consensus phylogeny of Hemiptera largely supported the relationships (((Fulgoromorpha,Sternorrhyncha),Cicadomorpha),Heteroptera), and thus supported the classic phylogeny of Hemiptera. Selection of optimal evolutionary models (exclusion and inclusion of two rRNA genes or of third codon positions of protein-coding genes) demonstrated that rapidly evolving and saturated sites should be removed from the analyses. PMID:23144967

A molecular phylogeny of Hemiptera inferred from mitochondrial genome sequences.

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Nan Song

Full Text Available Classically, Hemiptera is comprised of two suborders: Homoptera and Heteroptera. Homoptera includes Cicadomorpha, Fulgoromorpha and Sternorrhyncha. However, according to previous molecular phylogenetic studies based on 18S rDNA, Fulgoromorpha has a closer relationship to Heteroptera than to other hemipterans, leaving Homoptera as paraphyletic. Therefore, the position of Fulgoromorpha is important for studying phylogenetic structure of Hemiptera. We inferred the evolutionary affiliations of twenty-five superfamilies of Hemiptera using mitochondrial protein-coding genes and rRNAs. We sequenced three mitogenomes, from Pyrops candelaria, Lycorma delicatula and Ricania marginalis, representing two additional families in Fulgoromorpha. Pyrops and Lycorma are representatives of an additional major family Fulgoridae in Fulgoromorpha, whereas Ricania is a second representative of the highly derived clade Ricaniidae. The organization and size of these mitogenomes are similar to those of the sequenced fulgoroid species. Our consensus phylogeny of Hemiptera largely supported the relationships (((Fulgoromorpha,Sternorrhyncha,Cicadomorpha,Heteroptera, and thus supported the classic phylogeny of Hemiptera. Selection of optimal evolutionary models (exclusion and inclusion of two rRNA genes or of third codon positions of protein-coding genes demonstrated that rapidly evolving and saturated sites should be removed from the analyses.

High-Resolution Replication Profiles Define the Stochastic Nature of Genome Replication Initiation and Termination

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Michelle Hawkins

2013-11-01

Full Text Available Eukaryotic genome replication is stochastic, and each cell uses a different cohort of replication origins. We demonstrate that interpreting high-resolution Saccharomyces cerevisiae genome replication data with a mathematical model allows quantification of the stochastic nature of genome replication, including the efficiency of each origin and the distribution of termination events. Single-cell measurements support the inferred values for stochastic origin activation time. A strain, in which three origins were inactivated, confirmed that the distribution of termination events is primarily dictated by the stochastic activation time of origins. Cell-to-cell variability in origin activity ensures that termination events are widely distributed across virtually the whole genome. We propose that the heterogeneity in origin usage contributes to genome stability by limiting potentially deleterious events from accumulating at particular loci.

Inference rule and problem solving

Energy Technology Data Exchange (ETDEWEB)

Goto, S

1982-04-01

Intelligent information processing signifies an opportunity of having man's intellectual activity executed on the computer, in which inference, in place of ordinary calculation, is used as the basic operational mechanism for such an information processing. Many inference rules are derived from syllogisms in formal logic. The problem of programming this inference function is referred to as a problem solving. Although logically inference and problem-solving are in close relation, the calculation ability of current computers is on a low level for inferring. For clarifying the relation between inference and computers, nonmonotonic logic has been considered. The paper deals with the above topics. 16 references.

Untangling Genomes from Metagenomes: Revealing an Uncultured Class of Marine Euryarchaeota

Science.gov (United States)

Iverson, Vaughn; Morris, Robert M.; Frazar, Christian D.; Berthiaume, Chris T.; Morales, Rhonda L.; Armbrust, E. Virginia

2012-02-01

Ecosystems are shaped by complex communities of mostly unculturable microbes. Metagenomes provide a fragmented view of such communities, but the ecosystem functions of major groups of organisms remain mysterious. To better characterize members of these communities, we developed methods to reconstruct genomes directly from mate-paired short-read metagenomes. We closed a genome representing the as-yet uncultured marine group II Euryarchaeota, assembled de novo from 1.7% of a metagenome sequenced from surface seawater. The genome describes a motile, photo-heterotrophic cell focused on degradation of protein and lipids and clarifies the origin of proteorhodopsin. It also demonstrates that high-coverage mate-paired sequence can overcome assembly difficulties caused by interstrain variation in complex microbial communities, enabling inference of ecosystem functions for uncultured members.

Knowledge and inference

CERN Document Server

Nagao, Makoto

1990-01-01

Knowledge and Inference discusses an important problem for software systems: How do we treat knowledge and ideas on a computer and how do we use inference to solve problems on a computer? The book talks about the problems of knowledge and inference for the purpose of merging artificial intelligence and library science. The book begins by clarifying the concept of """"knowledge"""" from many points of view, followed by a chapter on the current state of library science and the place of artificial intelligence in library science. Subsequent chapters cover central topics in the artificial intellig

Reconstructing transcriptional regulatory networks through genomics data

OpenAIRE

Sun, Ning; Zhao, Hongyu

2009-01-01

One central problem in biology is to understand how gene expression is regulated under different conditions. Microarray gene expression data and other high throughput data have made it possible to dissect transcriptional regulatory networks at the genomics level. Owing to the very large number of genes that need to be studied, the relatively small number of data sets available, the noise in the data and the different natures of the distinct data types, network inference presents great challen...

The African Genome Variation Project shapes medical genetics in Africa

Science.gov (United States)

Gurdasani, Deepti; Carstensen, Tommy; Tekola-Ayele, Fasil; Pagani, Luca; Tachmazidou, Ioanna; Hatzikotoulas, Konstantinos; Karthikeyan, Savita; Iles, Louise; Pollard, Martin O.; Choudhury, Ananyo; Ritchie, Graham R. S.; Xue, Yali; Asimit, Jennifer; Nsubuga, Rebecca N.; Young, Elizabeth H.; Pomilla, Cristina; Kivinen, Katja; Rockett, Kirk; Kamali, Anatoli; Doumatey, Ayo P.; Asiki, Gershim; Seeley, Janet; Sisay-Joof, Fatoumatta; Jallow, Muminatou; Tollman, Stephen; Mekonnen, Ephrem; Ekong, Rosemary; Oljira, Tamiru; Bradman, Neil; Bojang, Kalifa; Ramsay, Michele; Adeyemo, Adebowale; Bekele, Endashaw; Motala, Ayesha; Norris, Shane A.; Pirie, Fraser; Kaleebu, Pontiano; Kwiatkowski, Dominic; Tyler-Smith, Chris; Rotimi, Charles; Zeggini, Eleftheria; Sandhu, Manjinder S.

2015-01-01

Given the importance of Africa to studies of human origins and disease susceptibility, detailed characterization of African genetic diversity is needed. The African Genome Variation Project provides a resource with which to design, implement and interpret genomic studies in sub-Saharan Africa and worldwide. The African Genome Variation Project represents dense genotypes from 1,481 individuals and whole-genome sequences from 320 individuals across sub-Saharan Africa. Using this resource, we find novel evidence of complex, regionally distinct hunter-gatherer and Eurasian admixture across sub-Saharan Africa. We identify new loci under selection, including loci related to malaria susceptibility and hypertension. We show that modern imputation panels (sets of reference genotypes from which unobserved or missing genotypes in study sets can be inferred) can identify association signals at highly differentiated loci across populations in sub-Saharan Africa. Using whole-genome sequencing, we demonstrate further improvements in imputation accuracy, strengthening the case for large-scale sequencing efforts of diverse African haplotypes. Finally, we present an efficient genotype array design capturing common genetic variation in Africa.

The African Genome Variation Project shapes medical genetics in Africa.

Science.gov (United States)

Gurdasani, Deepti; Carstensen, Tommy; Tekola-Ayele, Fasil; Pagani, Luca; Tachmazidou, Ioanna; Hatzikotoulas, Konstantinos; Karthikeyan, Savita; Iles, Louise; Pollard, Martin O; Choudhury, Ananyo; Ritchie, Graham R S; Xue, Yali; Asimit, Jennifer; Nsubuga, Rebecca N; Young, Elizabeth H; Pomilla, Cristina; Kivinen, Katja; Rockett, Kirk; Kamali, Anatoli; Doumatey, Ayo P; Asiki, Gershim; Seeley, Janet; Sisay-Joof, Fatoumatta; Jallow, Muminatou; Tollman, Stephen; Mekonnen, Ephrem; Ekong, Rosemary; Oljira, Tamiru; Bradman, Neil; Bojang, Kalifa; Ramsay, Michele; Adeyemo, Adebowale; Bekele, Endashaw; Motala, Ayesha; Norris, Shane A; Pirie, Fraser; Kaleebu, Pontiano; Kwiatkowski, Dominic; Tyler-Smith, Chris; Rotimi, Charles; Zeggini, Eleftheria; Sandhu, Manjinder S

2015-01-15

Given the importance of Africa to studies of human origins and disease susceptibility, detailed characterization of African genetic diversity is needed. The African Genome Variation Project provides a resource with which to design, implement and interpret genomic studies in sub-Saharan Africa and worldwide. The African Genome Variation Project represents dense genotypes from 1,481 individuals and whole-genome sequences from 320 individuals across sub-Saharan Africa. Using this resource, we find novel evidence of complex, regionally distinct hunter-gatherer and Eurasian admixture across sub-Saharan Africa. We identify new loci under selection, including loci related to malaria susceptibility and hypertension. We show that modern imputation panels (sets of reference genotypes from which unobserved or missing genotypes in study sets can be inferred) can identify association signals at highly differentiated loci across populations in sub-Saharan Africa. Using whole-genome sequencing, we demonstrate further improvements in imputation accuracy, strengthening the case for large-scale sequencing efforts of diverse African haplotypes. Finally, we present an efficient genotype array design capturing common genetic variation in Africa.

Geometric statistical inference

International Nuclear Information System (INIS)

Periwal, Vipul

1999-01-01

A reparametrization-covariant formulation of the inverse problem of probability is explicitly solved for finite sample sizes. The inferred distribution is explicitly continuous for finite sample size. A geometric solution of the statistical inference problem in higher dimensions is outlined

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks

Science.gov (United States)

Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E.; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A.; Kellis, Manolis

2012-01-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein–protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level. PMID:22456606

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks.

Science.gov (United States)

Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A; Kellis, Manolis

2012-07-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein-protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level.

Integrated Genome-Based Studies of Shewanella Ecophysiology

Energy Technology Data Exchange (ETDEWEB)

Andrei L. Osterman, Ph.D.

2012-12-17

Integration of bioinformatics and experimental techniques was applied to mapping and characterization of the key components (pathways, enzymes, transporters, regulators) of the core metabolic machinery in Shewanella oneidensis and related species with main focus was on metabolic and regulatory pathways involved in utilization of various carbon and energy sources. Among the main accomplishments reflected in ten joint publications with other participants of Shewanella Federation are: (i) A systems-level reconstruction of carbohydrate utilization pathways in the genus of Shewanella (19 species). This analysis yielded reconstruction of 18 sugar utilization pathways including 10 novel pathway variants and prediction of > 60 novel protein families of enzymes, transporters and regulators involved in these pathways. Selected functional predictions were verified by focused biochemical and genetic experiments. Observed growth phenotypes were consistent with bioinformatic predictions providing strong validation of the technology and (ii) Global genomic reconstruction of transcriptional regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors, 8 riboswitches and 6 translational attenuators. Of those, 45 regulons were inferred directly from the genome context analysis, whereas others were propagated from previously characterized regulons in other species. Selected regulatory predictions were experimentally tested. Integration of this analysis with microarray data revealed overall consistency and provided additional layer of interactions between regulons. All the results were captured in the new database RegPrecise, which is a joint development with the LBNL team. A more detailed analysis of the individual subsystems, pathways and regulons in Shewanella spp included bioinfiormatics-based prediction and experimental characterization of: (i) N-Acetylglucosamine catabolic pathway; (ii)Lactate utilization machinery; (iii) Novel Nrt

Alignment-free microbial phylogenomics under scenarios of sequence divergence, genome rearrangement and lateral genetic transfer.

Science.gov (United States)

Bernard, Guillaume; Chan, Cheong Xin; Ragan, Mark A

2016-07-01

Alignment-free (AF) approaches have recently been highlighted as alternatives to methods based on multiple sequence alignment in phylogenetic inference. However, the sensitivity of AF methods to genome-scale evolutionary scenarios is little known. Here, using simulated microbial genome data we systematically assess the sensitivity of nine AF methods to three important evolutionary scenarios: sequence divergence, lateral genetic transfer (LGT) and genome rearrangement. Among these, AF methods are most sensitive to the extent of sequence divergence, less sensitive to low and moderate frequencies of LGT, and most robust against genome rearrangement. We describe the application of AF methods to three well-studied empirical genome datasets, and introduce a new application of the jackknife to assess node support. Our results demonstrate that AF phylogenomics is computationally scalable to multi-genome data and can generate biologically meaningful phylogenies and insights into microbial evolution.

Comparative Genomics of Vibrio cholerae O1 Isolated from Cholera Patients in Bangladesh

DEFF Research Database (Denmark)

Hossain, Zenat Zebin; Leekitcharoenphon, Pimlapas; Dalsgaard, Anders

patients was co-infected with two V. cholerae strains (VC-1 and VC-3). Major virulence factors, biotype and antimicrobial resistance genes were identified by WGS. A global phylogenetic tree was inferred using genome wide SNPs (Single Nucleotide Polymorphism) analysis. RESULTS: All the V. cholerae strains...

Mitochondrial genome sequences illuminate maternal lineages of conservation concern in a rare carnivore

Science.gov (United States)

Brian J. Knaus; Richard Cronn; Aaron Liston; Kristine Pilgrim; Michael K. Schwartz

2011-01-01

Science-based wildlife management relies on genetic information to infer population connectivity and identify conservation units. The most commonly used genetic marker for characterizing animal biodiversity and identifying maternal lineages is the mitochondrial genome. Mitochondrial genotyping figures prominently in conservation and management plans, with much of the...

Genomic legacy of the African cheetah, Acinonyx jubatus.

Science.gov (United States)

Dobrynin, Pavel; Liu, Shiping; Tamazian, Gaik; Xiong, Zijun; Yurchenko, Andrey A; Krasheninnikova, Ksenia; Kliver, Sergey; Schmidt-Küntzel, Anne; Koepfli, Klaus-Peter; Johnson, Warren; Kuderna, Lukas F K; García-Pérez, Raquel; Manuel, Marc de; Godinez, Ricardo; Komissarov, Aleksey; Makunin, Alexey; Brukhin, Vladimir; Qiu, Weilin; Zhou, Long; Li, Fang; Yi, Jian; Driscoll, Carlos; Antunes, Agostinho; Oleksyk, Taras K; Eizirik, Eduardo; Perelman, Polina; Roelke, Melody; Wildt, David; Diekhans, Mark; Marques-Bonet, Tomas; Marker, Laurie; Bhak, Jong; Wang, Jun; Zhang, Guojie; O'Brien, Stephen J

2015-12-10

Patterns of genetic and genomic variance are informative in inferring population history for human, model species and endangered populations. Here the genome sequence of wild-born African cheetahs reveals extreme genomic depletion in SNV incidence, SNV density, SNVs of coding genes, MHC class I and II genes, and mitochondrial DNA SNVs. Cheetah genomes are on average 95 % homozygous compared to the genomes of the outbred domestic cat (24.08 % homozygous), Virunga Mountain Gorilla (78.12 %), inbred Abyssinian cat (62.63 %), Tasmanian devil, domestic dog and other mammalian species. Demographic estimators impute two ancestral population bottlenecks: one >100,000 years ago coincident with cheetah migrations out of the Americas and into Eurasia and Africa, and a second 11,084-12,589 years ago in Africa coincident with late Pleistocene large mammal extinctions. MHC class I gene loss and dramatic reduction in functional diversity of MHC genes would explain why cheetahs ablate skin graft rejection among unrelated individuals. Significant excess of non-synonymous mutations in AKAP4 (pcheetah fixation of five function-damaging amino acid variants distinct from AKAP4 homologues of other Felidae or mammals; AKAP4 dysfunction may cause the cheetah's extremely high (>80 %) pleiomorphic sperm. The study provides an unprecedented genomic perspective for the rare cheetah, with potential relevance to the species' natural history, physiological adaptations and unique reproductive disposition.

Integration of steady-state and temporal gene expression data for the inference of gene regulatory networks.

Science.gov (United States)

Wang, Yi Kan; Hurley, Daniel G; Schnell, Santiago; Print, Cristin G; Crampin, Edmund J

2013-01-01

We develop a new regression algorithm, cMIKANA, for inference of gene regulatory networks from combinations of steady-state and time-series gene expression data. Using simulated gene expression datasets to assess the accuracy of reconstructing gene regulatory networks, we show that steady-state and time-series data sets can successfully be combined to identify gene regulatory interactions using the new algorithm. Inferring gene networks from combined data sets was found to be advantageous when using noisy measurements collected with either lower sampling rates or a limited number of experimental replicates. We illustrate our method by applying it to a microarray gene expression dataset from human umbilical vein endothelial cells (HUVECs) which combines time series data from treatment with growth factor TNF and steady state data from siRNA knockdown treatments. Our results suggest that the combination of steady-state and time-series datasets may provide better prediction of RNA-to-RNA interactions, and may also reveal biological features that cannot be identified from dynamic or steady state information alone. Finally, we consider the experimental design of genomics experiments for gene regulatory network inference and show that network inference can be improved by incorporating steady-state measurements with time-series data.

Goal inferences about robot behavior : goal inferences and human response behaviors

NARCIS (Netherlands)

Broers, H.A.T.; Ham, J.R.C.; Broeders, R.; De Silva, P.; Okada, M.

2014-01-01

This explorative research focused on the goal inferences human observers draw based on a robot's behavior, and the extent to which those inferences predict people's behavior in response to that robot. Results show that different robot behaviors cause different response behavior from people.

A unifying model of genome evolution under parsimony.

Science.gov (United States)

Paten, Benedict; Zerbino, Daniel R; Hickey, Glenn; Haussler, David

2014-06-19

Parsimony and maximum likelihood methods of phylogenetic tree estimation and parsimony methods for genome rearrangements are central to the study of genome evolution yet to date they have largely been pursued in isolation. We present a data structure called a history graph that offers a practical basis for the analysis of genome evolution. It conceptually simplifies the study of parsimonious evolutionary histories by representing both substitutions and double cut and join (DCJ) rearrangements in the presence of duplications. The problem of constructing parsimonious history graphs thus subsumes related maximum parsimony problems in the fields of phylogenetic reconstruction and genome rearrangement. We show that tractable functions can be used to define upper and lower bounds on the minimum number of substitutions and DCJ rearrangements needed to explain any history graph. These bounds become tight for a special type of unambiguous history graph called an ancestral variation graph (AVG), which constrains in its combinatorial structure the number of operations required. We finally demonstrate that for a given history graph G, a finite set of AVGs describe all parsimonious interpretations of G, and this set can be explored with a few sampling moves. This theoretical study describes a model in which the inference of genome rearrangements and phylogeny can be unified under parsimony.

Sauropod dinosaurs evolved moderately sized genomes unrelated to body size.

Science.gov (United States)

Organ, Chris L; Brusatte, Stephen L; Stein, Koen

2009-12-22

Sauropodomorph dinosaurs include the largest land animals to have ever lived, some reaching up to 10 times the mass of an African elephant. Despite their status defining the upper range for body size in land animals, it remains unknown whether sauropodomorphs evolved larger-sized genomes than non-avian theropods, their sister taxon, or whether a relationship exists between genome size and body size in dinosaurs, two questions critical for understanding broad patterns of genome evolution in dinosaurs. Here we report inferences of genome size for 10 sauropodomorph taxa. The estimates are derived from a Bayesian phylogenetic generalized least squares approach that generates posterior distributions of regression models relating genome size to osteocyte lacunae volume in extant tetrapods. We estimate that the average genome size of sauropodomorphs was 2.02 pg (range of species means: 1.77-2.21 pg), a value in the upper range of extant birds (mean = 1.42 pg, range: 0.97-2.16 pg) and near the average for extant non-avian reptiles (mean = 2.24 pg, range: 1.05-5.44 pg). The results suggest that the variation in size and architecture of genomes in extinct dinosaurs was lower than the variation found in mammals. A substantial difference in genome size separates the two major clades within dinosaurs, Ornithischia (large genomes) and Saurischia (moderate to small genomes). We find no relationship between body size and estimated genome size in extinct dinosaurs, which suggests that neutral forces did not dominate the evolution of genome size in this group.

Mixed integer linear programming for maximum-parsimony phylogeny inference.

Science.gov (United States)

Sridhar, Srinath; Lam, Fumei; Blelloch, Guy E; Ravi, R; Schwartz, Russell

2008-01-01

Reconstruction of phylogenetic trees is a fundamental problem in computational biology. While excellent heuristic methods are available for many variants of this problem, new advances in phylogeny inference will be required if we are to be able to continue to make effective use of the rapidly growing stores of variation data now being gathered. In this paper, we present two integer linear programming (ILP) formulations to find the most parsimonious phylogenetic tree from a set of binary variation data. One method uses a flow-based formulation that can produce exponential numbers of variables and constraints in the worst case. The method has, however, proven extremely efficient in practice on datasets that are well beyond the reach of the available provably efficient methods, solving several large mtDNA and Y-chromosome instances within a few seconds and giving provably optimal results in times competitive with fast heuristics than cannot guarantee optimality. An alternative formulation establishes that the problem can be solved with a polynomial-sized ILP. We further present a web server developed based on the exponential-sized ILP that performs fast maximum parsimony inferences and serves as a front end to a database of precomputed phylogenies spanning the human genome.

Entropic Inference

OpenAIRE

Caticha, Ariel

2010-01-01

In this tutorial we review the essential arguments behing entropic inference. We focus on the epistemological notion of information and its relation to the Bayesian beliefs of rational agents. The problem of updating from a prior to a posterior probability distribution is tackled through an eliminative induction process that singles out the logarithmic relative entropy as the unique tool for inference. The resulting method of Maximum relative Entropy (ME), includes as special cases both MaxEn...

A Statistical Framework for Microbial Source Attribution: Measuring Uncertainty in Host Transmission Events Inferred from Genetic Data (Part 2 of a 2 Part Report)

Energy Technology Data Exchange (ETDEWEB)

Allen, J; Velsko, S

2009-11-16

This report explores the question of whether meaningful conclusions can be drawn regarding the transmission relationship between two microbial samples on the basis of differences observed between the two sample's respective genomes. Unlike similar forensic applications using human DNA, the rapid rate of microbial genome evolution combined with the dynamics of infectious disease require a shift in thinking on what it means for two samples to 'match' in support of a forensic hypothesis. Previous outbreaks for SARS-CoV, FMDV and HIV were examined to investigate the question of how microbial sequence data can be used to draw inferences that link two infected individuals by direct transmission. The results are counter intuitive with respect to human DNA forensic applications in that some genetic change rather than exact matching improve confidence in inferring direct transmission links, however, too much genetic change poses challenges, which can weaken confidence in inferred links. High rates of infection coupled with relatively weak selective pressure observed in the SARS-CoV and FMDV data lead to fairly low confidence for direct transmission links. Confidence values for forensic hypotheses increased when testing for the possibility that samples are separated by at most a few intermediate hosts. Moreover, the observed outbreak conditions support the potential to provide high confidence values for hypothesis that exclude direct transmission links. Transmission inferences are based on the total number of observed or inferred genetic changes separating two sequences rather than uniquely weighing the importance of any one genetic mismatch. Thus, inferences are surprisingly robust in the presence of sequencing errors provided the error rates are randomly distributed across all samples in the reference outbreak database and the novel sequence samples in question. When the number of observed nucleotide mutations are limited due to characteristics of the

Determination of genetic relatedness from low-coverage human genome sequences using pedigree simulations.

Science.gov (United States)

Martin, Michael D; Jay, Flora; Castellano, Sergi; Slatkin, Montgomery

2017-08-01

We develop and evaluate methods for inferring relatedness among individuals from low-coverage DNA sequences of their genomes, with particular emphasis on sequences obtained from fossil remains. We suggest the major factors complicating the determination of relatedness among ancient individuals are sequencing depth, the number of overlapping sites, the sequencing error rate and the presence of contamination from present-day genetic sources. We develop a theoretical model that facilitates the exploration of these factors and their relative effects, via measurement of pairwise genetic distances, without calling genotypes, and determine the power to infer relatedness under various scenarios of varying sequencing depth, present-day contamination and sequencing error. The model is validated by a simulation study as well as the analysis of aligned sequences from present-day human genomes. We then apply the method to the recently published genome sequences of ancient Europeans, developing a statistical treatment to determine confidence in assigned relatedness that is, in some cases, more precise than previously reported. As the majority of ancient specimens are from animals, this method would be applicable to investigate kinship in nonhuman remains. The developed software grups (Genetic Relatedness Using Pedigree Simulations) is implemented in Python and freely available. © 2017 John Wiley & Sons Ltd.

MIRA: An R package for DNA methylation-based inference of regulatory activity.

Science.gov (United States)

Lawson, John T; Tomazou, Eleni M; Bock, Christoph; Sheffield, Nathan C

2018-03-01

DNA methylation contains information about the regulatory state of the cell. MIRA aggregates genome-scale DNA methylation data into a DNA methylation profile for independent region sets with shared biological annotation. Using this profile, MIRA infers and scores the collective regulatory activity for each region set. MIRA facilitates regulatory analysis in situations where classical regulatory assays would be difficult and allows public sources of open chromatin and protein binding regions to be leveraged for novel insight into the regulatory state of DNA methylation datasets. R package available on Bioconductor: http://bioconductor.org/packages/release/bioc/html/MIRA.html. nsheffield@virginia.edu.

Reveal, A General Reverse Engineering Algorithm for Inference of Genetic Network Architectures

Science.gov (United States)

Liang, Shoudan; Fuhrman, Stefanie; Somogyi, Roland

1998-01-01

Given the immanent gene expression mapping covering whole genomes during development, health and disease, we seek computational methods to maximize functional inference from such large data sets. Is it possible, in principle, to completely infer a complex regulatory network architecture from input/output patterns of its variables? We investigated this possibility using binary models of genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene expression. By systematically analyzing the mutual information between input states and output states, one is able to infer the sets of input elements controlling each element or gene in the network. This process is unequivocal and exact for complete state transition tables. We implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and found the problem to be tractable within the conditions tested so far. For n = 50 (elements) and k = 3 (inputs per element), the analysis of incomplete state transition tables (100 state transition pairs out of a possible 10(exp 15)) reliably produced the original rule and wiring sets. While this study is limited to synchronous Boolean networks, the algorithm is generalizable to include multi-state models, essentially allowing direct application to realistic biological data sets. The ability to adequately solve the inverse problem may enable in-depth analysis of complex dynamic systems in biology and other fields.

Inferring Phylogenetic Networks from Gene Order Data

Directory of Open Access Journals (Sweden)

Alexey Anatolievich Morozov

2013-01-01

Full Text Available Existing algorithms allow us to infer phylogenetic networks from sequences (DNA, protein or binary, sets of trees, and distance matrices, but there are no methods to build them using the gene order data as an input. Here we describe several methods to build split networks from the gene order data, perform simulation studies, and use our methods for analyzing and interpreting different real gene order datasets. All proposed methods are based on intermediate data, which can be generated from genome structures under study and used as an input for network construction algorithms. Three intermediates are used: set of jackknife trees, distance matrix, and binary encoding. According to simulations and case studies, the best intermediates are jackknife trees and distance matrix (when used with Neighbor-Net algorithm. Binary encoding can also be useful, but only when the methods mentioned above cannot be used.

The genome of the obligate intracellular parasite Trachipleistophora hominis: new insights into microsporidian genome dynamics and reductive evolution.

Directory of Open Access Journals (Sweden)

Eva Heinz

Full Text Available The dynamics of reductive genome evolution for eukaryotes living inside other eukaryotic cells are poorly understood compared to well-studied model systems involving obligate intracellular bacteria. Here we present 8.5 Mb of sequence from the genome of the microsporidian Trachipleistophora hominis, isolated from an HIV/AIDS patient, which is an outgroup to the smaller compacted-genome species that primarily inform ideas of evolutionary mode for these enormously successful obligate intracellular parasites. Our data provide detailed information on the gene content, genome architecture and intergenic regions of a larger microsporidian genome, while comparative analyses allowed us to infer genomic features and metabolism of the common ancestor of the species investigated. Gene length reduction and massive loss of metabolic capacity in the common ancestor was accompanied by the evolution of novel microsporidian-specific protein families, whose conservation among microsporidians, against a background of reductive evolution, suggests they may have important functions in their parasitic lifestyle. The ancestor had already lost many metabolic pathways but retained glycolysis and the pentose phosphate pathway to provide cytosolic ATP and reduced coenzymes, and it had a minimal mitochondrion (mitosome making Fe-S clusters but not ATP. It possessed bacterial-like nucleotide transport proteins as a key innovation for stealing host-generated ATP, the machinery for RNAi, key elements of the early secretory pathway, canonical eukaryotic as well as microsporidian-specific regulatory elements, a diversity of repetitive and transposable elements, and relatively low average gene density. Microsporidian genome evolution thus appears to have proceeded in at least two major steps: an ancestral remodelling of the proteome upon transition to intracellular parasitism that involved reduction but also selective expansion, followed by a secondary compaction of genome

Learning Convex Inference of Marginals

OpenAIRE

Domke, Justin

2012-01-01

Graphical models trained using maximum likelihood are a common tool for probabilistic inference of marginal distributions. However, this approach suffers difficulties when either the inference process or the model is approximate. In this paper, the inference process is first defined to be the minimization of a convex function, inspired by free energy approximations. Learning is then done directly in terms of the performance of the inference process at univariate marginal prediction. The main ...

Assembling networks of microbial genomes using linear programming.

Science.gov (United States)

Holloway, Catherine; Beiko, Robert G

2010-11-20

Microbial genomes exhibit complex sets of genetic affinities due to lateral genetic transfer. Assessing the relative contributions of parent-to-offspring inheritance and gene sharing is a vital step in understanding the evolutionary origins and modern-day function of an organism, but recovering and showing these relationships is a challenging problem. We have developed a new approach that uses linear programming to find between-genome relationships, by treating tables of genetic affinities (here, represented by transformed BLAST e-values) as an optimization problem. Validation trials on simulated data demonstrate the effectiveness of the approach in recovering and representing vertical and lateral relationships among genomes. Application of the technique to a set comprising Aquifex aeolicus and 75 other thermophiles showed an important role for large genomes as 'hubs' in the gene sharing network, and suggested that genes are preferentially shared between organisms with similar optimal growth temperatures. We were also able to discover distinct and common genetic contributors to each sequenced representative of genus Pseudomonas. The linear programming approach we have developed can serve as an effective inference tool in its own right, and can be an efficient first step in a more-intensive phylogenomic analysis.

