Developing eThread Pipeline Using SAGA-Pilot Abstraction for Large-Scale Structural Bioinformatics

PubMed Central

Ragothaman, Anjani; Feinstein, Wei; Jha, Shantenu; Kim, Joohyun

2014-01-01

While most of computational annotation approaches are sequence-based, threading methods are becoming increasingly attractive because of predicted structural information that could uncover the underlying function. However, threading tools are generally compute-intensive and the number of protein sequences from even small genomes such as prokaryotes is large typically containing many thousands, prohibiting their application as a genome-wide structural systems biology tool. To leverage its utility, we have developed a pipeline for eThread—a meta-threading protein structure modeling tool, that can use computational resources efficiently and effectively. We employ a pilot-based approach that supports seamless data and task-level parallelism and manages large variation in workload and computational requirements. Our scalable pipeline is deployed on Amazon EC2 and can efficiently select resources based upon task requirements. We present runtime analysis to characterize computational complexity of eThread and EC2 infrastructure. Based on results, we suggest a pathway to an optimized solution with respect to metrics such as time-to-solution or cost-to-solution. Our eThread pipeline can scale to support a large number of sequences and is expected to be a viable solution for genome-scale structural bioinformatics and structure-based annotation, particularly, amenable for small genomes such as prokaryotes. The developed pipeline is easily extensible to other types of distributed cyberinfrastructure. PMID:24995285

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

PubMed Central

King, Zachary A.; Lu, Justin; Dräger, Andreas; Miller, Philip; Federowicz, Stephen; Lerman, Joshua A.; Ebrahim, Ali; Palsson, Bernhard O.; Lewis, Nathan E.

2016-01-01

Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data. PMID:26476456

Genomic insights into the Acidobacteria reveal strategies for their success in terrestrial environments

PubMed Central

Trojan, Daniela; Roux, Simon; Herbold, Craig; Rattei, Thomas; Woebken, Dagmar

2018-01-01

Summary Members of the phylum Acidobacteria are abundant and ubiquitous across soils. We performed a large‐scale comparative genome analysis spanning subdivisions 1, 3, 4, 6, 8 and 23 (n = 24) with the goal to identify features to help explain their prevalence in soils and understand their ecophysiology. Our analysis revealed that bacteriophage integration events along with transposable and mobile elements influenced the structure and plasticity of these genomes. Low‐ and high‐affinity respiratory oxygen reductases were detected in multiple genomes, suggesting the capacity for growing across different oxygen gradients. Among many genomes, the capacity to use a diverse collection of carbohydrates, as well as inorganic and organic nitrogen sources (such as via extracellular peptidases), was detected – both advantageous traits in environments with fluctuating nutrient environments. We also identified multiple soil acidobacteria with the potential to scavenge atmospheric concentrations of H2, now encompassing mesophilic soil strains within the subdivision 1 and 3, in addition to a previously identified thermophilic strain in subdivision 4. This large‐scale acidobacteria genome analysis reveal traits that provide genomic, physiological and metabolic versatility, presumably allowing flexibility and versatility in the challenging and fluctuating soil environment. PMID:29327410

Hi-C-constrained physical models of human chromosomes recover functionally-related properties of genome organization

NASA Astrophysics Data System (ADS)

di Stefano, Marco; Paulsen, Jonas; Lien, Tonje G.; Hovig, Eivind; Micheletti, Cristian

2016-10-01

Combining genome-wide structural models with phenomenological data is at the forefront of efforts to understand the organizational principles regulating the human genome. Here, we use chromosome-chromosome contact data as knowledge-based constraints for large-scale three-dimensional models of the human diploid genome. The resulting models remain minimally entangled and acquire several functional features that are observed in vivo and that were never used as input for the model. We find, for instance, that gene-rich, active regions are drawn towards the nuclear center, while gene poor and lamina associated domains are pushed to the periphery. These and other properties persist upon adding local contact constraints, suggesting their compatibility with non-local constraints for the genome organization. The results show that suitable combinations of data analysis and physical modelling can expose the unexpectedly rich functionally-related properties implicit in chromosome-chromosome contact data. Specific directions are suggested for further developments based on combining experimental data analysis and genomic structural modelling.

Hi-C-constrained physical models of human chromosomes recover functionally-related properties of genome organization.

PubMed

Di Stefano, Marco; Paulsen, Jonas; Lien, Tonje G; Hovig, Eivind; Micheletti, Cristian

2016-10-27

Combining genome-wide structural models with phenomenological data is at the forefront of efforts to understand the organizational principles regulating the human genome. Here, we use chromosome-chromosome contact data as knowledge-based constraints for large-scale three-dimensional models of the human diploid genome. The resulting models remain minimally entangled and acquire several functional features that are observed in vivo and that were never used as input for the model. We find, for instance, that gene-rich, active regions are drawn towards the nuclear center, while gene poor and lamina associated domains are pushed to the periphery. These and other properties persist upon adding local contact constraints, suggesting their compatibility with non-local constraints for the genome organization. The results show that suitable combinations of data analysis and physical modelling can expose the unexpectedly rich functionally-related properties implicit in chromosome-chromosome contact data. Specific directions are suggested for further developments based on combining experimental data analysis and genomic structural modelling.

Elucidating the triplicated ancestral genome structure of radish based on chromosome-level comparison with the Brassica genomes.

PubMed

Jeong, Young-Min; Kim, Namshin; Ahn, Byung Ohg; Oh, Mijin; Chung, Won-Hyong; Chung, Hee; Jeong, Seongmun; Lim, Ki-Byung; Hwang, Yoon-Jung; Kim, Goon-Bo; Baek, Seunghoon; Choi, Sang-Bong; Hyung, Dae-Jin; Lee, Seung-Won; Sohn, Seong-Han; Kwon, Soo-Jin; Jin, Mina; Seol, Young-Joo; Chae, Won Byoung; Choi, Keun Jin; Park, Beom-Seok; Yu, Hee-Ju; Mun, Jeong-Hwan

2016-07-01

This study presents a chromosome-scale draft genome sequence of radish that is assembled into nine chromosomal pseudomolecules. A comprehensive comparative genome analysis with the Brassica genomes provides genomic evidences on the evolution of the mesohexaploid radish genome. Radish (Raphanus sativus L.) is an agronomically important root vegetable crop and its origin and phylogenetic position in the tribe Brassiceae is controversial. Here we present a comprehensive analysis of the radish genome based on the chromosome sequences of R. sativus cv. WK10039. The radish genome was sequenced and assembled into 426.2 Mb spanning >98 % of the gene space, of which 344.0 Mb were integrated into nine chromosome pseudomolecules. Approximately 36 % of the genome was repetitive sequences and 46,514 protein-coding genes were predicted and annotated. Comparative mapping of the tPCK-like ancestral genome revealed that the radish genome has intermediate characteristics between the Brassica A/C and B genomes in the triplicated segments, suggesting an internal origin from the genus Brassica. The evolutionary characteristics shared between radish and other Brassica species provided genomic evidences that the current form of nine chromosomes in radish was rearranged from the chromosomes of hexaploid progenitor. Overall, this study provides a chromosome-scale draft genome sequence of radish as well as novel insight into evolution of the mesohexaploid genomes in the tribe Brassiceae.

The OME Framework for genome-scale systems biology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Palsson, Bernhard O.; Ebrahim, Ali; Federowicz, Steve

The life sciences are undergoing continuous and accelerating integration with computational and engineering sciences. The biology that many in the field have been trained on may be hardly recognizable in ten to twenty years. One of the major drivers for this transformation is the blistering pace of advancements in DNA sequencing and synthesis. These advances have resulted in unprecedented amounts of new data, information, and knowledge. Many software tools have been developed to deal with aspects of this transformation and each is sorely needed [1-3]. However, few of these tools have been forced to deal with the full complexity ofmore » genome-scale models along with high throughput genome- scale data. This particular situation represents a unique challenge, as it is simultaneously necessary to deal with the vast breadth of genome-scale models and the dizzying depth of high-throughput datasets. It has been observed time and again that as the pace of data generation continues to accelerate, the pace of analysis significantly lags behind [4]. It is also evident that, given the plethora of databases and software efforts [5-12], it is still a significant challenge to work with genome-scale metabolic models, let alone next-generation whole cell models [13-15]. We work at the forefront of model creation and systems scale data generation [16-18]. The OME Framework was borne out of a practical need to enable genome-scale modeling and data analysis under a unified framework to drive the next generation of genome-scale biological models. Here we present the OME Framework. It exists as a set of Python classes. However, we want to emphasize the importance of the underlying design as an addition to the discussions on specifications of a digital cell. A great deal of work and valuable progress has been made by a number of communities [13, 19-24] towards interchange formats and implementations designed to achieve similar goals. While many software tools exist for handling genome-scale metabolic models or for genome-scale data analysis, no implementations exist that explicitly handle data and models concurrently. The OME Framework structures data in a connected loop with models and the components those models are composed of. This results in the first full, practical implementation of a framework that can enable genome-scale design-build-test. Over the coming years many more software packages will be developed and tools will necessarily change. However, we hope that the underlying designs shared here can help to inform the design of future software.« less

The Genomic HyperBrowser: an analysis web server for genome-scale data

PubMed Central

Sandve, Geir K.; Gundersen, Sveinung; Johansen, Morten; Glad, Ingrid K.; Gunathasan, Krishanthi; Holden, Lars; Holden, Marit; Liestøl, Knut; Nygård, Ståle; Nygaard, Vegard; Paulsen, Jonas; Rydbeck, Halfdan; Trengereid, Kai; Clancy, Trevor; Drabløs, Finn; Ferkingstad, Egil; Kalaš, Matúš; Lien, Tonje; Rye, Morten B.; Frigessi, Arnoldo; Hovig, Eivind

2013-01-01

The immense increase in availability of genomic scale datasets, such as those provided by the ENCODE and Roadmap Epigenomics projects, presents unprecedented opportunities for individual researchers to pose novel falsifiable biological questions. With this opportunity, however, researchers are faced with the challenge of how to best analyze and interpret their genome-scale datasets. A powerful way of representing genome-scale data is as feature-specific coordinates relative to reference genome assemblies, i.e. as genomic tracks. The Genomic HyperBrowser (http://hyperbrowser.uio.no) is an open-ended web server for the analysis of genomic track data. Through the provision of several highly customizable components for processing and statistical analysis of genomic tracks, the HyperBrowser opens for a range of genomic investigations, related to, e.g., gene regulation, disease association or epigenetic modifications of the genome. PMID:23632163

The Genomic HyperBrowser: an analysis web server for genome-scale data.

PubMed

Sandve, Geir K; Gundersen, Sveinung; Johansen, Morten; Glad, Ingrid K; Gunathasan, Krishanthi; Holden, Lars; Holden, Marit; Liestøl, Knut; Nygård, Ståle; Nygaard, Vegard; Paulsen, Jonas; Rydbeck, Halfdan; Trengereid, Kai; Clancy, Trevor; Drabløs, Finn; Ferkingstad, Egil; Kalas, Matús; Lien, Tonje; Rye, Morten B; Frigessi, Arnoldo; Hovig, Eivind

2013-07-01

The immense increase in availability of genomic scale datasets, such as those provided by the ENCODE and Roadmap Epigenomics projects, presents unprecedented opportunities for individual researchers to pose novel falsifiable biological questions. With this opportunity, however, researchers are faced with the challenge of how to best analyze and interpret their genome-scale datasets. A powerful way of representing genome-scale data is as feature-specific coordinates relative to reference genome assemblies, i.e. as genomic tracks. The Genomic HyperBrowser (http://hyperbrowser.uio.no) is an open-ended web server for the analysis of genomic track data. Through the provision of several highly customizable components for processing and statistical analysis of genomic tracks, the HyperBrowser opens for a range of genomic investigations, related to, e.g., gene regulation, disease association or epigenetic modifications of the genome.

Discovery, genotyping and characterization of structural variation and novel sequence at single nucleotide resolution from de novo genome assemblies on a population scale.

PubMed

Liu, Siyang; Huang, Shujia; Rao, Junhua; Ye, Weijian; Krogh, Anders; Wang, Jun

2015-01-01

Comprehensive recognition of genomic variation in one individual is important for understanding disease and developing personalized medication and treatment. Many tools based on DNA re-sequencing exist for identification of single nucleotide polymorphisms, small insertions and deletions (indels) as well as large deletions. However, these approaches consistently display a substantial bias against the recovery of complex structural variants and novel sequence in individual genomes and do not provide interpretation information such as the annotation of ancestral state and formation mechanism. We present a novel approach implemented in a single software package, AsmVar, to discover, genotype and characterize different forms of structural variation and novel sequence from population-scale de novo genome assemblies up to nucleotide resolution. Application of AsmVar to several human de novo genome assemblies captures a wide spectrum of structural variants and novel sequences present in the human population in high sensitivity and specificity. Our method provides a direct solution for investigating structural variants and novel sequences from de novo genome assemblies, facilitating the construction of population-scale pan-genomes. Our study also highlights the usefulness of the de novo assembly strategy for definition of genome structure.

Genomic Diversity and Evolution of the Lyssaviruses

PubMed Central

Delmas, Olivier; Holmes, Edward C.; Talbi, Chiraz; Larrous, Florence; Dacheux, Laurent; Bouchier, Christiane; Bourhy, Hervé

2008-01-01

Lyssaviruses are RNA viruses with single-strand, negative-sense genomes responsible for rabies-like diseases in mammals. To date, genomic and evolutionary studies have most often utilized partial genome sequences, particularly of the nucleoprotein and glycoprotein genes, with little consideration of genome-scale evolution. Herein, we report the first genomic and evolutionary analysis using complete genome sequences of all recognised lyssavirus genotypes, including 14 new complete genomes of field isolates from 6 genotypes and one genotype that is completely sequenced for the first time. In doing so we significantly increase the extent of genome sequence data available for these important viruses. Our analysis of these genome sequence data reveals that all lyssaviruses have the same genomic organization. A phylogenetic analysis reveals strong geographical structuring, with the greatest genetic diversity in Africa, and an independent origin for the two known genotypes that infect European bats. We also suggest that multiple genotypes may exist within the diversity of viruses currently classified as ‘Lagos Bat’. In sum, we show that rigorous phylogenetic techniques based on full length genome sequence provide the best discriminatory power for genotype classification within the lyssaviruses. PMID:18446239

Single-molecule optical genome mapping of a human HapMap and a colorectal cancer cell line.

PubMed

Teo, Audrey S M; Verzotto, Davide; Yao, Fei; Nagarajan, Niranjan; Hillmer, Axel M

2015-01-01

Next-generation sequencing (NGS) technologies have changed our understanding of the variability of the human genome. However, the identification of genome structural variations based on NGS approaches with read lengths of 35-300 bases remains a challenge. Single-molecule optical mapping technologies allow the analysis of DNA molecules of up to 2 Mb and as such are suitable for the identification of large-scale genome structural variations, and for de novo genome assemblies when combined with short-read NGS data. Here we present optical mapping data for two human genomes: the HapMap cell line GM12878 and the colorectal cancer cell line HCT116. High molecular weight DNA was obtained by embedding GM12878 and HCT116 cells, respectively, in agarose plugs, followed by DNA extraction under mild conditions. Genomic DNA was digested with KpnI and 310,000 and 296,000 DNA molecules (≥ 150 kb and 10 restriction fragments), respectively, were analyzed per cell line using the Argus optical mapping system. Maps were aligned to the human reference by OPTIMA, a new glocal alignment method. Genome coverage of 6.8× and 5.7× was obtained, respectively; 2.9× and 1.7× more than the coverage obtained with previously available software. Optical mapping allows the resolution of large-scale structural variations of the genome, and the scaffold extension of NGS-based de novo assemblies. OPTIMA is an efficient new alignment method; our optical mapping data provide a resource for genome structure analyses of the human HapMap reference cell line GM12878, and the colorectal cancer cell line HCT116.

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

DOE PAGES

King, Zachary A.; Lu, Justin; Drager, Andreas; ...

2015-10-17

In this study, genome-scale metabolic models are mathematically structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scalemore » metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.« less

Re-annotation, improved large-scale assembly and establishment of a catalogue of noncoding loci for the genome of the model brown alga Ectocarpus.

PubMed

Cormier, Alexandre; Avia, Komlan; Sterck, Lieven; Derrien, Thomas; Wucher, Valentin; Andres, Gwendoline; Monsoor, Misharl; Godfroy, Olivier; Lipinska, Agnieszka; Perrineau, Marie-Mathilde; Van De Peer, Yves; Hitte, Christophe; Corre, Erwan; Coelho, Susana M; Cock, J Mark

2017-04-01

The genome of the filamentous brown alga Ectocarpus was the first to be completely sequenced from within the brown algal group and has served as a key reference genome both for this lineage and for the stramenopiles. We present a complete structural and functional reannotation of the Ectocarpus genome. The large-scale assembly of the Ectocarpus genome was significantly improved and genome-wide gene re-annotation using extensive RNA-seq data improved the structure of 11 108 existing protein-coding genes and added 2030 new loci. A genome-wide analysis of splicing isoforms identified an average of 1.6 transcripts per locus. A large number of previously undescribed noncoding genes were identified and annotated, including 717 loci that produce long noncoding RNAs. Conservation of lncRNAs between Ectocarpus and another brown alga, the kelp Saccharina japonica, suggests that at least a proportion of these loci serve a function. Finally, a large collection of single nucleotide polymorphism-based markers was developed for genetic analyses. These resources are available through an updated and improved genome database. This study significantly improves the utility of the Ectocarpus genome as a high-quality reference for the study of many important aspects of brown algal biology and as a reference for genomic analyses across the stramenopiles. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Bioinformatics and genomic analysis of transposable elements in eukaryotic genomes.

PubMed

Janicki, Mateusz; Rooke, Rebecca; Yang, Guojun

2011-08-01

A major portion of most eukaryotic genomes are transposable elements (TEs). During evolution, TEs have introduced profound changes to genome size, structure, and function. As integral parts of genomes, the dynamic presence of TEs will continue to be a major force in reshaping genomes. Early computational analyses of TEs in genome sequences focused on filtering out "junk" sequences to facilitate gene annotation. When the high abundance and diversity of TEs in eukaryotic genomes were recognized, these early efforts transformed into the systematic genome-wide categorization and classification of TEs. The availability of genomic sequence data reversed the classical genetic approaches to discovering new TE families and superfamilies. Curated TE databases and their accurate annotation of genome sequences in turn facilitated the studies on TEs in a number of frontiers including: (1) TE-mediated changes of genome size and structure, (2) the influence of TEs on genome and gene functions, (3) TE regulation by host, (4) the evolution of TEs and their population dynamics, and (5) genomic scale studies of TE activity. Bioinformatics and genomic approaches have become an integral part of large-scale studies on TEs to extract information with pure in silico analyses or to assist wet lab experimental studies. The current revolution in genome sequencing technology facilitates further progress in the existing frontiers of research and emergence of new initiatives. The rapid generation of large-sequence datasets at record low costs on a routine basis is challenging the computing industry on storage capacity and manipulation speed and the bioinformatics community for improvement in algorithms and their implementations.

Genome-Wide Analysis of Transposon and Retroviral Insertions Reveals Preferential Integrations in Regions of DNA Flexibility.

PubMed

Vrljicak, Pavle; Tao, Shijie; Varshney, Gaurav K; Quach, Helen Ngoc Bao; Joshi, Adita; LaFave, Matthew C; Burgess, Shawn M; Sampath, Karuna

2016-04-07

DNA transposons and retroviruses are important transgenic tools for genome engineering. An important consideration affecting the choice of transgenic vector is their insertion site preferences. Previous large-scale analyses of Ds transposon integration sites in plants were done on the basis of reporter gene expression or germ-line transmission, making it difficult to discern vertebrate integration preferences. Here, we compare over 1300 Ds transposon integration sites in zebrafish with Tol2 transposon and retroviral integration sites. Genome-wide analysis shows that Ds integration sites in the presence or absence of marker selection are remarkably similar and distributed throughout the genome. No strict motif was found, but a preference for structural features in the target DNA associated with DNA flexibility (Twist, Tilt, Rise, Roll, Shift, and Slide) was observed. Remarkably, this feature is also found in transposon and retroviral integrations in maize and mouse cells. Our findings show that structural features influence the integration of heterologous DNA in genomes, and have implications for targeted genome engineering. Copyright © 2016 Vrljicak et al.

Population genomics reveals structure at the individual, host-tree scale and persistence of genotypic variants of the undomesticated yeast Saccharomyces paradoxus in a natural woodland.

PubMed

Xia, Wenjing; Nielly-Thibault, Lou; Charron, Guillaume; Landry, Christian R; Kasimer, Dahlia; Anderson, James B; Kohn, Linda M

2017-02-01

Genetic diversity in experimental, domesticated and wild populations of the related yeasts, Saccharomyces cerevisiae and Saccharomyces paradoxus, has been well described at the global scale. We investigated the population genomics of a local population on a small spatial scale to address two main questions. First, is there genomic variation in a S. paradoxus population at a spatial scale spanning centimetres (microsites) to tens of metres? Second, does the distribution of genomic variants persist over time? Our sample consisted of 42 S. paradoxus strains from 2014 and 43 strains from 2015 collected from the same 72 microsites around four host trees (Quercus rubra and Quercus alba) within 1 km 2 in a mixed hardwood forest in southern Ontario. Six additional S. paradoxus strains recovered from adjacent maple and beech trees in 2015 are also included in the sample. Whole-genome sequencing and genomic SNP analysis revealed five differentiated groups (clades) within the sampled area. The signal of persistence of genotypes in their microsites from 2014 to 2015 was highly significant. Isolates from the same tree tended to be more related than strains from different trees, with limited evidence of dispersal between trees. In growth assays, one genotype had a significantly longer lag phase than the other strains. Our results indicate that different clades coexist at fine spatial scale and that population structure persists over at least a one-year interval in these wild yeasts, suggesting the efficacy of yearly sampling to follow longer term genetic dynamics in future studies. © 2016 John Wiley & Sons Ltd.

Structure and variation of the mitochondrial genome of fishes.

PubMed

Satoh, Takashi P; Miya, Masaki; Mabuchi, Kohji; Nishida, Mutsumi

2016-09-07

The mitochondrial (mt) genome has been used as an effective tool for phylogenetic and population genetic analyses in vertebrates. However, the structure and variability of the vertebrate mt genome are not well understood. A potential strategy for improving our understanding is to conduct a comprehensive comparative study of large mt genome data. The aim of this study was to characterize the structure and variability of the fish mt genome through comparative analysis of large datasets. An analysis of the secondary structure of proteins for 250 fish species (248 ray-finned and 2 cartilaginous fishes) illustrated that cytochrome c oxidase subunits (COI, COII, and COIII) and a cytochrome bc1 complex subunit (Cyt b) had substantial amino acid conservation. Among the four proteins, COI was the most conserved, as more than half of all amino acid sites were invariable among the 250 species. Our models identified 43 and 58 stems within 12S rRNA and 16S rRNA, respectively, with larger numbers than proposed previously for vertebrates. The models also identified 149 and 319 invariable sites in 12S rRNA and 16S rRNA, respectively, in all fishes. In particular, the present result verified that a region corresponding to the peptidyl transferase center in prokaryotic 23S rRNA, which is homologous to mt 16S rRNA, is also conserved in fish mt 16S rRNA. Concerning the gene order, we found 35 variations (in 32 families) that deviated from the common gene order in vertebrates. These gene rearrangements were mostly observed in the area spanning the ND5 gene to the control region as well as two tRNA gene cluster regions (IQM and WANCY regions). Although many of such gene rearrangements were unique to a specific taxon, some were shared polyphyletically between distantly related species. Through a large-scale comparative analysis of 250 fish species mt genomes, we elucidated various structural aspects of the fish mt genome and the encoded genes. The present results will be important for understanding functions of the mt genome and developing programs for nucleotide sequence analysis. This study demonstrated the significance of extensive comparisons for understanding the structure of the mt genome.

Secure web book to store structural genomics research data.

PubMed

Manjasetty, Babu A; Höppner, Klaus; Mueller, Uwe; Heinemann, Udo

2003-01-01

Recently established collaborative structural genomics programs aim at significantly accelerating the crystal structure analysis of proteins. These large-scale projects require efficient data management systems to ensure seamless collaboration between different groups of scientists working towards the same goal. Within the Berlin-based Protein Structure Factory, the synchrotron X-ray data collection and the subsequent crystal structure analysis tasks are located at BESSY, a third-generation synchrotron source. To organize file-based communication and data transfer at the BESSY site of the Protein Structure Factory, we have developed the web-based BCLIMS, the BESSY Crystallography Laboratory Information Management System. BCLIMS is a relational data management system which is powered by MySQL as the database engine and Apache HTTP as the web server. The database interface routines are written in Python programing language. The software is freely available to academic users. Here we describe the storage, retrieval and manipulation of laboratory information, mainly pertaining to the synchrotron X-ray diffraction experiments and the subsequent protein structure analysis, using BCLIMS.

Reconstructing Past Admixture Processes from Local Genomic Ancestry Using Wavelet Transformation

PubMed Central

Sanderson, Jean; Sudoyo, Herawati; Karafet, Tatiana M.; Hammer, Michael F.; Cox, Murray P.

2015-01-01

Admixture between long-separated populations is a defining feature of the genomes of many species. The mosaic block structure of admixed genomes can provide information about past contact events, including the time and extent of admixture. Here, we describe an improved wavelet-based technique that better characterizes ancestry block structure from observed genomic patterns. principal components analysis is first applied to genomic data to identify the primary population structure, followed by wavelet decomposition to develop a new characterization of local ancestry information along the chromosomes. For testing purposes, this method is applied to human genome-wide genotype data from Indonesia, as well as virtual genetic data generated using genome-scale sequential coalescent simulations under a wide range of admixture scenarios. Time of admixture is inferred using an approximate Bayesian computation framework, providing robust estimates of both admixture times and their associated levels of uncertainty. Crucially, we demonstrate that this revised wavelet approach, which we have released as the R package adwave, provides improved statistical power over existing wavelet-based techniques and can be used to address a broad range of admixture questions. PMID:25852078

Large-scale chromosome folding versus genomic DNA sequences: A discrete double Fourier transform technique.

PubMed

Chechetkin, V R; Lobzin, V V

2017-08-07

Using state-of-the-art techniques combining imaging methods and high-throughput genomic mapping tools leaded to the significant progress in detailing chromosome architecture of various organisms. However, a gap still remains between the rapidly growing structural data on the chromosome folding and the large-scale genome organization. Could a part of information on the chromosome folding be obtained directly from underlying genomic DNA sequences abundantly stored in the databanks? To answer this question, we developed an original discrete double Fourier transform (DDFT). DDFT serves for the detection of large-scale genome regularities associated with domains/units at the different levels of hierarchical chromosome folding. The method is versatile and can be applied to both genomic DNA sequences and corresponding physico-chemical parameters such as base-pairing free energy. The latter characteristic is closely related to the replication and transcription and can also be used for the assessment of temperature or supercoiling effects on the chromosome folding. We tested the method on the genome of E. coli K-12 and found good correspondence with the annotated domains/units established experimentally. As a brief illustration of further abilities of DDFT, the study of large-scale genome organization for bacteriophage PHIX174 and bacterium Caulobacter crescentus was also added. The combined experimental, modeling, and bioinformatic DDFT analysis should yield more complete knowledge on the chromosome architecture and genome organization. Copyright © 2017 Elsevier Ltd. All rights reserved.

IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites.

PubMed

Hadjithomas, Michalis; Chen, I-Min Amy; Chu, Ken; Ratner, Anna; Palaniappan, Krishna; Szeto, Ernest; Huang, Jinghua; Reddy, T B K; Cimermančič, Peter; Fischbach, Michael A; Ivanova, Natalia N; Markowitz, Victor M; Kyrpides, Nikos C; Pati, Amrita

2015-07-14

In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of "big" genomic data for discovering small molecules. IMG-ABC relies on IMG's comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC's focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in Alphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG's extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world. Copyright © 2015 Hadjithomas et al.

Transposon Insertions, Structural Variations, and SNPs Contribute to the Evolution of the Melon Genome.

PubMed

Sanseverino, Walter; Hénaff, Elizabeth; Vives, Cristina; Pinosio, Sara; Burgos-Paz, William; Morgante, Michele; Ramos-Onsins, Sebastián E; Garcia-Mas, Jordi; Casacuberta, Josep Maria

2015-10-01

The availability of extensive databases of crop genome sequences should allow analysis of crop variability at an unprecedented scale, which should have an important impact in plant breeding. However, up to now the analysis of genetic variability at the whole-genome scale has been mainly restricted to single nucleotide polymorphisms (SNPs). This is a strong limitation as structural variation (SV) and transposon insertion polymorphisms are frequent in plant species and have had an important mutational role in crop domestication and breeding. Here, we present the first comprehensive analysis of melon genetic diversity, which includes a detailed analysis of SNPs, SV, and transposon insertion polymorphisms. The variability found among seven melon varieties representing the species diversity and including wild accessions and highly breed lines, is relatively high due in part to the marked divergence of some lineages. The diversity is distributed nonuniformly across the genome, being lower at the extremes of the chromosomes and higher in the pericentromeric regions, which is compatible with the effect of purifying selection and recombination forces over functional regions. Additionally, this variability is greatly reduced among elite varieties, probably due to selection during breeding. We have found some chromosomal regions showing a high differentiation of the elite varieties versus the rest, which could be considered as strongly selected candidate regions. Our data also suggest that transposons and SV may be at the origin of an important fraction of the variability in melon, which highlights the importance of analyzing all types of genetic variability to understand crop genome evolution. © The Author 2015. 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.

A protocol for generating a high-quality genome-scale metabolic reconstruction.

PubMed

Thiele, Ines; Palsson, Bernhard Ø

2010-01-01

Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have been developed over the last 10 years. These reconstructions represent structured knowledge bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates a myriad of computational biological studies, including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge bases. Here we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction, as well as the common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process.

A protocol for generating a high-quality genome-scale metabolic reconstruction

PubMed Central

Thiele, Ines; Palsson, Bernhard Ø.