Predicting DNA Methylation State of CpG Dinucleotide Using Genome Topological Features and Deep Networks.

Science.gov (United States)

Wang, Yiheng; Liu, Tong; Xu, Dong; Shi, Huidong; Zhang, Chaoyang; Mo, Yin-Yuan; Wang, Zheng

2016-01-22

The hypo- or hyper-methylation of the human genome is one of the epigenetic features of leukemia. However, experimental approaches have only determined the methylation state of a small portion of the human genome. We developed deep learning based (stacked denoising autoencoders, or SdAs) software named "DeepMethyl" to predict the methylation state of DNA CpG dinucleotides using features inferred from three-dimensional genome topology (based on Hi-C) and DNA sequence patterns. We used the experimental data from immortalised myelogenous leukemia (K562) and healthy lymphoblastoid (GM12878) cell lines to train the learning models and assess prediction performance. We have tested various SdA architectures with different configurations of hidden layer(s) and amount of pre-training data and compared the performance of deep networks relative to support vector machines (SVMs). Using the methylation states of sequentially neighboring regions as one of the learning features, an SdA achieved a blind test accuracy of 89.7% for GM12878 and 88.6% for K562. When the methylation states of sequentially neighboring regions are unknown, the accuracies are 84.82% for GM12878 and 72.01% for K562. We also analyzed the contribution of genome topological features inferred from Hi-C. DeepMethyl can be accessed at http://dna.cs.usm.edu/deepmethyl/.

Dynamics of genome rearrangement in bacterial populations.

Directory of Open Access Journals (Sweden)

Aaron E Darling

2008-07-01

Full Text Available Genome structure variation has profound impacts on phenotype in organisms ranging from microbes to humans, yet little is known about how natural selection acts on genome arrangement. Pathogenic bacteria such as Yersinia pestis, which causes bubonic and pneumonic plague, often exhibit a high degree of genomic rearrangement. The recent availability of several Yersinia genomes offers an unprecedented opportunity to study the evolution of genome structure and arrangement. We introduce a set of statistical methods to study patterns of rearrangement in circular chromosomes and apply them to the Yersinia. We constructed a multiple alignment of eight Yersinia genomes using Mauve software to identify 78 conserved segments that are internally free from genome rearrangement. Based on the alignment, we applied Bayesian statistical methods to infer the phylogenetic inversion history of Yersinia. The sampling of genome arrangement reconstructions contains seven parsimonious tree topologies, each having different histories of 79 inversions. Topologies with a greater number of inversions also exist, but were sampled less frequently. The inversion phylogenies agree with results suggested by SNP patterns. We then analyzed reconstructed inversion histories to identify patterns of rearrangement. We confirm an over-representation of "symmetric inversions"-inversions with endpoints that are equally distant from the origin of chromosomal replication. Ancestral genome arrangements demonstrate moderate preference for replichore balance in Yersinia. We found that all inversions are shorter than expected under a neutral model, whereas inversions acting within a single replichore are much shorter than expected. We also found evidence for a canonical configuration of the origin and terminus of replication. Finally, breakpoint reuse analysis reveals that inversions with endpoints proximal to the origin of DNA replication are nearly three times more frequent. Our findings

Some limitations of public sequence data for phylogenetic inference (in plants).

Science.gov (United States)

Hinchliff, Cody E; Smith, Stephen Andrew

2014-01-01

The GenBank database contains essentially all of the nucleotide sequence data generated for published molecular systematic studies, but for the majority of taxa these data remain sparse. GenBank has value for phylogenetic methods that leverage data-mining and rapidly improving computational methods, but the limits imposed by the sparse structure of the data are not well understood. Here we present a tree representing 13,093 land plant genera--an estimated 80% of extant plant diversity--to illustrate the potential of public sequence data for broad phylogenetic inference in plants, and we explore the limits to inference imposed by the structure of these data using theoretical foundations from phylogenetic data decisiveness. We find that despite very high levels of missing data (over 96%), the present data retain the potential to inform over 86.3% of all possible phylogenetic relationships. Most of these relationships, however, are informed by small amounts of data--approximately half are informed by fewer than four loci, and more than 99% are informed by fewer than fifteen. We also apply an information theoretic measure of branch support to assess the strength of phylogenetic signal in the data, revealing many poorly supported branches concentrated near the tips of the tree, where data are sparse and the limiting effects of this sparseness are stronger. We argue that limits to phylogenetic inference and signal imposed by low data coverage may pose significant challenges for comprehensive phylogenetic inference at the species level. Computational requirements provide additional limits for large reconstructions, but these may be overcome by methodological advances, whereas insufficient data coverage can only be remedied by additional sampling effort. We conclude that public databases have exceptional value for modern systematics and evolutionary biology, and that a continued emphasis on expanding taxonomic and genomic coverage will play a critical role in developing

DOSE RESPONSE FROM HIGH THROUGHPUT GENE EXPRESSION STUDIES AND THE INFLUENCE OF TIME AND CELL LINE ON INFERRED MODE OF ACTION BY ONTOLOGIC ENRICHMENT (SOT)

Science.gov (United States)

Gene expression with ontologic enrichment and connectivity mapping tools is widely used to infer modes of action (MOA) for therapeutic drugs. Despite progress in high-throughput (HT) genomic systems, strategies suitable to identify industrial chemical MOA are needed. The L1000 is...

Simple Math is Enough: Two Examples of Inferring Functional Associations from Genomic Data

Science.gov (United States)

Liang, Shoudan

2003-01-01

Non-random features in the genomic data are usually biologically meaningful. The key is to choose the feature well. Having a p-value based score prioritizes the findings. If two proteins share a unusually large number of common interaction partners, they tend to be involved in the same biological process. We used this finding to predict the functions of 81 un-annotated proteins in yeast.

Toward integration of genomic selection with crop modelling: the development of an integrated approach to predicting rice heading dates.

Science.gov (United States)

Onogi, Akio; Watanabe, Maya; Mochizuki, Toshihiro; Hayashi, Takeshi; Nakagawa, Hiroshi; Hasegawa, Toshihiro; Iwata, Hiroyoshi

2016-04-01

It is suggested that accuracy in predicting plant phenotypes can be improved by integrating genomic prediction with crop modelling in a single hierarchical model. Accurate prediction of phenotypes is important for plant breeding and management. Although genomic prediction/selection aims to predict phenotypes on the basis of whole-genome marker information, it is often difficult to predict phenotypes of complex traits in diverse environments, because plant phenotypes are often influenced by genotype-environment interaction. A possible remedy is to integrate genomic prediction with crop/ecophysiological modelling, which enables us to predict plant phenotypes using environmental and management information. To this end, in the present study, we developed a novel method for integrating genomic prediction with phenological modelling of Asian rice (Oryza sativa, L.), allowing the heading date of untested genotypes in untested environments to be predicted. The method simultaneously infers the phenological model parameters and whole-genome marker effects on the parameters in a Bayesian framework. By cultivating backcross inbred lines of Koshihikari × Kasalath in nine environments, we evaluated the potential of the proposed method in comparison with conventional genomic prediction, phenological modelling, and two-step methods that applied genomic prediction to phenological model parameters inferred from Nelder-Mead or Markov chain Monte Carlo algorithms. In predicting heading dates of untested lines in untested environments, the proposed and two-step methods tended to provide more accurate predictions than the conventional genomic prediction methods, particularly in environments where phenotypes from environments similar to the target environment were unavailable for training genomic prediction. The proposed method showed greater accuracy in prediction than the two-step methods in all cross-validation schemes tested, suggesting the potential of the integrated approach in

Genome sequence diversity and clues to the evolution of variola (smallpox) virus.

Science.gov (United States)

Esposito, Joseph J; Sammons, Scott A; Frace, A Michael; Osborne, John D; Olsen-Rasmussen, Melissa; Zhang, Ming; Govil, Dhwani; Damon, Inger K; Kline, Richard; Laker, Miriam; Li, Yu; Smith, Geoffrey L; Meyer, Hermann; Leduc, James W; Wohlhueter, Robert M

2006-08-11

Comparative genomics of 45 epidemiologically varied variola virus isolates from the past 30 years of the smallpox era indicate low sequence diversity, suggesting that there is probably little difference in the isolates' functional gene content. Phylogenetic clustering inferred three clades coincident with their geographical origin and case-fatality rate; the latter implicated putative proteins that mediate viral virulence differences. Analysis of the viral linear DNA genome suggests that its evolution involved direct descent and DNA end-region recombination events. Knowing the sequences will help understand the viral proteome and improve diagnostic test precision, therapeutics, and systems for their assessment.

Population structure of Atlantic Mackerel inferred from RAD-seq derived SNP markers: effects of sequence clustering parameters and hierarchical SNP selection

KAUST Repository

Rodríguez-Ezpeleta, Naiara

2016-03-03

Restriction-site associated DNA sequencing (RAD-seq) and related methods are revolutionizing the field of population genomics in non-model organisms as they allow generating an unprecedented number of single nucleotide polymorphisms (SNPs) even when no genomic information is available. Yet, RAD-seq data analyses rely on assumptions on nature and number of nucleotide variants present in a single locus, the choice of which may lead to an under- or overestimated number of SNPs and/or to incorrectly called genotypes. Using the Atlantic mackerel (Scomber scombrus L.) and a close relative, the Atlantic chub mackerel (Scomber colias), as case study, here we explore the sensitivity of population structure inferences to two crucial aspects in RAD-seq data analysis: the maximum number of mismatches allowed to merge reads into a locus and the relatedness of the individuals used for genotype calling and SNP selection. Our study resolves the population structure of the Atlantic mackerel, but, most importantly, provides insights into the effects of alternative RAD-seq data analysis strategies on population structure inferences that are directly applicable to other species.

Probabilistic inductive inference: a survey

OpenAIRE

Ambainis, Andris

2001-01-01

Inductive inference is a recursion-theoretic theory of learning, first developed by E. M. Gold (1967). This paper surveys developments in probabilistic inductive inference. We mainly focus on finite inference of recursive functions, since this simple paradigm has produced the most interesting (and most complex) results.

LAIT: a local ancestry inference toolkit.

Science.gov (United States)

Hui, Daniel; Fang, Zhou; Lin, Jerome; Duan, Qing; Li, Yun; Hu, Ming; Chen, Wei

2017-09-06

Inferring local ancestry in individuals of mixed ancestry has many applications, most notably in identifying disease-susceptible loci that vary among different ethnic groups. Many software packages are available for inferring local ancestry in admixed individuals. However, most of these existing software packages require specific formatted input files and generate output files in various types, yielding practical inconvenience. We developed a tool set, Local Ancestry Inference Toolkit (LAIT), which can convert standardized files into software-specific input file formats as well as standardize and summarize inference results for four popular local ancestry inference software: HAPMIX, LAMP, LAMP-LD, and ELAI. We tested LAIT using both simulated and real data sets and demonstrated that LAIT provides convenience to run multiple local ancestry inference software. In addition, we evaluated the performance of local ancestry software among different supported software packages, mainly focusing on inference accuracy and computational resources used. We provided a toolkit to facilitate the use of local ancestry inference software, especially for users with limited bioinformatics background.

Genomic characterization of Burkholderia pseudomallei isolates selected for medical countermeasures testing: comparative genomics associated with differential virulence.

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Jason W Sahl

Full Text Available Burkholderia pseudomallei is the causative agent of melioidosis and a potential bioterrorism agent. In the development of medical countermeasures against B. pseudomallei infection, the US Food and Drug Administration (FDA animal Rule recommends using well-characterized strains in animal challenge studies. In this study, whole genome sequence data were generated for 6 B. pseudomallei isolates previously identified as candidates for animal challenge studies; an additional 5 isolates were sequenced that were associated with human inhalational melioidosis. A core genome single nucleotide polymorphism (SNP phylogeny inferred from a concatenated SNP alignment from the 11 isolates sequenced in this study and a diverse global collection of isolates demonstrated the diversity of the proposed Animal Rule isolates. To understand the genomic composition of each isolate, a large-scale blast score ratio (LS-BSR analysis was performed on the entire pan-genome; this demonstrated the variable composition of genes across the panel and also helped to identify genes unique to individual isolates. In addition, a set of ~550 genes associated with pathogenesis in B. pseudomallei were screened against the 11 sequenced genomes with LS-BSR. Differential gene distribution for 54 virulence-associated genes was observed between genomes and three of these genes were correlated with differential virulence observed in animal challenge studies using BALB/c mice. Differentially conserved genes and SNPs associated with disease severity were identified and could be the basis for future studies investigating the pathogenesis of B. pseudomallei. Overall, the genetic characterization of the 11 proposed Animal Rule isolates provides context for future studies involving B. pseudomallei pathogenesis, differential virulence, and efficacy to therapeutics.

Clusters of orthologous genes for 41 archaeal genomes and implications for evolutionary genomics of archaea

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Wolf Yuri I

2007-11-01

Full Text Available Abstract Background An evolutionary classification of genes from sequenced genomes that distinguishes between orthologs and paralogs is indispensable for genome annotation and evolutionary reconstruction. Shortly after multiple genome sequences of bacteria, archaea, and unicellular eukaryotes became available, an attempt on such a classification was implemented in Clusters of Orthologous Groups of proteins (COGs. Rapid accumulation of genome sequences creates opportunities for refining COGs but also represents a challenge because of error amplification. One of the practical strategies involves construction of refined COGs for phylogenetically compact subsets of genomes. Results New Archaeal Clusters of Orthologous Genes (arCOGs were constructed for 41 archaeal genomes (13 Crenarchaeota, 27 Euryarchaeota and one Nanoarchaeon using an improved procedure that employs a similarity tree between smaller, group-specific clusters, semi-automatically partitions orthology domains in multidomain proteins, and uses profile searches for identification of remote orthologs. The annotation of arCOGs is a consensus between three assignments based on the COGs, the CDD database, and the annotations of homologs in the NR database. The 7538 arCOGs, on average, cover ~88% of the genes in a genome compared to a ~76% coverage in COGs. The finer granularity of ortholog identification in the arCOGs is apparent from the fact that 4538 arCOGs correspond to 2362 COGs; ~40% of the arCOGs are new. The archaeal gene core (protein-coding genes found in all 41 genome consists of 166 arCOGs. The arCOGs were used to reconstruct gene loss and gene gain events during archaeal evolution and gene sets of ancestral forms. The Last Archaeal Common Ancestor (LACA is conservatively estimated to possess 996 genes compared to 1245 and 1335 genes for the last common ancestors of Crenarchaeota and Euryarchaeota, respectively. It is inferred that LACA was a chemoautotrophic hyperthermophile

Bayesian statistical inference

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Bruno De Finetti

2017-04-01

Full Text Available This work was translated into English and published in the volume: Bruno De Finetti, Induction and Probability, Biblioteca di Statistica, eds. P. Monari, D. Cocchi, Clueb, Bologna, 1993.Bayesian statistical Inference is one of the last fundamental philosophical papers in which we can find the essential De Finetti's approach to the statistical inference.

Genome-Based Microbial Taxonomy Coming of Age.

Science.gov (United States)

Hugenholtz, Philip; Skarshewski, Adam; Parks, Donovan H

2016-06-01

Reconstructing the complete evolutionary history of extant life on our planet will be one of the most fundamental accomplishments of scientific endeavor, akin to the completion of the periodic table, which revolutionized chemistry. The road to this goal is via comparative genomics because genomes are our most comprehensive and objective evolutionary documents. The genomes of plant and animal species have been systematically targeted over the past decade to provide coverage of the tree of life. However, multicellular organisms only emerged in the last 550 million years of more than three billion years of biological evolution and thus comprise a small fraction of total biological diversity. The bulk of biodiversity, both past and present, is microbial. We have only scratched the surface in our understanding of the microbial world, as most microorganisms cannot be readily grown in the laboratory and remain unknown to science. Ground-breaking, culture-independent molecular techniques developed over the past 30 years have opened the door to this so-called microbial dark matter with an accelerating momentum driven by exponential increases in sequencing capacity. We are on the verge of obtaining representative genomes across all life for the first time. However, historical use of morphology, biochemical properties, behavioral traits, and single-marker genes to infer organismal relationships mean that the existing highly incomplete tree is riddled with taxonomic errors. Concerted efforts are now needed to synthesize and integrate the burgeoning genomic data resources into a coherent universal tree of life and genome-based taxonomy. Copyright © 2016 Cold Spring Harbor Laboratory Press; all rights reserved.

Phylogenetic relationship and virulence inference of Streptococcus Anginosus Group: curated annotation and whole-genome comparative analysis support distinct species designation

Science.gov (United States)

2013-01-01

Background The Streptococcus Anginosus Group (SAG) represents three closely related species of the viridans group streptococci recognized as commensal bacteria of the oral, gastrointestinal and urogenital tracts. The SAG also cause severe invasive infections, and are pathogens during cystic fibrosis (CF) pulmonary exacerbation. Little genomic information or description of virulence mechanisms is currently available for SAG. We conducted intra and inter species whole-genome comparative analyses with 59 publically available Streptococcus genomes and seven in-house closed high quality finished SAG genomes; S. constellatus (3), S. intermedius (2), and S. anginosus (2). For each SAG species, we sequenced at least one numerically dominant strain from CF airways recovered during acute exacerbation and an invasive, non-lung isolate. We also evaluated microevolution that occurred within two isolates that were cultured from one individual one year apart. Results The SAG genomes were most closely related to S. gordonii and S. sanguinis, based on shared orthologs and harbor a similar number of proteins within each COG category as other Streptococcus species. Numerous characterized streptococcus virulence factor homologs were identified within the SAG genomes including; adherence, invasion, spreading factors, LPxTG cell wall proteins, and two component histidine kinases known to be involved in virulence gene regulation. Mobile elements, primarily integrative conjugative elements and bacteriophage, account for greater than 10% of the SAG genomes. S. anginosus was the most variable species sequenced in this study, yielding both the smallest and the largest SAG genomes containing multiple genomic rearrangements, insertions and deletions. In contrast, within the S. constellatus and S. intermedius species, there was extensive continuous synteny, with only slight differences in genome size between strains. Within S. constellatus we were able to determine important SNPs and changes in

Is there a hierarchy of social inferences? The likelihood and speed of inferring intentionality, mind, and personality.

Science.gov (United States)

Malle, Bertram F; Holbrook, Jess

2012-04-01

People interpret behavior by making inferences about agents' intentionality, mind, and personality. Past research studied such inferences 1 at a time; in real life, people make these inferences simultaneously. The present studies therefore examined whether 4 major inferences (intentionality, desire, belief, and personality), elicited simultaneously in response to an observed behavior, might be ordered in a hierarchy of likelihood and speed. To achieve generalizability, the studies included a wide range of stimulus behaviors, presented them verbally and as dynamic videos, and assessed inferences both in a retrieval paradigm (measuring the likelihood and speed of accessing inferences immediately after they were made) and in an online processing paradigm (measuring the speed of forming inferences during behavior observation). Five studies provide evidence for a hierarchy of social inferences-from intentionality and desire to belief to personality-that is stable across verbal and visual presentations and that parallels the order found in developmental and primate research. (c) 2012 APA, all rights reserved.

Genomics of Rapid Incipient Speciation in Sympatric Threespine Stickleback.

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David A Marques

2016-02-01

Full Text Available Ecological speciation is the process by which reproductively isolated populations emerge as a consequence of divergent natural or ecologically-mediated sexual selection. Most genomic studies of ecological speciation have investigated allopatric populations, making it difficult to infer reproductive isolation. The few studies on sympatric ecotypes have focused on advanced stages of the speciation process after thousands of generations of divergence. As a consequence, we still do not know what genomic signatures of the early onset of ecological speciation look like. Here, we examined genomic differentiation among migratory lake and resident stream ecotypes of threespine stickleback reproducing in sympatry in one stream, and in parapatry in another stream. Importantly, these ecotypes started diverging less than 150 years ago. We obtained 34,756 SNPs with restriction-site associated DNA sequencing and identified genomic islands of differentiation using a Hidden Markov Model approach. Consistent with incipient ecological speciation, we found significant genomic differentiation between ecotypes both in sympatry and parapatry. Of 19 islands of differentiation resisting gene flow in sympatry, all were also differentiated in parapatry and were thus likely driven by divergent selection among habitats. These islands clustered in quantitative trait loci controlling divergent traits among the ecotypes, many of them concentrated in one region with low to intermediate recombination. Our findings suggest that adaptive genomic differentiation at many genetic loci can arise and persist in sympatry at the very early stage of ecotype divergence, and that the genomic architecture of adaptation may facilitate this.

A Secure Alignment Algorithm for Mapping Short Reads to Human Genome.

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Zhao, Yongan; Wang, Xiaofeng; Tang, Haixu

2018-05-09

The elastic and inexpensive computing resources such as clouds have been recognized as a useful solution to analyzing massive human genomic data (e.g., acquired by using next-generation sequencers) in biomedical researches. However, outsourcing human genome computation to public or commercial clouds was hindered due to privacy concerns: even a small number of human genome sequences contain sufficient information for identifying the donor of the genomic data. This issue cannot be directly addressed by existing security and cryptographic techniques (such as homomorphic encryption), because they are too heavyweight to carry out practical genome computation tasks on massive data. In this article, we present a secure algorithm to accomplish the read mapping, one of the most basic tasks in human genomic data analysis based on a hybrid cloud computing model. Comparing with the existing approaches, our algorithm delegates most computation to the public cloud, while only performing encryption and decryption on the private cloud, and thus makes the maximum use of the computing resource of the public cloud. Furthermore, our algorithm reports similar results as the nonsecure read mapping algorithms, including the alignment between reads and the reference genome, which can be directly used in the downstream analysis such as the inference of genomic variations. We implemented the algorithm in C++ and Python on a hybrid cloud system, in which the public cloud uses an Apache Spark system.

INFERENCE BUILDING BLOCKS

Science.gov (United States)

2018-02-15

expressed a variety of inference techniques on discrete and continuous distributions: exact inference, importance sampling, Metropolis-Hastings (MH...without redoing any math or rewriting any code. And although our main goal is composable reuse, our performance is also good because we can use...control paths. • The Hakaru language can express mixtures of discrete and continuous distributions, but the current disintegration transformation

Practical Bayesian Inference

Science.gov (United States)

Bailer-Jones, Coryn A. L.

2017-04-01

Preface; 1. Probability basics; 2. Estimation and uncertainty; 3. Statistical models and inference; 4. Linear models, least squares, and maximum likelihood; 5. Parameter estimation: single parameter; 6. Parameter estimation: multiple parameters; 7. Approximating distributions; 8. Monte Carlo methods for inference; 9. Parameter estimation: Markov chain Monte Carlo; 10. Frequentist hypothesis testing; 11. Model comparison; 12. Dealing with more complicated problems; References; Index.

Genomic and Genetic Diversity within the Pseudomonas fluorescens Complex.

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Daniel Garrido-Sanz

Full Text Available The Pseudomonas fluorescens complex includes Pseudomonas strains that have been taxonomically assigned to more than fifty different species, many of which have been described as plant growth-promoting rhizobacteria (PGPR with potential applications in biocontrol and biofertilization. So far the phylogeny of this complex has been analyzed according to phenotypic traits, 16S rDNA, MLSA and inferred by whole-genome analysis. However, since most of the type strains have not been fully sequenced and new species are frequently described, correlation between taxonomy and phylogenomic analysis is missing. In recent years, the genomes of a large number of strains have been sequenced, showing important genomic heterogeneity and providing information suitable for genomic studies that are important to understand the genomic and genetic diversity shown by strains of this complex. Based on MLSA and several whole-genome sequence-based analyses of 93 sequenced strains, we have divided the P. fluorescens complex into eight phylogenomic groups that agree with previous works based on type strains. Digital DDH (dDDH identified 69 species and 75 subspecies within the 93 genomes. The eight groups corresponded to clustering with a threshold of 31.8% dDDH, in full agreement with our MLSA. The Average Nucleotide Identity (ANI approach showed inconsistencies regarding the assignment to species and to the eight groups. The small core genome of 1,334 CDSs and the large pan-genome of 30,848 CDSs, show the large diversity and genetic heterogeneity of the P. fluorescens complex. However, a low number of strains were enough to explain most of the CDSs diversity at core and strain-specific genomic fractions. Finally, the identification and analysis of group-specific genome and the screening for distinctive characters revealed a phylogenomic distribution of traits among the groups that provided insights into biocontrol and bioremediation applications as well as their role as

Inference of Tumor Phylogenies with Improved Somatic Mutation Discovery

KAUST Repository

Salari, Raheleh

2013-01-01

Next-generation sequencing technologies provide a powerful tool for studying genome evolution during progression of advanced diseases such as cancer. Although many recent studies have employed new sequencing technologies to detect mutations across multiple, genetically related tumors, current methods do not exploit available phylogenetic information to improve the accuracy of their variant calls. Here, we present a novel algorithm that uses somatic single nucleotide variations (SNVs) in multiple, related tissue samples as lineage markers for phylogenetic tree reconstruction. Our method then leverages the inferred phylogeny to improve the accuracy of SNV discovery. Experimental analyses demonstrate that our method achieves up to 32% improvement for somatic SNV calling of multiple related samples over the accuracy of GATK\\'s Unified Genotyper, the state of the art multisample SNV caller. © 2013 Springer-Verlag.

Genome evolution during progression to breast cancer

KAUST Repository

Newburger, D. E.; Kashef-Haghighi, D.; Weng, Z.; Salari, R.; Sweeney, R. T.; Brunner, A. L.; Zhu, S. X.; Guo, X.; Varma, S.; Troxell, M. L.; West, R. B.; Batzoglou, S.; Sidow, A.

2013-01-01

Cancer evolution involves cycles of genomic damage, epigenetic deregulation, and increased cellular proliferation that eventually culminate in the carcinoma phenotype. Early neoplasias, which are often found concurrently with carcinomas and are histologically distinguishable from normal breast tissue, are less advanced in phenotype than carcinomas and are thought to represent precursor stages. To elucidate their role in cancer evolution we performed comparative whole-genome sequencing of early neoplasias, matched normal tissue, and carcinomas from six patients, for a total of 31 samples. By using somatic mutations as lineage markers we built trees that relate the tissue samples within each patient. On the basis of these lineage trees we inferred the order, timing, and rates of genomic events. In four out of six cases, an early neoplasia and the carcinoma share a mutated common ancestor with recurring aneuploidies, and in all six cases evolution accelerated in the carcinoma lineage. Transition spectra of somatic mutations are stable and consistent across cases, suggesting that accumulation of somatic mutations is a result of increased ancestral cell division rather than specific mutational mechanisms. In contrast to highly advanced tumors that are the focus of much of the current cancer genome sequencing, neither the early neoplasia genomes nor the carcinomas are enriched with potentially functional somatic point mutations. Aneuploidies that occur in common ancestors of neoplastic and tumor cells are the earliest events that affect a large number of genes and may predispose breast tissue to eventual development of invasive carcinoma.

Genome evolution during progression to breast cancer

KAUST Repository

Newburger, D. E.

2013-04-08

Cancer evolution involves cycles of genomic damage, epigenetic deregulation, and increased cellular proliferation that eventually culminate in the carcinoma phenotype. Early neoplasias, which are often found concurrently with carcinomas and are histologically distinguishable from normal breast tissue, are less advanced in phenotype than carcinomas and are thought to represent precursor stages. To elucidate their role in cancer evolution we performed comparative whole-genome sequencing of early neoplasias, matched normal tissue, and carcinomas from six patients, for a total of 31 samples. By using somatic mutations as lineage markers we built trees that relate the tissue samples within each patient. On the basis of these lineage trees we inferred the order, timing, and rates of genomic events. In four out of six cases, an early neoplasia and the carcinoma share a mutated common ancestor with recurring aneuploidies, and in all six cases evolution accelerated in the carcinoma lineage. Transition spectra of somatic mutations are stable and consistent across cases, suggesting that accumulation of somatic mutations is a result of increased ancestral cell division rather than specific mutational mechanisms. In contrast to highly advanced tumors that are the focus of much of the current cancer genome sequencing, neither the early neoplasia genomes nor the carcinomas are enriched with potentially functional somatic point mutations. Aneuploidies that occur in common ancestors of neoplastic and tumor cells are the earliest events that affect a large number of genes and may predispose breast tissue to eventual development of invasive carcinoma.

Evolution of gastropod mitochondrial genome arrangements

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Zardoya Rafael

2008-02-01

Full Text Available Abstract Background Gastropod mitochondrial genomes exhibit an unusually great variety of gene orders compared to other metazoan mitochondrial genome such as e.g those of vertebrates. Hence, gastropod mitochondrial genomes constitute a good model system to study patterns, rates, and mechanisms of mitochondrial genome rearrangement. However, this kind of evolutionary comparative analysis requires a robust phylogenetic framework of the group under study, which has been elusive so far for gastropods in spite of the efforts carried out during the last two decades. Here, we report the complete nucleotide sequence of five mitochondrial genomes of gastropods (Pyramidella dolabrata, Ascobulla fragilis, Siphonaria pectinata, Onchidella celtica, and Myosotella myosotis, and we analyze them together with another ten complete mitochondrial genomes of gastropods currently available in molecular databases in order to reconstruct the phylogenetic relationships among the main lineages of gastropods. Results Comparative analyses with other mollusk mitochondrial genomes allowed us to describe molecular features and general trends in the evolution of mitochondrial genome organization in gastropods. Phylogenetic reconstruction with commonly used methods of phylogenetic inference (ME, MP, ML, BI arrived at a single topology, which was used to reconstruct the evolution of mitochondrial gene rearrangements in the group. Conclusion Four main lineages were identified within gastropods: Caenogastropoda, Vetigastropoda, Patellogastropoda, and Heterobranchia. Caenogastropoda and Vetigastropoda are sister taxa, as well as, Patellogastropoda and Heterobranchia. This result rejects the validity of the derived clade Apogastropoda (Caenogastropoda + Heterobranchia. The position of Patellogastropoda remains unclear likely due to long-branch attraction biases. Within Heterobranchia, the most heterogeneous group of gastropods, neither Euthyneura (because of the inclusion of P

Genome-driven evolutionary game theory helps understand the rise of metabolic interdependencies in microbial communities.

Science.gov (United States)

Zomorrodi, Ali R; Segrè, Daniel

2017-11-16

Metabolite exchanges in microbial communities give rise to ecological interactions that govern ecosystem diversity and stability. It is unclear, however, how the rise of these interactions varies across metabolites and organisms. Here we address this question by integrating genome-scale models of metabolism with evolutionary game theory. Specifically, we use microbial fitness values estimated by metabolic models to infer evolutionarily stable interactions in multi-species microbial "games". We first validate our approach using a well-characterized yeast cheater-cooperator system. We next perform over 80,000 in silico experiments to infer how metabolic interdependencies mediated by amino acid leakage in Escherichia coli vary across 189 amino acid pairs. While most pairs display shared patterns of inter-species interactions, multiple deviations are caused by pleiotropy and epistasis in metabolism. Furthermore, simulated invasion experiments reveal possible paths to obligate cross-feeding. Our study provides genomically driven insight into the rise of ecological interactions, with implications for microbiome research and synthetic ecology.

Methodology for the inference of gene function from phenotype data.

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Ascensao, Joao A; Dolan, Mary E; Hill, David P; Blake, Judith A

2014-12-12

Biomedical ontologies are increasingly instrumental in the advancement of biological research primarily through their use to efficiently consolidate large amounts of data into structured, accessible sets. However, ontology development and usage can be hampered by the segregation of knowledge by domain that occurs due to independent development and use of the ontologies. The ability to infer data associated with one ontology to data associated with another ontology would prove useful in expanding information content and scope. We here focus on relating two ontologies: the Gene Ontology (GO), which encodes canonical gene function, and the Mammalian Phenotype Ontology (MP), which describes non-canonical phenotypes, using statistical methods to suggest GO functional annotations from existing MP phenotype annotations. This work is in contrast to previous studies that have focused on inferring gene function from phenotype primarily through lexical or semantic similarity measures. We have designed and tested a set of algorithms that represents a novel methodology to define rules for predicting gene function by examining the emergent structure and relationships between the gene functions and phenotypes rather than inspecting the terms semantically. The algorithms inspect relationships among multiple phenotype terms to deduce if there are cases where they all arise from a single gene function. We apply this methodology to data about genes in the laboratory mouse that are formally represented in the Mouse Genome Informatics (MGI) resource. From the data, 7444 rule instances were generated from five generalized rules, resulting in 4818 unique GO functional predictions for 1796 genes. We show that our method is capable of inferring high-quality functional annotations from curated phenotype data. As well as creating inferred annotations, our method has the potential to allow for the elucidation of unforeseen, biologically significant associations between gene function and

Phylogeny and biogeography of highly diverged freshwater fish species (Leuciscinae, Cyprinidae, Teleostei) inferred from mitochondrial genome analysis.

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Imoto, Junichi M; Saitoh, Kenji; Sasaki, Takeshi; Yonezawa, Takahiro; Adachi, Jun; Kartavtsev, Yuri P; Miya, Masaki; Nishida, Mutsumi; Hanzawa, Naoto

2013-02-10

The distribution of freshwater taxa is a good biogeographic model to study pattern and process of vicariance and dispersal. The subfamily Leuciscinae (Cyprinidae, Teleostei) consists of many species distributed widely in Eurasia and North America. Leuciscinae have been divided into two phyletic groups, leuciscin and phoxinin. The phylogenetic relationships between major clades within the subfamily are poorly understood, largely because of the overwhelming diversity of the group. The origin of the Far Eastern phoxinin is an interesting question regarding the evolutionary history of Leuciscinae. Here we present phylogenetic analysis of 31 species of Leuciscinae and outgroups based on complete mitochondrial genome sequences to clarify the phylogenetic relationships and to infer the evolutionary history of the subfamily. Phylogenetic analysis suggests that the Far Eastern phoxinin species comprised the monophyletic clades Tribolodon, Pseudaspius, Oreoleuciscus and Far Eastern Phoxinus. The Far Eastern phoxinin clade was independent of other Leuciscinae lineages and was closer to North American phoxinins than European leuciscins. All of our analysis also suggested that leuciscins and phoxinins each constituted monophyletic groups. Divergence time estimation suggested that Leuciscinae species diverged from outgroups such as Tincinae to be 83.3 million years ago (Mya) in the Late Cretaceous and leuciscin and phoxinin shared a common ancestor 70.7 Mya. Radiation of Leuciscinae lineages occurred during the Late Cretaceous to Paleocene. This period also witnessed the radiation of tetrapods. Reconstruction of ancestral areas indicates Leuciscinae species originated within Europe. Leuciscin species evolved in Europe and the ancestor of phoxinin was distributed in North America. The Far Eastern phoxinins would have dispersed from North America to Far East across the Beringia land bridge. The present study suggests important roles for the continental rearrangements during the

Logical inference and evaluation

International Nuclear Information System (INIS)

Perey, F.G.

1981-01-01

Most methodologies of evaluation currently used are based upon the theory of statistical inference. It is generally perceived that this theory is not capable of dealing satisfactorily with what are called systematic errors. Theories of logical inference should be capable of treating all of the information available, including that not involving frequency data. A theory of logical inference is presented as an extension of deductive logic via the concept of plausibility and the application of group theory. Some conclusions, based upon the application of this theory to evaluation of data, are also given

The first mitochondrial genome for the butterfly family Riodinidae (Abisara fylloides) and its systematic implications.

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Zhao, Fang; Huang, Dun-Yuan; Sun, Xiao-Yan; Shi, Qing-Hui; Hao, Jia-Sheng; Zhang, Lan-Lan; Yang, Qun

2013-10-01

The Riodinidae is one of the lepidopteran butterfly families. This study describes the complete mitochondrial genome of the butterfly species Abisara fylloides, the first mitochondrial genome of the Riodinidae family. The results show that the entire mitochondrial genome of A. fylloides is 15 301 bp in length, and contains 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes and a 423 bp A+T-rich region. The gene content, orientation and order are identical to the majority of other lepidopteran insects. Phylogenetic reconstruction was conducted using the concatenated 13 protein-coding gene (PCG) sequences of 19 available butterfly species covering all the five butterfly families (Papilionidae, Nymphalidae, Peridae, Lycaenidae and Riodinidae). Both maximum likelihood and Bayesian inference analyses highly supported the monophyly of Lycaenidae+Riodinidae, which was standing as the sister of Nymphalidae. In addition, we propose that the riodinids be categorized into the family Lycaenidae as a subfamilial taxon. The Riodinidae is one of the lepidopteran butterfly families. This study describes the complete mitochondrial genome of the butterfly species Abisara fylloides , the first mitochondrial genome of the Riodinidae family. The results show that the entire mitochondrial genome of A. fylloides is 15 301 bp in length, and contains 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes and a 423 bp A+T-rich region. The gene content, orientation and order are identical to the majority of other lepidopteran insects. Phylogenetic reconstruction was conducted using the concatenated 13 protein-coding gene (PCG) sequences of 19 available butterfly species covering all the five butterfly families (Papilionidae, Nymphalidae, Peridae, Lycaenidae and Riodinidae). Both maximum likelihood and Bayesian inference analyses highly supported the monophyly of Lycaenidae+Riodinidae, which was standing as the sister of Nymphalidae. In addition, we propose

Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution.

Science.gov (United States)

2004-12-09

We present here a draft genome sequence of the red jungle fowl, Gallus gallus. Because the chicken is a modern descendant of the dinosaurs and the first non-mammalian amniote to have its genome sequenced, the draft sequence of its genome--composed of approximately one billion base pairs of sequence and an estimated 20,000-23,000 genes--provides a new perspective on vertebrate genome evolution, while also improving the annotation of mammalian genomes. For example, the evolutionary distance between chicken and human provides high specificity in detecting functional elements, both non-coding and coding. Notably, many conserved non-coding sequences are far from genes and cannot be assigned to defined functional classes. In coding regions the evolutionary dynamics of protein domains and orthologous groups illustrate processes that distinguish the lineages leading to birds and mammals. The distinctive properties of avian microchromosomes, together with the inferred patterns of conserved synteny, provide additional insights into vertebrate chromosome architecture.

A Genome-Scale Investigation of How Sequence, Function, and Tree-Based Gene Properties Influence Phylogenetic Inference.

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Shen, Xing-Xing; Salichos, Leonidas; Rokas, Antonis

2016-09-02

Molecular phylogenetic inference is inherently dependent on choices in both methodology and data. Many insightful studies have shown how choices in methodology, such as the model of sequence evolution or optimality criterion used, can strongly influence inference. In contrast, much less is known about the impact of choices in the properties of the data, typically genes, on phylogenetic inference. We investigated the relationships between 52 gene properties (24 sequence-based, 19 function-based, and 9 tree-based) with each other and with three measures of phylogenetic signal in two assembled data sets of 2,832 yeast and 2,002 mammalian genes. We found that most gene properties, such as evolutionary rate (measured through the percent average of pairwise identity across taxa) and total tree length, were highly correlated with each other. Similarly, several gene properties, such as gene alignment length, Guanine-Cytosine content, and the proportion of tree distance on internal branches divided by relative composition variability (treeness/RCV), were strongly correlated with phylogenetic signal. Analysis of partial correlations between gene properties and phylogenetic signal in which gene evolutionary rate and alignment length were simultaneously controlled, showed similar patterns of correlations, albeit weaker in strength. Examination of the relative importance of each gene property on phylogenetic signal identified gene alignment length, alongside with number of parsimony-informative sites and variable sites, as the most important predictors. Interestingly, the subsets of gene properties that optimally predicted phylogenetic signal differed considerably across our three phylogenetic measures and two data sets; however, gene alignment length and RCV were consistently included as predictors of all three phylogenetic measures in both yeasts and mammals. These results suggest that a handful of sequence-based gene properties are reliable predictors of phylogenetic signal

Complete genome sequences of cowpea polerovirus 1 and cowpea polerovirus 2 infecting cowpea plants in Burkina Faso.

Science.gov (United States)

Palanga, Essowè; Martin, Darren P; Galzi, Serge; Zabré, Jean; Bouda, Zakaria; Neya, James Bouma; Sawadogo, Mahamadou; Traore, Oumar; Peterschmitt, Michel; Roumagnac, Philippe; Filloux, Denis

2017-07-01

The full-length genome sequences of two novel poleroviruses found infecting cowpea plants, cowpea polerovirus 1 (CPPV1) and cowpea polerovirus 2 (CPPV2), were determined using overlapping RT-PCR and RACE-PCR. Whereas the 5845-nt CPPV1 genome was most similar to chickpea chlorotic stunt virus (73% identity), the 5945-nt CPPV2 genome was most similar to phasey bean mild yellow virus (86% identity). The CPPV1 and CPPV2 genomes both have a typical polerovirus genome organization. Phylogenetic analysis of the inferred P1-P2 and P3 amino acid sequences confirmed that CPPV1 and CPPV2 are indeed poleroviruses. Four apparently unique recombination events were detected within a dataset of 12 full polerovirus genome sequences, including two events in the CPPV2 genome. Based on the current species demarcation criteria for the family Luteoviridae, we tentatively propose that CPPV1 and CPPV2 should be considered members of novel polerovirus species.

Inference

DEFF Research Database (Denmark)

Møller, Jesper

(This text written by Jesper Møller, Aalborg University, is submitted for the collection ‘Stochastic Geometry: Highlights, Interactions and New Perspectives', edited by Wilfrid S. Kendall and Ilya Molchanov, to be published by ClarendonPress, Oxford, and planned to appear as Section 4.1 with the ......(This text written by Jesper Møller, Aalborg University, is submitted for the collection ‘Stochastic Geometry: Highlights, Interactions and New Perspectives', edited by Wilfrid S. Kendall and Ilya Molchanov, to be published by ClarendonPress, Oxford, and planned to appear as Section 4.......1 with the title ‘Inference'.) This contribution concerns statistical inference for parametric models used in stochastic geometry and based on quick and simple simulation free procedures as well as more comprehensive methods using Markov chain Monte Carlo (MCMC) simulations. Due to space limitations the focus...

Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks.

Science.gov (United States)

Deeter, Anthony; Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui

2017-01-01

The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.

DESCARTES' RULE OF SIGNS AND THE IDENTIFIABILITY OF POPULATION DEMOGRAPHIC MODELS FROM GENOMIC VARIATION DATA.

Science.gov (United States)

Bhaskar, Anand; Song, Yun S

2014-01-01

The sample frequency spectrum (SFS) is a widely-used summary statistic of genomic variation in a sample of homologous DNA sequences. It provides a highly efficient dimensional reduction of large-scale population genomic data and its mathematical dependence on the underlying population demography is well understood, thus enabling the development of efficient inference algorithms. However, it has been recently shown that very different population demographies can actually generate the same SFS for arbitrarily large sample sizes. Although in principle this nonidentifiability issue poses a thorny challenge to statistical inference, the population size functions involved in the counterexamples are arguably not so biologically realistic. Here, we revisit this problem and examine the identifiability of demographic models under the restriction that the population sizes are piecewise-defined where each piece belongs to some family of biologically-motivated functions. Under this assumption, we prove that the expected SFS of a sample uniquely determines the underlying demographic model, provided that the sample is sufficiently large. We obtain a general bound on the sample size sufficient for identifiability; the bound depends on the number of pieces in the demographic model and also on the type of population size function in each piece. In the cases of piecewise-constant, piecewise-exponential and piecewise-generalized-exponential models, which are often assumed in population genomic inferences, we provide explicit formulas for the bounds as simple functions of the number of pieces. Lastly, we obtain analogous results for the "folded" SFS, which is often used when there is ambiguity as to which allelic type is ancestral. Our results are proved using a generalization of Descartes' rule of signs for polynomials to the Laplace transform of piecewise continuous functions.

Lower complexity bounds for lifted inference

DEFF Research Database (Denmark)

Jaeger, Manfred

2015-01-01

instances of the model. Numerous approaches for such “lifted inference” techniques have been proposed. While it has been demonstrated that these techniques will lead to significantly more efficient inference on some specific models, there are only very recent and still quite restricted results that show...... the feasibility of lifted inference on certain syntactically defined classes of models. Lower complexity bounds that imply some limitations for the feasibility of lifted inference on more expressive model classes were established earlier in Jaeger (2000; Jaeger, M. 2000. On the complexity of inference about...... that under the assumption that NETIME≠ETIME, there is no polynomial lifted inference algorithm for knowledge bases of weighted, quantifier-, and function-free formulas. Further strengthening earlier results, this is also shown to hold for approximate inference and for knowledge bases not containing...

Genomic analyses inform on migration events during the peopling of Eurasia.

Science.gov (United States)

Pagani, Luca; Lawson, Daniel John; Jagoda, Evelyn; Mörseburg, Alexander; Eriksson, Anders; Mitt, Mario; Clemente, Florian; Hudjashov, Georgi; DeGiorgio, Michael; Saag, Lauri; Wall, Jeffrey D; Cardona, Alexia; Mägi, Reedik; Wilson Sayres, Melissa A; Kaewert, Sarah; Inchley, Charlotte; Scheib, Christiana L; Järve, Mari; Karmin, Monika; Jacobs, Guy S; Antao, Tiago; Iliescu, Florin Mircea; Kushniarevich, Alena; Ayub, Qasim; Tyler-Smith, Chris; Xue, Yali; Yunusbayev, Bayazit; Tambets, Kristiina; Mallick, Chandana Basu; Saag, Lehti; Pocheshkhova, Elvira; Andriadze, George; Muller, Craig; Westaway, Michael C; Lambert, David M; Zoraqi, Grigor; Turdikulova, Shahlo; Dalimova, Dilbar; Sabitov, Zhaxylyk; Sultana, Gazi Nurun Nahar; Lachance, Joseph; Tishkoff, Sarah; Momynaliev, Kuvat; Isakova, Jainagul; Damba, Larisa D; Gubina, Marina; Nymadawa, Pagbajabyn; Evseeva, Irina; Atramentova, Lubov; Utevska, Olga; Ricaut, François-Xavier; Brucato, Nicolas; Sudoyo, Herawati; Letellier, Thierry; Cox, Murray P; Barashkov, Nikolay A; Skaro, Vedrana; Mulahasanovic, Lejla; Primorac, Dragan; Sahakyan, Hovhannes; Mormina, Maru; Eichstaedt, Christina A; Lichman, Daria V; Abdullah, Syafiq; Chaubey, Gyaneshwer; Wee, Joseph T S; Mihailov, Evelin; Karunas, Alexandra; Litvinov, Sergei; Khusainova, Rita; Ekomasova, Natalya; Akhmetova, Vita; Khidiyatova, Irina; Marjanović, Damir; Yepiskoposyan, Levon; Behar, Doron M; Balanovska, Elena; Metspalu, Andres; Derenko, Miroslava; Malyarchuk, Boris; Voevoda, Mikhail; Fedorova, Sardana A; Osipova, Ludmila P; Lahr, Marta Mirazón; Gerbault, Pascale; Leavesley, Matthew; Migliano, Andrea Bamberg; Petraglia, Michael; Balanovsky, Oleg; Khusnutdinova, Elza K; Metspalu, Ene; Thomas, Mark G; Manica, Andrea; Nielsen, Rasmus; Villems, Richard; Willerslev, Eske; Kivisild, Toomas; Metspalu, Mait

2016-10-13

High-coverage whole-genome sequence studies have so far focused on a limited number of geographically restricted populations, or been targeted at specific diseases, such as cancer. Nevertheless, the availability of high-resolution genomic data has led to the development of new methodologies for inferring population history and refuelled the debate on the mutation rate in humans. Here we present the Estonian Biocentre Human Genome Diversity Panel (EGDP), a dataset of 483 high-coverage human genomes from 148 populations worldwide, including 379 new genomes from 125 populations, which we group into diversity and selection sets. We analyse this dataset to refine estimates of continent-wide patterns of heterozygosity, long- and short-distance gene flow, archaic admixture, and changes in effective population size through time as well as for signals of positive or balancing selection. We find a genetic signature in present-day Papuans that suggests that at least 2% of their genome originates from an early and largely extinct expansion of anatomically modern humans (AMHs) out of Africa. Together with evidence from the western Asian fossil record, and admixture between AMHs and Neanderthals predating the main Eurasian expansion, our results contribute to the mounting evidence for the presence of AMHs out of Africa earlier than 75,000 years ago.

Genomic analyses inform on migration events during the peopling of Eurasia

Science.gov (United States)

Pagani, Luca; Lawson, Daniel John; Jagoda, Evelyn; Mörseburg, Alexander; Eriksson, Anders; Mitt, Mario; Clemente, Florian; Hudjashov, Georgi; Degiorgio, Michael; Saag, Lauri; Wall, Jeffrey D.; Cardona, Alexia; Mägi, Reedik; Sayres, Melissa A. Wilson; Kaewert, Sarah; Inchley, Charlotte; Scheib, Christiana L.; Järve, Mari; Karmin, Monika; Jacobs, Guy S.; Antao, Tiago; Iliescu, Florin Mircea; Kushniarevich, Alena; Ayub, Qasim; Tyler-Smith, Chris; Xue, Yali; Yunusbayev, Bayazit; Tambets, Kristiina; Mallick, Chandana Basu; Saag, Lehti; Pocheshkhova, Elvira; Andriadze, George; Muller, Craig; Westaway, Michael C.; Lambert, David M.; Zoraqi, Grigor; Turdikulova, Shahlo; Dalimova, Dilbar; Sabitov, Zhaxylyk; Sultana, Gazi Nurun Nahar; Lachance, Joseph; Tishkoff, Sarah; Momynaliev, Kuvat; Isakova, Jainagul; Damba, Larisa D.; Gubina, Marina; Nymadawa, Pagbajabyn; Evseeva, Irina; Atramentova, Lubov; Utevska, Olga; Ricaut, François-Xavier; Brucato, Nicolas; Sudoyo, Herawati; Letellier, Thierry; Cox, Murray P.; Barashkov, Nikolay A.; Škaro, Vedrana; Mulaha´, Lejla; Primorac, Dragan; Sahakyan, Hovhannes; Mormina, Maru; Eichstaedt, Christina A.; Lichman, Daria V.; Abdullah, Syafiq; Chaubey, Gyaneshwer; Wee, Joseph T. S.; Mihailov, Evelin; Karunas, Alexandra; Litvinov, Sergei; Khusainova, Rita; Ekomasova, Natalya; Akhmetova, Vita; Khidiyatova, Irina; Marjanović, Damir; Yepiskoposyan, Levon; Behar, Doron M.; Balanovska, Elena; Metspalu, Andres; Derenko, Miroslava; Malyarchuk, Boris; Voevoda, Mikhail; Fedorova, Sardana A.; Osipova, Ludmila P.; Lahr, Marta Mirazón; Gerbault, Pascale; Leavesley, Matthew; Migliano, Andrea Bamberg; Petraglia, Michael; Balanovsky, Oleg; Khusnutdinova, Elza K.; Metspalu, Ene; Thomas, Mark G.; Manica, Andrea; Nielsen, Rasmus; Villems, Richard; Willerslev, Eske; Kivisild, Toomas; Metspalu, Mait

2016-10-01

High-coverage whole-genome sequence studies have so far focused on a limited number of geographically restricted populations, or been targeted at specific diseases, such as cancer. Nevertheless, the availability of high-resolution genomic data has led to the development of new methodologies for inferring population history and refuelled the debate on the mutation rate in humans. Here we present the Estonian Biocentre Human Genome Diversity Panel (EGDP), a dataset of 483 high-coverage human genomes from 148 populations worldwide, including 379 new genomes from 125 populations, which we group into diversity and selection sets. We analyse this dataset to refine estimates of continent-wide patterns of heterozygosity, long- and short-distance gene flow, archaic admixture, and changes in effective population size through time as well as for signals of positive or balancing selection. We find a genetic signature in present-day Papuans that suggests that at least 2% of their genome originates from an early and largely extinct expansion of anatomically modern humans (AMHs) out of Africa. Together with evidence from the western Asian fossil record, and admixture between AMHs and Neanderthals predating the main Eurasian expansion, our results contribute to the mounting evidence for the presence of AMHs out of Africa earlier than 75,000 years ago.

Challenges and Approaches to Statistical Design and Inference in High Dimensional Investigations

Science.gov (United States)

Garrett, Karen A.; Allison, David B.

2015-01-01

Summary Advances in modern technologies have facilitated high-dimensional experiments (HDEs) that generate tremendous amounts of genomic, proteomic, and other “omic” data. HDEs involving whole-genome sequences and polymorphisms, expression levels of genes, protein abundance measurements, and combinations thereof have become a vanguard for new analytic approaches to the analysis of HDE data. Such situations demand creative approaches to the processes of statistical inference, estimation, prediction, classification, and study design. The novel and challenging biological questions asked from HDE data have resulted in many specialized analytic techniques being developed. This chapter discusses some of the unique statistical challenges facing investigators studying high-dimensional biology, and describes some approaches being developed by statistical scientists. We have included some focus on the increasing interest in questions involving testing multiple propositions simultaneously, appropriate inferential indicators for the types of questions biologists are interested in, and the need for replication of results across independent studies, investigators, and settings. A key consideration inherent throughout is the challenge in providing methods that a statistician judges to be sound and a biologist finds informative. PMID:19588106

Challenges and approaches to statistical design and inference in high-dimensional investigations.

Science.gov (United States)

Gadbury, Gary L; Garrett, Karen A; Allison, David B

2009-01-01

Advances in modern technologies have facilitated high-dimensional experiments (HDEs) that generate tremendous amounts of genomic, proteomic, and other "omic" data. HDEs involving whole-genome sequences and polymorphisms, expression levels of genes, protein abundance measurements, and combinations thereof have become a vanguard for new analytic approaches to the analysis of HDE data. Such situations demand creative approaches to the processes of statistical inference, estimation, prediction, classification, and study design. The novel and challenging biological questions asked from HDE data have resulted in many specialized analytic techniques being developed. This chapter discusses some of the unique statistical challenges facing investigators studying high-dimensional biology and describes some approaches being developed by statistical scientists. We have included some focus on the increasing interest in questions involving testing multiple propositions simultaneously, appropriate inferential indicators for the types of questions biologists are interested in, and the need for replication of results across independent studies, investigators, and settings. A key consideration inherent throughout is the challenge in providing methods that a statistician judges to be sound and a biologist finds informative.

Finding the missing honey bee genes: lessons learned from a genome upgrade.

Science.gov (United States)

Elsik, Christine G; Worley, Kim C; Bennett, Anna K; Beye, Martin; Camara, Francisco; Childers, Christopher P; de Graaf, Dirk C; Debyser, Griet; Deng, Jixin; Devreese, Bart; Elhaik, Eran; Evans, Jay D; Foster, Leonard J; Graur, Dan; Guigo, Roderic; Hoff, Katharina Jasmin; Holder, Michael E; Hudson, Matthew E; Hunt, Greg J; Jiang, Huaiyang; Joshi, Vandita; Khetani, Radhika S; Kosarev, Peter; Kovar, Christie L; Ma, Jian; Maleszka, Ryszard; Moritz, Robin F A; Munoz-Torres, Monica C; Murphy, Terence D; Muzny, Donna M; Newsham, Irene F; Reese, Justin T; Robertson, Hugh M; Robinson, Gene E; Rueppell, Olav; Solovyev, Victor; Stanke, Mario; Stolle, Eckart; Tsuruda, Jennifer M; Vaerenbergh, Matthias Van; Waterhouse, Robert M; Weaver, Daniel B; Whitfield, Charles W; Wu, Yuanqing; Zdobnov, Evgeny M; Zhang, Lan; Zhu, Dianhui; Gibbs, Richard A

2014-01-30

The first generation of genome sequence assemblies and annotations have had a significant impact upon our understanding of the biology of the sequenced species, the phylogenetic relationships among species, the study of populations within and across species, and have informed the biology of humans. As only a few Metazoan genomes are approaching finished quality (human, mouse, fly and worm), there is room for improvement of most genome assemblies. The honey bee (Apis mellifera) genome, published in 2006, was noted for its bimodal GC content distribution that affected the quality of the assembly in some regions and for fewer genes in the initial gene set (OGSv1.0) compared to what would be expected based on other sequenced insect genomes. Here, we report an improved honey bee genome assembly (Amel_4.5) with a new gene annotation set (OGSv3.2), and show that the honey bee genome contains a number of genes similar to that of other insect genomes, contrary to what was suggested in OGSv1.0. The new genome assembly is more contiguous and complete and the new gene set includes ~5000 more protein-coding genes, 50% more than previously reported. About 1/6 of the additional genes were due to improvements to the assembly, and the remaining were inferred based on new RNAseq and protein data. Lessons learned from this genome upgrade have important implications for future genome sequencing projects. Furthermore, the improvements significantly enhance genomic resources for the honey bee, a key model for social behavior and essential to global ecology through pollination.

Variations on Bayesian Prediction and Inference

Science.gov (United States)

2016-05-09

inference 2.2.1 Background There are a number of statistical inference problems that are not generally formulated via a full probability model...problem of inference about an unknown parameter, the Bayesian approach requires a full probability 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND...the problem of inference about an unknown parameter, the Bayesian approach requires a full probability model/likelihood which can be an obstacle

The mitochondrial genomes of the acoelomorph worms Paratomella rubra, Isodiametra pulchra and Archaphanostoma ylvae.

Science.gov (United States)

Robertson, Helen E; Lapraz, François; Egger, Bernhard; Telford, Maximilian J; Schiffer, Philipp H

2017-05-12

Acoels are small, ubiquitous - but understudied - marine worms with a very simple body plan. Their internal phylogeny is still not fully resolved, and the position of their proposed phylum Xenacoelomorpha remains debated. Here we describe mitochondrial genome sequences from the acoels Paratomella rubra and Isodiametra pulchra, and the complete mitochondrial genome of the acoel Archaphanostoma ylvae. The P. rubra and A. ylvae sequences are typical for metazoans in size and gene content. The larger I. pulchra  mitochondrial genome contains both ribosomal genes, 21 tRNAs, but only 11 protein-coding genes. We find evidence suggesting a duplicated sequence in the I. pulchra mitochondrial genome. The P. rubra, I. pulchra and A. ylvae mitochondria have a unique genome organisation in comparison to other metazoan mitochondrial genomes. We found a large degree of protein-coding gene and tRNA overlap with little non-coding sequence in the compact P. rubra genome. Conversely, the A. ylvae and I. pulchra genomes have many long non-coding sequences between genes, likely driving genome size expansion in the latter. Phylogenetic trees inferred from mitochondrial genes retrieve Xenacoelomorpha as an early branching taxon in the deuterostomes. Sequence divergence analysis between P. rubra sampled in England and Spain indicates cryptic diversity.

Global population genomics and comparisons of selective signatures from two invasions of melon fly, Zeugodacus cucurbitae (Diptera: Tephritidae)

Science.gov (United States)

Population genetics is a powerful tool for invasion biology and pest management, from tracing invasion pathways to informing management decisions with inference of population demographics. Genomics greatly increases the resolution of population-scale analyses, yet outside of model species with exten...

Gene expression inference with deep learning.

Science.gov (United States)

Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui

2016-06-15

Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. D-GEX is available at https://github.com/uci-cbcl/D-GEX CONTACT: xhx@ics.uci.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The Physcomitrella genome reveals evolutionary insights into the conquest of land by plants

Energy Technology Data Exchange (ETDEWEB)

Rensing, Stefan A.; Lang, Daniel; Zimmer, Andreas D.; Terry, Astrid; Salamov, Asaf; Shapiro, Harris; Nishiyama, Tomaoki; Perroud, Pierre-Francois; Lindquist, Erika A.; Kamisugi, Yasuko; Tanahashi, Takako; Sakakibara, Keiko; Fujita, Tomomichi; Oishi, Kazuko; Shin, Tadasu; Kuroki, Yoko; Toyoda, Atsushi; Suzuki, Yutaka; Hashimoto, Shin-ichi; Yamaguchi, Kazuo; Sugano, Sumio; Kohara, Yuji; Fujiyama, Asao; Anterola, Aldwin; Aoki, Setsuyuki; Ashton, Neil; Barbazuk, W. Brad; Barker, Elizabeth; Bennetzen, Jeffrey L.; Blankenship, Robert; Cho, Sung Hyun; Dutcher, Susan K.; Estelle, Mark; Fawcett, Jeffrey A.; Gundlach, Heidrum; Hanada, Kousuke; Melkozernov, Alexander; Murata, Takashi; Nelson, David R.; Pils, Birgit; Prigge, Michael; Reiss, Bernd; Renner, Tanya; Rombauts, Stephane; Rushton, Paul J.; Sanderfoot, Anton; Schween, Gabriele; Shiu, Shin-Han; Stueber, Kurt; Theodoulou, Frederica L.; Tu, Hank; Van de Peer, Yves; Verrier, Paul J.; Waters, Elizabeth; Wood, Andrew; Yang, Lixing; Cove, David; Cuming, Andrew C.; Hasebe, Mitsayasu; Lucas, Susan; Mishler, Brent D.; Reski, Ralf; Grigoriev, Igor V.; Quatrano, Rakph S.; Boore, Jeffrey L.