2011-01-01

Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have developed over the past 10 years. These reconstructions represent structured knowledge-bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates myriad computational biological studies including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics, and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge-bases. Here, we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction as well as common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process. PMID:20057383

Recurrence time statistics: versatile tools for genomic DNA sequence analysis.

PubMed

Cao, Yinhe; Tung, Wen-Wen; Gao, J B

2004-01-01

With the completion of the human and a few model organisms' genomes, and the genomes of many other organisms waiting to be sequenced, it has become increasingly important to develop faster computational tools which are capable of easily identifying the structures and extracting features from DNA sequences. One of the more important structures in a DNA sequence is repeat-related. Often they have to be masked before protein coding regions along a DNA sequence are to be identified or redundant expressed sequence tags (ESTs) are to be sequenced. Here we report a novel recurrence time based method for sequence analysis. The method can conveniently study all kinds of periodicity and exhaustively find all repeat-related features from a genomic DNA sequence. An efficient codon index is also derived from the recurrence time statistics, which has the salient features of being largely species-independent and working well on very short sequences. Efficient codon indices are key elements of successful gene finding algorithms, and are particularly useful for determining whether a suspected EST belongs to a coding or non-coding region. We illustrate the power of the method by studying the genomes of E. coli, the yeast S. cervisivae, the nematode worm C. elegans, and the human, Homo sapiens. Computationally, our method is very efficient. It allows us to carry out analysis of genomes on the whole genomic scale by a PC.

The Divided Bacterial Genome: Structure, Function, and Evolution.

PubMed

diCenzo, George C; Finan, Turlough M

2017-09-01

Approximately 10% of bacterial genomes are split between two or more large DNA fragments, a genome architecture referred to as a multipartite genome. This multipartite organization is found in many important organisms, including plant symbionts, such as the nitrogen-fixing rhizobia, and plant, animal, and human pathogens, including the genera Brucella , Vibrio , and Burkholderia . The availability of many complete bacterial genome sequences means that we can now examine on a broad scale the characteristics of the different types of DNA molecules in a genome. Recent work has begun to shed light on the unique properties of each class of replicon, the unique functional role of chromosomal and nonchromosomal DNA molecules, and how the exploitation of novel niches may have driven the evolution of the multipartite genome. The aims of this review are to (i) outline the literature regarding bacterial genomes that are divided into multiple fragments, (ii) provide a meta-analysis of completed bacterial genomes from 1,708 species as a way of reviewing the abundant information present in these genome sequences, and (iii) provide an encompassing model to explain the evolution and function of the multipartite genome structure. This review covers, among other topics, salient genome terminology; mechanisms of multipartite genome formation; the phylogenetic distribution of multipartite genomes; how each part of a genome differs with respect to genomic signatures, genetic variability, and gene functional annotation; how each DNA molecule may interact; as well as the costs and benefits of this genome structure. Copyright © 2017 American Society for Microbiology.

Phylogenomics of nonavian reptiles and the structure of the ancestral amniote genome

PubMed Central

Shedlock, Andrew M.; Botka, Christopher W.; Zhao, Shaying; Shetty, Jyoti; Zhang, Tingting; Liu, Jun S.; Deschavanne, Patrick J.; Edwards, Scott V.

2007-01-01

We report results of a megabase-scale phylogenomic analysis of the Reptilia, the sister group of mammals. Large-scale end-sequence scanning of genomic clones of a turtle, alligator, and lizard reveals diverse, mammal-like landscapes of retroelements and simple sequence repeats (SSRs) not found in the chicken. Several global genomic traits, including distinctive phylogenetic lineages of CR1-like long interspersed elements (LINEs) and a paucity of A-T rich SSRs, characterize turtles and archosaur genomes, whereas higher frequencies of tandem repeats and a lower global GC content reveal mammal-like features in Anolis. Nonavian reptile genomes also possess a high frequency of diverse and novel 50-bp unit tandem duplications not found in chicken or mammals. The frequency distributions of ≈65,000 8-mer oligonucleotides suggest that rates of DNA-word frequency change are an order of magnitude slower in reptiles than in mammals. These results suggest a diverse array of interspersed and SSRs in the common ancestor of amniotes and a genomic conservatism and gradual loss of retroelements in reptiles that culminated in the minimalist chicken genome. PMID:17307883

CoCoNUT: an efficient system for the comparison and analysis of genomes

PubMed Central

2008-01-01

Background Comparative genomics is the analysis and comparison of genomes from different species. This area of research is driven by the large number of sequenced genomes and heavily relies on efficient algorithms and software to perform pairwise and multiple genome comparisons. Results Most of the software tools available are tailored for one specific task. In contrast, we have developed a novel system CoCoNUT (Computational Comparative geNomics Utility Toolkit) that allows solving several different tasks in a unified framework: (1) finding regions of high similarity among multiple genomic sequences and aligning them, (2) comparing two draft or multi-chromosomal genomes, (3) locating large segmental duplications in large genomic sequences, and (4) mapping cDNA/EST to genomic sequences. Conclusion CoCoNUT is competitive with other software tools w.r.t. the quality of the results. The use of state of the art algorithms and data structures allows CoCoNUT to solve comparative genomics tasks more efficiently than previous tools. With the improved user interface (including an interactive visualization component), CoCoNUT provides a unified, versatile, and easy-to-use software tool for large scale studies in comparative genomics. PMID:19014477

RNA-Seq analysis of yak ovary: improving yak gene structure information and mining reproduction-related genes.

PubMed

Lan, DaoLiang; Xiong, XianRong; Wei, YanLi; Xu, Tong; Zhong, JinCheng; Zhi, XiangDong; Wang, Yong; Li, Jian

2014-09-01

RNA-Seq, a high-throughput (HT) sequencing technique, has been used effectively in large-scale transcriptomic studies, and is particularly useful for improving gene structure information and mining of new genes. In this study, RNA-Seq HT technology was employed to analyze the transcriptome of yak ovary. After Illumina-Solexa deep sequencing, 26826516 clean reads with a total of 4828772880 bp were obtained from the ovary library. Alignment analysis showed that 16992 yak genes mapped to the yak genome and 3734 of these genes were involved in alternative splicing. Gene structure refinement analysis showed that 7340 genes that were annotated in the yak genome could be extended at the 5' or 3' ends based on the alignments been the transcripts and the genome sequence. Novel transcript prediction analysis identified 6321 new transcripts with lengths ranging from 180 to 14884 bp, and 2267 of them were predicted to code proteins. BLAST analysis of the new transcripts showed that 1200?4933 mapped to the non-redundant (nr), nucleotide (nt) and/or SwissProt sequence databases. Comparative statistical analysis of the new mapped transcripts showed that the majority of them were similar to genes in Bos taurus (41.4%), Bos grunniens mutus (33.0%), Ovis aries (6.3%), Homo sapiens (2.8%), Mus musculus (1.6%) and other species. Functional analysis showed that these expressed genes were involved in various Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes pathways. GO analysis of the new transcripts found that the largest proportion of them was associated with reproduction. The results of this study will provide a basis for describing the normal transcriptome map of yak ovary and for future studies on yak breeding performance. Moreover, the results confirmed that RNA-Seq HT technology is highly advantageous in improving gene structure information and mining of new genes, as well as in providing valuable data to expand the yak genome information.

The Paris-Sud yeast structural genomics pilot-project: from structure to function.

PubMed

Quevillon-Cheruel, Sophie; Liger, Dominique; Leulliot, Nicolas; Graille, Marc; Poupon, Anne; Li de La Sierra-Gallay, Inès; Zhou, Cong-Zhao; Collinet, Bruno; Janin, Joël; Van Tilbeurgh, Herman

2004-01-01

We present here the outlines and results from our yeast structural genomics (YSG) pilot-project. A lab-scale platform for the systematic production and structure determination is presented. In order to validate this approach, 250 non-membrane proteins of unknown structure were targeted. Strategies and final statistics are evaluated. We finally discuss the opportunity of structural genomics programs to contribute to functional biochemical annotation.

Ensembl Genomes 2013: scaling up access to genome-wide data

USDA-ARS?s Scientific Manuscript database

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species. The project exploits and extends technologies for genome annotation, analysis and dissemination, developed in the context of the vertebrate-focused Ensembl project, and provi...

Genomes as documents of evolutionary history: a probabilistic macrosynteny model for the reconstruction of ancestral genomes

PubMed Central

Nakatani, Yoichiro; McLysaght, Aoife

2017-01-01

Abstract Motivation: It has been argued that whole-genome duplication (WGD) exerted a profound influence on the course of evolution. For the purpose of fully understanding the impact of WGD, several formal algorithms have been developed for reconstructing pre-WGD gene order in yeast and plant. However, to the best of our knowledge, those algorithms have never been successfully applied to WGD events in teleost and vertebrate, impeded by extensive gene shuffling and gene losses. Results: Here, we present a probabilistic model of macrosynteny (i.e. conserved linkage or chromosome-scale distribution of orthologs), develop a variational Bayes algorithm for inferring the structure of pre-WGD genomes, and study estimation accuracy by simulation. Then, by applying the method to the teleost WGD, we demonstrate effectiveness of the algorithm in a situation where gene-order reconstruction algorithms perform relatively poorly due to a high rate of rearrangement and extensive gene losses. Our high-resolution reconstruction reveals previously overlooked small-scale rearrangements, necessitating a revision to previous views on genome structure evolution in teleost and vertebrate. Conclusions: We have reconstructed the structure of a pre-WGD genome by employing a variational Bayes approach that was originally developed for inferring topics from millions of text documents. Interestingly, comparison of the macrosynteny and topic model algorithms suggests that macrosynteny can be regarded as documents on ancestral genome structure. From this perspective, the present study would seem to provide a textbook example of the prevalent metaphor that genomes are documents of evolutionary history. Availability and implementation: The analysis data are available for download at http://www.gen.tcd.ie/molevol/supp_data/MacrosyntenyTGD.zip, and the software written in Java is available upon request. Contact: yoichiro.nakatani@tcd.ie or aoife.mclysaght@tcd.ie Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28881993

Genomes as documents of evolutionary history: a probabilistic macrosynteny model for the reconstruction of ancestral genomes.

PubMed

Nakatani, Yoichiro; McLysaght, Aoife

2017-07-15

It has been argued that whole-genome duplication (WGD) exerted a profound influence on the course of evolution. For the purpose of fully understanding the impact of WGD, several formal algorithms have been developed for reconstructing pre-WGD gene order in yeast and plant. However, to the best of our knowledge, those algorithms have never been successfully applied to WGD events in teleost and vertebrate, impeded by extensive gene shuffling and gene losses. Here, we present a probabilistic model of macrosynteny (i.e. conserved linkage or chromosome-scale distribution of orthologs), develop a variational Bayes algorithm for inferring the structure of pre-WGD genomes, and study estimation accuracy by simulation. Then, by applying the method to the teleost WGD, we demonstrate effectiveness of the algorithm in a situation where gene-order reconstruction algorithms perform relatively poorly due to a high rate of rearrangement and extensive gene losses. Our high-resolution reconstruction reveals previously overlooked small-scale rearrangements, necessitating a revision to previous views on genome structure evolution in teleost and vertebrate. We have reconstructed the structure of a pre-WGD genome by employing a variational Bayes approach that was originally developed for inferring topics from millions of text documents. Interestingly, comparison of the macrosynteny and topic model algorithms suggests that macrosynteny can be regarded as documents on ancestral genome structure. From this perspective, the present study would seem to provide a textbook example of the prevalent metaphor that genomes are documents of evolutionary history. The analysis data are available for download at http://www.gen.tcd.ie/molevol/supp_data/MacrosyntenyTGD.zip , and the software written in Java is available upon request. yoichiro.nakatani@tcd.ie or aoife.mclysaght@tcd.ie. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Systems biology of the structural proteome.

PubMed

Brunk, Elizabeth; Mih, Nathan; Monk, Jonathan; Zhang, Zhen; O'Brien, Edward J; Bliven, Spencer E; Chen, Ke; Chang, Roger L; Bourne, Philip E; Palsson, Bernhard O

2016-03-11

The success of genome-scale models (GEMs) can be attributed to the high-quality, bottom-up reconstructions of metabolic, protein synthesis, and transcriptional regulatory networks on an organism-specific basis. Such reconstructions are biochemically, genetically, and genomically structured knowledge bases that can be converted into a mathematical format to enable a myriad of computational biological studies. In recent years, genome-scale reconstructions have been extended to include protein structural information, which has opened up new vistas in systems biology research and empowered applications in structural systems biology and systems pharmacology. Here, we present the generation, application, and dissemination of genome-scale models with protein structures (GEM-PRO) for Escherichia coli and Thermotoga maritima. We show the utility of integrating molecular scale analyses with systems biology approaches by discussing several comparative analyses on the temperature dependence of growth, the distribution of protein fold families, substrate specificity, and characteristic features of whole cell proteomes. Finally, to aid in the grand challenge of big data to knowledge, we provide several explicit tutorials of how protein-related information can be linked to genome-scale models in a public GitHub repository ( https://github.com/SBRG/GEMPro/tree/master/GEMPro_recon/). Translating genome-scale, protein-related information to structured data in the format of a GEM provides a direct mapping of gene to gene-product to protein structure to biochemical reaction to network states to phenotypic function. Integration of molecular-level details of individual proteins, such as their physical, chemical, and structural properties, further expands the description of biochemical network-level properties, and can ultimately influence how to model and predict whole cell phenotypes as well as perform comparative systems biology approaches to study differences between organisms. GEM-PRO offers insight into the physical embodiment of an organism's genotype, and its use in this comparative framework enables exploration of adaptive strategies for these organisms, opening the door to many new lines of research. With these provided tools, tutorials, and background, the reader will be in a position to run GEM-PRO for their own purposes.

Genome-wide population structure and evolutionary history of the Frizarta dairy sheep.

PubMed

Kominakis, A; Hager-Theodorides, A L; Saridaki, A; Antonakos, G; Tsiamis, G

2017-10-01

In the present study, we used genomic data, generated with a medium density single nucleotide polymorphisms (SNP) array, to acquire more information on the population structure and evolutionary history of the synthetic Frizarta dairy sheep. First, two typical measures of linkage disequilibrium (LD) were estimated at various physical distances that were then used to make inferences on the effective population size at key past time points. Population structure was also assessed by both multidimensional scaling analysis and k-means clustering on the distance matrix obtained from the animals' genomic relationships. The Wright's fixation F ST index was also employed to assess herds' genetic homogeneity and to indirectly estimate past migration rates. The Wright's fixation F IS index and genomic inbreeding coefficients based on the genomic relationship matrix as well as on runs of homozygosity were also estimated. The Frizarta breed displays relatively low LD levels with r 2 and |D'| equal to 0.18 and 0.50, respectively, at an average inter-marker distance of 31 kb. Linkage disequilibrium decayed rapidly by distance and persisted over just a few thousand base pairs. Rate of LD decay (β) varied widely among the 26 autosomes with larger values estimated for shorter chromosomes (e.g. β=0.057, for OAR6) and smaller values for longer ones (e.g. β=0.022, for OAR2). The inferred effective population size at the beginning of the breed's formation was as high as 549, was then reduced to 463 in 1981 (end of the breed's formation) and further declined to 187, one generation ago. Multidimensional scaling analysis and k-means clustering suggested a genetically homogenous population, F ST estimates indicated relatively low genetic differentiation between herds, whereas a heat map of the animals' genomic kinship relationships revealed a stratified population, at a herd level. Estimates of genomic inbreeding coefficients suggested that most recent parental relatedness may have been a major determinant of the current effective population size. A denser than the 50k SNP panel may be more beneficial when performing genome wide association studies in the breed.