2007-09-18

We report the draft genome sequence of the model moss Physcomitrella patens and compare its features with those of flowering plants, from which it is separated by more than 400 million years, and unicellular aquatic algae. This comparison reveals genomic changes concomitant with the evolutionary movement to land, including a general increase in gene family complexity; loss of genes associated with aquatic environments (e.g., flagellar arms); acquisition of genes for tolerating terrestrial stresses (e.g., variation in temperature and water availability); and the development of the auxin and abscisic acid signaling pathways for coordinating multicellular growth and dehydration response. The Physcomitrella genome provides a resource for phylogenetic inferences about gene function and for experimental analysis of plant processes through this plant's unique facility for reverse genetics.

Ancient Ethiopian genome reveals extensive Eurasian admixture in Eastern Africa

KAUST Repository

Gallego Llorente, M.

2015-10-09

Characterizing genetic diversity in Africa is a crucial step for most analyses reconstructing the evolutionary history of anatomically modern humans. However, historic migrations from Eurasia into Africa have affected many contemporary populations, confounding inferences. Here, we present a 12.5×coverage ancient genome of an Ethiopian male ("Mota") who lived approximately 4500 years ago. We use this genome to demonstrate that the Eurasian backflow into Africa came from a population closely related to Early Neolithic farmers, who had colonized Europe 4000 years earlier. The extent of this backflow was much greater than previously reported, reaching all the way to Central, West, and Southern Africa, affecting even populations such as Yoruba and Mbuti, previously thought to be relatively unadmixed, who harbor 6 to 7% Eurasian ancestry.

Ancient Ethiopian genome reveals extensive Eurasian admixture in Eastern Africa

KAUST Repository

Gallego Llorente, M.; Jones, E. R.; Eriksson, Anders; Siska, V.; Arthur, K. W.; Arthur, J. W.; Curtis, M. C.; Stock, J. T.; Coltorti, M.; Pieruccini, P.; Stretton, S.; Brock, F.; Higham, T.; Park, Y.; Hofreiter, M.; Bradley, D. G.; Bhak, J.; Pinhasi, R.; Manica, A.

2015-01-01

Characterizing genetic diversity in Africa is a crucial step for most analyses reconstructing the evolutionary history of anatomically modern humans. However, historic migrations from Eurasia into Africa have affected many contemporary populations, confounding inferences. Here, we present a 12.5×coverage ancient genome of an Ethiopian male ("Mota") who lived approximately 4500 years ago. We use this genome to demonstrate that the Eurasian backflow into Africa came from a population closely related to Early Neolithic farmers, who had colonized Europe 4000 years earlier. The extent of this backflow was much greater than previously reported, reaching all the way to Central, West, and Southern Africa, affecting even populations such as Yoruba and Mbuti, previously thought to be relatively unadmixed, who harbor 6 to 7% Eurasian ancestry.

An overview of recent developments in genomics and associated statistical methods.

Science.gov (United States)

Bickel, Peter J; Brown, James B; Huang, Haiyan; Li, Qunhua

2009-11-13

The landscape of genomics has changed drastically in the last two decades. Increasingly inexpensive sequencing has shifted the primary focus from the acquisition of biological sequences to the study of biological function. Assays have been developed to study many intricacies of biological systems, and publicly available databases have given rise to integrative analyses that combine information from many sources to draw complex conclusions. Such research was the focus of the recent workshop at the Isaac Newton Institute, 'High dimensional statistics in biology'. Many computational methods from modern genomics and related disciplines were presented and discussed. Using, as much as possible, the material from these talks, we give an overview of modern genomics: from the essential assays that make data-generation possible, to the statistical methods that yield meaningful inference. We point to current analytical challenges, where novel methods, or novel applications of extant methods, are presently needed.

A universe of dwarfs and giants: genome size and chromosome evolution in the monocot family Melanthiaceae.

Science.gov (United States)

Pellicer, Jaume; Kelly, Laura J; Leitch, Ilia J; Zomlefer, Wendy B; Fay, Michael F

2014-03-01

• Since the occurrence of giant genomes in angiosperms is restricted to just a few lineages, identifying where shifts towards genome obesity have occurred is essential for understanding the evolutionary mechanisms triggering this process. • Genome sizes were assessed using flow cytometry in 79 species and new chromosome numbers were obtained. Phylogenetically based statistical methods were applied to infer ancestral character reconstructions of chromosome numbers and nuclear DNA contents. • Melanthiaceae are the most diverse family in terms of genome size, with C-values ranging more than 230-fold. Our data confirmed that giant genomes are restricted to tribe Parideae, with most extant species in the family characterized by small genomes. Ancestral genome size reconstruction revealed that the most recent common ancestor (MRCA) for the family had a relatively small genome (1C = 5.37 pg). Chromosome losses and polyploidy are recovered as the main evolutionary mechanisms generating chromosome number change. • Genome evolution in Melanthiaceae has been characterized by a trend towards genome size reduction, with just one episode of dramatic DNA accumulation in Parideae. Such extreme contrasting profiles of genome size evolution illustrate the key role of transposable elements and chromosome rearrangements in driving the evolution of plant genomes. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Segmenting the human genome based on states of neutral genetic divergence.

Science.gov (United States)

Kuruppumullage Don, Prabhani; Ananda, Guruprasad; Chiaromonte, Francesca; Makova, Kateryna D

2013-09-03

Many studies have demonstrated that divergence levels generated by different mutation types vary and covary across the human genome. To improve our still-incomplete understanding of the mechanistic basis of this phenomenon, we analyze several mutation types simultaneously, anchoring their variation to specific regions of the genome. Using hidden Markov models on insertion, deletion, nucleotide substitution, and microsatellite divergence estimates inferred from human-orangutan alignments of neutrally evolving genomic sequences, we segment the human genome into regions corresponding to different divergence states--each uniquely characterized by specific combinations of divergence levels. We then parsed the mutagenic contributions of various biochemical processes associating divergence states with a broad range of genomic landscape features. We find that high divergence states inhabit guanine- and cytosine (GC)-rich, highly recombining subtelomeric regions; low divergence states cover inner parts of autosomes; chromosome X forms its own state with lowest divergence; and a state of elevated microsatellite mutability is interspersed across the genome. These general trends are mirrored in human diversity data from the 1000 Genomes Project, and departures from them highlight the evolutionary history of primate chromosomes. We also find that genes and noncoding functional marks [annotations from the Encyclopedia of DNA Elements (ENCODE)] are concentrated in high divergence states. Our results provide a powerful tool for biomedical data analysis: segmentations can be used to screen personal genome variants--including those associated with cancer and other diseases--and to improve computational predictions of noncoding functional elements.

Adaptive Inference on General Graphical Models

OpenAIRE

Acar, Umut A.; Ihler, Alexander T.; Mettu, Ramgopal; Sumer, Ozgur

2012-01-01

Many algorithms and applications involve repeatedly solving variations of the same inference problem; for example we may want to introduce new evidence to the model or perform updates to conditional dependencies. The goal of adaptive inference is to take advantage of what is preserved in the model and perform inference more rapidly than from scratch. In this paper, we describe techniques for adaptive inference on general graphs that support marginal computation and updates to the conditional ...

Defining and Evaluating a Core Genome Multilocus Sequence Typing Scheme for Genome-Wide Typing of Clostridium difficile.

Science.gov (United States)

Bletz, Stefan; Janezic, Sandra; Harmsen, Dag; Rupnik, Maja; Mellmann, Alexander

2018-06-01

Clostridium difficile , recently renamed Clostridioides difficile , is the most common cause of antibiotic-associated nosocomial gastrointestinal infections worldwide. To differentiate endogenous infections and transmission events, highly discriminatory subtyping is necessary. Today, methods based on whole-genome sequencing data are increasingly used to subtype bacterial pathogens; however, frequently a standardized methodology and typing nomenclature are missing. Here we report a core genome multilocus sequence typing (cgMLST) approach developed for C. difficile Initially, we determined the breadth of the C. difficile population based on all available MLST sequence types with Bayesian inference (BAPS). The resulting BAPS partitions were used in combination with C. difficile clade information to select representative isolates that were subsequently used to define cgMLST target genes. Finally, we evaluated the novel cgMLST scheme with genomes from 3,025 isolates. BAPS grouping ( n = 6 groups) together with the clade information led to a total of 11 representative isolates that were included for cgMLST definition and resulted in 2,270 cgMLST genes that were present in all isolates. Overall, 2,184 to 2,268 cgMLST targets were detected in the genome sequences of 70 outbreak-associated and reference strains, and on average 99.3% cgMLST targets (1,116 to 2,270 targets) were present in 2,954 genomes downloaded from the NCBI database, underlining the representativeness of the cgMLST scheme. Moreover, reanalyzing different cluster scenarios with cgMLST were concordant to published single nucleotide variant analyses. In conclusion, the novel cgMLST is representative for the whole C. difficile population, is highly discriminatory in outbreak situations, and provides a unique nomenclature facilitating interlaboratory exchange. Copyright © 2018 American Society for Microbiology.

Comparative Genomics Reveals the Core Gene Toolbox for the Fungus-Insect Symbiosis

Science.gov (United States)

Stata, Matt; Wang, Wei; White, Merlin M.; Moncalvo, Jean-Marc

2018-01-01

ABSTRACT Modern genomics has shed light on many entomopathogenic fungi and expanded our knowledge widely; however, little is known about the genomic features of the insect-commensal fungi. Harpellales are obligate commensals living in the digestive tracts of disease-bearing insects (black flies, midges, and mosquitoes). In this study, we produced and annotated whole-genome sequences of nine Harpellales taxa and conducted the first comparative analyses to infer the genomic diversity within the members of the Harpellales. The genomes of the insect gut fungi feature low (26% to 37%) GC content and large genome size variations (25 to 102 Mb). Further comparisons with insect-pathogenic fungi (from both Ascomycota and Zoopagomycota), as well as with free-living relatives (as negative controls), helped to identify a gene toolbox that is essential to the fungus-insect symbiosis. The results not only narrow the genomic scope of fungus-insect interactions from several thousands to eight core players but also distinguish host invasion strategies employed by insect pathogens and commensals. The genomic content suggests that insect commensal fungi rely mostly on adhesion protein anchors that target digestive system, while entomopathogenic fungi have higher numbers of transmembrane helices, signal peptides, and pathogen-host interaction (PHI) genes across the whole genome and enrich genes as well as functional domains to inactivate the host inflammation system and suppress the host defense. Phylogenomic analyses have revealed that genome sizes of Harpellales fungi vary among lineages with an integer-multiple pattern, which implies that ancient genome duplications may have occurred within the gut of insects. PMID:29764946

A Meta-Analysis of Multiple Matched Copy Number and Transcriptomics Data Sets for Inferring Gene Regulatory Relationships

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Newton, Richard; Wernisch, Lorenz

2014-01-01

Inferring gene regulatory relationships from observational data is challenging. Manipulation and intervention is often required to unravel causal relationships unambiguously. However, gene copy number changes, as they frequently occur in cancer cells, might be considered natural manipulation experiments on gene expression. An increasing number of data sets on matched array comparative genomic hybridisation and transcriptomics experiments from a variety of cancer pathologies are becoming publicly available. Here we explore the potential of a meta-analysis of thirty such data sets. The aim of our analysis was to assess the potential of in silico inference of trans-acting gene regulatory relationships from this type of data. We found sufficient correlation signal in the data to infer gene regulatory relationships, with interesting similarities between data sets. A number of genes had highly correlated copy number and expression changes in many of the data sets and we present predicted potential trans-acted regulatory relationships for each of these genes. The study also investigates to what extent heterogeneity between cell types and between pathologies determines the number of statistically significant predictions available from a meta-analysis of experiments. PMID:25148247

Analysis of adaptive evolution in Lyssavirus genomes reveals pervasive diversifying selection during species diversification.

Science.gov (United States)

Voloch, Carolina M; Capellão, Renata T; Mello, Beatriz; Schrago, Carlos G

2014-11-19

Lyssavirus is a diverse genus of viruses that infect a variety of mammalian hosts, typically causing encephalitis. The evolution of this lineage, particularly the rabies virus, has been a focus of research because of the extensive occurrence of cross-species transmission, and the distinctive geographical patterns present throughout the diversification of these viruses. Although numerous studies have examined pattern-related questions concerning Lyssavirus evolution, analyses of the evolutionary processes acting on Lyssavirus diversification are scarce. To clarify the relevance of positive natural selection in Lyssavirus diversification, we conducted a comprehensive scan for episodic diversifying selection across all lineages and codon sites of the five coding regions in lyssavirus genomes. Although the genomes of these viruses are generally conserved, the glycoprotein (G), RNA-dependent RNA polymerase (L) and polymerase (P) genes were frequently targets of adaptive evolution during the diversification of the genus. Adaptive evolution is particularly manifest in the glycoprotein gene, which was inferred to have experienced the highest density of positively selected codon sites along branches. Substitutions in the L gene were found to be associated with the early diversification of phylogroups. A comparison between the number of positively selected sites inferred along the branches of RABV population branches and Lyssavirus intespecies branches suggested that the occurrence of positive selection was similar on the five coding regions of the genome in both groups.

Analysis of Adaptive Evolution in Lyssavirus Genomes Reveals Pervasive Diversifying Selection during Species Diversification

Directory of Open Access Journals (Sweden)

Carolina M. Voloch

2014-11-01

Full Text Available Lyssavirus is a diverse genus of viruses that infect a variety of mammalian hosts, typically causing encephalitis. The evolution of this lineage, particularly the rabies virus, has been a focus of research because of the extensive occurrence of cross-species transmission, and the distinctive geographical patterns present throughout the diversification of these viruses. Although numerous studies have examined pattern-related questions concerning Lyssavirus evolution, analyses of the evolutionary processes acting on Lyssavirus diversification are scarce. To clarify the relevance of positive natural selection in Lyssavirus diversification, we conducted a comprehensive scan for episodic diversifying selection across all lineages and codon sites of the five coding regions in lyssavirus genomes. Although the genomes of these viruses are generally conserved, the glycoprotein (G, RNA-dependent RNA polymerase (L and polymerase (P genes were frequently targets of adaptive evolution during the diversification of the genus. Adaptive evolution is particularly manifest in the glycoprotein gene, which was inferred to have experienced the highest density of positively selected codon sites along branches. Substitutions in the L gene were found to be associated with the early diversification of phylogroups. A comparison between the number of positively selected sites inferred along the branches of RABV population branches and Lyssavirus intespecies branches suggested that the occurrence of positive selection was similar on the five coding regions of the genome in both groups.

Complete Chloroplast Genome of the Wollemi Pine (Wollemia nobilis): Structure and Evolution.

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Yap, Jia-Yee S; Rohner, Thore; Greenfield, Abigail; Van Der Merwe, Marlien; McPherson, Hannah; Glenn, Wendy; Kornfeld, Geoff; Marendy, Elessa; Pan, Annie Y H; Wilton, Alan; Wilkins, Marc R; Rossetto, Maurizio; Delaney, Sven K

2015-01-01

The Wollemi pine (Wollemia nobilis) is a rare Southern conifer with striking morphological similarity to fossil pines. A small population of W. nobilis was discovered in 1994 in a remote canyon system in the Wollemi National Park (near Sydney, Australia). This population contains fewer than 100 individuals and is critically endangered. Previous genetic studies of the Wollemi pine have investigated its evolutionary relationship with other pines in the family Araucariaceae, and have suggested that the Wollemi pine genome contains little or no variation. However, these studies were performed prior to the widespread use of genome sequencing, and their conclusions were based on a limited fraction of the Wollemi pine genome. In this study, we address this problem by determining the entire sequence of the W. nobilis chloroplast genome. A detailed analysis of the structure of the genome is presented, and the evolution of the genome is inferred by comparison with the chloroplast sequences of other members of the Araucariaceae and the related family Podocarpaceae. Pairwise alignments of whole genome sequences, and the presence of unique pseudogenes, gene duplications and insertions in W. nobilis and Araucariaceae, indicate that the W. nobilis chloroplast genome is most similar to that of its sister taxon Agathis. However, the W. nobilis genome contains an unusually high number of repetitive sequences, and these could be used in future studies to investigate and conserve any remnant genetic diversity in the Wollemi pine.

Connectivity in the yeast cell cycle transcription network: inferences from neural networks.

Directory of Open Access Journals (Sweden)

Christopher E Hart

2006-12-01

Full Text Available A current challenge is to develop computational approaches to infer gene network regulatory relationships based on multiple types of large-scale functional genomic data. We find that single-layer feed-forward artificial neural network (ANN models can effectively discover gene network structure by integrating global in vivo protein:DNA interaction data (ChIP/Array with genome-wide microarray RNA data. We test this on the yeast cell cycle transcription network, which is composed of several hundred genes with phase-specific RNA outputs. These ANNs were robust to noise in data and to a variety of perturbations. They reliably identified and ranked 10 of 12 known major cell cycle factors at the top of a set of 204, based on a sum-of-squared weights metric. Comparative analysis of motif occurrences among multiple yeast species independently confirmed relationships inferred from ANN weights analysis. ANN models can capitalize on properties of biological gene networks that other kinds of models do not. ANNs naturally take advantage of patterns of absence, as well as presence, of factor binding associated with specific expression output; they are easily subjected to in silico "mutation" to uncover biological redundancies; and they can use the full range of factor binding values. A prominent feature of cell cycle ANNs suggested an analogous property might exist in the biological network. This postulated that "network-local discrimination" occurs when regulatory connections (here between MBF and target genes are explicitly disfavored in one network module (G2, relative to others and to the class of genes outside the mitotic network. If correct, this predicts that MBF motifs will be significantly depleted from the discriminated class and that the discrimination will persist through evolution. Analysis of distantly related Schizosaccharomyces pombe confirmed this, suggesting that network-local discrimination is real and complements well-known enrichment of

Inferring Properties of Ancient Cyanobacteria from Biogeochemical Activity and Genomes of Siderophilic Cyanobacteria

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McKay, David S.; Brown, I. I.; Tringe, S. G.; Thomas-Keprta, K. E.; Bryant, D. A.; Sarkisova, S. S.; Malley, K.; Sosa, O.; Klatt, C. G.; McKay, D. S.

2010-01-01

Interrelationships between life and the planetary system could have simultaneously left landmarks in genomes of microbes and physicochemical signatures in the lithosphere. Verifying the links between genomic features in living organisms and the mineralized signatures generated by these organisms will help to reveal traces of life on Earth and beyond. Among contemporary environments, iron-depositing hot springs (IDHS) may represent one of the most appropriate natural models [1] for insights into ancient life since organisms may have originated on Earth and probably Mars in association with hydrothermal activity [2,3]. IDHS also seem to be appropriate models for studying certain biogeochemical processes that could have taken place in the late Archean and,-or early Paleoproterozoic eras [4, 5]. It has been suggested that inorganic polyphosphate (PPi), in chains of tens to hundreds of phosphate residues linked by high-energy bonds, is environmentally ubiquitous and abundant [6]. Cyanobacteria (CB) react to increased heavy metal concentrations and UV by enhanced generation of PPi bodies (PPB) [7], which are believed to be signatures of life [8]. However, the role of PPi in oxygenic prokaryotes for the suppression of oxidative stress induced by high Fe is poorly studied. Here we present preliminary results of a new mechanism of Fe mineralization in oxygenic prokaryotes, the effect of Fe on the generation of PPi bodies in CB, as well as preliminary analysis of the diversity and phylogeny of proteins involved in the prevention of oxidative stress in phototrophs inhabiting IDHS.

Yleaf: Software for Human Y-Chromosomal Haplogroup Inference from Next-Generation Sequencing Data.

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Ralf, Arwin; Montiel González, Diego; Zhong, Kaiyin; Kayser, Manfred

2018-05-01

Next-generation sequencing (NGS) technologies offer immense possibilities given the large genomic data they simultaneously deliver. The human Y-chromosome serves as good example how NGS benefits various applications in evolution, anthropology, genealogy, and forensics. Prior to NGS, the Y-chromosome phylogenetic tree consisted of a few hundred branches, based on NGS data, it now contains many thousands. The complexity of both, Y tree and NGS data provide challenges for haplogroup assignment. For effective analysis and interpretation of Y-chromosome NGS data, we present Yleaf, a publically available, automated, user-friendly software for high-resolution Y-chromosome haplogroup inference independently of library and sequencing methods.

The inference from a single case: moral versus scientific inferences in implementing new biotechnologies.

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Hofmann, B

2008-06-01

Are there similarities between scientific and moral inference? This is the key question in this article. It takes as its point of departure an instance of one person's story in the media changing both Norwegian public opinion and a brand-new Norwegian law prohibiting the use of saviour siblings. The case appears to falsify existing norms and to establish new ones. The analysis of this case reveals similarities in the modes of inference in science and morals, inasmuch as (a) a single case functions as a counter-example to an existing rule; (b) there is a common presupposition of stability, similarity and order, which makes it possible to reason from a few cases to a general rule; and (c) this makes it possible to hold things together and retain order. In science, these modes of inference are referred to as falsification, induction and consistency. In morals, they have a variety of other names. Hence, even without abandoning the fact-value divide, there appear to be similarities between inference in science and inference in morals, which may encourage communication across the boundaries between "the two cultures" and which are relevant to medical humanities.

Genome-wide Studies of Mycolic Acid Bacteria: Computational Identification and Analysis of a Minimal Genome

KAUST Repository

Kamanu, Frederick Kinyua

2012-12-01

The mycolic acid bacteria are a distinct suprageneric group of asporogenous Grampositive, high GC-content bacteria, distinguished by the presence of mycolic acids in their cell envelope. They exhibit great diversity in their cell and morphology; although primarily non-pathogens, this group contains three major pathogens Mycobacterium leprae, Mycobacterium tuberculosis complex, and Corynebacterium diphtheria. Although the mycolic acid bacteria are a clearly defined group of bacteria, the taxonomic relationships between its constituent genera and species are less well defined. Two approaches were tested for their suitability in describing the taxonomy of the group. First, a Multilocus Sequence Typing (MLST) experiment was assessed and found to be superior to monophyletic (16S small ribosomal subunit) in delineating a total of 52 mycolic acid bacterial species. Phylogenetic inference was performed using the neighbor-joining method. To further refine phylogenetic analysis and to take advantage of the widespread availability of bacterial genome data, a computational framework that simulates DNA-DNA hybridisation was developed and validated using multiscale bootstrap resampling. The tool classifies microbial genomes based on whole genome DNA, and was deployed as a web-application using PHP and Javascript. It is accessible online at http://cbrc.kaust.edu.sa/dna_hybridization/ A third study was a computational and statistical methods in the identification and analysis of a putative minimal mycolic acid bacterial genome so as to better understand (1) the genomic requirements to encode a mycolic acid bacterial cell and (2) the role and type of genes and genetic elements that lead to the massive increase in genome size in environmental mycolic acid bacteria. Using a reciprocal comparison approach, a total of 690 orthologous gene clusters forming a putative minimal genome were identified across 24 mycolic acid bacterial species. In order to identify new potential drug

Introductory statistical inference

CERN Document Server

Mukhopadhyay, Nitis

2014-01-01

This gracefully organized text reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, figures, tables, and computer simulations to develop and illustrate concepts. Drills and boxed summaries emphasize and reinforce important ideas and special techniques.Beginning with a review of the basic concepts and methods in probability theory, moments, and moment generating functions, the author moves to more intricate topics. Introductory Statistical Inference studies multivariate random variables, exponential families of dist

The mitochondrial genomes of Amphiascoides atopus and Schizopera knabeni (Harpacticoida: Miraciidae) reveal similarities between the copepod orders Harpacticoida and Poecilostomatoida.

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Easton, Erin E; Darrow, Emily M; Spears, Trisha; Thistle, David

2014-03-15

Members of subclass Copepoda are abundant, diverse, and-as a result of their variety of ecological roles in marine and freshwater environments-important, but their phylogenetic interrelationships are unclear. Recent studies of arthropods have used gene arrangements in the mitochondrial (mt) genome to infer phylogenies, but for copepods, only seven complete mt genomes have been published. These data revealed several within-order and few among-order similarities. To increase the data available for comparisons, we sequenced the complete mt genome (13,831base pairs) of Amphiascoides atopus and 10,649base pairs of the mt genome of Schizopera knabeni (both in the family Miraciidae of the order Harpacticoida). Comparison of our data to those for Tigriopus japonicus (family Harpacticidae, order Harpacticoida) revealed similarities in gene arrangement among these three species that were consistent with those found within and among families of other copepod orders. Comparison of the mt genomes of our species with those known from other copepod orders revealed the arrangement of mt genes of our Harpacticoida species to be more similar to that of Sinergasilus polycolpus (order Poecilostomatoida) than to that of T. japonicus. The similarities between S. polycolpus and our species are the first to be noted across the boundaries of copepod orders and support the possibility that mt-gene arrangement might be used to infer copepod phylogenies. We also found that our two species had extremely truncated transfer RNAs and that gene overlaps occurred much more frequently than has been reported for other copepod mt genomes. Published by Elsevier B.V.

Genomic diversity and introgression in O. sativa reveal the impact of domestication and breeding on the rice genome.

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Keyan Zhao

2010-05-01

Full Text Available The domestication of Asian rice (Oryza sativa was a complex process punctuated by episodes of introgressive hybridization among and between subpopulations. Deep genetic divergence between the two main varietal groups (Indica and Japonica suggests domestication from at least two distinct wild populations. However, genetic uniformity surrounding key domestication genes across divergent subpopulations suggests cultural exchange of genetic material among ancient farmers.In this study, we utilize a novel 1,536 SNP panel genotyped across 395 diverse accessions of O. sativa to study genome-wide patterns of polymorphism, to characterize population structure, and to infer the introgression history of domesticated Asian rice. Our population structure analyses support the existence of five major subpopulations (indica, aus, tropical japonica, temperate japonica and GroupV consistent with previous analyses. Our introgression analysis shows that most accessions exhibit some degree of admixture, with many individuals within a population sharing the same introgressed segment due to artificial selection. Admixture mapping and association analysis of amylose content and grain length illustrate the potential for dissecting the genetic basis of complex traits in domesticated plant populations.Genes in these regions control a myriad of traits including plant stature, blast resistance, and amylose content. These analyses highlight the power of population genomics in agricultural systems to identify functionally important regions of the genome and to decipher the role of human-directed breeding in refashioning the genomes of a domesticated species.

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

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Hero, Alfred O.; Rajaratnam, Bala

2015-01-01

When can reliable inference be drawn in fue “Big Data” context? This paper presents a framework for answering this fundamental question in the context of correlation mining, wifu implications for general large scale inference. In large scale data applications like genomics, connectomics, and eco-informatics fue dataset is often variable-rich but sample-starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than fue number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for “Big Data”. Sample complexity however has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address fuis gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where fue variable dimension is fixed and fue sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; 3) the purely high dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa cale data dimension. We illustrate this high dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables fua t are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. we demonstrate various regimes of correlation mining based on the unifying perspective of high dimensional learning rates and sample complexity for different structured covariance models and different inference tasks. PMID:27087700

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining.

Science.gov (United States)

Hero, Alfred O; Rajaratnam, Bala

2016-01-01

When can reliable inference be drawn in fue "Big Data" context? This paper presents a framework for answering this fundamental question in the context of correlation mining, wifu implications for general large scale inference. In large scale data applications like genomics, connectomics, and eco-informatics fue dataset is often variable-rich but sample-starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than fue number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for "Big Data". Sample complexity however has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address fuis gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where fue variable dimension is fixed and fue sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; 3) the purely high dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa cale data dimension. We illustrate this high dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables fua t are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. we demonstrate various regimes of correlation mining based on the unifying perspective of high dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.

ARG-walker: inference of individual specific strengths of meiotic recombination hotspots by population genomics analysis.

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Chen, Hao; Yang, Peng; Guo, Jing; Kwoh, Chee Keong; Przytycka, Teresa M; Zheng, Jie

2015-01-01

Meiotic recombination hotspots play important roles in various aspects of genomics, but the underlying mechanisms for regulating the locations and strengths of recombination hotspots are not yet fully revealed. Most existing algorithms for estimating recombination rates from sequence polymorphism data can only output average recombination rates of a population, although there is evidence for the heterogeneity in recombination rates among individuals. For genome-wide association studies (GWAS) of recombination hotspots, an efficient algorithm that estimates the individualized strengths of recombination hotspots is highly desirable. In this work, we propose a novel graph mining algorithm named ARG-walker, based on random walks on ancestral recombination graphs (ARG), to estimate individual-specific recombination hotspot strengths. Extensive simulations demonstrate that ARG-walker is able to distinguish the hot allele of a recombination hotspot from the cold allele. Integrated with output of ARG-walker, we performed GWAS on the phased haplotype data of the 22 autosome chromosomes of the HapMap Asian population samples of Chinese and Japanese (JPT+CHB). Significant cis-regulatory signals have been detected, which is corroborated by the enrichment of the well-known 13-mer motif CCNCCNTNNCCNC of PRDM9 protein. Moreover, two new DNA motifs have been identified in the flanking regions of the significantly associated SNPs (single nucleotide polymorphisms), which are likely to be new cis-regulatory elements of meiotic recombination hotspots of the human genome. Our results on both simulated and real data suggest that ARG-walker is a promising new method for estimating the individual recombination variations. In the future, it could be used to uncover the mechanisms of recombination regulation and human diseases related with recombination hotspots.

An empirical Bayes method for updating inferences in analysis of quantitative trait loci using information from related genome scans.

Science.gov (United States)

Zhang, Kui; Wiener, Howard; Beasley, Mark; George, Varghese; Amos, Christopher I; Allison, David B

2006-08-01

Individual genome scans for quantitative trait loci (QTL) mapping often suffer from low statistical power and imprecise estimates of QTL location and effect. This lack of precision yields large confidence intervals for QTL location, which are problematic for subsequent fine mapping and positional cloning. In prioritizing areas for follow-up after an initial genome scan and in evaluating the credibility of apparent linkage signals, investigators typically examine the results of other genome scans of the same phenotype and informally update their beliefs about which linkage signals in their scan most merit confidence and follow-up via a subjective-intuitive integration approach. A method that acknowledges the wisdom of this general paradigm but formally borrows information from other scans to increase confidence in objectivity would be a benefit. We developed an empirical Bayes analytic method to integrate information from multiple genome scans. The linkage statistic obtained from a single genome scan study is updated by incorporating statistics from other genome scans as prior information. This technique does not require that all studies have an identical marker map or a common estimated QTL effect. The updated linkage statistic can then be used for the estimation of QTL location and effect. We evaluate the performance of our method by using extensive simulations based on actual marker spacing and allele frequencies from available data. Results indicate that the empirical Bayes method can account for between-study heterogeneity, estimate the QTL location and effect more precisely, and provide narrower confidence intervals than results from any single individual study. We also compared the empirical Bayes method with a method originally developed for meta-analysis (a closely related but distinct purpose). In the face of marked heterogeneity among studies, the empirical Bayes method outperforms the comparator.