Human structural variation: mechanisms of chromosome rearrangements

PubMed Central

Weckselblatt, Brooke; Rudd, M. Katharine

2015-01-01

Chromosome structural variation (SV) is a normal part of variation in the human genome, but some classes of SV can cause neurodevelopmental disorders. Analysis of the DNA sequence at SV breakpoints can reveal mutational mechanisms and risk factors for chromosome rearrangement. Large-scale SV breakpoint studies have become possible recently owing to advances in next-generation sequencing (NGS) including whole-genome sequencing (WGS). These findings have shed light on complex forms of SV such as triplications, inverted duplications, insertional translocations, and chromothripsis. Sequence-level breakpoint data resolve SV structure and determine how genes are disrupted, fused, and/or misregulated by breakpoints. Recent improvements in breakpoint sequencing have also revealed non-allelic homologous recombination (NAHR) between paralogous long interspersed nuclear element (LINE) or human endogenous retrovirus (HERV) repeats as a cause of deletions, duplications, and translocations. This review covers the genomic organization of simple and complex constitutional SVs, as well as the molecular mechanisms of their formation. PMID:26209074

Large Scale Comparative Visualisation of Regulatory Networks with TRNDiff

DOE PAGES

Chua, Xin-Yi; Buckingham, Lawrence; Hogan, James M.; ...

2015-06-01

The advent of Next Generation Sequencing (NGS) technologies has seen explosive growth in genomic datasets, and dense coverage of related organisms, supporting study of subtle, strain-specific variations as a determinant of function. Such data collections present fresh and complex challenges for bioinformatics, those of comparing models of complex relationships across hundreds and even thousands of sequences. Transcriptional Regulatory Network (TRN) structures document the influence of regulatory proteins called Transcription Factors (TFs) on associated Target Genes (TGs). TRNs are routinely inferred from model systems or iterative search, and analysis at these scales requires simultaneous displays of multiple networks well beyond thosemore » of existing network visualisation tools [1]. In this paper we describe TRNDiff, an open source system supporting the comparative analysis and visualization of TRNs (and similarly structured data) from many genomes, allowing rapid identification of functional variations within species. The approach is demonstrated through a small scale multiple TRN analysis of the Fur iron-uptake system of Yersinia, suggesting a number of candidate virulence factors; and through a larger study exploiting integration with the RegPrecise database (http://regprecise.lbl.gov; [2]) - a collection of hundreds of manually curated and predicted transcription factor regulons drawn from across the entire spectrum of prokaryotic organisms.« less

Structural and functional analysis of the finished genome of the recently isolated toxic Anabaena sp. WA102.

PubMed

Brown, Nathan M; Mueller, Ryan S; Shepardson, Jonathan W; Landry, Zachary C; Morré, Jeffrey T; Maier, Claudia S; Hardy, F Joan; Dreher, Theo W

2016-06-13

Very few closed genomes of the cyanobacteria that commonly produce toxic blooms in lakes and reservoirs are available, limiting our understanding of the properties of these organisms. A new anatoxin-a-producing member of the Nostocaceae, Anabaena sp. WA102, was isolated from a freshwater lake in Washington State, USA, in 2013 and maintained in non-axenic culture. The Anabaena sp. WA102 5.7 Mbp genome assembly has been closed with long-read, single-molecule sequencing and separately a draft genome assembly has been produced with short-read sequencing technology. The closed and draft genome assemblies are compared, showing a correlation between long repeats in the genome and the many gaps in the short-read assembly. Anabaena sp. WA102 encodes anatoxin-a biosynthetic genes, as does its close relative Anabaena sp. AL93 (also introduced in this study). These strains are distinguished by differences in the genes for light-harvesting phycobilins, with Anabaena sp. AL93 possessing a phycoerythrocyanin operon. Biologically relevant structural variants in the Anabaena sp. WA102 genome were detected only by long-read sequencing: a tandem triplication of the anaBCD promoter region in the anatoxin-a synthase gene cluster (not triplicated in Anabaena sp. AL93) and a 5-kbp deletion variant present in two-thirds of the population. The genome has a large number of mobile elements (160). Strikingly, there was no synteny with the genome of its nearest fully assembled relative, Anabaena sp. 90. Structural and functional genome analyses indicate that Anabaena sp. WA102 has a flexible genome. Genome closure, which can be readily achieved with long-read sequencing, reveals large scale (e.g., gene order) and local structural features that should be considered in understanding genome evolution and function.

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

PubMed

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 bacterial genomes. Analytical capabilities include exploration of: regulon content, structure and function; TF binding site motifs; conservation and variations in genome-wide regulatory networks across all taxonomic groups of Bacteria. RegPrecise 3.0 was selected as a core resource on transcriptional regulation of the Department of Energy Systems Biology Knowledgebase, an emerging software and data environment designed to enable researchers to collaboratively generate, test and share new hypotheses about gene and protein functions, perform large-scale analyses, and model interactions in microbes, plants, and their communities.

The membrane skeleton in Paramecium: Molecular characterization of a novel epiplasmin family and preliminary GFP expression results.

PubMed

Pomel, Sébastien; Diogon, Marie; Bouchard, Philippe; Pradel, Lydie; Ravet, Viviane; Coffe, Gérard; Viguès, Bernard

2006-02-01

Previous attempts to identify the membrane skeleton of Paramecium cells have revealed a protein pattern that is both complex and specific. The most prominent structural elements, epiplasmic scales, are centered around ciliary units and are closely apposed to the cytoplasmic side of the inner alveolar membrane. We sought to characterize epiplasmic scale proteins (epiplasmins) at the molecular level. PCR approaches enabled the cloning and sequencing of two closely related genes by amplifications of sequences from a macronuclear genomic library. Using these two genes (EPI-1 and EPI-2), we have contributed to the annotation of the Paramecium tetraurelia macronuclear genome and identified 39 additional (paralogous) sequences. Two orthologous sequences were found in the Tetrahymena thermophila genome. Structural analysis of the 43 sequences indicates that the hallmark of this new multigenic family is a 79 aa domain flanked by two Q-, P- and V-rich stretches of sequence that are much more variable in amino-acid composition. Such features clearly distinguish members of the multigenic family from epiplasmic proteins previously sequenced in other ciliates. The expression of Green Fluorescent Protein (GFP)-tagged epiplasmin showed significant labeling of epiplasmic scales as well as oral structures. We expect that the GFP construct described herein will prove to be a useful tool for comparative subcellular localization of different putative epiplasmins in Paramecium.

IMG-ABC. A knowledge base to fuel discovery of biosynthetic gene clusters and novel secondary metabolites

DOE PAGES

Hadjithomas, Michalis; Chen, I-Min Amy; Chu, Ken; ...

2015-07-14

In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of “big” genomic data for discovering small molecules. IMG-ABC relies on IMG’s comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve asmore » the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC’s focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in lphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG’s extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world.« less

The connectivity structure, giant strong component and centrality of metabolic networks.

PubMed

Ma, Hong-Wu; Zeng, An-Ping

2003-07-22

Structural and functional analysis of genome-based large-scale metabolic networks is important for understanding the design principles and regulation of the metabolism at a system level. The metabolic network is conventionally considered to be highly integrated and very complex. A rational reduction of the metabolic network to its core structure and a deeper understanding of its functional modules are important. In this work, we show that the metabolites in a metabolic network are far from fully connected. A connectivity structure consisting of four major subsets of metabolites and reactions, i.e. a fully connected sub-network, a substrate subset, a product subset and an isolated subset is found to exist in metabolic networks of 65 fully sequenced organisms. The largest fully connected part of a metabolic network, called 'the giant strong component (GSC)', represents the most complicated part and the core of the network and has the feature of scale-free networks. The average path length of the whole network is primarily determined by that of the GSC. For most of the organisms, GSC normally contains less than one-third of the nodes of the network. This connectivity structure is very similar to the 'bow-tie' structure of World Wide Web. Our results indicate that the bow-tie structure may be common for large-scale directed networks. More importantly, the uncovered structure feature makes a structural and functional analysis of large-scale metabolic network more amenable. As shown in this work, comparing the closeness centrality of the nodes in the GSC can identify the most central metabolites of a metabolic network. To quantitatively characterize the overall connection structure of the GSC we introduced the term 'overall closeness centralization index (OCCI)'. OCCI correlates well with the average path length of the GSC and is a useful parameter for a system-level comparison of metabolic networks of different organisms. http://genome.gbf.de/bioinformatics/

Genetic Structures of Copy Number Variants Revealed by Genotyping Single Sperm

PubMed Central

Luo, Minjie; Cui, Xiangfeng; Fredman, David; Brookes, Anthony J.; Azaro, Marco A.; Greenawalt, Danielle M.; Hu, Guohong; Wang, Hui-Yun; Tereshchenko, Irina V.; Lin, Yong; Shentu, Yue; Gao, Richeng; Shen, Li; Li, Honghua

2009-01-01

Background Copy number variants (CNVs) occupy a significant portion of the human genome and may have important roles in meiotic recombination, human genome evolution and gene expression. Many genetic diseases may be underlain by CNVs. However, because of the presence of their multiple copies, variability in copy numbers and the diploidy of the human genome, detailed genetic structure of CNVs cannot be readily studied by available techniques. Methodology/Principal Findings Single sperm samples were used as the primary subjects for the study so that CNV haplotypes in the sperm donors could be studied individually. Forty-eight CNVs characterized in a previous study were analyzed using a microarray-based high-throughput genotyping method after multiplex amplification. Seventeen single nucleotide polymorphisms (SNPs) were also included as controls. Two single-base variants, either allelic or paralogous, could be discriminated for all markers. Microarray data were used to resolve SNP alleles and CNV haplotypes, to quantitatively assess the numbers and compositions of the paralogous segments in each CNV haplotype. Conclusions/Significance This is the first study of the genetic structure of CNVs on a large scale. Resulting information may help understand evolution of the human genome, gain insight into many genetic processes, and discriminate between CNVs and SNPs. The highly sensitive high-throughput experimental system with haploid sperm samples as subjects may be used to facilitate detailed large-scale CNV analysis. PMID:19384415

Computational analysis of conserved RNA secondary structure in transcriptomes and genomes.

PubMed

Eddy, Sean R

2014-01-01

Transcriptomics experiments and computational predictions both enable systematic discovery of new functional RNAs. However, many putative noncoding transcripts arise instead from artifacts and biological noise, and current computational prediction methods have high false positive rates. I discuss prospects for improving computational methods for analyzing and identifying functional RNAs, with a focus on detecting signatures of conserved RNA secondary structure. An interesting new front is the application of chemical and enzymatic experiments that probe RNA structure on a transcriptome-wide scale. I review several proposed approaches for incorporating structure probing data into the computational prediction of RNA secondary structure. Using probabilistic inference formalisms, I show how all these approaches can be unified in a well-principled framework, which in turn allows RNA probing data to be easily integrated into a wide range of analyses that depend on RNA secondary structure inference. Such analyses include homology search and genome-wide detection of new structural RNAs.

Comprehensive phylogeny of ray-finned fishes (Actinopterygii) based on transcriptomic and genomic data.

PubMed

Hughes, Lily C; Ortí, Guillermo; Huang, Yu; Sun, Ying; Baldwin, Carole C; Thompson, Andrew W; Arcila, Dahiana; Betancur-R, Ricardo; Li, Chenhong; Becker, Leandro; Bellora, Nicolás; Zhao, Xiaomeng; Li, Xiaofeng; Wang, Min; Fang, Chao; Xie, Bing; Zhou, Zhuocheng; Huang, Hai; Chen, Songlin; Venkatesh, Byrappa; Shi, Qiong

2018-05-14

Our understanding of phylogenetic relationships among bony fishes has been transformed by analysis of a small number of genes, but uncertainty remains around critical nodes. Genome-scale inferences so far have sampled a limited number of taxa and genes. Here we leveraged 144 genomes and 159 transcriptomes to investigate fish evolution with an unparalleled scale of data: >0.5 Mb from 1,105 orthologous exon sequences from 303 species, representing 66 out of 72 ray-finned fish orders. We apply phylogenetic tests designed to trace the effect of whole-genome duplication events on gene trees and find paralogy-free loci using a bioinformatics approach. Genome-wide data support the structure of the fish phylogeny, and hypothesis-testing procedures appropriate for phylogenomic datasets using explicit gene genealogy interrogation settle some long-standing uncertainties, such as the branching order at the base of the teleosts and among early euteleosts, and the sister lineage to the acanthomorph and percomorph radiations. Comprehensive fossil calibrations date the origin of all major fish lineages before the end of the Cretaceous.

ssbio: a Python framework for structural systems biology.

PubMed

Mih, Nathan; Brunk, Elizabeth; Chen, Ke; Catoiu, Edward; Sastry, Anand; Kavvas, Erol; Monk, Jonathan M; Zhang, Zhen; Palsson, Bernhard O

2018-06-15

Working with protein structures at the genome-scale has been challenging in a variety of ways. Here, we present ssbio, a Python package that provides a framework to easily work with structural information in the context of genome-scale network reconstructions, which can contain thousands of individual proteins. The ssbio package provides an automated pipeline to construct high quality genome-scale models with protein structures (GEM-PROs), wrappers to popular third-party programs to compute associated protein properties, and methods to visualize and annotate structures directly in Jupyter notebooks, thus lowering the barrier of linking 3D structural data with established systems workflows. ssbio is implemented in Python and available to download under the MIT license at http://github.com/SBRG/ssbio. Documentation and Jupyter notebook tutorials are available at http://ssbio.readthedocs.io/en/latest/. Interactive notebooks can be launched using Binder at https://mybinder.org/v2/gh/SBRG/ssbio/master?filepath=Binder.ipynb. Supplementary data are available at Bioinformatics online.

Large-scale genomic analyses reveal the population structure and evolutionary trends of Streptococcus agalactiae strains in Brazilian fish farms.

PubMed

Barony, Gustavo M; Tavares, Guilherme C; Pereira, Felipe L; Carvalho, Alex F; Dorella, Fernanda A; Leal, Carlos A G; Figueiredo, Henrique C P

2017-10-19

Streptococcus agalactiae is a major pathogen and a hindrance on tilapia farming worldwide. The aims of this work were to analyze the genomic evolution of Brazilian strains of S. agalactiae and to establish spatial and temporal relations between strains isolated from different outbreaks of streptococcosis. A total of 39 strains were obtained from outbreaks and their whole genomes were sequenced and annotated for comparative analysis of multilocus sequence typing, genomic similarity and whole genome multilocus sequence typing (wgMLST). The Brazilian strains presented two sequence types, including a newly described ST, and a non-typeable lineage. The use of wgMLST could differentiate each strain in a single clone and was used to establish temporal and geographical correlations among strains. Bayesian phylogenomic analysis suggests that the studied Brazilian population was co-introduced in the country with their host, approximately 60 years ago. Brazilian strains of S. agalactiae were shown to be heterogeneous in their genome sequences and were distributed in different regions of the country according to their genotype, which allowed the use of wgMLST analysis to track each outbreak event individually.