Finding the missing honey bee genes: Lessons learned from a genome upgrade

KAUST Repository

Elsik, Christine G; Worley, Kim C; Bennett, Anna K; Beye, Martin; Camara, Francisco; Childers, Christopher P; de Graaf, Dirk C; Debyser, Griet; Deng, Jixin; Devreese, Bart; Elhaik, Eran; Evans, Jay D; Foster, Leonard J; Graur, Dan; Guigo, Roderic; Hoff, Katharina Jasmin; Holder, Michael E; Hudson, Matthew E; Hunt, Greg J; Jiang, Huaiyang; Joshi, Vandita; Khetani, Radhika S; Kosarev, Peter; Kovar, Christie L; Ma, Jian; Maleszka, Ryszard; Moritz, Robin F A; Munoz-Torres, Monica C; Murphy, Terence D; Muzny, Donna M; Newsham, Irene F; Reese, Justin T; Robertson, Hugh M; Robinson, Gene E; Rueppell, Olav; Solovyev, Victor; Stanke, Mario; Stolle, Eckart; Tsuruda, Jennifer M; Vaerenbergh, Matthias Van; Waterhouse, Robert M; Weaver, Daniel B; Whitfield, Charles W; Wu, Yuanqing; Zdobnov, Evgeny M; Zhang, Lan; Zhu, Dianhui; Gibbs, Richard A; Patil, S.; Gubbala, S.; Aqrawi, P.; Arias, F.; Bess, C.; Blankenburg, K. B.; Brocchini, M.; Buhay, C.; Challis, D.; Chang, K.; Chen, D.; Coleman, P.; Drummond, J.; English, A.; Evani, U.; Francisco, L.; Fu, Q.; Goodspeed, R.; Haessly, T. H.; Hale, W.; Han, H.; Hu, Y.; Jackson, L.; Jakkamsetti, A.; Jayaseelan, J. C.; Kakkar, N.; Kalra, D.; Kandadi, H.; Lee, S.; Li, H.; Liu, Y.; Macmil, S.; Mandapat, C. M.; Mata, R.; Mathew, T.; Matskevitch, T.; Munidasa, M.; Nagaswamy, U.; Najjar, R.; Nguyen, N.; Niu, J.; Opheim, D.; Palculict, T.; Paul, S.; Pellon, M.; Perales, L.; Pham, C.; Pham, P.

2014-01-01

Background: The first generation of genome sequence assemblies and annotations have had a significant impact upon our understanding of the biology of the sequenced species, the phylogenetic relationships among species, the study of populations within and across species, and have informed the biology of humans. As only a few Metazoan genomes are approaching finished quality (human, mouse, fly and worm), there is room for improvement of most genome assemblies. The honey bee (Apis mellifera) genome, published in 2006, was noted for its bimodal GC content distribution that affected the quality of the assembly in some regions and for fewer genes in the initial gene set (OGSv1.0) compared to what would be expected based on other sequenced insect genomes. Results: Here, we report an improved honey bee genome assembly (Amel_4.5) with a new gene annotation set (OGSv3.2), and show that the honey bee genome contains a number of genes similar to that of other insect genomes, contrary to what was suggested in OGSv1.0. The new genome assembly is more contiguous and complete and the new gene set includes ~5000 more protein-coding genes, 50% more than previously reported. About 1/6 of the additional genes were due to improvements to the assembly, and the remaining were inferred based on new RNAseq and protein data. Conclusions: Lessons learned from this genome upgrade have important implications for future genome sequencing projects. Furthermore, the improvements significantly enhance genomic resources for the honey bee, a key model for social behavior and essential to global ecology through pollination. 2014 Elsik et al.; licensee BioMed Central Ltd.

Finding the missing honey bee genes: Lessons learned from a genome upgrade

KAUST Repository

Elsik, Christine G

2014-01-30

Background: The first generation of genome sequence assemblies and annotations have had a significant impact upon our understanding of the biology of the sequenced species, the phylogenetic relationships among species, the study of populations within and across species, and have informed the biology of humans. As only a few Metazoan genomes are approaching finished quality (human, mouse, fly and worm), there is room for improvement of most genome assemblies. The honey bee (Apis mellifera) genome, published in 2006, was noted for its bimodal GC content distribution that affected the quality of the assembly in some regions and for fewer genes in the initial gene set (OGSv1.0) compared to what would be expected based on other sequenced insect genomes. Results: Here, we report an improved honey bee genome assembly (Amel_4.5) with a new gene annotation set (OGSv3.2), and show that the honey bee genome contains a number of genes similar to that of other insect genomes, contrary to what was suggested in OGSv1.0. The new genome assembly is more contiguous and complete and the new gene set includes ~5000 more protein-coding genes, 50% more than previously reported. About 1/6 of the additional genes were due to improvements to the assembly, and the remaining were inferred based on new RNAseq and protein data. Conclusions: Lessons learned from this genome upgrade have important implications for future genome sequencing projects. Furthermore, the improvements significantly enhance genomic resources for the honey bee, a key model for social behavior and essential to global ecology through pollination. 2014 Elsik et al.; licensee BioMed Central Ltd.

Active inference, communication and hermeneutics.

Science.gov (United States)

Friston, Karl J; Frith, Christopher D

2015-07-01

Hermeneutics refers to interpretation and translation of text (typically ancient scriptures) but also applies to verbal and non-verbal communication. In a psychological setting it nicely frames the problem of inferring the intended content of a communication. In this paper, we offer a solution to the problem of neural hermeneutics based upon active inference. In active inference, action fulfils predictions about how we will behave (e.g., predicting we will speak). Crucially, these predictions can be used to predict both self and others--during speaking and listening respectively. Active inference mandates the suppression of prediction errors by updating an internal model that generates predictions--both at fast timescales (through perceptual inference) and slower timescales (through perceptual learning). If two agents adopt the same model, then--in principle--they can predict each other and minimise their mutual prediction errors. Heuristically, this ensures they are singing from the same hymn sheet. This paper builds upon recent work on active inference and communication to illustrate perceptual learning using simulated birdsongs. Our focus here is the neural hermeneutics implicit in learning, where communication facilitates long-term changes in generative models that are trying to predict each other. In other words, communication induces perceptual learning and enables others to (literally) change our minds and vice versa. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Using DNA fingerprints to infer familial relationships within NHANES III households.

Science.gov (United States)

Katki, Hormuzd A; Sanders, Christopher L; Graubard, Barry I; Bergen, Andrew W

2010-06-01

Developing, targeting, and evaluating genomic strategies for population-based disease prevention require population-based data. In response to this urgent need, genotyping has been conducted within the Third National Health and Nutrition Examination (NHANES III), the nationally-representative household-interview health survey in the U.S. However, before these genetic analyses can occur, family relationships within households must be accurately ascertained. Unfortunately, reported family relationships within NHANES III households based on questionnaire data are incomplete and inconclusive with regards to actual biological relatedness of family members. We inferred family relationships within households using DNA fingerprints (Identifiler(R)) that contain the DNA loci used by law enforcement agencies for forensic identification of individuals. However, performance of these loci for relationship inference is not well understood. We evaluated two competing statistical methods for relationship inference on pairs of household members: an exact likelihood ratio relying on allele frequencies to an Identical By State (IBS) likelihood ratio that only requires matching alleles. We modified these methods to account for genotyping errors and population substructure. The two methods usually agree on the rankings of the most likely relationships. However, the IBS method underestimates the likelihood ratio by not accounting for the informativeness of matching rare alleles. The likelihood ratio is sensitive to estimates of population substructure, and parent-child relationships are sensitive to the specified genotyping error rate. These loci were unable to distinguish second-degree relationships and cousins from being unrelated. The genetic data is also useful for verifying reported relationships and identifying data quality issues. An important by-product is the first explicitly nationally-representative estimates of allele frequencies at these ubiquitous forensic loci.

The new physician as unwitting quantum mechanic: is adapting Dirac's inference system best practice for personalized medicine, genomics, and proteomics?

Science.gov (United States)

Robson, Barry

2007-08-01

What is the Best Practice for automated inference in Medical Decision Support for personalized medicine? A known system already exists as Dirac's inference system from quantum mechanics (QM) using bra-kets and bras where A and B are states, events, or measurements representing, say, clinical and biomedical rules. Dirac's system should theoretically be the universal best practice for all inference, though QM is notorious as sometimes leading to bizarre conclusions that appear not to be applicable to the macroscopic world of everyday world human experience and medical practice. It is here argued that this apparent difficulty vanishes if QM is assigned one new multiplication function @, which conserves conditionality appropriately, making QM applicable to classical inference including a quantitative form of the predicate calculus. An alternative interpretation with the same consequences is if every i = radical-1 in Dirac's QM is replaced by h, an entity distinct from 1 and i and arguably a hidden root of 1 such that h2 = 1. With that exception, this paper is thus primarily a review of the application of Dirac's system, by application of linear algebra in the complex domain to help manipulate information about associations and ontology in complicated data. Any combined bra-ket can be shown to be composed only of the sum of QM-like bra and ket weights c(), times an exponential function of Fano's mutual information measure I(A; B) about the association between A and B, that is, an association rule from data mining. With the weights and Fano measure re-expressed as expectations on finite data using Riemann's Incomplete (i.e., Generalized) Zeta Functions, actual counts of observations for real world sparse data can be readily utilized. Finally, the paper compares identical character, distinguishability of states events or measurements, correlation, mutual information, and orthogonal character, important issues in data mining and biomedical analytics, as in QM.

Whole-genome analyses resolve early branches in the tree of life of modern birds

DEFF Research Database (Denmark)

Sicheritz-Pontén, Thomas; Li, Cai; Li, Bo

2014-01-01

To better determine the history of modern birds, we performed a genome-scale phylogenetic analysis of 48 species representing all orders of Neoaves using phylogenomic methods created to handle genome-scale data. We recovered a highly resolved tree that confirms previously controversial sister...... or close relationships. We identified the first divergence in Neoaves, two groups we named Passerea and Columbea, representing independent lineages of diverse and convergently evolved land and water bird species. Among Passerea, we infer the common ancestor of core landbirds to have been an apex predator...... and confirm independent gains of vocal learning. Among Columbea, we identify pigeons and flamingoes as belonging to sister clades. Even with whole genomes, some of the earliest branches in Neoaves proved challenging to resolve, which was best explained by massive protein-coding sequence convergence and high...

So many genes, so little time: A practical approach to divergence-time estimation in the genomic era.

Science.gov (United States)

Smith, Stephen A; Brown, Joseph W; Walker, Joseph F

2018-01-01

Phylogenomic datasets have been successfully used to address questions involving evolutionary relationships, patterns of genome structure, signatures of selection, and gene and genome duplications. However, despite the recent explosion in genomic and transcriptomic data, the utility of these data sources for efficient divergence-time inference remains unexamined. Phylogenomic datasets pose two distinct problems for divergence-time estimation: (i) the volume of data makes inference of the entire dataset intractable, and (ii) the extent of underlying topological and rate heterogeneity across genes makes model mis-specification a real concern. "Gene shopping", wherein a phylogenomic dataset is winnowed to a set of genes with desirable properties, represents an alternative approach that holds promise in alleviating these issues. We implemented an approach for phylogenomic datasets (available in SortaDate) that filters genes by three criteria: (i) clock-likeness, (ii) reasonable tree length (i.e., discernible information content), and (iii) least topological conflict with a focal species tree (presumed to have already been inferred). Such a winnowing procedure ensures that errors associated with model (both clock and topology) mis-specification are minimized, therefore reducing error in divergence-time estimation. We demonstrated the efficacy of this approach through simulation and applied it to published animal (Aves, Diplopoda, and Hymenoptera) and plant (carnivorous Caryophyllales, broad Caryophyllales, and Vitales) phylogenomic datasets. By quantifying rate heterogeneity across both genes and lineages we found that every empirical dataset examined included genes with clock-like, or nearly clock-like, behavior. Moreover, many datasets had genes that were clock-like, exhibited reasonable evolutionary rates, and were mostly compatible with the species tree. We identified overlap in age estimates when analyzing these filtered genes under strict clock and uncorrelated

CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes

Science.gov (United States)

Parks, Donovan H.; Imelfort, Michael; Skennerton, Connor T.; Hugenholtz, Philip; Tyson, Gene W.

2015-01-01

Large-scale recovery of genomes from isolates, single cells, and metagenomic data has been made possible by advances in computational methods and substantial reductions in sequencing costs. Although this increasing breadth of draft genomes is providing key information regarding the evolutionary and functional diversity of microbial life, it has become impractical to finish all available reference genomes. Making robust biological inferences from draft genomes requires accurate estimates of their completeness and contamination. Current methods for assessing genome quality are ad hoc and generally make use of a limited number of “marker” genes conserved across all bacterial or archaeal genomes. Here we introduce CheckM, an automated method for assessing the quality of a genome using a broader set of marker genes specific to the position of a genome within a reference genome tree and information about the collocation of these genes. We demonstrate the effectiveness of CheckM using synthetic data and a wide range of isolate-, single-cell-, and metagenome-derived genomes. CheckM is shown to provide accurate estimates of genome completeness and contamination and to outperform existing approaches. Using CheckM, we identify a diverse range of errors currently impacting publicly available isolate genomes and demonstrate that genomes obtained from single cells and metagenomic data vary substantially in quality. In order to facilitate the use of draft genomes, we propose an objective measure of genome quality that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities. PMID:25977477

A fungal phylogeny based on 42 complete genomes derived from supertree and combined gene analysis

Directory of Open Access Journals (Sweden)

Stajich Jason E

2006-11-01

Full Text Available Abstract Background To date, most fungal phylogenies have been derived from single gene comparisons, or from concatenated alignments of a small number of genes. The increase in fungal genome sequencing presents an opportunity to reconstruct evolutionary events using entire genomes. As a tool for future comparative, phylogenomic and phylogenetic studies, we used both supertrees and concatenated alignments to infer relationships between 42 species of fungi for which complete genome sequences are available. Results A dataset of 345,829 genes was extracted from 42 publicly available fungal genomes. Supertree methods were employed to derive phylogenies from 4,805 single gene families. We found that the average consensus supertree method may suffer from long-branch attraction artifacts, while matrix representation with parsimony (MRP appears to be immune from these. A genome phylogeny was also reconstructed from a concatenated alignment of 153 universally distributed orthologs. Our MRP supertree and concatenated phylogeny are highly congruent. Within the Ascomycota, the sub-phyla Pezizomycotina and Saccharomycotina were resolved. Both phylogenies infer that the Leotiomycetes are the closest sister group to the Sordariomycetes. There is some ambiguity regarding the placement of Stagonospora nodurum, the sole member of the class Dothideomycetes present in the dataset. Within the Saccharomycotina, a monophyletic clade containing organisms that translate CTG as serine instead of leucine is evident. There is also strong support for two groups within the CTG clade, one containing the fully sexual species Candida lusitaniae, Candida guilliermondii and Debaryomyces hansenii, and the second group containing Candida albicans, Candida dubliniensis, Candida tropicalis, Candida parapsilosis and Lodderomyces elongisporus. The second major clade within the Saccharomycotina contains species whose genomes have undergone a whole genome duplication (WGD, and their close

Complete mitochondrial genomes of the 'intermediate form' of Fasciola and Fasciola gigantica, and their comparison with F. hepatica.

Science.gov (United States)

Liu, Guo-Hua; Gasser, Robin B; Young, Neil D; Song, Hui-Qun; Ai, Lin; Zhu, Xing-Quan

2014-03-31

Fascioliasis is an important and neglected disease of humans and other mammals, caused by trematodes of the genus Fasciola. Fasciola hepatica and F. gigantica are valid species that infect humans and animals, but the specific status of Fasciola sp. ('intermediate form') is unclear. Single specimens inferred to represent Fasciola sp. ('intermediate form'; Heilongjiang) and F. gigantica (Guangxi) from China were genetically identified and characterized using PCR-based sequencing of the first and second internal transcribed spacer regions of nuclear ribosomal DNA. The complete mitochondrial (mt) genomes of these representative specimens were then sequenced. The relationships of these specimens with selected members of the Trematoda were assessed by phylogenetic analysis of concatenated amino acid sequence datasets by Bayesian inference (BI). The complete mt genomes of representatives of Fasciola sp. and F. gigantica were 14,453 bp and 14,478 bp in size, respectively. Both mt genomes contain 12 protein-coding genes, 22 transfer RNA genes and two ribosomal RNA genes, but lack an atp8 gene. All protein-coding genes are transcribed in the same direction, and the gene order in both mt genomes is the same as that published for F. hepatica. Phylogenetic analysis of the concatenated amino acid sequence data for all 12 protein-coding genes showed that the specimen of Fasciola sp. was more closely related to F. gigantica than to F. hepatica. The mt genomes characterized here provide a rich source of markers, which can be used in combination with nuclear markers and imaging techniques, for future comparative studies of the biology of Fasciola sp. from China and other countries.

Whole genome resequencing reveals natural target site preferences of transposable elements in Drosophila melanogaster.

Directory of Open Access Journals (Sweden)

Raquel S Linheiro

Full Text Available Transposable elements are mobile DNA sequences that integrate into host genomes using diverse mechanisms with varying degrees of target site specificity. While the target site preferences of some engineered transposable elements are well studied, the natural target preferences of most transposable elements are poorly characterized. Using population genomic resequencing data from 166 strains of Drosophila melanogaster, we identified over 8,000 new insertion sites not present in the reference genome sequence that we used to decode the natural target preferences of 22 families of transposable element in this species. We found that terminal inverted repeat transposon and long terminal repeat retrotransposon families present clade-specific target site duplications and target site sequence motifs. Additionally, we found that the sequence motifs at transposable element target sites are always palindromes that extend beyond the target site duplication. Our results demonstrate the utility of population genomics data for high-throughput inference of transposable element targeting preferences in the wild and establish general rules for terminal inverted repeat transposon and long terminal repeat retrotransposon target site selection in eukaryotic genomes.

Genomic analyses inform on migration events during the peopling of Eurasia

KAUST Repository

Pagani, Luca

2016-09-20

High-Coverage whole-genome sequence studies have so far focused on a limited number of geographically restricted populations, or been targeted at specific diseases, such as cancer. Nevertheless, the availability of high-resolution genomic data has led to the development of new methodologies for inferring population history and refuelled the debate on the mutation rate in humans. Here we present the Estonian Biocentre Human Genome Diversity Panel (EGDP), a dataset of 483 high-coverage human genomes from 148 populations worldwide, including 379 new genomes from 125 populations, which we group into diversity and selection sets. We analyse this dataset to refine estimates of continent-wide patterns of heterozygosity, long-and short-distance gene flow, archaic admixture, and changes in effective population size through time as well as for signals of positive or balancing selection. We find a genetic signature in present-day Papuans that suggests that at least 2% of their genome originates from an early and largely extinct expansion of anatomically modern humans (AMHs) out of Africa. Together with evidence from the western Asian fossil record, and admixture between AMHs and Neanderthals predating the main Eurasian expansion, our results contribute to the mounting evidence for the presence of AMHs out of Africa earlier than 75,000 years ago. © 2016 Macmillan Publishers Limited, part of Springer Nature.

HAL: a hierarchical format for storing and analyzing multiple genome alignments.

Science.gov (United States)

Hickey, Glenn; Paten, Benedict; Earl, Dent; Zerbino, Daniel; Haussler, David

2013-05-15

Large multiple genome alignments and inferred ancestral genomes are ideal resources for comparative studies of molecular evolution, and advances in sequencing and computing technology are making them increasingly obtainable. These structures can provide a rich understanding of the genetic relationships between all subsets of species they contain. Current formats for storing genomic alignments, such as XMFA and MAF, are all indexed or ordered using a single reference genome, however, which limits the information that can be queried with respect to other species and clades. This loss of information grows with the number of species under comparison, as well as their phylogenetic distance. We present HAL, a compressed, graph-based hierarchical alignment format for storing multiple genome alignments and ancestral reconstructions. HAL graphs are indexed on all genomes they contain. Furthermore, they are organized phylogenetically, which allows for modular and parallel access to arbitrary subclades without fragmentation because of rearrangements that have occurred in other lineages. HAL graphs can be created or read with a comprehensive C++ API. A set of tools is also provided to perform basic operations, such as importing and exporting data, identifying mutations and coordinate mapping (liftover). All documentation and source code for the HAL API and tools are freely available at http://github.com/glennhickey/hal. hickey@soe.ucsc.edu or haussler@soe.ucsc.edu Supplementary data are available at Bioinformatics online.

Genomic analyses inform on migration events during the peopling of Eurasia

KAUST Repository

Pagani, Luca; Lawson, Daniel John; Jagoda, Evelyn; Mö rseburg, Alexander; Eriksson, Anders; Mitt, Mario; Clemente, Florian; Hudjashov, Georgi; DeGiorgio, Michael; Saag, Lauri; Wall, Jeffrey D.; Cardona, Alexia; Mä gi, Reedik; Sayres, Melissa A. Wilson; Kaewert, Sarah; Inchley, Charlotte; Scheib, Christiana L.; Jä rve, Mari; Karmin, Monika; Jacobs, Guy S.; Antao, Tiago; Iliescu, Florin Mircea; Kushniarevich, Alena; Ayub, Qasim; Tyler-Smith, Chris; Xue, Yali; Yunusbayev, Bayazit; Tambets, Kristiina; Mallick, Chandana Basu; Saag, Lehti; Pocheshkhova, Elvira; Andriadze, George; Muller, Craig; Westaway, Michael C.; Lambert, David M.; Zoraqi, Grigor; Turdikulova, Shahlo; Dalimova, Dilbar; Sabitov, Zhaxylyk; Sultana, Gazi Nurun Nahar; Lachance, Joseph; Tishkoff, Sarah; Momynaliev, Kuvat; Isakova, Jainagul; Damba, Larisa D.; Gubina, Marina; Nymadawa, Pagbajabyn; Evseeva, Irina; Atramentova, Lubov; Utevska, Olga; Ricaut, Franç ois-Xavier; Brucato, Nicolas; Sudoyo, Herawati; Letellier, Thierry; Cox, Murray P.; Barashkov, Nikolay A.; Škaro, Vedrana; Mulahasanovic´ , Lejla; Primorac, Dragan; Sahakyan, Hovhannes; Mormina, Maru; Eichstaedt, Christina A.; Lichman, Daria V.; Abdullah, Syafiq; Chaubey, Gyaneshwer; Wee, Joseph T. S.; Mihailov, Evelin; Karunas, Alexandra; Litvinov, Sergei; Khusainova, Rita; Ekomasova, Natalya; Akhmetova, Vita; Khidiyatova, Irina; Marjanović, Damir; Yepiskoposyan, Levon; Behar, Doron M.; Balanovska, Elena; Metspalu, Andres; Derenko, Miroslava; Malyarchuk, Boris; Voevoda, Mikhail; Fedorova, Sardana A.; Osipova, Ludmila P.; Lahr, Marta Mirazó n; Gerbault, Pascale; Leavesley, Matthew; Migliano, Andrea Bamberg; Petraglia, Michael; Balanovsky, Oleg; Khusnutdinova, Elza K.; Metspalu, Ene; Thomas, Mark G.; Manica, Andrea; Nielsen, Rasmus; Villems, Richard; Willerslev, Eske; Kivisild, Toomas; Metspalu, Mait

2016-01-01

High-Coverage whole-genome sequence studies have so far focused on a limited number of geographically restricted populations, or been targeted at specific diseases, such as cancer. Nevertheless, the availability of high-resolution genomic data has led to the development of new methodologies for inferring population history and refuelled the debate on the mutation rate in humans. Here we present the Estonian Biocentre Human Genome Diversity Panel (EGDP), a dataset of 483 high-coverage human genomes from 148 populations worldwide, including 379 new genomes from 125 populations, which we group into diversity and selection sets. We analyse this dataset to refine estimates of continent-wide patterns of heterozygosity, long-and short-distance gene flow, archaic admixture, and changes in effective population size through time as well as for signals of positive or balancing selection. We find a genetic signature in present-day Papuans that suggests that at least 2% of their genome originates from an early and largely extinct expansion of anatomically modern humans (AMHs) out of Africa. Together with evidence from the western Asian fossil record, and admixture between AMHs and Neanderthals predating the main Eurasian expansion, our results contribute to the mounting evidence for the presence of AMHs out of Africa earlier than 75,000 years ago. © 2016 Macmillan Publishers Limited, part of Springer Nature.

Complete mitochondrial genome of Concholepas concholepas inferred by 454 pyrosequencing and mtDNA expression in two mollusc populations.

Science.gov (United States)

Núñez-Acuña, Gustavo; Aguilar-Espinoza, Andrea; Gallardo-Escárate, Cristian

2013-03-01

Despite the great relevance of mitochondrial genome analysis in evolutionary studies, there is scarce information on how the transcripts associated with the mitogenome are expressed and their role in the genetic structuring of populations. This work reports the complete mitochondrial genome of the marine gastropod Concholepas concholepas, obtained by 454 pryosequencing, and an analysis of mitochondrial transcripts of two populations 1000 km apart along the Chilean coast. The mitochondrion of C. concholepas is 15,495 base pairs (bp) in size and contains the 37 subunits characteristic of metazoans, as well as a non-coding region of 330 bp. In silico analysis of mitochondrial gene variability showed significant differences among populations. In terms of levels of relative abundance of transcripts associated with mitochondrion in the two populations (assessed by qPCR), the genes associated with complexes III and IV of the mitochondrial genome had the highest levels of expression in the northern population while transcripts associated with the ATP synthase complex had the highest levels of expression in the southern population. Moreover, fifteen polymorphic SNPs were identified in silico between the mitogenomes of the two populations. Four of these markers implied different amino acid substitutions (non-synonymous SNPs). This work contributes novel information regarding the mitochondrial genome structure and mRNA expression levels of C. concholepas. Copyright © 2012 Elsevier Inc. All rights reserved.

Insights and inferences about integron evolution from genomic data

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Martin Andrew P

2008-05-01

Full Text Available Abstract Background Integrons are mechanisms that facilitate horizontal gene transfer, allowing bacteria to integrate and express foreign DNA. These are important in the exchange of antibiotic resistance determinants, but can also transfer a diverse suite of genes unrelated to pathogenicity. Here, we provide a systematic analysis of the distribution and diversity of integron intI genes and integron-containing bacteria. Results We found integrons in 103 different pathogenic and non-pathogenic bacteria, in six major phyla. Integrons were widely scattered, and their presence was not confined to specific clades within bacterial orders. Nearly 1/3 of the intI genes that we identified were pseudogenes, containing either an internal stop codon or a frameshift mutation that would render the protein product non-functional. Additionally, 20% of bacteria contained more than one integrase gene. dN/dS ratios revealed mutational hotspots in clades of Vibrio and Shewanella intI genes. Finally, we characterized the gene cassettes associated with integrons in Methylobacillus flagellatus KT and Dechloromonas aromatica RCB, and found a heavy metal efflux gene as well as genes involved in protein folding and stability. Conclusion Our analysis suggests that the present distribution of integrons is due to multiple losses and gene transfer events. While, in some cases, the ability to integrate and excise foreign DNA may be selectively advantageous, the gain, loss, or rearrangment of gene cassettes could also be deleterious, selecting against functional integrases. Thus, such a high fraction of pseudogenes may suggest that the selective impact of integrons on genomes is variable, oscillating between beneficial and deleterious, possibly depending on environmental conditions.

Comparative genomics of metabolic capacities of regulons controlled by cis-regulatory RNA motifs in bacteria.

Science.gov (United States)

Sun, Eric I; Leyn, Semen A; Kazanov, Marat D; Saier, Milton H; Novichkov, Pavel S; Rodionov, Dmitry A

2013-09-02

In silico comparative genomics approaches have been efficiently used for functional prediction and reconstruction of metabolic and regulatory networks. Riboswitches are metabolite-sensing structures often found in bacterial mRNA leaders controlling gene expression on transcriptional or translational levels.An increasing number of riboswitches and other cis-regulatory RNAs have been recently classified into numerous RNA families in the Rfam database. High conservation of these RNA motifs provides a unique advantage for their genomic identification and comparative analysis. A comparative genomics approach implemented in the RegPredict tool was used for reconstruction and functional annotation of regulons controlled by RNAs from 43 Rfam families in diverse taxonomic groups of Bacteria. The inferred regulons include ~5200 cis-regulatory RNAs and more than 12000 target genes in 255 microbial genomes. All predicted RNA-regulated genes were classified into specific and overall functional categories. Analysis of taxonomic distribution of these categories allowed us to establish major functional preferences for each analyzed cis-regulatory RNA motif family. Overall, most RNA motif regulons showed predictable functional content in accordance with their experimentally established effector ligands. Our results suggest that some RNA motifs (including thiamin pyrophosphate and cobalamin riboswitches that control the cofactor metabolism) are widespread and likely originated from the last common ancestor of all bacteria. However, many more analyzed RNA motifs are restricted to a narrow taxonomic group of bacteria and likely represent more recent evolutionary innovations. The reconstructed regulatory networks for major known RNA motifs substantially expand the existing knowledge of transcriptional regulation in bacteria. The inferred regulons can be used for genetic experiments, functional annotations of genes, metabolic reconstruction and evolutionary analysis. The obtained genome

Comparative genomic assessment of Multi-Locus Sequence Typing: rapid accumulation of genomic heterogeneity among clonal isolates of Campylobacter jejuni

Directory of Open Access Journals (Sweden)

Nash John HE

2008-08-01

Full Text Available Abstract Background Multi-Locus Sequence Typing (MLST has emerged as a leading molecular typing method owing to its high ability to discriminate among bacterial isolates, the relative ease with which data acquisition and analysis can be standardized, and the high portability of the resulting sequence data. While MLST has been successfully applied to the study of the population structure for a number of different bacterial species, it has also provided compelling evidence for high rates of recombination in some species. We have analyzed a set of Campylobacter jejuni strains using MLST and Comparative Genomic Hybridization (CGH on a full-genome microarray in order to determine whether recombination and high levels of genomic mosaicism adversely affect the inference of strain relationships based on the analysis of a restricted number of genetic loci. Results Our results indicate that, in general, there is significant concordance between strain relationships established by MLST and those based on shared gene content as established by CGH. While MLST has significant predictive power with respect to overall genome similarity of isolates, we also found evidence for significant differences in genomic content among strains that would otherwise appear to be highly related based on their MLST profiles. Conclusion The extensive genomic mosaicism between closely related strains has important implications in the context of establishing strain to strain relationships because it suggests that the exact gene content of strains, and by extension their phenotype, is less likely to be "predicted" based on a small number of typing loci. This in turn suggests that a greater emphasis should be placed on analyzing genes of clinical interest as we forge ahead with the next generation of molecular typing methods.

Evolutionary analysis of whole-genome sequences confirms inter-farm transmission of Aleutian mink disease virus

DEFF Research Database (Denmark)

Hagberg, Emma Elisabeth; Pedersen, Anders Gorm; Larsen, Lars E

2017-01-01

Aleutian mink disease virus (AMDV) is a frequently encountered pathogen associated with mink farming. Previous phylogenetic analyses of AMDV have been based on shorter and more conserved parts of the genome, e.g. the partial NS1 gene. Such fragments are suitable for detection but are less useful...... direction of spread. It was however impossible to infer transmission pathways from the partial NS1 gene tree, since all samples from the case farms branched out from a single internal node. A sliding window analysis showed that there were no shorter genomic regions providing the same phylogenetic resolution...

Optimization methods for logical inference

CERN Document Server

Chandru, Vijay

2011-01-01

Merging logic and mathematics in deductive inference-an innovative, cutting-edge approach. Optimization methods for logical inference? Absolutely, say Vijay Chandru and John Hooker, two major contributors to this rapidly expanding field. And even though ""solving logical inference problems with optimization methods may seem a bit like eating sauerkraut with chopsticks. . . it is the mathematical structure of a problem that determines whether an optimization model can help solve it, not the context in which the problem occurs."" Presenting powerful, proven optimization techniques for logic in

Influence of salinity on bacterioplankton communities from the Brazilian rain forest to the coastal Atlantic Ocean.

Science.gov (United States)

Silveira, Cynthia B; Vieira, Ricardo P; Cardoso, Alexander M; Paranhos, Rodolfo; Albano, Rodolpho M; Martins, Orlando B

2011-03-09

bacterioplankton communities in a tropical island at the South Atlantic Ocean.

Influence of salinity on bacterioplankton communities from the Brazilian rain forest to the coastal Atlantic Ocean.

Directory of Open Access Journals (Sweden)

Cynthia B Silveira

parameters. Furthermore, this paper reveals for the first time the pristine bacterioplankton communities in a tropical island at the South Atlantic Ocean.

Influence of Salinity on Bacterioplankton Communities from the Brazilian Rain Forest to the Coastal Atlantic Ocean

Science.gov (United States)

Silveira, Cynthia B.; Vieira, Ricardo P.; Cardoso, Alexander M.; Paranhos, Rodolfo; Albano, Rodolpho M.; Martins, Orlando B.

2011-01-01

. Furthermore, this paper reveals for the first time the pristine bacterioplankton communities in a tropical island at the South Atlantic Ocean. PMID:21408023

Tempo and mode of genomic mutations unveil human evolutionary history.

Science.gov (United States)

Hara, Yuichiro

2015-01-01

Mutations that have occurred in human genomes provide insight into various aspects of evolutionary history such as speciation events and degrees of natural selection. Comparing genome sequences between human and great apes or among humans is a feasible approach for inferring human evolutionary history. Recent advances in high-throughput or so-called 'next-generation' DNA sequencing technologies have enabled the sequencing of thousands of individual human genomes, as well as a variety of reference genomes of hominids, many of which are publicly available. These sequence data can help to unveil the detailed demographic history of the lineage leading to humans as well as the explosion of modern human population size in the last several thousand years. In addition, high-throughput sequencing illustrates the tempo and mode of de novo mutations, which are producing human genetic variation at this moment. Pedigree-based human genome sequencing has shown that mutation rates vary significantly across the human genome. These studies have also provided an improved timescale of human evolution, because the mutation rate estimated from pedigree analysis is half that estimated from traditional analyses based on molecular phylogeny. Because of the dramatic reduction in sequencing cost, sequencing on-demand samples designed for specific studies is now also becoming popular. To produce data of sufficient quality to meet the requirements of the study, it is necessary to set an explicit sequencing plan that includes the choice of sample collection methods, sequencing platforms, and number of sequence reads.

Inference in `poor` languages

Energy Technology Data Exchange (ETDEWEB)

Petrov, S.

1996-10-01

Languages with a solvable implication problem but without complete and consistent systems of inference rules (`poor` languages) are considered. The problem of existence of finite complete and consistent inference rule system for a ``poor`` language is stated independently of the language or rules syntax. Several properties of the problem arc proved. An application of results to the language of join dependencies is given.

Ancestry inference using principal component analysis and spatial analysis: a distance-based analysis to account for population substructure.

Science.gov (United States)

Byun, Jinyoung; Han, Younghun; Gorlov, Ivan P; Busam, Jonathan A; Seldin, Michael F; Amos, Christopher I

2017-10-16

Accurate inference of genetic ancestry is of fundamental interest to many biomedical, forensic, and anthropological research areas. Genetic ancestry memberships may relate to genetic disease risks. In a genome association study, failing to account for differences in genetic ancestry between cases and controls may also lead to false-positive results. Although a number of strategies for inferring and taking into account the confounding effects of genetic ancestry are available, applying them to large studies (tens thousands samples) is challenging. The goal of this study is to develop an approach for inferring genetic ancestry of samples with unknown ancestry among closely related populations and to provide accurate estimates of ancestry for application to large-scale studies. In this study we developed a novel distance-based approach, Ancestry Inference using Principal component analysis and Spatial analysis (AIPS) that incorporates an Inverse Distance Weighted (IDW) interpolation method from spatial analysis to assign individuals to population memberships. We demonstrate the benefits of AIPS in analyzing population substructure, specifically related to the four most commonly used tools EIGENSTRAT, STRUCTURE, fastSTRUCTURE, and ADMIXTURE using genotype data from various intra-European panels and European-Americans. While the aforementioned commonly used tools performed poorly in inferring ancestry from a large number of subpopulations, AIPS accurately distinguished variations between and within subpopulations. Our results show that AIPS can be applied to large-scale data sets to discriminate the modest variability among intra-continental populations as well as for characterizing inter-continental variation. The method we developed will protect against spurious associations when mapping the genetic basis of a disease. Our approach is more accurate and computationally efficient method for inferring genetic ancestry in the large-scale genetic studies.

EI: A Program for Ecological Inference

Directory of Open Access Journals (Sweden)

Gary King

2004-09-01

Full Text Available The program EI provides a method of inferring individual behavior from aggregate data. It implements the statistical procedures, diagnostics, and graphics from the book A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data (King 1997. Ecological inference, as traditionally defined, is the process of using aggregate (i.e., "ecological" data to infer discrete individual-level relationships of interest when individual-level data are not available. Ecological inferences are required in political science research when individual-level surveys are unavailable (e.g., local or comparative electoral politics, unreliable (racial politics, insufficient (political geography, or infeasible (political history. They are also required in numerous areas of ma jor significance in public policy (e.g., for applying the Voting Rights Act and other academic disciplines ranging from epidemiology and marketing to sociology and quantitative history.

King penguin demography since the last glaciation inferred from genome-wide data.

Science.gov (United States)

Trucchi, Emiliano; Gratton, Paolo; Whittington, Jason D; Cristofari, Robin; Le Maho, Yvon; Stenseth, Nils Chr; Le Bohec, Céline

2014-07-22

How natural climate cycles, such as past glacial/interglacial patterns, have shaped species distributions at the high-latitude regions of the Southern Hemisphere is still largely unclear. Here, we show how the post-glacial warming following the Last Glacial Maximum (ca 18 000 years ago), allowed the (re)colonization of the fragmented sub-Antarctic habitat by an upper-level marine predator, the king penguin Aptenodytes patagonicus. Using restriction site-associated DNA sequencing and standard mitochondrial data, we tested the behaviour of subsets of anonymous nuclear loci in inferring past demography through coalescent-based and allele frequency spectrum analyses. Our results show that the king penguin population breeding on Crozet archipelago steeply increased in size, closely following the Holocene warming recorded in the Epica Dome C ice core. The following population growth can be explained by a threshold model in which the ecological requirements of this species (year-round ice-free habitat for breeding and access to a major source of food such as the Antarctic Polar Front) were met on Crozet soon after the Pleistocene/Holocene climatic transition. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

eHive: An Artificial Intelligence workflow system for genomic analysis

Science.gov (United States)

2010-01-01

Background The Ensembl project produces updates to its comparative genomics resources with each of its several releases per year. During each release cycle approximately two weeks are allocated to generate all the genomic alignments and the protein homology predictions. The number of calculations required for this task grows approximately quadratically with the number of species. We currently support 50 species in Ensembl and we expect the number to continue to grow in the future. Results We present eHive, a new fault tolerant distributed processing system initially designed to support comparative genomic analysis, based on blackboard systems, network distributed autonomous agents, dataflow graphs and block-branch diagrams. In the eHive system a MySQL database serves as the central blackboard and the autonomous agent, a Perl script, queries the system and runs jobs as required. The system allows us to define dataflow and branching rules to suit all our production pipelines. We describe the implementation of three pipelines: (1) pairwise whole genome alignments, (2) multiple whole genome alignments and (3) gene trees with protein homology inference. Finally, we show the efficiency of the system in real case scenarios. Conclusions eHive allows us to produce computationally demanding results in a reliable and efficient way with minimal supervision and high throughput. Further documentation is available at: http://www.ensembl.org/info/docs/eHive/. PMID:20459813

eHive: An Artificial Intelligence workflow system for genomic analysis

Directory of Open Access Journals (Sweden)

Gordon Leo

2010-05-01

Full Text Available Abstract Background The Ensembl project produces updates to its comparative genomics resources with each of its several releases per year. During each release cycle approximately two weeks are allocated to generate all the genomic alignments and the protein homology predictions. The number of calculations required for this task grows approximately quadratically with the number of species. We currently support 50 species in Ensembl and we expect the number to continue to grow in the future. Results We present eHive, a new fault tolerant distributed processing system initially designed to support comparative genomic analysis, based on blackboard systems, network distributed autonomous agents, dataflow graphs and block-branch diagrams. In the eHive system a MySQL database serves as the central blackboard and the autonomous agent, a Perl script, queries the system and runs jobs as required. The system allows us to define dataflow and branching rules to suit all our production pipelines. We describe the implementation of three pipelines: (1 pairwise whole genome alignments, (2 multiple whole genome alignments and (3 gene trees with protein homology inference. Finally, we show the efficiency of the system in real case scenarios. Conclusions eHive allows us to produce computationally demanding results in a reliable and efficient way with minimal supervision and high throughput. Further documentation is available at: http://www.ensembl.org/info/docs/eHive/.

eHive: an artificial intelligence workflow system for genomic analysis.

Science.gov (United States)

Severin, Jessica; Beal, Kathryn; Vilella, Albert J; Fitzgerald, Stephen; Schuster, Michael; Gordon, Leo; Ureta-Vidal, Abel; Flicek, Paul; Herrero, Javier

2010-05-11

The Ensembl project produces updates to its comparative genomics resources with each of its several releases per year. During each release cycle approximately two weeks are allocated to generate all the genomic alignments and the protein homology predictions. The number of calculations required for this task grows approximately quadratically with the number of species. We currently support 50 species in Ensembl and we expect the number to continue to grow in the future. We present eHive, a new fault tolerant distributed processing system initially designed to support comparative genomic analysis, based on blackboard systems, network distributed autonomous agents, dataflow graphs and block-branch diagrams. In the eHive system a MySQL database serves as the central blackboard and the autonomous agent, a Perl script, queries the system and runs jobs as required. The system allows us to define dataflow and branching rules to suit all our production pipelines. We describe the implementation of three pipelines: (1) pairwise whole genome alignments, (2) multiple whole genome alignments and (3) gene trees with protein homology inference. Finally, we show the efficiency of the system in real case scenarios. eHive allows us to produce computationally demanding results in a reliable and efficient way with minimal supervision and high throughput. Further documentation is available at: http://www.ensembl.org/info/docs/eHive/.

Organization of plastid genomes in the freshwater red algal order Batrachospermales (Rhodophyta).

Science.gov (United States)

Paiano, Monica Orlandi; Del Cortona, Andrea; Costa, Joana F; Liu, Shao-Lun; Verbruggen, Heroen; De Clerck, Olivier; Necchi, Orlando

2018-02-01

Little is known about genome organization in members of the order Batrachospermales, and the infra-ordinal relationship remains unresolved. Plastid (cp) genomes of seven members of the freshwater red algal order Batrachospermales were sequenced, with the following aims: (i) to describe the characteristics of cp genomes and compare these with other red algal groups; (ii) to infer the phylogenetic relationships among these members to better understand the infra-ordinal classification. Cp genomes of Batrachospermales are large, with several cases of gene loss, they are gene-dense (high gene content for the genome size and short intergenic regions) and have highly conserved gene order. Phylogenetic analyses based on concatenated nucleotide genome data roughly supports the current taxonomic system for the order. Comparative analyses confirm data for members of the class Florideophyceae that cp genomes in Batrachospermales is highly conserved, with little variation in gene composition. However, relevant new features were revealed in our study: genome sizes in members of Batrachospermales are close to the lowest values reported for Florideophyceae; differences in cp genome size within the order are large in comparison with other orders (Ceramiales, Gelidiales, Gracilariales, Hildenbrandiales, and Nemaliales); and members of Batrachospermales have the lowest number of protein-coding genes among the Florideophyceae. In terms of gene loss, apcF, which encodes the allophycocyanin beta subunit, is absent in all sequenced taxa of Batrachospermales. We reinforce that the interordinal relationships between the freshwater orders Batrachospermales and Thoreales within the Nemaliophycidae is not well resolved due to limited taxon sampling. © 2017 Phycological Society of America.

De novo prediction of human chromosome structures: Epigenetic marking patterns encode genome architecture.

Science.gov (United States)

Di Pierro, Michele; Cheng, Ryan R; Lieberman Aiden, Erez; Wolynes, Peter G; Onuchic, José N

2017-11-14

Inside the cell nucleus, genomes fold into organized structures that are characteristic of cell type. Here, we show that this chromatin architecture can be predicted de novo using epigenetic data derived from chromatin immunoprecipitation-sequencing (ChIP-Seq). We exploit the idea that chromosomes encode a 1D sequence of chromatin structural types. Interactions between these chromatin types determine the 3D structural ensemble of chromosomes through a process similar to phase separation. First, a neural network is used to infer the relation between the epigenetic marks present at a locus, as assayed by ChIP-Seq, and the genomic compartment in which those loci reside, as measured by DNA-DNA proximity ligation (Hi-C). Next, types inferred from this neural network are used as an input to an energy landscape model for chromatin organization [Minimal Chromatin Model (MiChroM)] to generate an ensemble of 3D chromosome conformations at a resolution of 50 kilobases (kb). After training the model, dubbed Maximum Entropy Genomic Annotation from Biomarkers Associated to Structural Ensembles (MEGABASE), on odd-numbered chromosomes, we predict the sequences of chromatin types and the subsequent 3D conformational ensembles for the even chromosomes. We validate these structural ensembles by using ChIP-Seq tracks alone to predict Hi-C maps, as well as distances measured using 3D fluorescence in situ hybridization (FISH) experiments. Both sets of experiments support the hypothesis of phase separation being the driving process behind compartmentalization. These findings strongly suggest that epigenetic marking patterns encode sufficient information to determine the global architecture of chromosomes and that de novo structure prediction for whole genomes may be increasingly possible. Copyright © 2017 the Author(s). Published by PNAS.

Pan-Genome Analysis Links the Hereditary Variation of Leptospirillum ferriphilum With Its Evolutionary Adaptation

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Xian Zhang

2018-03-01

Full Text Available Niche adaptation has long been recognized to drive intra-species differentiation and speciation, yet knowledge about its relatedness with hereditary variation of microbial genomes is relatively limited. Using Leptospirillum ferriphilum species as a case study, we present a detailed analysis of genomic features of five recognized strains. Genome-to-genome distance calculation preliminarily determined the roles of spatial distance and environmental heterogeneity that potentially contribute to intra-species variation within L. ferriphilum species at the genome level. Mathematical models were further constructed to extrapolate the expansion of L. ferriphilum genomes (an ‘open’ pan-genome, indicating the emergence of novel genes with new sequenced genomes. The identification of diverse mobile genetic elements (MGEs (such as transposases, integrases, and phage-associated genes revealed the prevalence of horizontal gene transfer events, which is an important evolutionary mechanism that provides avenues for the recruitment of novel functionalities and further for the genetic divergence of microbial genomes. Comprehensive analysis also demonstrated that the genome reduction by gene loss in a broad sense might contribute to the observed diversification. We thus inferred a plausible explanation to address this observation: the community-dependent adaptation that potentially economizes the limiting resources of the entire community. Now that the introduction of new genes is accompanied by a parallel abandonment of some other ones, our results provide snapshots on the biological fitness cost of environmental adaptation within the L. ferriphilum genomes. In short, our genome-wide analyses bridge the relation between genetic variation of L. ferriphilum with its evolutionary adaptation.

On the criticality of inferred models

Science.gov (United States)

Mastromatteo, Iacopo; Marsili, Matteo

2011-10-01

Advanced inference techniques allow one to reconstruct a pattern of interaction from high dimensional data sets, from probing simultaneously thousands of units of extended systems—such as cells, neural tissues and financial markets. We focus here on the statistical properties of inferred models and argue that inference procedures are likely to yield models which are close to singular values of parameters, akin to critical points in physics where phase transitions occur. These are points where the response of physical systems to external perturbations, as measured by the susceptibility, is very large and diverges in the limit of infinite size. We show that the reparameterization invariant metrics in the space of probability distributions of these models (the Fisher information) are directly related to the susceptibility of the inferred model. As a result, distinguishable models tend to accumulate close to critical points, where the susceptibility diverges in infinite systems. This region is the one where the estimate of inferred parameters is most stable. In order to illustrate these points, we discuss inference of interacting point processes with application to financial data and show that sensible choices of observation time scales naturally yield models which are close to criticality.

On the criticality of inferred models

International Nuclear Information System (INIS)

Mastromatteo, Iacopo; Marsili, Matteo

2011-01-01

Advanced inference techniques allow one to reconstruct a pattern of interaction from high dimensional data sets, from probing simultaneously thousands of units of extended systems—such as cells, neural tissues and financial markets. We focus here on the statistical properties of inferred models and argue that inference procedures are likely to yield models which are close to singular values of parameters, akin to critical points in physics where phase transitions occur. These are points where the response of physical systems to external perturbations, as measured by the susceptibility, is very large and diverges in the limit of infinite size. We show that the reparameterization invariant metrics in the space of probability distributions of these models (the Fisher information) are directly related to the susceptibility of the inferred model. As a result, distinguishable models tend to accumulate close to critical points, where the susceptibility diverges in infinite systems. This region is the one where the estimate of inferred parameters is most stable. In order to illustrate these points, we discuss inference of interacting point processes with application to financial data and show that sensible choices of observation time scales naturally yield models which are close to criticality

DESCARTES’ RULE OF SIGNS AND THE IDENTIFIABILITY OF POPULATION DEMOGRAPHIC MODELS FROM GENOMIC VARIATION DATA1

Science.gov (United States)

Bhaskar, Anand; Song, Yun S.

2016-01-01

The sample frequency spectrum (SFS) is a widely-used summary statistic of genomic variation in a sample of homologous DNA sequences. It provides a highly efficient dimensional reduction of large-scale population genomic data and its mathematical dependence on the underlying population demography is well understood, thus enabling the development of efficient inference algorithms. However, it has been recently shown that very different population demographies can actually generate the same SFS for arbitrarily large sample sizes. Although in principle this nonidentifiability issue poses a thorny challenge to statistical inference, the population size functions involved in the counterexamples are arguably not so biologically realistic. Here, we revisit this problem and examine the identifiability of demographic models under the restriction that the population sizes are piecewise-defined where each piece belongs to some family of biologically-motivated functions. Under this assumption, we prove that the expected SFS of a sample uniquely determines the underlying demographic model, provided that the sample is sufficiently large. We obtain a general bound on the sample size sufficient for identifiability; the bound depends on the number of pieces in the demographic model and also on the type of population size function in each piece. In the cases of piecewise-constant, piecewise-exponential and piecewise-generalized-exponential models, which are often assumed in population genomic inferences, we provide explicit formulas for the bounds as simple functions of the number of pieces. Lastly, we obtain analogous results for the “folded” SFS, which is often used when there is ambiguity as to which allelic type is ancestral. Our results are proved using a generalization of Descartes’ rule of signs for polynomials to the Laplace transform of piecewise continuous functions. PMID:28018011

Phylogenetic Conflict in Bears Identified by Automated Discovery of Transposable Element Insertions in Low-Coverage Genomes

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Gallus, Susanne; Janke, Axel

2017-01-01

Abstract Phylogenetic reconstruction from transposable elements (TEs) offers an additional perspective to study evolutionary processes. However, detecting phylogenetically informative TE insertions requires tedious experimental work, limiting the power of phylogenetic inference. Here, we analyzed the genomes of seven bear species using high-throughput sequencing data to detect thousands of TE insertions. The newly developed pipeline for TE detection called TeddyPi (TE detection and discovery for Phylogenetic Inference) identified 150,513 high-quality TE insertions in the genomes of ursine and tremarctine bears. By integrating different TE insertion callers and using a stringent filtering approach, the TeddyPi pipeline produced highly reliable TE insertion calls, which were confirmed by extensive in vitro validation experiments. Analysis of single nucleotide substitutions in the flanking regions of the TEs shows that these substitutions correlate with the phylogenetic signal from the TE insertions. Our phylogenomic analyses show that TEs are a major driver of genomic variation in bears and enabled phylogenetic reconstruction of a well-resolved species tree, despite strong signals for incomplete lineage sorting and introgression. The analyses show that the Asiatic black, sun, and sloth bear form a monophyletic clade, in which phylogenetic incongruence originates from incomplete lineage sorting. TeddyPi is open source and can be adapted to various TE and structural variation callers. The pipeline makes it possible to confidently extract thousands of TE insertions even from low-coverage genomes (∼10×) of nonmodel organisms. This opens new possibilities for biologists to study phylogenies and evolutionary processes as well as rates and patterns of (retro-)transposition and structural variation. PMID:28985298

An Inference Language for Imaging

DEFF Research Database (Denmark)

Pedemonte, Stefano; Catana, Ciprian; Van Leemput, Koen

2014-01-01

We introduce iLang, a language and software framework for probabilistic inference. The iLang framework enables the definition of directed and undirected probabilistic graphical models and the automated synthesis of high performance inference algorithms for imaging applications. The iLang framewor...

Comparative analyses identified species-specific functional roles in oral microbial genomes

Science.gov (United States)

Chen, Tsute; Gajare, Prasad; Olsen, Ingar; Dewhirst, Floyd E.

2017-01-01

ABSTRACT The advent of next generation sequencing is producing more genomic sequences for various strains of many human oral microbial species and allows for insightful functional comparisons at both intra- and inter-species levels. This study performed in-silico functional comparisons for currently available genomic sequences of major species associated with periodontitis including Aggregatibacter actinomycetemcomitans (AA), Porphyromonas gingivalis (PG), Treponema denticola (TD), and Tannerella forsythia (TF), as well as several cariogenic and commensal streptococcal species. Complete or draft sequences were annotated with the RAST to infer structured functional subsystems for each genome. The subsystems profiles were clustered to groups of functions with similar patterns. Functional enrichment and depletion were evaluated based on hypergeometric distribution to identify subsystems that are unique or missing between two groups of genomes. Unique or missing metabolic pathways and biological functions were identified in different species. For example, components involved in flagellar motility were found only in the motile species TD, as expected, with few exceptions scattered in several streptococcal species, likely associated with chemotaxis. Transposable elements were only found in the two Bacteroidales species PG and TF, and half of the AA genomes. Genes involved in CRISPR were prevalent in most oral species. Furthermore, prophage related subsystems were also commonly found in most species except for PG and Streptococcus mutans, in which very few genomes contain prophage components. Comparisons between pathogenic (P) and nonpathogenic (NP) genomes also identified genes potentially important for virulence. Two such comparisons were performed between AA (P) and several A. aphrophilus (NP) strains, and between S. mutans + S. sobrinus (P) and other oral streptococcal species (NP). This comparative genomics approach can be readily used to identify functions unique to

Large-scale modeling of condition-specific gene regulatory networks by information integration and inference.

Science.gov (United States)

Ellwanger, Daniel Christian; Leonhardt, Jörn Florian; Mewes, Hans-Werner

2014-12-01

Understanding how regulatory networks globally coordinate the response of a cell to changing conditions, such as perturbations by shifting environments, is an elementary challenge in systems biology which has yet to be met. Genome-wide gene expression measurements are high dimensional as these are reflecting the condition-specific interplay of thousands of cellular components. The integration of prior biological knowledge into the modeling process of systems-wide gene regulation enables the large-scale interpretation of gene expression signals in the context of known regulatory relations. We developed COGERE (http://mips.helmholtz-muenchen.de/cogere), a method for the inference of condition-specific gene regulatory networks in human and mouse. We integrated existing knowledge of regulatory interactions from multiple sources to a comprehensive model of prior information. COGERE infers condition-specific regulation by evaluating the mutual dependency between regulator (transcription factor or miRNA) and target gene expression using prior information. This dependency is scored by the non-parametric, nonlinear correlation coefficient η(2) (eta squared) that is derived by a two-way analysis of variance. We show that COGERE significantly outperforms alternative methods in predicting condition-specific gene regulatory networks on simulated data sets. Furthermore, by inferring the cancer-specific gene regulatory network from the NCI-60 expression study, we demonstrate the utility of COGERE to promote hypothesis-driven clinical research. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Species boundaries and hybridization in central-European Nymphaea species inferred from genome size and morphometric data

Czech Academy of Sciences Publication Activity Database

Kabátová, Klára; Vít, Petr; Suda, Jan

2014-01-01

Roč. 86, č. 2 (2014), s. 131-154 ISSN 0032-7786 R&D Projects: GA ČR GB14-36079G Institutional support: RVO:67985939 Keywords : genome size * multivariate morphometrics * Nymphaea Subject RIV: EF - Botanics Impact factor: 4.104, year: 2014

The first complete chloroplast genome sequence of a lycophyte,Huperzia lucidula (Lycopodiaceae)

Energy Technology Data Exchange (ETDEWEB)

Wolf, Paul G.; Karol, Kenneth G.; Mandoli, Dina F.; Kuehl,Jennifer V.; Arumuganathan, K.; Ellis, Mark W.; Mishler, Brent D.; Kelch,Dean G.; Olmstead, Richard G.; Boore, Jeffrey L.

2005-02-01

We used a unique combination of techniques to sequence the first complete chloroplast genome of a lycophyte, Huperzia lucidula. This plant belongs to a significant clade hypothesized to represent the sister group to all other vascular plants. We used fluorescence-activated cell sorting (FACS) to isolate the organelles, rolling circle amplification (RCA) to amplify the genome, and shotgun sequencing to 8x depth coverage to obtain the complete chloroplast genome sequence. The genome is 154,373bp, containing inverted repeats of 15,314 bp each, a large single-copy region of 104,088 bp, and a small single-copy region of 19,671 bp. Gene order is more similar to those of mosses, liverworts, and hornworts than to gene order for other vascular plants. For example, the Huperziachloroplast genome possesses the bryophyte gene order for a previously characterized 30 kb inversion, thus supporting the hypothesis that lycophytes are sister to all other extant vascular plants. The lycophytechloroplast genome data also enable a better reconstruction of the basaltracheophyte genome, which is useful for inferring relationships among bryophyte lineages. Several unique characters are observed in Huperzia, such as movement of the gene ndhF from the small single copy region into the inverted repeat. We present several analyses of evolutionary relationships among land plants by using nucleotide data, amino acid sequences, and by comparing gene arrangements from chloroplast genomes. The results, while still tentative pending the large number of chloroplast genomes from other key lineages that are soon to be sequenced, are intriguing in themselves, and contribute to a growing comparative database of genomic and morphological data across the green plants.

Inference

DEFF Research Database (Denmark)

Møller, Jesper

2010-01-01

Chapter 9: This contribution concerns statistical inference for parametric models used in stochastic geometry and based on quick and simple simulation free procedures as well as more comprehensive methods based on a maximum likelihood or Bayesian approach combined with markov chain Monte Carlo...... (MCMC) techniques. Due to space limitations the focus is on spatial point processes....

A statistical framework to predict functional non-coding regions in the human genome through integrated analysis of annotation data.

Science.gov (United States)

Lu, Qiongshi; Hu, Yiming; Sun, Jiehuan; Cheng, Yuwei; Cheung, Kei-Hoi; Zhao, Hongyu

2015-05-27

Identifying functional regions in the human genome is a major goal in human genetics. Great efforts have been made to functionally annotate the human genome either through computational predictions, such as genomic conservation, or high-throughput experiments, such as the ENCODE project. These efforts have resulted in a rich collection of functional annotation data of diverse types that need to be jointly analyzed for integrated interpretation and annotation. Here we present GenoCanyon, a whole-genome annotation method that performs unsupervised statistical learning using 22 computational and experimental annotations thereby inferring the functional potential of each position in the human genome. With GenoCanyon, we are able to predict many of the known functional regions. The ability of predicting functional regions as well as its generalizable statistical framework makes GenoCanyon a unique and powerful tool for whole-genome annotation. The GenoCanyon web server is available at http://genocanyon.med.yale.edu.

Feature Inference Learning and Eyetracking

Science.gov (United States)

Rehder, Bob; Colner, Robert M.; Hoffman, Aaron B.

2009-01-01

Besides traditional supervised classification learning, people can learn categories by inferring the missing features of category members. It has been proposed that feature inference learning promotes learning a category's internal structure (e.g., its typical features and interfeature correlations) whereas classification promotes the learning of…

Phylogeny of the Celastraceae inferred from phytochrome B gene sequence and morphology.