In vivo genome-wide profiling of RNA secondary structure reveals novel regulatory features.

PubMed

Ding, Yiliang; Tang, Yin; Kwok, Chun Kit; Zhang, Yu; Bevilacqua, Philip C; Assmann, Sarah M

2014-01-30

RNA structure has critical roles in processes ranging from ligand sensing to the regulation of translation, polyadenylation and splicing. However, a lack of genome-wide in vivo RNA structural data has limited our understanding of how RNA structure regulates gene expression in living cells. Here we present a high-throughput, genome-wide in vivo RNA structure probing method, structure-seq, in which dimethyl sulphate methylation of unprotected adenines and cytosines is identified by next-generation sequencing. Application of this method to Arabidopsis thaliana seedlings yielded the first in vivo genome-wide RNA structure map at nucleotide resolution for any organism, with quantitative structural information across more than 10,000 transcripts. Our analysis reveals a three-nucleotide periodic repeat pattern in the structure of coding regions, as well as a less-structured region immediately upstream of the start codon, and shows that these features are strongly correlated with translation efficiency. We also find patterns of strong and weak secondary structure at sites of alternative polyadenylation, as well as strong secondary structure at 5' splice sites that correlates with unspliced events. Notably, in vivo structures of messenger RNAs annotated for stress responses are poorly predicted in silico, whereas mRNA structures of genes related to cell function maintenance are well predicted. Global comparison of several structural features between these two categories shows that the mRNAs associated with stress responses tend to have more single-strandedness, longer maximal loop length and higher free energy per nucleotide, features that may allow these RNAs to undergo conformational changes in response to environmental conditions. Structure-seq allows the RNA structurome and its biological roles to be interrogated on a genome-wide scale and should be applicable to any organism.

Scalable Parameter Estimation for Genome-Scale Biochemical Reaction Networks

PubMed Central

Kaltenbacher, Barbara; Hasenauer, Jan

2017-01-01

Mechanistic mathematical modeling of biochemical reaction networks using ordinary differential equation (ODE) models has improved our understanding of small- and medium-scale biological processes. While the same should in principle hold for large- and genome-scale processes, the computational methods for the analysis of ODE models which describe hundreds or thousands of biochemical species and reactions are missing so far. While individual simulations are feasible, the inference of the model parameters from experimental data is computationally too intensive. In this manuscript, we evaluate adjoint sensitivity analysis for parameter estimation in large scale biochemical reaction networks. We present the approach for time-discrete measurement and compare it to state-of-the-art methods used in systems and computational biology. Our comparison reveals a significantly improved computational efficiency and a superior scalability of adjoint sensitivity analysis. The computational complexity is effectively independent of the number of parameters, enabling the analysis of large- and genome-scale models. Our study of a comprehensive kinetic model of ErbB signaling shows that parameter estimation using adjoint sensitivity analysis requires a fraction of the computation time of established methods. The proposed method will facilitate mechanistic modeling of genome-scale cellular processes, as required in the age of omics. PMID:28114351

GenoMycDB: a database for comparative analysis of mycobacterial genes and genomes.

PubMed

Catanho, Marcos; Mascarenhas, Daniel; Degrave, Wim; Miranda, Antonio Basílio de

2006-03-31

Several databases and computational tools have been created with the aim of organizing, integrating and analyzing the wealth of information generated by large-scale sequencing projects of mycobacterial genomes and those of other organisms. However, with very few exceptions, these databases and tools do not allow for massive and/or dynamic comparison of these data. GenoMycDB (http://www.dbbm.fiocruz.br/GenoMycDB) is a relational database built for large-scale comparative analyses of completely sequenced mycobacterial genomes, based on their predicted protein content. Its central structure is composed of the results obtained after pair-wise sequence alignments among all the predicted proteins coded by the genomes of six mycobacteria: Mycobacterium tuberculosis (strains H37Rv and CDC1551), M. bovis AF2122/97, M. avium subsp. paratuberculosis K10, M. leprae TN, and M. smegmatis MC2 155. The database stores the computed similarity parameters of every aligned pair, providing for each protein sequence the predicted subcellular localization, the assigned cluster of orthologous groups, the features of the corresponding gene, and links to several important databases. Tables containing pairs or groups of potential homologs between selected species/strains can be produced dynamically by user-defined criteria, based on one or multiple sequence similarity parameters. In addition, searches can be restricted according to the predicted subcellular localization of the protein, the DNA strand of the corresponding gene and/or the description of the protein. Massive data search and/or retrieval are available, and different ways of exporting the result are offered. GenoMycDB provides an on-line resource for the functional classification of mycobacterial proteins as well as for the analysis of genome structure, organization, and evolution.

Discovery of functional elements in 12 Drosophila genomes using evolutionary signatures

PubMed Central

Stark, Alexander; Lin, Michael F.; Kheradpour, Pouya; Pedersen, Jakob S.; Parts, Leopold; Carlson, Joseph W.; Crosby, Madeline A.; Rasmussen, Matthew D.; Roy, Sushmita; Deoras, Ameya N.; Ruby, J. Graham; Brennecke, Julius; Hodges, Emily; Hinrichs, Angie S.; Caspi, Anat; Paten, Benedict; Park, Seung-Won; Han, Mira V.; Maeder, Morgan L.; Polansky, Benjamin J.; Robson, Bryanne E.; Aerts, Stein; van Helden, Jacques; Hassan, Bassem; Gilbert, Donald G.; Eastman, Deborah A.; Rice, Michael; Weir, Michael; Hahn, Matthew W.; Park, Yongkyu; Dewey, Colin N.; Pachter, Lior; Kent, W. James; Haussler, David; Lai, Eric C.; Bartel, David P.; Hannon, Gregory J.; Kaufman, Thomas C.; Eisen, Michael B.; Clark, Andrew G.; Smith, Douglas; Celniker, Susan E.; Gelbart, William M.; Kellis, Manolis

2008-01-01

Sequencing of multiple related species followed by comparative genomics analysis constitutes a powerful approach for the systematic understanding of any genome. Here, we use the genomes of 12 Drosophila species for the de novo discovery of functional elements in the fly. Each type of functional element shows characteristic patterns of change, or ‘evolutionary signatures’, dictated by its precise selective constraints. Such signatures enable recognition of new protein-coding genes and exons, spurious and incorrect gene annotations, and numerous unusual gene structures, including abundant stop-codon readthrough. Similarly, we predict non-protein-coding RNA genes and structures, and new microRNA (miRNA) genes. We provide evidence of miRNA processing and functionality from both hairpin arms and both DNA strands. We identify several classes of pre- and post-transcriptional regulatory motifs, and predict individual motif instances with high confidence. We also study how discovery power scales with the divergence and number of species compared, and we provide general guidelines for comparative studies. PMID:17994088

A new genome-mining tool redefines the lasso peptide biosynthetic landscape

PubMed Central

Tietz, Jonathan I.; Schwalen, Christopher J.; Patel, Parth S.; Maxson, Tucker; Blair, Patricia M.; Tai, Hua-Chia; Zakai, Uzma I.; Mitchell, Douglas A.

2016-01-01

Ribosomally synthesized and post-translationally modified peptide (RiPP) natural products are attractive for genome-driven discovery and re-engineering, but limitations in bioinformatic methods and exponentially increasing genomic data make large-scale mining difficult. We report RODEO (Rapid ORF Description and Evaluation Online), which combines hidden Markov model-based analysis, heuristic scoring, and machine learning to identify biosynthetic gene clusters and predict RiPP precursor peptides. We initially focused on lasso peptides, which display intriguing physiochemical properties and bioactivities, but their hypervariability renders them challenging prospects for automated mining. Our approach yielded the most comprehensive mapping of lasso peptide space, revealing >1,300 compounds. We characterized the structures and bioactivities of six lasso peptides, prioritized based on predicted structural novelty, including an unprecedented handcuff-like topology and another with a citrulline modification exceptionally rare among bacteria. These combined insights significantly expand the knowledge of lasso peptides, and more broadly, provide a framework for future genome-mining efforts. PMID:28244986

Human Genome Sequencing in Health and Disease

PubMed Central

Gonzaga-Jauregui, Claudia; Lupski, James R.; Gibbs, Richard A.

2013-01-01

Following the “finished,” euchromatic, haploid human reference genome sequence, the rapid development of novel, faster, and cheaper sequencing technologies is making possible the era of personalized human genomics. Personal diploid human genome sequences have been generated, and each has contributed to our better understanding of variation in the human genome. We have consequently begun to appreciate the vastness of individual genetic variation from single nucleotide to structural variants. Translation of genome-scale variation into medically useful information is, however, in its infancy. This review summarizes the initial steps undertaken in clinical implementation of personal genome information, and describes the application of whole-genome and exome sequencing to identify the cause of genetic diseases and to suggest adjuvant therapies. Better analysis tools and a deeper understanding of the biology of our genome are necessary in order to decipher, interpret, and optimize clinical utility of what the variation in the human genome can teach us. Personal genome sequencing may eventually become an instrument of common medical practice, providing information that assists in the formulation of a differential diagnosis. We outline herein some of the remaining challenges. PMID:22248320

The Mouse Genomes Project: a repository of inbred laboratory mouse strain genomes.

PubMed

Adams, David J; Doran, Anthony G; Lilue, Jingtao; Keane, Thomas M

2015-10-01

The Mouse Genomes Project was initiated in 2009 with the goal of using next-generation sequencing technologies to catalogue molecular variation in the common laboratory mouse strains, and a selected set of wild-derived inbred strains. The initial sequencing and survey of sequence variation in 17 inbred strains was completed in 2011 and included comprehensive catalogue of single nucleotide polymorphisms, short insertion/deletions, larger structural variants including their fine scale architecture and landscape of transposable element variation, and genomic sites subject to post-transcriptional alteration of RNA. From this beginning, the resource has expanded significantly to include 36 fully sequenced inbred laboratory mouse strains, a refined and updated data processing pipeline, and new variation querying and data visualisation tools which are available on the project's website ( http://www.sanger.ac.uk/resources/mouse/genomes/ ). The focus of the project is now the completion of de novo assembled chromosome sequences and strain-specific gene structures for the core strains. We discuss how the assembled chromosomes will power comparative analysis, data access tools and future directions of mouse genetics.

NCBI prokaryotic genome annotation pipeline.

PubMed

Tatusova, Tatiana; DiCuccio, Michael; Badretdin, Azat; Chetvernin, Vyacheslav; Nawrocki, Eric P; Zaslavsky, Leonid; Lomsadze, Alexandre; Pruitt, Kim D; Borodovsky, Mark; Ostell, James

2016-08-19

Recent technological advances have opened unprecedented opportunities for large-scale sequencing and analysis of populations of pathogenic species in disease outbreaks, as well as for large-scale diversity studies aimed at expanding our knowledge across the whole domain of prokaryotes. To meet the challenge of timely interpretation of structure, function and meaning of this vast genetic information, a comprehensive approach to automatic genome annotation is critically needed. In collaboration with Georgia Tech, NCBI has developed a new approach to genome annotation that combines alignment based methods with methods of predicting protein-coding and RNA genes and other functional elements directly from sequence. A new gene finding tool, GeneMarkS+, uses the combined evidence of protein and RNA placement by homology as an initial map of annotation to generate and modify ab initio gene predictions across the whole genome. Thus, the new NCBI's Prokaryotic Genome Annotation Pipeline (PGAP) relies more on sequence similarity when confident comparative data are available, while it relies more on statistical predictions in the absence of external evidence. The pipeline provides a framework for generation and analysis of annotation on the full breadth of prokaryotic taxonomy. For additional information on PGAP see https://www.ncbi.nlm.nih.gov/genome/annotation_prok/ and the NCBI Handbook, https://www.ncbi.nlm.nih.gov/books/NBK174280/. Published by Oxford University Press on behalf of Nucleic Acids Research 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Molecular evolution and expression of archosaurian β-keratins: diversification and expansion of archosaurian β-keratins and the origin of feather β-keratins.

PubMed

Greenwold, Matthew J; Sawyer, Roger H

2013-09-01

The archosauria consist of two living groups, crocodilians, and birds. Here we compare the structure, expression, and phylogeny of the beta (β)-keratins in two crocodilian genomes and two avian genomes to gain a better understanding of the evolutionary origin of the feather β-keratins. Unlike squamates such as the green anole with 40 β-keratins in its genome, the chicken and zebra finch genomes have over 100 β-keratin genes in their genomes, while the American alligator has 20 β-keratin genes, and the saltwater crocodile has 21 β-keratin genes. The crocodilian β-keratins are similar to those of birds and these structural proteins have a central filament domain and N- and C-termini, which contribute to the matrix material between the twisted β-sheets, which form the 2-3 nm filament. Overall the expression of alligator β-keratin genes in the integument increases during development. Phylogenetic analysis demonstrates that a crocodilian β-keratin clade forms a monophyletic group with the avian scale and feather β-keratins, suggesting that avian scale and feather β-keratins along with a subset of crocodilian β-keratins evolved from a common ancestral gene/s. Overall, our analyses support the view that the epidermal appendages of basal archosaurs used a diverse array of β-keratins, which evolved into crocodilian and avian specific clades. In birds, the scale and feather subfamilies appear to have evolved independently in the avian lineage from a subset of archosaurian claw β-keratins. The expansion of the avian specific feather β-keratin genes accompanied the diversification of birds and the evolution of feathers. Copyright © 2013 Wiley Periodicals, Inc.

Landscape genomics in Atlantic salmon (Salmo salar): searching for gene-environment interactions driving local adaptation.

PubMed

Vincent, Bourret; Dionne, Mélanie; Kent, Matthew P; Lien, Sigbjørn; Bernatchez, Louis

2013-12-01

A growing number of studies are examining the factors driving historical and contemporary evolution in wild populations. By combining surveys of genomic variation with a comprehensive assessment of environmental parameters, such studies can increase our understanding of the genomic and geographical extent of local adaptation in wild populations. We used a large-scale landscape genomics approach to examine adaptive and neutral differentiation across 54 North American populations of Atlantic salmon representing seven previously defined genetically distinct regional groups. Over 5500 genome-wide single nucleotide polymorphisms were genotyped in 641 individuals and 28 bulk assays of 25 pooled individuals each. Genome scans, linkage map, and 49 environmental variables were combined to conduct an innovative landscape genomic analysis. Our results provide valuable insight into the links between environmental variation and both neutral and potentially adaptive genetic divergence. In particular, we identified markers potentially under divergent selection, as well as associated selective environmental factors and biological functions with the observed adaptive divergence. Multivariate landscape genetic analysis revealed strong associations of both genetic and environmental structures. We found an enrichment of growth-related functions among outlier markers. Climate (temperature-precipitation) and geological characteristics were significantly associated with both potentially adaptive and neutral genetic divergence and should be considered as candidate loci involved in adaptation at the regional scale in Atlantic salmon. Hence, this study significantly contributes to the improvement of tools used in modern conservation and management schemes of Atlantic salmon wild populations. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Form and function of topologically associating genomic domains in budding yeast.