Science.gov (United States)

Simmons, M P; Clevinger, C C; Savolainen, V; Archer, R H; Mathews, S; Doyle, J J

2001-02-01

Phylogenetic relationships within Celastraceae were inferred using a simultaneous analysis of 61 morphological characters and 1123 base pairs of phytochrome B exon 1 from the nuclear genome. No gaps were inferred, and the gene tree topology suggests that the primers were specific to a single locus that did not duplicate among the lineages sampled. This region of phytochrome B was most useful for examining relationships among closely related genera. Fifty-one species from 38 genera of Celastraceae were sampled. The Celastraceae sensu lato (including Hippocrateaceae) were resolved as a monophyletic group. Loesener's subfamilies and tribes of Celastraceae were not supported. The Hippocrateaceae were resolved as a monophyletic group nested within a paraphyletic Celastraceae sensu stricto. Goupia was resolved as more closely related to Euphorbiaceae, Corynocarpaceae, and Linaceae than to Celastraceae. Plagiopteron (Flacourtiaceae) was resolved as the sister group of Hippocrateoideae. Brexia (Brexiaceae) was resolved as closely related to Elaeodendron and Pleurostylia. Canotia was resolved as the sister group of Acanthothamnus within Celastraceae. Perrottetia and Mortonia were resolved as the sister group of the rest of the Celastraceae. Siphonodon was resolved as a derived member of Celastraceae. Maytenus was resolved as three disparate groups, suggesting that this large genus needs to be recircumscribed.

Powerful Inference With the D-Statistic on Low-Coverage Whole-Genome Data

DEFF Research Database (Denmark)

Soraggi, Samuele; Wiuf, Carsten; Albrechtsen, Anders

2018-01-01

The detection of ancient gene flow between human populations is an important issue in population genetics. A common tool for detecting ancient admixture events is the D-statistic. The D-statistic is based on the hypothesis of a genetic relationship that involves four populations, whose correctness...... is assessed by evaluating specific coincidences of alleles between the groups. When working with high throughput sequencing data calling genotypes accurately is not always possible, therefore the D-statistic currently samples a single base from the reads of one individual per population. This implies ignoring...... much of the information in the data, an issue especially striking in the case of ancient genomes. We provide a significant improvement to overcome the problems of the D-statistic by considering all reads from multiple individuals in each population. We also apply type-specific error correction...

Visualization of RNA structure models within the Integrative Genomics Viewer.

Science.gov (United States)

Busan, Steven; Weeks, Kevin M

2017-07-01

Analyses of the interrelationships between RNA structure and function are increasingly important components of genomic studies. The SHAPE-MaP strategy enables accurate RNA structure probing and realistic structure modeling of kilobase-length noncoding RNAs and mRNAs. Existing tools for visualizing RNA structure models are not suitable for efficient analysis of long, structurally heterogeneous RNAs. In addition, structure models are often advantageously interpreted in the context of other experimental data and gene annotation information, for which few tools currently exist. We have developed a module within the widely used and well supported open-source Integrative Genomics Viewer (IGV) that allows visualization of SHAPE and other chemical probing data, including raw reactivities, data-driven structural entropies, and data-constrained base-pair secondary structure models, in context with linear genomic data tracks. We illustrate the usefulness of visualizing RNA structure in the IGV by exploring structure models for a large viral RNA genome, comparing bacterial mRNA structure in cells with its structure under cell- and protein-free conditions, and comparing a noncoding RNA structure modeled using SHAPE data with a base-pairing model inferred through sequence covariation analysis. © 2017 Busan and Weeks; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Forward and backward inference in spatial cognition.

Directory of Open Access Journals (Sweden)

Will D Penny

Full Text Available This paper shows that the various computations underlying spatial cognition can be implemented using statistical inference in a single probabilistic model. Inference is implemented using a common set of 'lower-level' computations involving forward and backward inference over time. For example, to estimate where you are in a known environment, forward inference is used to optimally combine location estimates from path integration with those from sensory input. To decide which way to turn to reach a goal, forward inference is used to compute the likelihood of reaching that goal under each option. To work out which environment you are in, forward inference is used to compute the likelihood of sensory observations under the different hypotheses. For reaching sensory goals that require a chaining together of decisions, forward inference can be used to compute a state trajectory that will lead to that goal, and backward inference to refine the route and estimate control signals that produce the required trajectory. We propose that these computations are reflected in recent findings of pattern replay in the mammalian brain. Specifically, that theta sequences reflect decision making, theta flickering reflects model selection, and remote replay reflects route and motor planning. We also propose a mapping of the above computational processes onto lateral and medial entorhinal cortex and hippocampus.

Genomic Changes Associated with the Evolutionary Transitions of Nostoc to a Plant Symbiont

Science.gov (United States)

Liaimer, Anton; Pederson, Eric; Kim, Sea-Yong; Shapiro, Nicole; Woyke, Tanja; Altermark, Bjørn; Pawlowski, Katharina; Weyman, Philip D; Dupont, Christopher L

2018-01-01

Abstract Cyanobacteria belonging to the genus Nostoc comprise free-living strains and also facultative plant symbionts. Symbiotic strains can enter into symbiosis with taxonomically diverse range of host plants. Little is known about genomic changes associated with evolutionary transition of Nostoc from free-living to plant symbiont. Here, we compared the genomes derived from 11 symbiotic Nostoc strains isolated from different host plants and infer phylogenetic relationships between strains. Phylogenetic reconstructions of 89 Nostocales showed that symbiotic Nostoc strains with a broad host range, entering epiphytic and intracellular or extracellular endophytic interactions, form a monophyletic clade indicating a common evolutionary history. A polyphyletic origin was found for Nostoc strains which enter only extracellular symbioses, and inference of transfer events implied that this trait was likely acquired several times in the evolution of the Nostocales. Symbiotic Nostoc strains showed enriched functions in transport and metabolism of organic sulfur, chemotaxis and motility, as well as the uptake of phosphate, branched-chain amino acids, and ammonium. The genomes of the intracellular clade differ from that of other Nostoc strains, with a gain/enrichment of genes encoding proteins to generate l-methionine from sulfite and pathways for the degradation of the plant metabolites vanillin and vanillate, and of the macromolecule xylan present in plant cell walls. These compounds could function as C-sources for members of the intracellular clade. Molecular clock analysis indicated that the intracellular clade emerged ca. 600 Ma, suggesting that intracellular Nostoc symbioses predate the origin of land plants and the emergence of their extant hosts. PMID:29554291

Complete Mitochondrial Genomes of the Cherskii’s Sculpin and Siberian Taimen Reveal GenBank Entry Errors: Incorrect Species Identification and Recombinant Mitochondrial Genome

Directory of Open Access Journals (Sweden)

Evgeniy S Balakirev

2017-08-01

Full Text Available The complete mitochondrial (mt genome is sequenced in 2 individuals of the Cherskii’s sculpin Cottus czerskii . A surprisingly high level of sequence divergence (10.3% has been detected between the 2 genomes of C czerskii studied here and the GenBank mt genome of C czerskii (KJ956027. At the same time, a surprisingly low level of divergence (1.4% has been detected between the GenBank C czerskii (KJ956027 and the Amur sculpin Cottus szanaga (KX762049, KX762050. We argue that the observed discrepancies are due to incorrect taxonomic identification so that the GenBank accession number KJ956027 represents actually the mt genome of C szanaga erroneously identified as C czerskii . Our results are of consequence concerning the GenBank database quality, highlighting the potential negative consequences of entry errors, which once they are introduced tend to be propagated among databases and subsequent publications. We illustrate the premise with the data on recombinant mt genome of the Siberian taimen Hucho taimen (NCBI Reference Sequence Database NC_016426.1; GenBank accession number HQ897271.1, bearing 2 introgressed fragments (≈0.9 kb [kilobase] from 2 lenok subspecies, Brachymystax lenok and Brachymystax lenok tsinlingensis , submitted to GenBank on June 12, 2011. Since the time of submission, the H taimen recombinant mt genome leading to incorrect phylogenetic inferences was propagated in multiple subsequent publications despite the fact that nonrecombinant H taimen genomes were also available (submitted to GenBank on August 2, 2014; KJ711549, KJ711550. Other examples of recombinant sequences persisting in GenBank are also considered. A GenBank Entry Error Depositary is urgently needed to monitor and avoid a progressive accumulation of wrong biological information.

A formal model of interpersonal inference

Directory of Open Access Journals (Sweden)

Michael eMoutoussis

2014-03-01

Full Text Available Introduction: We propose that active Bayesian inference – a general framework for decision-making – can equally be applied to interpersonal exchanges. Social cognition, however, entails special challenges. We address these challenges through a novel formulation of a formal model and demonstrate its psychological significance. Method: We review relevant literature, especially with regards to interpersonal representations, formulate a mathematical model and present a simulation study. The model accommodates normative models from utility theory and places them within the broader setting of Bayesian inference. Crucially, we endow people's prior beliefs, into which utilities are absorbed, with preferences of self and others. The simulation illustrates the model's dynamics and furnishes elementary predictions of the theory. Results: 1. Because beliefs about self and others inform both the desirability and plausibility of outcomes, in this framework interpersonal representations become beliefs that have to be actively inferred. This inference, akin to 'mentalising' in the psychological literature, is based upon the outcomes of interpersonal exchanges. 2. We show how some well-known social-psychological phenomena (e.g. self-serving biases can be explained in terms of active interpersonal inference. 3. Mentalising naturally entails Bayesian updating of how people value social outcomes. Crucially this includes inference about one’s own qualities and preferences. Conclusion: We inaugurate a Bayes optimal framework for modelling intersubject variability in mentalising during interpersonal exchanges. Here, interpersonal representations are endowed with explicit functional and affective properties. We suggest the active inference framework lends itself to the study of psychiatric conditions where mentalising is distorted.

Navigating the Interface Between Landscape Genetics and Landscape Genomics

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Andrew Storfer

2018-03-01

Full Text Available As next-generation sequencing data become increasingly available for non-model organisms, a shift has occurred in the focus of studies of the geographic distribution of genetic variation. Whereas landscape genetics studies primarily focus on testing the effects of landscape variables on gene flow and genetic population structure, landscape genomics studies focus on detecting candidate genes under selection that indicate possible local adaptation. Navigating the transition between landscape genomics and landscape genetics can be challenging. The number of molecular markers analyzed has shifted from what used to be a few dozen loci to thousands of loci and even full genomes. Although genome scale data can be separated into sets of neutral loci for analyses of gene flow and population structure and putative loci under selection for inference of local adaptation, there are inherent differences in the questions that are addressed in the two study frameworks. We discuss these differences and their implications for study design, marker choice and downstream analysis methods. Similar to the rapid proliferation of analysis methods in the early development of landscape genetics, new analytical methods for detection of selection in landscape genomics studies are burgeoning. We focus on genome scan methods for detection of selection, and in particular, outlier differentiation methods and genetic-environment association tests because they are the most widely used. Use of genome scan methods requires an understanding of the potential mismatches between the biology of a species and assumptions inherent in analytical methods used, which can lead to high false positive rates of detected loci under selection. Key to choosing appropriate genome scan methods is an understanding of the underlying demographic structure of study populations, and such data can be obtained using neutral loci from the generated genome-wide data or prior knowledge of a species

Distributional Inference

NARCIS (Netherlands)

Kroese, A.H.; van der Meulen, E.A.; Poortema, Klaas; Schaafsma, W.

1995-01-01

The making of statistical inferences in distributional form is conceptionally complicated because the epistemic 'probabilities' assigned are mixtures of fact and fiction. In this respect they are essentially different from 'physical' or 'frequency-theoretic' probabilities. The distributional form is

The mitochondrial genome of the legume Vigna radiata and the analysis of recombination across short mitochondrial repeats.

Directory of Open Access Journals (Sweden)

Andrew J Alverson

2011-01-01

Full Text Available The mitochondrial genomes of seed plants are exceptionally fluid in size, structure, and sequence content, with the accumulation and activity of repetitive sequences underlying much of this variation. We report the first fully sequenced mitochondrial genome of a legume, Vigna radiata (mung bean, and show that despite its unexceptional size (401,262 nt, the genome is unusually depauperate in repetitive DNA and "promiscuous" sequences from the chloroplast and nuclear genomes. Although Vigna lacks the large, recombinationally active repeats typical of most other seed plants, a PCR survey of its modest repertoire of short (38-297 nt repeats nevertheless revealed evidence for recombination across all of them. A set of novel control assays showed, however, that these results could instead reflect, in part or entirely, artifacts of PCR-mediated recombination. Consequently, we recommend that other methods, especially high-depth genome sequencing, be used instead of PCR to infer patterns of plant mitochondrial recombination. The average-sized but repeat- and feature-poor mitochondrial genome of Vigna makes it ever more difficult to generalize about the factors shaping the size and sequence content of plant mitochondrial genomes.

Continuous Integrated Invariant Inference, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The proposed project will develop a new technique for invariant inference and embed this and other current invariant inference and checking techniques in an...

Comparing genomes with rearrangements and segmental duplications.

Science.gov (United States)

Shao, Mingfu; Moret, Bernard M E

2015-06-15

Large-scale evolutionary events such as genomic rearrange.ments and segmental duplications form an important part of the evolution of genomes and are widely studied from both biological and computational perspectives. A basic computational problem is to infer these events in the evolutionary history for given modern genomes, a task for which many algorithms have been proposed under various constraints. Algorithms that can handle both rearrangements and content-modifying events such as duplications and losses remain few and limited in their applicability. We study the comparison of two genomes under a model including general rearrangements (through double-cut-and-join) and segmental duplications. We formulate the comparison as an optimization problem and describe an exact algorithm to solve it by using an integer linear program. We also devise a sufficient condition and an efficient algorithm to identify optimal substructures, which can simplify the problem while preserving optimality. Using the optimal substructures with the integer linear program (ILP) formulation yields a practical and exact algorithm to solve the problem. We then apply our algorithm to assign in-paralogs and orthologs (a necessary step in handling duplications) and compare its performance with that of the state-of-the-art method MSOAR, using both simulations and real data. On simulated datasets, our method outperforms MSOAR by a significant margin, and on five well-annotated species, MSOAR achieves high accuracy, yet our method performs slightly better on each of the 10 pairwise comparisons. http://lcbb.epfl.ch/softwares/coser. © The Author 2015. Published by Oxford University Press.

Complete sequencing of five araliaceae chloroplast genomes and the phylogenetic implications.

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Rong Li

Full Text Available BACKGROUND: The ginseng family (Araliaceae includes a number of economically important plant species. Previously phylogenetic studies circumscribed three major clades within the core ginseng plant family, yet the internal relationships of each major group have been poorly resolved perhaps due to rapid radiation of these lineages. Recent studies have shown that phyogenomics based on chloroplast genomes provides a viable way to resolve complex relationships. METHODOLOGY/PRINCIPAL FINDINGS: We report the complete nucleotide sequences of five Araliaceae chloroplast genomes using next-generation sequencing technology. The five chloroplast genomes are 156,333-156,459 bp in length including a pair of inverted repeats (25,551-26,108 bp separated by the large single-copy (86,028-86,566 bp and small single-copy (18,021-19,117 bp regions. Each chloroplast genome contains the same 114 unique genes consisting of 30 transfer RNA genes, four ribosomal RNA genes, and 80 protein coding genes. Gene size, content, and order, AT content, and IR/SC boundary structure are similar among all Araliaceae chloroplast genomes. A total of 140 repeats were identified in the five chloroplast genomes with palindromic repeat as the most common type. Phylogenomic analyses using parsimony, likelihood, and Bayesian inference based on the complete chloroplast genomes strongly supported the monophyly of the Asian Palmate group and the Aralia-Panax group. Furthermore, the relationships among the sampled taxa within the Asian Palmate group were well resolved. Twenty-six DNA markers with the percentage of variable sites higher than 5% were identified, which may be useful for phylogenetic studies of Araliaceae. CONCLUSION: The chloroplast genomes of Araliaceae are highly conserved in all aspects of genome features. The large-scale phylogenomic data based on the complete chloroplast DNA sequences is shown to be effective for the phylogenetic reconstruction of Araliaceae.

Estimating uncertainty of inference for validation

Energy Technology Data Exchange (ETDEWEB)

Booker, Jane M [Los Alamos National Laboratory; Langenbrunner, James R [Los Alamos National Laboratory; Hemez, Francois M [Los Alamos National Laboratory; Ross, Timothy J [UNM

2010-09-30

We present a validation process based upon the concept that validation is an inference-making activity. This has always been true, but the association has not been as important before as it is now. Previously, theory had been confirmed by more data, and predictions were possible based on data. The process today is to infer from theory to code and from code to prediction, making the role of prediction somewhat automatic, and a machine function. Validation is defined as determining the degree to which a model and code is an accurate representation of experimental test data. Imbedded in validation is the intention to use the computer code to predict. To predict is to accept the conclusion that an observable final state will manifest; therefore, prediction is an inference whose goodness relies on the validity of the code. Quantifying the uncertainty of a prediction amounts to quantifying the uncertainty of validation, and this involves the characterization of uncertainties inherent in theory/models/codes and the corresponding data. An introduction to inference making and its associated uncertainty is provided as a foundation for the validation problem. A mathematical construction for estimating the uncertainty in the validation inference is then presented, including a possibility distribution constructed to represent the inference uncertainty for validation under uncertainty. The estimation of inference uncertainty for validation is illustrated using data and calculations from Inertial Confinement Fusion (ICF). The ICF measurements of neutron yield and ion temperature were obtained for direct-drive inertial fusion capsules at the Omega laser facility. The glass capsules, containing the fusion gas, were systematically selected with the intent of establishing a reproducible baseline of high-yield 10{sup 13}-10{sup 14} neutron output. The deuterium-tritium ratio in these experiments was varied to study its influence upon yield. This paper on validation inference is the

Neandertal admixture in Eurasia confirmed by maximum-likelihood analysis of three genomes.

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Lohse, Konrad; Frantz, Laurent A F

2014-04-01

Although there has been much interest in estimating histories of divergence and admixture from genomic data, it has proved difficult to distinguish recent admixture from long-term structure in the ancestral population. Thus, recent genome-wide analyses based on summary statistics have sparked controversy about the possibility of interbreeding between Neandertals and modern humans in Eurasia. Here we derive the probability of full mutational configurations in nonrecombining sequence blocks under both admixture and ancestral structure scenarios. Dividing the genome into short blocks gives an efficient way to compute maximum-likelihood estimates of parameters. We apply this likelihood scheme to triplets of human and Neandertal genomes and compare the relative support for a model of admixture from Neandertals into Eurasian populations after their expansion out of Africa against a history of persistent structure in their common ancestral population in Africa. Our analysis allows us to conclusively reject a model of ancestral structure in Africa and instead reveals strong support for Neandertal admixture in Eurasia at a higher rate (3.4-7.3%) than suggested previously. Using analysis and simulations we show that our inference is more powerful than previous summary statistics and robust to realistic levels of recombination.

Mechanisms of Base Substitution Mutagenesis in Cancer Genomes

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Albino Bacolla

2014-03-01

Full Text Available Cancer genome sequence data provide an invaluable resource for inferring the key mechanisms by which mutations arise in cancer cells, favoring their survival, proliferation and invasiveness. Here we examine recent advances in understanding the molecular mechanisms responsible for the predominant type of genetic alteration found in cancer cells, somatic single base substitutions (SBSs. Cytosine methylation, demethylation and deamination, charge transfer reactions in DNA, DNA replication timing, chromatin status and altered DNA proofreading activities are all now known to contribute to the mechanisms leading to base substitution mutagenesis. We review current hypotheses as to the major processes that give rise to SBSs and evaluate their relative relevance in the light of knowledge acquired from cancer genome sequencing projects and the study of base modifications, DNA repair and lesion bypass. Although gene expression data on APOBEC3B enzymes provide support for a role in cancer mutagenesis through U:G mismatch intermediates, the enzyme preference for single-stranded DNA may limit its activity genome-wide. For SBSs at both CG:CG and YC:GR sites, we outline evidence for a prominent role of damage by charge transfer reactions that follow interactions of the DNA with reactive oxygen species (ROS and other endogenous or exogenous electron-abstracting molecules.

Mechanisms of base substitution mutagenesis in cancer genomes.

Science.gov (United States)

Bacolla, Albino; Cooper, David N; Vasquez, Karen M

2014-03-05

Cancer genome sequence data provide an invaluable resource for inferring the key mechanisms by which mutations arise in cancer cells, favoring their survival, proliferation and invasiveness. Here we examine recent advances in understanding the molecular mechanisms responsible for the predominant type of genetic alteration found in cancer cells, somatic single base substitutions (SBSs). Cytosine methylation, demethylation and deamination, charge transfer reactions in DNA, DNA replication timing, chromatin status and altered DNA proofreading activities are all now known to contribute to the mechanisms leading to base substitution mutagenesis. We review current hypotheses as to the major processes that give rise to SBSs and evaluate their relative relevance in the light of knowledge acquired from cancer genome sequencing projects and the study of base modifications, DNA repair and lesion bypass. Although gene expression data on APOBEC3B enzymes provide support for a role in cancer mutagenesis through U:G mismatch intermediates, the enzyme preference for single-stranded DNA may limit its activity genome-wide. For SBSs at both CG:CG and YC:GR sites, we outline evidence for a prominent role of damage by charge transfer reactions that follow interactions of the DNA with reactive oxygen species (ROS) and other endogenous or exogenous electron-abstracting molecules.

The influence of molecular markers and methods on inferring the phylogenetic relationships between the representatives of the Arini (parrots, Psittaciformes), determined on the basis of their complete mitochondrial genomes.

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Urantowka, Adam Dawid; Kroczak, Aleksandra; Mackiewicz, Paweł

2017-07-14

Conures are a morphologically diverse group of Neotropical parrots classified as members of the tribe Arini, which has recently been subjected to a taxonomic revision. The previously broadly defined Aratinga genus of this tribe has been split into the 'true' Aratinga and three additional genera, Eupsittula, Psittacara and Thectocercus. Popular markers used in the reconstruction of the parrots' phylogenies derive from mitochondrial DNA. However, current phylogenetic analyses seem to indicate conflicting relationships between Aratinga and other conures, and also among other Arini members. Therefore, it is not clear if the mtDNA phylogenies can reliably define the species tree. The inconsistencies may result from the variable evolution rate of the markers used or their weak phylogenetic signal. To resolve these controversies and to assess to what extent the phylogenetic relationships in the tribe Arini can be inferred from mitochondrial genomes, we compared representative Arini mitogenomes as well as examined the usefulness of the individual mitochondrial markers and the efficiency of various phylogenetic methods. Single molecular markers produced inconsistent tree topologies, while different methods offered various topologies even for the same marker. A significant disagreement in these tree topologies occurred for cytb, nd2 and nd6 genes, which are commonly used in parrot phylogenies. The strongest phylogenetic signal was found in the control region and RNA genes. However, these markers cannot be used alone in inferring Arini phylogenies because they do not provide fully resolved trees. The most reliable phylogeny of the parrots under study is obtained only on the concatenated set of all mitochondrial markers. The analyses established significantly resolved relationships within the former Aratinga representatives and the main genera of the tribe Arini. Such mtDNA phylogeny can be in agreement with the species tree, owing to its match with synapomorphic features in

The complete mitochondrial genome of the giant African snail Achatina fulica (Mollusca: Achatinidae).

Science.gov (United States)

Yang, Huirong; Zhang, Jia-En; Guo, Jing; Deng, Zhixin; Luo, Hao; Luo, Mingzhu; Zhao, Benliang

2016-05-01

We present the complete mitochondrial genome of the Achatina fulica in this study. The results show that the mitochondrial genome is 15,057 bp in length, which is comprised of 13 protein-coding genes, 2 rRNA genes, 21 tRNA genes. The nucleotide compositions of the light strand are 35.47% of A, 27.97% of T 19.46% of C, and 17.10% of G. Except the ND3, 7 tRNA, ATP6, ATP8, COX3 and 12S-rRNA on the light strand, the rest are encoded on the heavy strand. Five types of inferred initiation codons are ATA (ND1, ND5), GTG (ND6), ATG (COX3, COX2), ATT (ND4) and TTG (COX1, ND2, ND3, ND4L, ATP6, ATP8, Cytb), and 3 types of inferred termination codons are T (COX3, ND2), TAA (ND1, ND4L, ND5, ND6, ATP6), and TAG (ND3, ND4, COX1, COX2, Cytb, ATP8). There are 24 intergenic spacers and 6 gene overlaps. The tandem repeat sequence (total 52 bp) of (AATAATT)n is observed in 16S-rRNA. Gene arrangement and distribution are inconsistent with the typical vertebrates.

Polytene chromosomal maps of 11 Drosophila species: the order of genomic scaffolds inferred from genetic and physical maps.

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Schaeffer, Stephen W; Bhutkar, Arjun; McAllister, Bryant F; Matsuda, Muneo; Matzkin, Luciano M; O'Grady, Patrick M; Rohde, Claudia; Valente, Vera L S; Aguadé, Montserrat; Anderson, Wyatt W; Edwards, Kevin; Garcia, Ana C L; Goodman, Josh; Hartigan, James; Kataoka, Eiko; Lapoint, Richard T; Lozovsky, Elena R; Machado, Carlos A; Noor, Mohamed A F; Papaceit, Montserrat; Reed, Laura K; Richards, Stephen; Rieger, Tania T; Russo, Susan M; Sato, Hajime; Segarra, Carmen; Smith, Douglas R; Smith, Temple F; Strelets, Victor; Tobari, Yoshiko N; Tomimura, Yoshihiko; Wasserman, Marvin; Watts, Thomas; Wilson, Robert; Yoshida, Kiyohito; Markow, Therese A; Gelbart, William M; Kaufman, Thomas C

2008-07-01

The sequencing of the 12 genomes of members of the genus Drosophila was taken as an opportunity to reevaluate the genetic and physical maps for 11 of the species, in part to aid in the mapping of assembled scaffolds. Here, we present an overview of the importance of cytogenetic maps to Drosophila biology and to the concepts of chromosomal evolution. Physical and genetic markers were used to anchor the genome assembly scaffolds to the polytene chromosomal maps for each species. In addition, a computational approach was used to anchor smaller scaffolds on the basis of the analysis of syntenic blocks. We present the chromosomal map data from each of the 11 sequenced non-Drosophila melanogaster species as a series of sections. Each section reviews the history of the polytene chromosome maps for each species, presents the new polytene chromosome maps, and anchors the genomic scaffolds to the cytological maps using genetic and physical markers. The mapping data agree with Muller's idea that the majority of Drosophila genes are syntenic. Despite the conservation of genes within homologous chromosome arms across species, the karyotypes of these species have changed through the fusion of chromosomal arms followed by subsequent rearrangement events.

Demographic history and biologically relevant genetic variation of Native Mexicans inferred from whole-genome sequencing

OpenAIRE

Romero-Hidalgo, Sandra; Ochoa-Leyva, Adrián; Garcíarrubio, Alejandro; Acuña-Alonzo, Victor; Antúnez-Argüelles, Erika; Balcazar-Quintero, Martha; Barquera-Lozano, Rodrigo; Carnevale, Alessandra; Cornejo-Granados, Fernanda; Fernández-López, Juan Carlos; García-Herrera, Rodrigo; García-Ortíz, Humberto; Granados-Silvestre, Ángeles; Granados, Julio; Guerrero-Romero, Fernando

2017-01-01

Understanding the genetic structure of Native American populations is important to clarify their diversity, demographic history, and to identify genetic factors relevant for biomedical traits. Here, we show a demographic history reconstruction from 12 Native American whole genomes belonging to six distinct ethnic groups representing the three main described genetic clusters of Mexico (Northern, Southern, and Maya). Effective population size estimates of all Native American groups remained bel...

Genomic islands predict functional adaptation in marine actinobacteria

Energy Technology Data Exchange (ETDEWEB)

Penn, Kevin; Jenkins, Caroline; Nett, Markus; Udwary, Daniel; Gontang, Erin; McGlinchey, Ryan; Foster, Brian; Lapidus, Alla; Podell, Sheila; Allen, Eric; Moore, Bradley; Jensen, Paul

2009-04-01

Linking functional traits to bacterial phylogeny remains a fundamental but elusive goal of microbial ecology 1. Without this information, it becomes impossible to resolve meaningful units of diversity and the mechanisms by which bacteria interact with each other and adapt to environmental change. Ecological adaptations among bacterial populations have been linked to genomic islands, strain-specific regions of DNA that house functionally adaptive traits 2. In the case of environmental bacteria, these traits are largely inferred from bioinformatic or gene expression analyses 2, thus leaving few examples in which the functions of island genes have been experimentally characterized. Here we report the complete genome sequences of Salinispora tropica and S. arenicola, the first cultured, obligate marine Actinobacteria 3. These two species inhabit benthic marine environments and dedicate 8-10percent of their genomes to the biosynthesis of secondary metabolites. Despite a close phylogenetic relationship, 25 of 37 secondary metabolic pathways are species-specific and located within 21 genomic islands, thus providing new evidence linking secondary metabolism to ecological adaptation. Species-specific differences are also observed in CRISPR sequences, suggesting that variations in phage immunity provide fitness advantages that contribute to the cosmopolitan distribution of S. arenicola 4. The two Salinispora genomes have evolved by complex processes that include the duplication and acquisition of secondary metabolite genes, the products of which provide immediate opportunities for molecular diversification and ecological adaptation. Evidence that secondary metabolic pathways are exchanged by Horizontal Gene Transfer (HGT) yet are fixed among globally distributed populations 5 supports a functional role for their products and suggests that pathway acquisition represents a previously unrecognized force driving bacterial diversification

Quantum-Like Representation of Non-Bayesian Inference

Science.gov (United States)

Asano, M.; Basieva, I.; Khrennikov, A.; Ohya, M.; Tanaka, Y.

2013-01-01

This research is related to the problem of "irrational decision making or inference" that have been discussed in cognitive psychology. There are some experimental studies, and these statistical data cannot be described by classical probability theory. The process of decision making generating these data cannot be reduced to the classical Bayesian inference. For this problem, a number of quantum-like coginitive models of decision making was proposed. Our previous work represented in a natural way the classical Bayesian inference in the frame work of quantum mechanics. By using this representation, in this paper, we try to discuss the non-Bayesian (irrational) inference that is biased by effects like the quantum interference. Further, we describe "psychological factor" disturbing "rationality" as an "environment" correlating with the "main system" of usual Bayesian inference.

Bayesian Inference Methods for Sparse Channel Estimation

DEFF Research Database (Denmark)

Pedersen, Niels Lovmand

2013-01-01

This thesis deals with sparse Bayesian learning (SBL) with application to radio channel estimation. As opposed to the classical approach for sparse signal representation, we focus on the problem of inferring complex signals. Our investigations within SBL constitute the basis for the development...... of Bayesian inference algorithms for sparse channel estimation. Sparse inference methods aim at finding the sparse representation of a signal given in some overcomplete dictionary of basis vectors. Within this context, one of our main contributions to the field of SBL is a hierarchical representation...... analysis of the complex prior representation, where we show that the ability to induce sparse estimates of a given prior heavily depends on the inference method used and, interestingly, whether real or complex variables are inferred. We also show that the Bayesian estimators derived from the proposed...