PubMed

Eser, Umut; Chandler-Brown, Devon; Ay, Ferhat; Straight, Aaron F; Duan, Zhijun; Noble, William Stafford; Skotheim, Jan M

2017-04-11

The genome of metazoan cells is organized into topologically associating domains (TADs) that have similar histone modifications, transcription level, and DNA replication timing. Although similar structures appear to be conserved in fission yeast, computational modeling and analysis of high-throughput chromosome conformation capture (Hi-C) data have been used to argue that the small, highly constrained budding yeast chromosomes could not have these structures. In contrast, herein we analyze Hi-C data for budding yeast and identify 200-kb scale TADs, whose boundaries are enriched for transcriptional activity. Furthermore, these boundaries separate regions of similarly timed replication origins connecting the long-known effect of genomic context on replication timing to genome architecture. To investigate the molecular basis of TAD formation, we performed Hi-C experiments on cells depleted for the Forkhead transcription factors, Fkh1 and Fkh2, previously associated with replication timing. Forkhead factors do not regulate TAD formation, but do promote longer-range genomic interactions and control interactions between origins near the centromere. Thus, our work defines spatial organization within the budding yeast nucleus, demonstrates the conserved role of genome architecture in regulating DNA replication, and identifies a molecular mechanism specifically regulating interactions between pericentric origins.

Comparative genomics of Eucalyptus and Corymbia reveals low rates of genome structural rearrangement.

PubMed

Butler, J B; Vaillancourt, R E; Potts, B M; Lee, D J; King, G J; Baten, A; Shepherd, M; Freeman, J S

2017-05-22

Previous studies suggest genome structure is largely conserved between Eucalyptus species. However, it is unknown if this conservation extends to more divergent eucalypt taxa. We performed comparative genomics between the eucalypt genera Eucalyptus and Corymbia. Our results will facilitate transfer of genomic information between these important taxa and provide further insights into the rate of structural change in tree genomes. We constructed three high density linkage maps for two Corymbia species (Corymbia citriodora subsp. variegata and Corymbia torelliana) which were used to compare genome structure between both species and Eucalyptus grandis. Genome structure was highly conserved between the Corymbia species. However, the comparison of Corymbia and E. grandis suggests large (from 1-13 MB) intra-chromosomal rearrangements have occurred on seven of the 11 chromosomes. Most rearrangements were supported through comparisons of the three independent Corymbia maps to the E. grandis genome sequence, and to other independently constructed Eucalyptus linkage maps. These are the first large scale chromosomal rearrangements discovered between eucalypts. Nonetheless, in the general context of plants, the genomic structure of the two genera was remarkably conserved; adding to a growing body of evidence that conservation of genome structure is common amongst woody angiosperms.

Genomic correlates of recombination rate and its variability across eight recombination maps in the western honey bee (Apis mellifera L.).

PubMed

Ross, Caitlin R; DeFelice, Dominick S; Hunt, Greg J; Ihle, Kate E; Amdam, Gro V; Rueppell, Olav

2015-02-21

Meiotic recombination has traditionally been explained based on the structural requirement to stabilize homologous chromosome pairs to ensure their proper meiotic segregation. Competing hypotheses seek to explain the emerging findings of significant heterogeneity in recombination rates within and between genomes, but intraspecific comparisons of genome-wide recombination patterns are rare. The honey bee (Apis mellifera) exhibits the highest rate of genomic recombination among multicellular animals with about five cross-over events per chromatid. Here, we present a comparative analysis of recombination rates across eight genetic linkage maps of the honey bee genome to investigate which genomic sequence features are correlated with recombination rate and with its variation across the eight data sets, ranging in average marker spacing ranging from 1 Mbp to 120 kbp. Overall, we found that GC content explained best the variation in local recombination rate along chromosomes at the analyzed 100 kbp scale. In contrast, variation among the different maps was correlated to the abundance of microsatellites and several specific tri- and tetra-nucleotides. The combined evidence from eight medium-scale recombination maps of the honey bee genome suggests that recombination rate variation in this highly recombining genome might be due to the DNA configuration instead of distinct sequence motifs. However, more fine-scale analyses are needed. The empirical basis of eight differing genetic maps allowed for robust conclusions about the correlates of the local recombination rates and enabled the study of the relation between DNA features and variability in local recombination rates, which is particularly relevant in the honey bee genome with its exceptionally high recombination rate.

Fungal Genomics Program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grigoriev, Igor

The JGI Fungal Genomics Program aims to scale up sequencing and analysis of fungal genomes to explore the diversity of fungi important for energy and the environment, and to promote functional studies on a system level. Combining new sequencing technologies and comparative genomics tools, JGI is now leading the world in fungal genome sequencing and analysis. Over 120 sequenced fungal genomes with analytical tools are available via MycoCosm (www.jgi.doe.gov/fungi), a web-portal for fungal biologists. Our model of interacting with user communities, unique among other sequencing centers, helps organize these communities, improves genome annotation and analysis work, and facilitates new larger-scalemore » genomic projects. This resulted in 20 high-profile papers published in 2011 alone and contributing to the Genomics Encyclopedia of Fungi, which targets fungi related to plant health (symbionts, pathogens, and biocontrol agents) and biorefinery processes (cellulose degradation, sugar fermentation, industrial hosts). Our next grand challenges include larger scale exploration of fungal diversity (1000 fungal genomes), developing molecular tools for DOE-relevant model organisms, and analysis of complex systems and metagenomes.« less

Home - The Cancer Genome Atlas - Cancer Genome - TCGA

Cancer.gov

The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to accelerate our understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing.

A proteome view of structural, functional, and taxonomic characteristics of major protein domain clusters.

PubMed

Sun, Chia-Tsen; Chiang, Austin W T; Hwang, Ming-Jing

2017-10-27

Proteome-scale bioinformatics research is increasingly conducted as the number of completely sequenced genomes increases, but analysis of protein domains (PDs) usually relies on similarity in their amino acid sequences and/or three-dimensional structures. Here, we present results from a bi-clustering analysis on presence/absence data for 6,580 unique PDs in 2,134 species with a sequenced genome, thus covering a complete set of proteins, for the three superkingdoms of life, Bacteria, Archaea, and Eukarya. Our analysis revealed eight distinctive PD clusters, which, following an analysis of enrichment of Gene Ontology functions and CATH classification of protein structures, were shown to exhibit structural and functional properties that are taxa-characteristic. For examples, the largest cluster is ubiquitous in all three superkingdoms, constituting a set of 1,472 persistent domains created early in evolution and retained in living organisms and characterized by basic cellular functions and ancient structural architectures, while an Archaea and Eukarya bi-superkingdom cluster suggests its PDs may have existed in the ancestor of the two superkingdoms, and others are single superkingdom- or taxa (e.g. Fungi)-specific. These results contribute to increase our appreciation of PD diversity and our knowledge of how PDs are used in species, yielding implications on species evolution.

A genome-wide 20 K citrus microarray for gene expression analysis

PubMed Central

Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

2008-01-01

Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database [1] was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. Conclusion This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global studies in citrus by using it to catalogue genes expressed in citrus globular embryos. PMID:18598343

Structural Analysis of Biodiversity

PubMed Central

Sirovich, Lawrence; Stoeckle, Mark Y.; Zhang, Yu

2010-01-01

Large, recently-available genomic databases cover a wide range of life forms, suggesting opportunity for insights into genetic structure of biodiversity. In this study we refine our recently-described technique using indicator vectors to analyze and visualize nucleotide sequences. The indicator vector approach generates correlation matrices, dubbed Klee diagrams, which represent a novel way of assembling and viewing large genomic datasets. To explore its potential utility, here we apply the improved algorithm to a collection of almost 17000 DNA barcode sequences covering 12 widely-separated animal taxa, demonstrating that indicator vectors for classification gave correct assignment in all 11000 test cases. Indicator vector analysis revealed discontinuities corresponding to species- and higher-level taxonomic divisions, suggesting an efficient approach to classification of organisms from poorly-studied groups. As compared to standard distance metrics, indicator vectors preserve diagnostic character probabilities, enable automated classification of test sequences, and generate high-information density single-page displays. These results support application of indicator vectors for comparative analysis of large nucleotide data sets and raise prospect of gaining insight into broad-scale patterns in the genetic structure of biodiversity. PMID:20195371

Navigating the Interface Between Landscape Genetics and Landscape Genomics.

PubMed

Storfer, Andrew; Patton, Austin; Fraik, Alexandra K

2018-01-01

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' phylogeographic history. To this end, we summarize recent simulation studies that test the power and accuracy of genome scan methods under a variety of demographic scenarios and sampling designs. We conclude with a discussion of additional considerations for future method development, and a summary of methods that show promise for landscape genomics studies but are not yet widely used.

Navigating the Interface Between Landscape Genetics and Landscape Genomics

PubMed Central

Storfer, Andrew; Patton, Austin; Fraik, Alexandra K.

2018-01-01

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' phylogeographic history. To this end, we summarize recent simulation studies that test the power and accuracy of genome scan methods under a variety of demographic scenarios and sampling designs. We conclude with a discussion of additional considerations for future method development, and a summary of methods that show promise for landscape genomics studies but are not yet widely used. PMID:29593776

Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics.

PubMed

Kelly, Benjamin J; Fitch, James R; Hu, Yangqiu; Corsmeier, Donald J; Zhong, Huachun; Wetzel, Amy N; Nordquist, Russell D; Newsom, David L; White, Peter

2015-01-20

While advances in genome sequencing technology make population-scale genomics a possibility, current approaches for analysis of these data rely upon parallelization strategies that have limited scalability, complex implementation and lack reproducibility. Churchill, a balanced regional parallelization strategy, overcomes these challenges, fully automating the multiple steps required to go from raw sequencing reads to variant discovery. Through implementation of novel deterministic parallelization techniques, Churchill allows computationally efficient analysis of a high-depth whole genome sample in less than two hours. The method is highly scalable, enabling full analysis of the 1000 Genomes raw sequence dataset in a week using cloud resources. http://churchill.nchri.org/.

How life changes itself: the Read-Write (RW) genome.

PubMed

Shapiro, James A

2013-09-01

The genome has traditionally been treated as a Read-Only Memory (ROM) subject to change by copying errors and accidents. In this review, I propose that we need to change that perspective and understand the genome as an intricately formatted Read-Write (RW) data storage system constantly subject to cellular modifications and inscriptions. Cells operate under changing conditions and are continually modifying themselves by genome inscriptions. These inscriptions occur over three distinct time-scales (cell reproduction, multicellular development and evolutionary change) and involve a variety of different processes at each time scale (forming nucleoprotein complexes, epigenetic formatting and changes in DNA sequence structure). Research dating back to the 1930s has shown that genetic change is the result of cell-mediated processes, not simply accidents or damage to the DNA. This cell-active view of genome change applies to all scales of DNA sequence variation, from point mutations to large-scale genome rearrangements and whole genome duplications (WGDs). This conceptual change to active cell inscriptions controlling RW genome functions has profound implications for all areas of the life sciences. © 2013 Elsevier B.V. All rights reserved.

The detailed 3D multi-loop aggregate/rosette chromatin architecture and functional dynamic organization of the human and mouse genomes.

PubMed

Knoch, Tobias A; Wachsmuth, Malte; Kepper, Nick; Lesnussa, Michael; Abuseiris, Anis; Ali Imam, A M; Kolovos, Petros; Zuin, Jessica; Kockx, Christel E M; Brouwer, Rutger W W; van de Werken, Harmen J G; van IJcken, Wilfred F J; Wendt, Kerstin S; Grosveld, Frank G

2016-01-01

The dynamic three-dimensional chromatin architecture of genomes and its co-evolutionary connection to its function-the storage, expression, and replication of genetic information-is still one of the central issues in biology. Here, we describe the much debated 3D architecture of the human and mouse genomes from the nucleosomal to the megabase pair level by a novel approach combining selective high-throughput high-resolution chromosomal interaction capture ( T2C ), polymer simulations, and scaling analysis of the 3D architecture and the DNA sequence. The genome is compacted into a chromatin quasi-fibre with ~5 ± 1 nucleosomes/11 nm, folded into stable ~30-100 kbp loops forming stable loop aggregates/rosettes connected by similar sized linkers. Minor but significant variations in the architecture are seen between cell types and functional states. The architecture and the DNA sequence show very similar fine-structured multi-scaling behaviour confirming their co-evolution and the above. This architecture, its dynamics, and accessibility, balance stability and flexibility ensuring genome integrity and variation enabling gene expression/regulation by self-organization of (in)active units already in proximity. Our results agree with the heuristics of the field and allow "architectural sequencing" at a genome mechanics level to understand the inseparable systems genomic properties.

Modeling and Simulation of Optimal Resource Management during the Diurnal Cycle in Emiliania huxleyi by Genome-Scale Reconstruction and an Extended Flux Balance Analysis Approach.

PubMed

Knies, David; Wittmüß, Philipp; Appel, Sebastian; Sawodny, Oliver; Ederer, Michael; Feuer, Ronny

2015-10-28

The coccolithophorid unicellular alga Emiliania huxleyi is known to form large blooms, which have a strong effect on the marine carbon cycle. As a photosynthetic organism, it is subjected to a circadian rhythm due to the changing light conditions throughout the day. For a better understanding of the metabolic processes under these periodically-changing environmental conditions, a genome-scale model based on a genome reconstruction of the E. huxleyi strain CCMP 1516 was created. It comprises 410 reactions and 363 metabolites. Biomass composition is variable based on the differentiation into functional biomass components and storage metabolites. The model is analyzed with a flux balance analysis approach called diurnal flux balance analysis (diuFBA) that was designed for organisms with a circadian rhythm. It allows storage metabolites to accumulate or be consumed over the diurnal cycle, while keeping the structure of a classical FBA problem. A feature of this approach is that the production and consumption of storage metabolites is not defined externally via the biomass composition, but the result of optimal resource management adapted to the diurnally-changing environmental conditions. The model in combination with this approach is able to simulate the variable biomass composition during the diurnal cycle in proximity to literature data.