Statistical inference an integrated Bayesianlikelihood approach

CERN Document Server

Aitkin, Murray

2010-01-01

Filling a gap in current Bayesian theory, Statistical Inference: An Integrated Bayesian/Likelihood Approach presents a unified Bayesian treatment of parameter inference and model comparisons that can be used with simple diffuse prior specifications. This novel approach provides new solutions to difficult model comparison problems and offers direct Bayesian counterparts of frequentist t-tests and other standard statistical methods for hypothesis testing.After an overview of the competing theories of statistical inference, the book introduces the Bayes/likelihood approach used throughout. It pre

New views on strand asymmetry in insect mitochondrial genomes.

Directory of Open Access Journals (Sweden)

Shu-Jun Wei

Full Text Available Strand asymmetry in nucleotide composition is a remarkable feature of animal mitochondrial genomes. Understanding the mutation processes that shape strand asymmetry is essential for comprehensive knowledge of genome evolution, demographical population history and accurate phylogenetic inference. Previous studies found that the relative contributions of different substitution types to strand asymmetry are associated with replication alone or both replication and transcription. However, the relative contributions of replication and transcription to strand asymmetry remain unclear. Here we conducted a broad survey of strand asymmetry across 120 insect mitochondrial genomes, with special reference to the correlation between the signs of skew values and replication orientation/gene direction. The results show that the sign of GC skew on entire mitochondrial genomes is reversed in all species of three distantly related families of insects, Philopteridae (Phthiraptera, Aleyrodidae (Hemiptera and Braconidae (Hymenoptera; the replication-related elements in the A+T-rich regions of these species are inverted, confirming that reversal of strand asymmetry (GC skew was caused by inversion of replication origin; and finally, the sign of GC skew value is associated with replication orientation but not with gene direction, while that of AT skew value varies with gene direction, replication and codon positions used in analyses. These findings show that deaminations during replication and other mutations contribute more than selection on amino acid sequences to strand compositions of G and C, and that the replication process has a stronger affect on A and T content than does transcription. Our results may contribute to genome-wide studies of replication and transcription mechanisms.

Exploring the possibilities and limitations of a nanomaterials genome.

Science.gov (United States)

Qian, Chenxi; Siler, Todd; Ozin, Geoffrey A

2015-01-07

What are we going to do with the cornucopia of nanomaterials appearing in the open and patent literature, every day? Imagine the benefits of an intelligent and convenient means of categorizing, organizing, sifting, sorting, connecting, and utilizing this information in scientifically and technologically innovative ways by building a Nanomaterials Genome founded upon an all-purpose Periodic Table of Nanomaterials. In this Concept article, inspired by work on the Human Genome project, which began in 1989 together with motivation from the recent emergence of the Materials Genome project initiated in 2011 and the Nanoinformatics Roadmap 2020 instigated in 2010, we envision the development of a Nanomaterials Genome (NMG) database with the most advanced data-mining tools that leverage inference engines to help connect and interpret patterns of nanomaterials information. It will be equipped with state-of-the-art visualization techniques that rapidly organize and picture, categorize and interrelate the inherited behavior of complex nanomatter from the information programmed in its constituent nanomaterials building blocks. A Nanomaterials Genome Initiative (NMGI) of the type imagined herein has the potential to serve the global nanoscience community with an opportunity to speed up the development continuum of nanomaterials through the innovation process steps of discovery, structure determination and property optimization, functionality elucidation, system design and integration, certification and manufacturing to deployment in technologies that apply these versatile nanomaterials in environmentally responsible ways. The possibilities and limitations of this concept are critically evaluated in this article. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Complete mitochondrial genomes of the ‘intermediate form’ of Fasciola and Fasciola gigantica, and their comparison with F. hepatica

Science.gov (United States)

2014-01-01

Background Fascioliasis is an important and neglected disease of humans and other mammals, caused by trematodes of the genus Fasciola. Fasciola hepatica and F. gigantica are valid species that infect humans and animals, but the specific status of Fasciola sp. (‘intermediate form’) is unclear. Methods Single specimens inferred to represent Fasciola sp. (‘intermediate form’; Heilongjiang) and F. gigantica (Guangxi) from China were genetically identified and characterized using PCR-based sequencing of the first and second internal transcribed spacer regions of nuclear ribosomal DNA. The complete mitochondrial (mt) genomes of these representative specimens were then sequenced. The relationships of these specimens with selected members of the Trematoda were assessed by phylogenetic analysis of concatenated amino acid sequence datasets by Bayesian inference (BI). Results The complete mt genomes of representatives of Fasciola sp. and F. gigantica were 14,453 bp and 14,478 bp in size, respectively. Both mt genomes contain 12 protein-coding genes, 22 transfer RNA genes and two ribosomal RNA genes, but lack an atp8 gene. All protein-coding genes are transcribed in the same direction, and the gene order in both mt genomes is the same as that published for F. hepatica. Phylogenetic analysis of the concatenated amino acid sequence data for all 12 protein-coding genes showed that the specimen of Fasciola sp. was more closely related to F. gigantica than to F. hepatica. Conclusions The mt genomes characterized here provide a rich source of markers, which can be used in combination with nuclear markers and imaging techniques, for future comparative studies of the biology of Fasciola sp. from China and other countries. PMID:24685294

Phylogenetic Conflict in Bears Identified by Automated Discovery of Transposable Element Insertions in Low-Coverage Genomes.

Science.gov (United States)

Lammers, Fritjof; Gallus, Susanne; Janke, Axel; Nilsson, Maria A

2017-10-01

Phylogenetic reconstruction from transposable elements (TEs) offers an additional perspective to study evolutionary processes. However, detecting phylogenetically informative TE insertions requires tedious experimental work, limiting the power of phylogenetic inference. Here, we analyzed the genomes of seven bear species using high-throughput sequencing data to detect thousands of TE insertions. The newly developed pipeline for TE detection called TeddyPi (TE detection and discovery for Phylogenetic Inference) identified 150,513 high-quality TE insertions in the genomes of ursine and tremarctine bears. By integrating different TE insertion callers and using a stringent filtering approach, the TeddyPi pipeline produced highly reliable TE insertion calls, which were confirmed by extensive in vitro validation experiments. Analysis of single nucleotide substitutions in the flanking regions of the TEs shows that these substitutions correlate with the phylogenetic signal from the TE insertions. Our phylogenomic analyses show that TEs are a major driver of genomic variation in bears and enabled phylogenetic reconstruction of a well-resolved species tree, despite strong signals for incomplete lineage sorting and introgression. The analyses show that the Asiatic black, sun, and sloth bear form a monophyletic clade, in which phylogenetic incongruence originates from incomplete lineage sorting. TeddyPi is open source and can be adapted to various TE and structural variation callers. The pipeline makes it possible to confidently extract thousands of TE insertions even from low-coverage genomes (∼10×) of nonmodel organisms. This opens new possibilities for biologists to study phylogenies and evolutionary processes as well as rates and patterns of (retro-)transposition and structural variation. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

cDREM: inferring dynamic combinatorial gene regulation.

Science.gov (United States)

Wise, Aaron; Bar-Joseph, Ziv

2015-04-01

Genes are often combinatorially regulated by multiple transcription factors (TFs). Such combinatorial regulation plays an important role in development and facilitates the ability of cells to respond to different stresses. While a number of approaches have utilized sequence and ChIP-based datasets to study combinational regulation, these have often ignored the combinational logic and the dynamics associated with such regulation. Here we present cDREM, a new method for reconstructing dynamic models of combinatorial regulation. cDREM integrates time series gene expression data with (static) protein interaction data. The method is based on a hidden Markov model and utilizes the sparse group Lasso to identify small subsets of combinatorially active TFs, their time of activation, and the logical function they implement. We tested cDREM on yeast and human data sets. Using yeast we show that the predicted combinatorial sets agree with other high throughput genomic datasets and improve upon prior methods developed to infer combinatorial regulation. Applying cDREM to study human response to flu, we were able to identify several combinatorial TF sets, some of which were known to regulate immune response while others represent novel combinations of important TFs.

MobilomeFINDER: web-based tools for in silico and experimental discovery of bacterial genomic islands

Science.gov (United States)

Ou, Hong-Yu; He, Xinyi; Harrison, Ewan M.; Kulasekara, Bridget R.; Thani, Ali Bin; Kadioglu, Aras; Lory, Stephen; Hinton, Jay C. D.; Barer, Michael R.; Rajakumar, Kumar

2007-01-01

MobilomeFINDER (http://mml.sjtu.edu.cn/MobilomeFINDER) is an interactive online tool that facilitates bacterial genomic island or ‘mobile genome’ (mobilome) discovery; it integrates the ArrayOme and tRNAcc software packages. ArrayOme utilizes a microarray-derived comparative genomic hybridization input data set to generate ‘inferred contigs’ produced by merging adjacent genes classified as ‘present’. Collectively these ‘fragments’ represent a hypothetical ‘microarray-visualized genome (MVG)’. ArrayOme permits recognition of discordances between physical genome and MVG sizes, thereby enabling identification of strains rich in microarray-elusive novel genes. Individual tRNAcc tools facilitate automated identification of genomic islands by comparative analysis of the contents and contexts of tRNA sites and other integration hotspots in closely related sequenced genomes. Accessory tools facilitate design of hotspot-flanking primers for in silico and/or wet-science-based interrogation of cognate loci in unsequenced strains and analysis of islands for features suggestive of foreign origins; island-specific and genome-contextual features are tabulated and represented in schematic and graphical forms. To date we have used MobilomeFINDER to analyse several Enterobacteriaceae, Pseudomonas aeruginosa and Streptococcus suis genomes. MobilomeFINDER enables high-throughput island identification and characterization through increased exploitation of emerging sequence data and PCR-based profiling of unsequenced test strains; subsequent targeted yeast recombination-based capture permits full-length sequencing and detailed functional studies of novel genomic islands. PMID:17537813

Phylogenetic signal from rearrangements in 18 Anopheles species by joint scaffolding extant and ancestral genomes.

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Anselmetti, Yoann; Duchemin, Wandrille; Tannier, Eric; Chauve, Cedric; Bérard, Sèverine

2018-05-09

Genomes rearrangements carry valuable information for phylogenetic inference or the elucidation of molecular mechanisms of adaptation. However, the detection of genome rearrangements is often hampered by current deficiencies in data and methods: Genomes obtained from short sequence reads have generally very fragmented assemblies, and comparing multiple gene orders generally leads to computationally intractable algorithmic questions. We present a computational method, ADSEQ, which, by combining ancestral gene order reconstruction, comparative scaffolding and de novo scaffolding methods, overcomes these two caveats. ADSEQ provides simultaneously improved assemblies and ancestral genomes, with statistical supports on all local features. Compared to previous comparative methods, it runs in polynomial time, it samples solutions in a probabilistic space, and it can handle a significantly larger gene complement from the considered extant genomes, with complex histories including gene duplications and losses. We use ADSEQ to provide improved assemblies and a genome history made of duplications, losses, gene translocations, rearrangements, of 18 complete Anopheles genomes, including several important malaria vectors. We also provide additional support for a differentiated mode of evolution of the sex chromosome and of the autosomes in these mosquito genomes. We demonstrate the method's ability to improve extant assemblies accurately through a procedure simulating realistic assembly fragmentation. We study a debated issue regarding the phylogeny of the Gambiae complex group of Anopheles genomes in the light of the evolution of chromosomal rearrangements, suggesting that the phylogenetic signal they carry can differ from the phylogenetic signal carried by gene sequences, more prone to introgression.

Inference Attacks and Control on Database Structures

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Muhamed Turkanovic

2015-02-01

Full Text Available Today’s databases store information with sensitivity levels that range from public to highly sensitive, hence ensuring confidentiality can be highly important, but also requires costly control. This paper focuses on the inference problem on different database structures. It presents possible treats on privacy with relation to the inference, and control methods for mitigating these treats. The paper shows that using only access control, without any inference control is inadequate, since these models are unable to protect against indirect data access. Furthermore, it covers new inference problems which rise from the dimensions of new technologies like XML, semantics, etc.

RFMix: A Discriminative Modeling Approach for Rapid and Robust Local-Ancestry Inference

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Maples, Brian K.; Gravel, Simon; Kenny, Eimear E.; Bustamante, Carlos D.

2013-01-01

Local-ancestry inference is an important step in the genetic analysis of fully sequenced human genomes. Current methods can only detect continental-level ancestry (i.e., European versus African versus Asian) accurately even when using millions of markers. Here, we present RFMix, a powerful discriminative modeling approach that is faster (∼30×) and more accurate than existing methods. We accomplish this by using a conditional random field parameterized by random forests trained on reference panels. RFMix is capable of learning from the admixed samples themselves to boost performance and autocorrect phasing errors. RFMix shows high sensitivity and specificity in simulated Hispanics/Latinos and African Americans and admixed Europeans, Africans, and Asians. Finally, we demonstrate that African Americans in HapMap contain modest (but nonzero) levels of Native American ancestry (∼0.4%). PMID:23910464

Quantitative inference of dynamic regulatory pathways via microarray data

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Chen Bor-Sen

2005-03-01

Full Text Available Abstract Background The cellular signaling pathway (network is one of the main topics of organismic investigations. The intracellular interactions between genes in a signaling pathway are considered as the foundation of functional genomics. Thus, what genes and how much they influence each other through transcriptional binding or physical interactions are essential problems. Under the synchronous measures of gene expression via a microarray chip, an amount of dynamic information is embedded and remains to be discovered. Using a systematically dynamic modeling approach, we explore the causal relationship among genes in cellular signaling pathways from the system biology approach. Results In this study, a second-order dynamic model is developed to describe the regulatory mechanism of a target gene from the upstream causality point of view. From the expression profile and dynamic model of a target gene, we can estimate its upstream regulatory function. According to this upstream regulatory function, we would deduce the upstream regulatory genes with their regulatory abilities and activation delays, and then link up a regulatory pathway. Iteratively, these regulatory genes are considered as target genes to trace back their upstream regulatory genes. Then we could construct the regulatory pathway (or network to the genome wide. In short, we can infer the genetic regulatory pathways from gene-expression profiles quantitatively, which can confirm some doubted paths or seek some unknown paths in a regulatory pathway (network. Finally, the proposed approach is validated by randomly reshuffling the time order of microarray data. Conclusion We focus our algorithm on the inference of regulatory abilities of the identified causal genes, and how much delay before they regulate the downstream genes. With this information, a regulatory pathway would be built up using microarray data. In the present study, two signaling pathways, i.e. circadian regulatory

Real-time definition of non-randomness in the distribution of genomic events.

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Ulrich Abel

Full Text Available Features such as mutations or structural characteristics can be non-randomly or non-uniformly distributed within a genome. So far, computer simulations were required for statistical inferences on the distribution of sequence motifs. Here, we show that these analyses are possible using an analytical, mathematical approach. For the assessment of non-randomness, our calculations only require information including genome size, number of (sampled sequence motifs and distance parameters. We have developed computer programs evaluating our analytical formulas for the real-time determination of expected values and p-values. This approach permits a flexible cluster definition that can be applied to most effectively identify non-random or non-uniform sequence motif distribution. As an example, we show the effectivity and reliability of our mathematical approach in clinical retroviral vector integration site distribution.

Evolution of the NANOG pseudogene family in the human and chimpanzee genomes

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Maughan Peter J

2006-02-01

Full Text Available Abstract Background The NANOG gene is expressed in mammalian embryonic stem cells where it maintains cellular pluripotency. An unusually large family of pseudogenes arose from it with one unprocessed and ten processed pseudogenes in the human genome. This article compares the NANOG gene and its pseudogenes in the human and chimpanzee genomes and derives an evolutionary history of this pseudogene family. Results The NANOG gene and all pseudogenes except NANOGP8 are present at their expected orthologous chromosomal positions in the chimpanzee genome when compared to the human genome, indicating that their origins predate the human-chimpanzee divergence. Analysis of flanking DNA sequences demonstrates that NANOGP8 is absent from the chimpanzee genome. Conclusion Based on the most parsimonious ordering of inferred source-gene mutations, the deduced evolutionary origins for the NANOG pseudogene family in the human and chimpanzee genomes, in order of most ancient to most recent, are NANOGP6, NANOGP5, NANOGP3, NANOGP10, NANOGP2, NANOGP9, NANOGP7, NANOGP1, and NANOGP4. All of these pseudogenes were fixed in the genome of the human-chimpanzee common ancestor. NANOGP8 is the most recent pseudogene and it originated exclusively in the human lineage after the human-chimpanzee divergence. NANOGP1 is apparently an unprocessed pseudogene. Comparison of its sequence to the functional NANOG gene's reading frame suggests that this apparent pseudogene remained functional after duplication and, therefore, was subject to selection-driven conservation of its reading frame, and that it may retain some functionality or that its loss of function may be evolutionarily recent.

Type Inference with Inequalities

DEFF Research Database (Denmark)

Schwartzbach, Michael Ignatieff

1991-01-01

of (monotonic) inequalities on the types of variables and expressions. A general result about systems of inequalities over semilattices yields a solvable form. We distinguish between deciding typability (the existence of solutions) and type inference (the computation of a minimal solution). In our case, both......Type inference can be phrased as constraint-solving over types. We consider an implicitly typed language equipped with recursive types, multiple inheritance, 1st order parametric polymorphism, and assignments. Type correctness is expressed as satisfiability of a possibly infinite collection...

The apicoplast genomes of two taxonomic units of Babesia from sheep.

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Wang, Tao; Guan, Guiquan; Korhonen, Pasi K; Koehler, Anson V; Hall, Ross S; Young, Neil D; Yin, Hong; Gasser, Robin B

2017-01-15

The apicoplast (ap) is a unique, non-photosynthetic organelle found in most apicomplexan parasites. Due to the essential roles that this organelle has, it has been widely considered as target for drugs against diseases caused by apicomplexans. Exploring the ap genomes of such parasites would provide a better understanding of their systematics and their basic molecular biology for therapeutics. However, there is limited information available on the ap genomes of apicomplexan parasites. In the present study, the ap genomes of two operational taxonomic units of Babesia (known as Babesia sp. Lintan [Bl] and Babesia sp. Xinjiang [Bx]) from sheep were sequenced, assembled and annotated using a massive parallel sequencing-based approach. Then, the gene content and gene order in these ap genomes (∼30.7kb in size) were defined and compared, and the genetic differences were assessed. In addition, a phylogenetic analysis of ap genomic data sets was carried out to assess the relationships of these taxonomic units with other apicomplexan parasites for which complete ap genomic data sets were publicly available. The results showed that the ap genomes of Bl and Bx encode 59 and 57 genes, respectively, including 2 ribosomal RNA genes, 25 transfer RNA genes and 30-32 protein-encoding genes, being similar in content to those of Babesia bovis and B. orientalis. Ap gene regions that might serve as markers for future epidemiological and population genetic studies of Babesia species were identified. Using sequence data for a subset of six protein-encoding genes, a close relationship of Bl and Bx with Babesia bovis from cattle and B. orientalis from water buffalo was inferred. Although the focus of the present study was on Babesia, we propose that the present sequencing-bioinformatic approach should be applicable to organellar genomes of a wide range of apicomplexans of veterinary importance. Copyright © 2016 Elsevier B.V. All rights reserved.

The complete mitochondrial genome of Pseudocellus pearsei (Chelicerata: Ricinulei and a comparison of mitochondrial gene rearrangements in Arachnida

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Braband Anke

2007-10-01

Full Text Available Abstract Background Mitochondrial genomes are widely utilized for phylogenetic and population genetic analyses among animals. In addition to sequence data the mitochondrial gene order and RNA secondary structure data are used in phylogenetic analyses. Arachnid phylogeny is still highly debated and there is a lack of sufficient sequence data for many taxa. Ricinulei (hooded tickspiders are a morphologically distinct clade of arachnids with uncertain phylogenetic affinities. Results The first complete mitochondrial DNA genome of a member of the Ricinulei, Pseudocellus pearsei (Arachnida: Ricinulei was sequenced using a PCR-based approach. The mitochondrial genome is a typical circular duplex DNA molecule with a size of 15,099 bp, showing the complete set of genes usually present in bilaterian mitochondrial genomes. Five tRNA genes (trnW, trnY, trnN, trnL(CUN, trnV show different relative positions compared to other Chelicerata (e.g. Limulus polyphemus, Ixodes spp.. We propose that two events led to this derived gene order: (1 a tandem duplication followed by random deletion and (2 an independent translocation of trnN. Most of the inferred tRNA secondary structures show the common cloverleaf pattern except tRNA-Glu where the TψC-arm is missing. In phylogenetic analyses (maximum likelihood, maximum parsimony, Bayesian inference using concatenated amino acid and nucleotide sequences of protein-coding genes the basal relationships of arachnid orders remain unresolved. Conclusion Phylogenetic analyses (ML, MP, BI of arachnid mitochondrial genomes fail to resolve interordinal relationships of Arachnida and remain in a preliminary stage because there is still a lack of mitogenomic data from important taxa such as Opiliones and Pseudoscorpiones. Gene order varies considerably within Arachnida – only eight out of 23 species have retained the putative arthropod ground pattern. Some gene order changes are valuable characters in phylogenetic analysis of

A preliminary mitochondrial genome phylogeny of Orthoptera (Insecta) and approaches to maximizing phylogenetic signal found within mitochondrial genome data.

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Fenn, J Daniel; Song, Hojun; Cameron, Stephen L; Whiting, Michael F

2008-10-01

The phylogenetic utility of mitochondrial genomes (mtgenomes) is examined using the framework of a preliminary phylogeny of Orthoptera. This study presents five newly sequenced genomes from four orthopteran families. While all ensiferan and polyneopteran taxa retain the ancestral gene order, all caeliferan lineages including the newly sequenced caeliferan species contain a tRNA rearrangement from the insect ground plan tRNA(Lys)(K)-tRNA(Asp)(D) swapping to tRNA(Asp) (D)-tRNA(Lys) (K) confirming that this rearrangement is a possible molecular synapomorphy for this suborder. The phylogenetic signal in mtgenomes is rigorously examined under the analytical regimens of parsimony, maximum likelihood and Bayesian inference, along with how gene inclusion/exclusion, data recoding, gap coding, and different partitioning schemes influence the phylogenetic reconstruction. When all available data are analyzed simultaneously, the monophyly of Orthoptera and its two suborders, Caelifera and Ensifera, are consistently recovered in the context of our taxon sampling, regardless of the optimality criteria. When protein-coding genes are analyzed as a single partition, nearly identical topology to the combined analyses is recovered, suggesting that much of the signals of the mtgenome come from the protein-coding genes. Transfer and ribosomal RNAs perform poorly when analyzed individually, but contribute signal when analyzed in combination with the protein-coding genes. Inclusion of third codon position of the protein-coding genes does not negatively affect the phylogenetic reconstruction when all genes are analyzed together, whereas recoding of the protein-coding genes into amino acid sequences introduces artificial resolution. Over-partitioning in a Bayesian framework appears to have a negative effect in achieving convergence. Our findings suggest that the best phylogenetic inferences are made when all available nucleotide data from the mtgenome are analyzed simultaneously, and that

Conservation and losses of non-coding RNAs in avian genomes.

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Paul P Gardner

Full Text Available Here we present the results of a large-scale bioinformatics annotation of non-coding RNA loci in 48 avian genomes. Our approach uses probabilistic models of hand-curated families from the Rfam database to infer conserved RNA families within each avian genome. We supplement these annotations with predictions from the tRNA annotation tool, tRNAscan-SE and microRNAs from miRBase. We identify 34 lncRNA-associated loci that are conserved between birds and mammals and validate 12 of these in chicken. We report several intriguing cases where a reported mammalian lncRNA, but not its function, is conserved. We also demonstrate extensive conservation of classical ncRNAs (e.g., tRNAs and more recently discovered ncRNAs (e.g., snoRNAs and miRNAs in birds. Furthermore, we describe numerous "losses" of several RNA families, and attribute these to either genuine loss, divergence or missing data. In particular, we show that many of these losses are due to the challenges associated with assembling avian microchromosomes. These combined results illustrate the utility of applying homology-based methods for annotating novel vertebrate genomes.

Inference in models with adaptive learning

NARCIS (Netherlands)

Chevillon, G.; Massmann, M.; Mavroeidis, S.

2010-01-01

Identification of structural parameters in models with adaptive learning can be weak, causing standard inference procedures to become unreliable. Learning also induces persistent dynamics, and this makes the distribution of estimators and test statistics non-standard. Valid inference can be

Evolutionary rates at codon sites may be used to align sequences and infer protein domain function

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Hazelhurst Scott

2010-03-01

Full Text Available Abstract Background Sequence alignments form part of many investigations in molecular biology, including the determination of phylogenetic relationships, the prediction of protein structure and function, and the measurement of evolutionary rates. However, to obtain meaningful results, a significant degree of sequence similarity is required to ensure that the alignments are accurate and the inferences correct. Limitations arise when sequence similarity is low, which is particularly problematic when working with fast-evolving genes, evolutionary distant taxa, genomes with nucleotide biases, and cases of convergent evolution. Results A novel approach was conceptualized to address the "low sequence similarity" alignment problem. We developed an alignment algorithm termed FIRE (Functional Inference using the Rates of Evolution, which aligns sequences using the evolutionary rate at codon sites, as measured by the dN/dS ratio, rather than nucleotide or amino acid residues. FIRE was used to test the hypotheses that evolutionary rates can be used to align sequences and that the alignments may be used to infer protein domain function. Using a range of test data, we found that aligning domains based on evolutionary rates was possible even when sequence similarity was very low (for example, antibody variable regions. Furthermore, the alignment has the potential to infer protein domain function, indicating that domains with similar functions are subject to similar evolutionary constraints. These data suggest that an evolutionary rate-based approach to sequence analysis (particularly when combined with structural data may be used to study cases of convergent evolution or when sequences have very low similarity. However, when aligning homologous gene sets with sequence similarity, FIRE did not perform as well as the best traditional alignment algorithms indicating that the conventional approach of aligning residues as opposed to evolutionary rates remains the

Current theoretical models fail to predict the topological complexity of the human genome

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Javier eArsuaga

2015-08-01

Full Text Available Understanding the folding of the human genome is a key challenge of modern structural biology. The emergence of chromatin conformation capture assays ({it e.g.} Hi-C has revolutionized chromosome biology and provided new insights into the three dimensional structure of the genome. The experimental data are highly complex and need to be analyzed with quantitative tools. It has been argued that the data obtained from Hi-C assays are consistent with a fractal organization of the genome. A key characteristic textcolor{red}{of the fractal globule} is the lack of topological complexity (knotting or inter-linking. However, the absence of topological complexity contradicts results from polymer physics showing that the entanglement of long linear polymers in a confined volume increases rapidly with the length and with decreasing volume. textcolor{red}{{it In vivo} and {it in vitro} assays support this claim in some biological systems. We simulate knotted lattice polygons confined inside a sphere and demonstrate that their contact frequencies agree with the human Hi-C data.} We conclude that the topological complexity of the human genome cannot be inferred from current Hi-C data.

Genome-wide prediction of traits with different genetic architecture through efficient variable selection.

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Wimmer, Valentin; Lehermeier, Christina; Albrecht, Theresa; Auinger, Hans-Jürgen; Wang, Yu; Schön, Chris-Carolin

2013-10-01

In genome-based prediction there is considerable uncertainty about the statistical model and method required to maximize prediction accuracy. For traits influenced by a small number of quantitative trait loci (QTL), predictions are expected to benefit from methods performing variable selection [e.g., BayesB or the least absolute shrinkage and selection operator (LASSO)] compared to methods distributing effects across the genome [ridge regression best linear unbiased prediction (RR-BLUP)]. We investigate the assumptions underlying successful variable selection by combining computer simulations with large-scale experimental data sets from rice (Oryza sativa L.), wheat (Triticum aestivum L.), and Arabidopsis thaliana (L.). We demonstrate that variable selection can be successful when the number of phenotyped individuals is much larger than the number of causal mutations contributing to the trait. We show that the sample size required for efficient variable selection increases dramatically with decreasing trait heritabilities and increasing extent of linkage disequilibrium (LD). We contrast and discuss contradictory results from simulation and experimental studies with respect to superiority of variable selection methods over RR-BLUP. Our results demonstrate that due to long-range LD, medium heritabilities, and small sample sizes, superiority of variable selection methods cannot be expected in plant breeding populations even for traits like FRIGIDA gene expression in Arabidopsis and flowering time in rice, assumed to be influenced by a few major QTL. We extend our conclusions to the analysis of whole-genome sequence data and infer upper bounds for the number of causal mutations which can be identified by LASSO. Our results have major impact on the choice of statistical method needed to make credible inferences about genetic architecture and prediction accuracy of complex traits.

Fiducial inference - A Neyman-Pearson interpretation

NARCIS (Netherlands)

Salome, D; VonderLinden, W; Dose,; Fischer, R; Preuss, R

1999-01-01

Fisher's fiducial argument is a tool for deriving inferences in the form of a probability distribution on the parameter space, not based on Bayes's Theorem. Lindley established that in exceptional situations fiducial inferences coincide with posterior distributions; in the other situations fiducial

Uncertainty in prediction and in inference

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Hilgevoord, J.; Uffink, J.

1991-01-01

The concepts of uncertainty in prediction and inference are introduced and illustrated using the diffraction of light as an example. The close re-lationship between the concepts of uncertainty in inference and resolving power is noted. A general quantitative measure of uncertainty in

Leveraging Comparative Genomics to Identify and Functionally Characterize Genes Associated with Sperm Phenotypes in Python bivittatus (Burmese Python

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Kristopher J. L. Irizarry

2016-01-01

Full Text Available Comparative genomics approaches provide a means of leveraging functional genomics information from a highly annotated model organism’s genome (such as the mouse genome in order to make physiological inferences about the role of genes and proteins in a less characterized organism’s genome (such as the Burmese python. We employed a comparative genomics approach to produce the functional annotation of Python bivittatus genes encoding proteins associated with sperm phenotypes. We identify 129 gene-phenotype relationships in the python which are implicated in 10 specific sperm phenotypes. Results obtained through our systematic analysis identified subsets of python genes exhibiting associations with gene ontology annotation terms. Functional annotation data was represented in a semantic scatter plot. Together, these newly annotated Python bivittatus genome resources provide a high resolution framework from which the biology relating to reptile spermatogenesis, fertility, and reproduction can be further investigated. Applications of our research include (1 production of genetic diagnostics for assessing fertility in domestic and wild reptiles; (2 enhanced assisted reproduction technology for endangered and captive reptiles; and (3 novel molecular targets for biotechnology-based approaches aimed at reducing fertility and reproduction of invasive reptiles. Additional enhancements to reptile genomic resources will further enhance their value.