Widespread signatures of local mRNA folding structure selection in four Dengue virus serotypes

PubMed Central

2015-01-01

Background It is known that mRNA folding can affect and regulate various gene expression steps both in living organisms and in viruses. Previous studies have recognized functional RNA structures in the genome of the Dengue virus. However, these studies usually focused either on the viral untranslated regions or on very specific and limited regions at the beginning of the coding sequences, in a limited number of strains, and without considering evolutionary selection. Results Here we performed the first large scale comprehensive genomics analysis of selection for local mRNA folding strength in the Dengue virus coding sequences, based on a total of 1,670 genomes and 4 serotypes. Our analysis identified clusters of positions along the coding regions that may undergo a conserved evolutionary selection for strong or weak local folding maintained across different viral variants. Specifically, 53-66 clusters for strong folding and 49-73 clusters for weak folding (depending on serotype) aggregated of positions with a significant conservation of folding energy signals (related to partially overlapping local genomic regions) were recognized. In addition, up to 7% of these positions were found to be conserved in more than 90% of the viral genomes. Although some of the identified positions undergo frequent synonymous / non-synonymous substitutions, the selection for folding strength therein is preserved, and thus cannot be trivially explained based on sequence conservation alone. Conclusions The fact that many of the positions with significant folding related signals are conserved among different Dengue variants suggests that a better understanding of the mRNA structures in the corresponding regions may promote the development of prospective anti- Dengue vaccination strategies. The comparative genomics approach described here can be employed in the future for detecting functional regions in other pathogens with very high mutations rates. PMID:26449467

Multiscale modeling of three-dimensional genome

NASA Astrophysics Data System (ADS)

Zhang, Bin; Wolynes, Peter

The genome, the blueprint of life, contains nearly all the information needed to build and maintain an entire organism. A comprehensive understanding of the genome is of paramount interest to human health and will advance progress in many areas, including life sciences, medicine, and biotechnology. The overarching goal of my research is to understand the structure-dynamics-function relationships of the human genome. In this talk, I will be presenting our efforts in moving towards that goal, with a particular emphasis on studying the three-dimensional organization, the structure of the genome with multi-scale approaches. Specifically, I will discuss the reconstruction of genome structures at both interphase and metaphase by making use of data from chromosome conformation capture experiments. Computationally modeling of chromatin fiber at atomistic level from first principles will also be presented as our effort for studying the genome structure from bottom up.

Genome-scale approaches to the epigenetics of common human disease

PubMed Central

2011-01-01

Traditionally, the pathology of human disease has been focused on microscopic examination of affected tissues, chemical and biochemical analysis of biopsy samples, other available samples of convenience, such as blood, and noninvasive or invasive imaging of varying complexity, in order to classify disease and illuminate its mechanistic basis. The molecular age has complemented this armamentarium with gene expression arrays and selective analysis of individual genes. However, we are entering a new era of epigenomic profiling, i.e., genome-scale analysis of cell-heritable nonsequence genetic change, such as DNA methylation. The epigenome offers access to stable measurements of cellular state and to biobanked material for large-scale epidemiological studies. Some of these genome-scale technologies are beginning to be applied to create the new field of epigenetic epidemiology. PMID:19844740

A low-latency, big database system and browser for storage, querying and visualization of 3D genomic data.

PubMed

Butyaev, Alexander; Mavlyutov, Ruslan; Blanchette, Mathieu; Cudré-Mauroux, Philippe; Waldispühl, Jérôme

2015-09-18

Recent releases of genome three-dimensional (3D) structures have the potential to transform our understanding of genomes. Nonetheless, the storage technology and visualization tools need to evolve to offer to the scientific community fast and convenient access to these data. We introduce simultaneously a database system to store and query 3D genomic data (3DBG), and a 3D genome browser to visualize and explore 3D genome structures (3DGB). We benchmark 3DBG against state-of-the-art systems and demonstrate that it is faster than previous solutions, and importantly gracefully scales with the size of data. We also illustrate the usefulness of our 3D genome Web browser to explore human genome structures. The 3D genome browser is available at http://3dgb.cs.mcgill.ca/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

A low-latency, big database system and browser for storage, querying and visualization of 3D genomic data

PubMed Central

Butyaev, Alexander; Mavlyutov, Ruslan; Blanchette, Mathieu; Cudré-Mauroux, Philippe; Waldispühl, Jérôme

2015-01-01

Recent releases of genome three-dimensional (3D) structures have the potential to transform our understanding of genomes. Nonetheless, the storage technology and visualization tools need to evolve to offer to the scientific community fast and convenient access to these data. We introduce simultaneously a database system to store and query 3D genomic data (3DBG), and a 3D genome browser to visualize and explore 3D genome structures (3DGB). We benchmark 3DBG against state-of-the-art systems and demonstrate that it is faster than previous solutions, and importantly gracefully scales with the size of data. We also illustrate the usefulness of our 3D genome Web browser to explore human genome structures. The 3D genome browser is available at http://3dgb.cs.mcgill.ca/. PMID:25990738

CoryneRegNet: an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks.

PubMed

Baumbach, Jan; Brinkrolf, Karina; Czaja, Lisa F; Rahmann, Sven; Tauch, Andreas

2006-02-14

The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation.

Inferring transposons activity chronology by TRANScendence - TEs database and de-novo mining tool.

PubMed

Startek, Michał Piotr; Nogły, Jakub; Gromadka, Agnieszka; Grzebelus, Dariusz; Gambin, Anna

2017-10-16

The constant progress in sequencing technology leads to ever increasing amounts of genomic data. In the light of current evidence transposable elements (TEs for short) are becoming useful tools for learning about the evolution of host genome. Therefore the software for genome-wide detection and analysis of TEs is of great interest. Here we describe the computational tool for mining, classifying and storing TEs from newly sequenced genomes. This is an online, web-based, user-friendly service, enabling users to upload their own genomic data, and perform de-novo searches for TEs. The detected TEs are automatically analyzed, compared to reference databases, annotated, clustered into families, and stored in TEs repository. Also, the genome-wide nesting structure of found elements are detected and analyzed by new method for inferring evolutionary history of TEs. We illustrate the functionality of our tool by performing a full-scale analyses of TE landscape in Medicago truncatula genome. TRANScendence is an effective tool for the de-novo annotation and classification of transposable elements in newly-acquired genomes. Its streamlined interface makes it well-suited for evolutionary studies.

Energy Landscapes of Folding Chromosomes

NASA Astrophysics Data System (ADS)

Zhang, Bin

The genome, the blueprint of life, contains nearly all the information needed to build and maintain an entire organism. A comprehensive understanding of the genome is of paramount interest to human health and will advance progress in many areas, including life sciences, medicine, and biotechnology. The overarching goal of my research is to understand the structure-dynamics-function relationships of the human genome. In this talk, I will be presenting our efforts in moving towards that goal, with a particular emphasis on studying the three-dimensional organization, the structure of the genome with multi-scale approaches. Specifically, I will discuss the reconstruction of genome structures at both interphase and metaphase by making use of data from chromosome conformation capture experiments. Computationally modeling of chromatin fiber at atomistic level from first principles will also be presented as our effort for studying the genome structure from bottom up.

Ensembl Genomes: an integrative resource for genome-scale data from non-vertebrate species.

PubMed

Kersey, Paul J; Staines, Daniel M; Lawson, Daniel; Kulesha, Eugene; Derwent, Paul; Humphrey, Jay C; Hughes, Daniel S T; Keenan, Stephan; Kerhornou, Arnaud; Koscielny, Gautier; Langridge, Nicholas; McDowall, Mark D; Megy, Karine; Maheswari, Uma; Nuhn, Michael; Paulini, Michael; Pedro, Helder; Toneva, Iliana; Wilson, Derek; Yates, Andrew; Birney, Ewan

2012-01-01

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrative resource for genome-scale data from non-vertebrate species. The project exploits and extends technology (for genome annotation, analysis and dissemination) developed in the context of the (vertebrate-focused) Ensembl project and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. Since its launch in 2009, Ensembl Genomes has undergone rapid expansion, with the goal of providing coverage of all major experimental organisms, and additionally including taxonomic reference points to provide the evolutionary context in which genes can be understood. Against the backdrop of a continuing increase in genome sequencing activities in all parts of the tree of life, we seek to work, wherever possible, with the communities actively generating and using data, and are participants in a growing range of collaborations involved in the annotation and analysis of genomes.

SGP-1: Prediction and Validation of Homologous Genes Based on Sequence Alignments

PubMed Central

Wiehe, Thomas; Gebauer-Jung, Steffi; Mitchell-Olds, Thomas; Guigó, Roderic

2001-01-01

Conventional methods of gene prediction rely on the recognition of DNA-sequence signals, the coding potential or the comparison of a genomic sequence with a cDNA, EST, or protein database. Reasons for limited accuracy in many circumstances are species-specific training and the incompleteness of reference databases. Lately, comparative genome analysis has attracted increasing attention. Several analysis tools that are based on human/mouse comparisons are already available. Here, we present a program for the prediction of protein-coding genes, termed SGP-1 (Syntenic Gene Prediction), which is based on the similarity of homologous genomic sequences. In contrast to most existing tools, the accuracy of SGP-1 depends little on species-specific properties such as codon usage or the nucleotide distribution. SGP-1 may therefore be applied to nonstandard model organisms in vertebrates as well as in plants, without the need for extensive parameter training. In addition to predicting genes in large-scale genomic sequences, the program may be useful to validate gene structure annotations from databases. To this end, SGP-1 output also contains comparisons between predicted and annotated gene structures in HTML format. The program can be accessed via a Web server at http://soft.ice.mpg.de/sgp-1. The source code, written in ANSI C, is available on request from the authors. PMID:11544202

Genome-wide SNP discovery and population structure analysis in pepper (Capsicum annuum) using genotyping by sequencing.

PubMed

Taranto, F; D'Agostino, N; Greco, B; Cardi, T; Tripodi, P

2016-11-21

Knowledge on population structure and genetic diversity in vegetable crops is essential for association mapping studies and genomic selection. Genotyping by sequencing (GBS) represents an innovative method for large scale SNP detection and genotyping of genetic resources. Herein we used the GBS approach for the genome-wide identification of SNPs in a collection of Capsicum spp. accessions and for the assessment of the level of genetic diversity in a subset of 222 cultivated pepper (Capsicum annum) genotypes. GBS analysis generated a total of 7,568,894 master tags, of which 43.4% uniquely aligned to the reference genome CM334. A total of 108,591 SNP markers were identified, of which 105,184 were in C. annuum accessions. In order to explore the genetic diversity of C. annuum and to select a minimal core set representing most of the total genetic variation with minimum redundancy, a subset of 222 C. annuum accessions were analysed using 32,950 high quality SNPs. Based on Bayesian and Hierarchical clustering it was possible to divide the collection into three clusters. Cluster I had the majority of varieties and landraces mainly from Southern and Northern Italy, and from Eastern Europe, whereas clusters II and III comprised accessions of different geographical origins. Considering the genome-wide genetic variation among the accessions included in cluster I, a second round of Bayesian (K = 3) and Hierarchical (K = 2) clustering was performed. These analysis showed that genotypes were grouped not only based on geographical origin, but also on fruit-related features. GBS data has proven useful to assess the genetic diversity in a collection of C. annuum accessions. The high number of SNP markers, uniformly distributed on the 12 chromosomes, allowed the accessions to be distinguished according to geographical origin and fruit-related features. SNP markers and information on population structure developed in this study will undoubtedly support genome-wide association mapping studies and marker-assisted selection programs.

The Physcomitrella patens chromosome-scale assembly reveals moss genome structure and evolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lang, Daniel; Ullrich, Kristian K.; Murat, Florent

Here, the draft genome of the moss model, Physcomitrella patens, comprised approximately 2000 unordered scaffolds. In order to enable analyses of genome structure and evolution we generated a chromosome–scale genome assembly using genetic linkage as well as (end) sequencing of long DNA fragments. We find that 57% of the genome comprises transposable elements (TEs), some of which may be actively transposing during the life cycle. Unlike in flowering plant genomes, gene– and TE–rich regions show an overall even distribution along the chromosomes. However, the chromosomes are mono–centric with peaks of a class of Copia elements potentially coinciding with centromeres. Genemore » body methylation is evident in 5.7% of the protein–coding genes, typically coinciding with low GC and low expression. Some giant virus insertions are transcriptionally active and might protect gametes from viral infection via siRNA mediated silencing. Structure–based detection methods show that the genome evolved via two rounds of whole genome duplications (WGDs), apparently common in mosses but not in liverworts and hornworts. Several hundred genes are present in colinear regions conserved since the last common ancestor of plants. These syntenic regions are enriched for functions related to plant–specific cell growth and tissue organization. The P. patens genome lacks the TE–rich pericentromeric and gene–rich distal regions typical for most flowering plant genomes. More non–seed plant genomes are needed to unravel how plant genomes evolve, and to understand whether the P. patens genome structure is typical for mosses or bryophytes.« less

The Physcomitrella patens chromosome-scale assembly reveals moss genome structure and evolution

DOE PAGES

Lang, Daniel; Ullrich, Kristian K.; Murat, Florent; ...

2017-12-13

Here, the draft genome of the moss model, Physcomitrella patens, comprised approximately 2000 unordered scaffolds. In order to enable analyses of genome structure and evolution we generated a chromosome–scale genome assembly using genetic linkage as well as (end) sequencing of long DNA fragments. We find that 57% of the genome comprises transposable elements (TEs), some of which may be actively transposing during the life cycle. Unlike in flowering plant genomes, gene– and TE–rich regions show an overall even distribution along the chromosomes. However, the chromosomes are mono–centric with peaks of a class of Copia elements potentially coinciding with centromeres. Genemore » body methylation is evident in 5.7% of the protein–coding genes, typically coinciding with low GC and low expression. Some giant virus insertions are transcriptionally active and might protect gametes from viral infection via siRNA mediated silencing. Structure–based detection methods show that the genome evolved via two rounds of whole genome duplications (WGDs), apparently common in mosses but not in liverworts and hornworts. Several hundred genes are present in colinear regions conserved since the last common ancestor of plants. These syntenic regions are enriched for functions related to plant–specific cell growth and tissue organization. The P. patens genome lacks the TE–rich pericentromeric and gene–rich distal regions typical for most flowering plant genomes. More non–seed plant genomes are needed to unravel how plant genomes evolve, and to understand whether the P. patens genome structure is typical for mosses or bryophytes.« less

A review of genome-wide approaches to study the genetic basis for spermatogenic defects.

PubMed

Aston, Kenneth I; Conrad, Donald F

2013-01-01

Rapidly advancing tools for genetic analysis on a genome-wide scale have been instrumental in identifying the genetic bases for many complex diseases. About half of male infertility cases are of unknown etiology in spite of tremendous efforts to characterize the genetic basis for the disorder. Advancing our understanding of the genetic basis for male infertility will require the application of established and emerging genomic tools. This chapter introduces many of the tools available for genetic studies on a genome-wide scale along with principles of study design and data analysis.

Structural Genomics: Correlation Blocks, Population Structure, and Genome Architecture

PubMed Central

Hu, Xin-Sheng; Yeh, Francis C.; Wang, Zhiquan

2011-01-01

An integration of the pattern of genome-wide inter-site associations with evolutionary forces is important for gaining insights into the genomic evolution in natural or artificial populations. Here, we assess the inter-site correlation blocks and their distributions along chromosomes. A correlation block is broadly termed as the DNA segment within which strong correlations exist between genetic diversities at any two sites. We bring together the population genetic structure and the genomic diversity structure that have been independently built on different scales and synthesize the existing theories and methods for characterizing genomic structure at the population level. We discuss how population structure could shape correlation blocks and their patterns within and between populations. Effects of evolutionary forces (selection, migration, genetic drift, and mutation) on the pattern of genome-wide correlation blocks are discussed. In eukaryote organisms, we briefly discuss the associations between the pattern of correlation blocks and genome assembly features in eukaryote organisms, including the impacts of multigene family, the perturbation of transposable elements, and the repetitive nongenic sequences and GC-rich isochores. Our reviews suggest that the observable pattern of correlation blocks can refine our understanding of the ecological and evolutionary processes underlying the genomic evolution at the population level. PMID:21886455

The SGC beyond structural genomics: redefining the role of 3D structures by coupling genomic stratification with fragment-based discovery.

PubMed

Bradley, Anthony R; Echalier, Aude; Fairhead, Michael; Strain-Damerell, Claire; Brennan, Paul; Bullock, Alex N; Burgess-Brown, Nicola A; Carpenter, Elisabeth P; Gileadi, Opher; Marsden, Brian D; Lee, Wen Hwa; Yue, Wyatt; Bountra, Chas; von Delft, Frank

2017-11-08

The ongoing explosion in genomics data has long since outpaced the capacity of conventional biochemical methodology to verify the large number of hypotheses that emerge from the analysis of such data. In contrast, it is still a gold-standard for early phenotypic validation towards small-molecule drug discovery to use probe molecules (or tool compounds), notwithstanding the difficulty and cost of generating them. Rational structure-based approaches to ligand discovery have long promised the efficiencies needed to close this divergence; in practice, however, this promise remains largely unfulfilled, for a host of well-rehearsed reasons and despite the huge technical advances spearheaded by the structural genomics initiatives of the noughties. Therefore the current, fourth funding phase of the Structural Genomics Consortium (SGC), building on its extensive experience in structural biology of novel targets and design of protein inhibitors, seeks to redefine what it means to do structural biology for drug discovery. We developed the concept of a Target Enabling Package (TEP) that provides, through reagents, assays and data, the missing link between genetic disease linkage and the development of usefully potent compounds. There are multiple prongs to the ambition: rigorously assessing targets' genetic disease linkages through crowdsourcing to a network of collaborating experts; establishing a systematic approach to generate the protocols and data that comprise each target's TEP; developing new, X-ray-based fragment technologies for generating high quality chemical matter quickly and cheaply; and exploiting a stringently open access model to build multidisciplinary partnerships throughout academia and industry. By learning how to scale these approaches, the SGC aims to make structures finally serve genomics, as originally intended, and demonstrate how 3D structures systematically allow new modes of druggability to be discovered for whole classes of targets. © 2017 The Author(s).

Structured populations of Sulfolobus acidocaldarius with susceptibility to mobile genetic elements

USGS Publications Warehouse

Anderson, Rika E.; Kouris, Angela; Seward, Christopher H.; Campbell, Kate M.; Whitaker, Rachel J.

2017-01-01

The impact of a structured environment on genome evolution can be determined through comparative population genomics of species that live in the same habitat. Recent work comparing three genome sequences of Sulfolobus acidocaldarius suggested that highly structured, extreme, hot spring environments do not limit dispersal of this thermoacidophile, in contrast to other co-occurring Sulfolobus species. Instead, a high level of conservation among these three S. acidocaldarius genomes was hypothesized to result from rapid, global-scale dispersal promoted by low susceptibility to viruses that sets S. acidocaldarius apart from its sister Sulfolobus species. To test this hypothesis, we conducted a comparative analysis of 47 genomes of S. acidocaldarius from spatial and temporal sampling of two hot springs in Yellowstone National Park. While we confirm the low diversity in the core genome, we observe differentiation among S. acidocaldarius populations, likely resulting from low migration among hot spring “islands” in Yellowstone National Park. Patterns of genomic variation indicate that differing geological contexts result in the elimination or preservation of diversity among differentiated populations. We observe multiple deletions associated with a large genomic island rich in glycosyltransferases, differential integrations of the Sulfolobus turreted icosahedral virus, as well as two different plasmid elements. These data demonstrate that neither rapid dispersal nor lack of mobile genetic elements result in low diversity in the S. acidocaldariusgenomes. We suggest instead that significant differences in the recent evolutionary history, or the intrinsic evolutionary rates, of sister Sulfolobusspecies result in the relatively low diversity of the S. acidocaldarius genome.

A New Perspective on Polyploid Fragaria (Strawberry) Genome Composition Based on Large-Scale, Multi-Locus Phylogenetic Analysis

PubMed Central

Yang, Yilong

2017-01-01

Abstract The subgenomic compositions of the octoploid (2n = 8× = 56) strawberry (Fragaria) species, including the economically important cultivated species Fragaria x ananassa, have been a topic of long-standing interest. Phylogenomic approaches utilizing next-generation sequencing technologies offer a new window into species relationships and the subgenomic compositions of polyploids. We have conducted a large-scale phylogenetic analysis of Fragaria (strawberry) species using the Fluidigm Access Array system and 454 sequencing platform. About 24 single-copy or low-copy nuclear genes distributed across the genome were amplified and sequenced from 96 genomic DNA samples representing 16 Fragaria species from diploid (2×) to decaploid (10×), including the most extensive sampling of octoploid taxa yet reported. Individual gene trees were constructed by different tree-building methods. Mosaic genomic structures of diploid Fragaria species consisting of sequences at different phylogenetic positions were observed. Our findings support the presence in octoploid species of genetic signatures from at least five diploid ancestors (F. vesca, F. iinumae, F. bucharica, F. viridis, and at least one additional allele contributor of unknown identity), and questions the extent to which distinct subgenomes are preserved over evolutionary time in the allopolyploid Fragaria species. In addition, our data support divergence between the two wild octoploid species, F. virginiana and F. chiloensis. PMID:29045639

Atlas2 Cloud: a framework for personal genome analysis in the cloud

PubMed Central

2012-01-01

Background Until recently, sequencing has primarily been carried out in large genome centers which have invested heavily in developing the computational infrastructure that enables genomic sequence analysis. The recent advancements in next generation sequencing (NGS) have led to a wide dissemination of sequencing technologies and data, to highly diverse research groups. It is expected that clinical sequencing will become part of diagnostic routines shortly. However, limited accessibility to computational infrastructure and high quality bioinformatic tools, and the demand for personnel skilled in data analysis and interpretation remains a serious bottleneck. To this end, the cloud computing and Software-as-a-Service (SaaS) technologies can help address these issues. Results We successfully enabled the Atlas2 Cloud pipeline for personal genome analysis on two different cloud service platforms: a community cloud via the Genboree Workbench, and a commercial cloud via the Amazon Web Services using Software-as-a-Service model. We report a case study of personal genome analysis using our Atlas2 Genboree pipeline. We also outline a detailed cost structure for running Atlas2 Amazon on whole exome capture data, providing cost projections in terms of storage, compute and I/O when running Atlas2 Amazon on a large data set. Conclusions We find that providing a web interface and an optimized pipeline clearly facilitates usage of cloud computing for personal genome analysis, but for it to be routinely used for large scale projects there needs to be a paradigm shift in the way we develop tools, in standard operating procedures, and in funding mechanisms. PMID:23134663

Atlas2 Cloud: a framework for personal genome analysis in the cloud.

PubMed

Evani, Uday S; Challis, Danny; Yu, Jin; Jackson, Andrew R; Paithankar, Sameer; Bainbridge, Matthew N; Jakkamsetti, Adinarayana; Pham, Peter; Coarfa, Cristian; Milosavljevic, Aleksandar; Yu, Fuli

2012-01-01

Until recently, sequencing has primarily been carried out in large genome centers which have invested heavily in developing the computational infrastructure that enables genomic sequence analysis. The recent advancements in next generation sequencing (NGS) have led to a wide dissemination of sequencing technologies and data, to highly diverse research groups. It is expected that clinical sequencing will become part of diagnostic routines shortly. However, limited accessibility to computational infrastructure and high quality bioinformatic tools, and the demand for personnel skilled in data analysis and interpretation remains a serious bottleneck. To this end, the cloud computing and Software-as-a-Service (SaaS) technologies can help address these issues. We successfully enabled the Atlas2 Cloud pipeline for personal genome analysis on two different cloud service platforms: a community cloud via the Genboree Workbench, and a commercial cloud via the Amazon Web Services using Software-as-a-Service model. We report a case study of personal genome analysis using our Atlas2 Genboree pipeline. We also outline a detailed cost structure for running Atlas2 Amazon on whole exome capture data, providing cost projections in terms of storage, compute and I/O when running Atlas2 Amazon on a large data set. We find that providing a web interface and an optimized pipeline clearly facilitates usage of cloud computing for personal genome analysis, but for it to be routinely used for large scale projects there needs to be a paradigm shift in the way we develop tools, in standard operating procedures, and in funding mechanisms.

VariantSpark: population scale clustering of genotype information.

PubMed

O'Brien, Aidan R; Saunders, Neil F W; Guo, Yi; Buske, Fabian A; Scott, Rodney J; Bauer, Denis C

2015-12-10

Genomic information is increasingly used in medical practice giving rise to the need for efficient analysis methodology able to cope with thousands of individuals and millions of variants. The widely used Hadoop MapReduce architecture and associated machine learning library, Mahout, provide the means for tackling computationally challenging tasks. However, many genomic analyses do not fit the Map-Reduce paradigm. We therefore utilise the recently developed SPARK engine, along with its associated machine learning library, MLlib, which offers more flexibility in the parallelisation of population-scale bioinformatics tasks. The resulting tool, VARIANTSPARK provides an interface from MLlib to the standard variant format (VCF), offers seamless genome-wide sampling of variants and provides a pipeline for visualising results. To demonstrate the capabilities of VARIANTSPARK, we clustered more than 3,000 individuals with 80 Million variants each to determine the population structure in the dataset. VARIANTSPARK is 80 % faster than the SPARK-based genome clustering approach, ADAM, the comparable implementation using Hadoop/Mahout, as well as ADMIXTURE, a commonly used tool for determining individual ancestries. It is over 90 % faster than traditional implementations using R and Python. The benefits of speed, resource consumption and scalability enables VARIANTSPARK to open up the usage of advanced, efficient machine learning algorithms to genomic data.

Harnessing Whole Genome Sequencing in Medical Mycology.

PubMed

Cuomo, Christina A

2017-01-01

Comparative genome sequencing studies of human fungal pathogens enable identification of genes and variants associated with virulence and drug resistance. This review describes current approaches, resources, and advances in applying whole genome sequencing to study clinically important fungal pathogens. Genomes for some important fungal pathogens were only recently assembled, revealing gene family expansions in many species and extreme gene loss in one obligate species. The scale and scope of species sequenced is rapidly expanding, leveraging technological advances to assemble and annotate genomes with higher precision. By using iteratively improved reference assemblies or those generated de novo for new species, recent studies have compared the sequence of isolates representing populations or clinical cohorts. Whole genome approaches provide the resolution necessary for comparison of closely related isolates, for example, in the analysis of outbreaks or sampled across time within a single host. Genomic analysis of fungal pathogens has enabled both basic research and diagnostic studies. The increased scale of sequencing can be applied across populations, and new metagenomic methods allow direct analysis of complex samples.

Evolution of genome size and complexity in the rhabdoviridae.

PubMed

Walker, Peter J; Firth, Cadhla; Widen, Steven G; Blasdell, Kim R; Guzman, Hilda; Wood, Thomas G; Paradkar, Prasad N; Holmes, Edward C; Tesh, Robert B; Vasilakis, Nikos

2015-02-01

RNA viruses exhibit substantial structural, ecological and genomic diversity. However, genome size in RNA viruses is likely limited by a high mutation rate, resulting in the evolution of various mechanisms to increase complexity while minimising genome expansion. Here we conduct a large-scale analysis of the genome sequences of 99 animal rhabdoviruses, including 45 genomes which we determined de novo, to identify patterns of genome expansion and the evolution of genome complexity. All but seven of the rhabdoviruses clustered into 17 well-supported monophyletic groups, of which eight corresponded to established genera, seven were assigned as new genera, and two were taxonomically ambiguous. We show that the acquisition and loss of new genes appears to have been a central theme of rhabdovirus evolution, and has been associated with the appearance of alternative, overlapping and consecutive ORFs within the major structural protein genes, and the insertion and loss of additional ORFs in each gene junction in a clade-specific manner. Changes in the lengths of gene junctions accounted for as much as 48.5% of the variation in genome size from the smallest to the largest genome, and the frequency with which new ORFs were observed increased in the 3' to 5' direction along the genome. We also identify several new families of accessory genes encoded in these regions, and show that non-canonical expression strategies involving TURBS-like termination-reinitiation, ribosomal frame-shifts and leaky ribosomal scanning appear to be common. We conclude that rhabdoviruses have an unusual capacity for genomic plasticity that may be linked to their discontinuous transcription strategy from the negative-sense single-stranded RNA genome, and propose a model that accounts for the regular occurrence of genome expansion and contraction throughout the evolution of the Rhabdoviridae.

Evolution of Genome Size and Complexity in the Rhabdoviridae

PubMed Central

Walker, Peter J.; Firth, Cadhla; Widen, Steven G.; Blasdell, Kim R.; Guzman, Hilda; Wood, Thomas G.; Paradkar, Prasad N.; Holmes, Edward C.; Tesh, Robert B.; Vasilakis, Nikos

2015-01-01

RNA viruses exhibit substantial structural, ecological and genomic diversity. However, genome size in RNA viruses is likely limited by a high mutation rate, resulting in the evolution of various mechanisms to increase complexity while minimising genome expansion. Here we conduct a large-scale analysis of the genome sequences of 99 animal rhabdoviruses, including 45 genomes which we determined de novo, to identify patterns of genome expansion and the evolution of genome complexity. All but seven of the rhabdoviruses clustered into 17 well-supported monophyletic groups, of which eight corresponded to established genera, seven were assigned as new genera, and two were taxonomically ambiguous. We show that the acquisition and loss of new genes appears to have been a central theme of rhabdovirus evolution, and has been associated with the appearance of alternative, overlapping and consecutive ORFs within the major structural protein genes, and the insertion and loss of additional ORFs in each gene junction in a clade-specific manner. Changes in the lengths of gene junctions accounted for as much as 48.5% of the variation in genome size from the smallest to the largest genome, and the frequency with which new ORFs were observed increased in the 3’ to 5’ direction along the genome. We also identify several new families of accessory genes encoded in these regions, and show that non-canonical expression strategies involving TURBS-like termination-reinitiation, ribosomal frame-shifts and leaky ribosomal scanning appear to be common. We conclude that rhabdoviruses have an unusual capacity for genomic plasticity that may be linked to their discontinuous transcription strategy from the negative-sense single-stranded RNA genome, and propose a model that accounts for the regular occurrence of genome expansion and contraction throughout the evolution of the Rhabdoviridae. PMID:25679389

Phylogenomic Reconstruction of the Oomycete Phylogeny Derived from 37 Genomes

PubMed Central

McCarthy, Charley G. P.

2017-01-01

ABSTRACT The oomycetes are a class of microscopic, filamentous eukaryotes within the Stramenopiles-Alveolata-Rhizaria (SAR) supergroup which includes ecologically significant animal and plant pathogens, most infamously the causative agent of potato blight Phytophthora infestans. Single-gene and concatenated phylogenetic studies both of individual oomycete genera and of members of the larger class have resulted in conflicting conclusions concerning species phylogenies within the oomycetes, particularly for the large Phytophthora genus. Genome-scale phylogenetic studies have successfully resolved many eukaryotic relationships by using supertree methods, which combine large numbers of potentially disparate trees to determine evolutionary relationships that cannot be inferred from individual phylogenies alone. With a sufficient amount of genomic data now available, we have undertaken the first whole-genome phylogenetic analysis of the oomycetes using data from 37 oomycete species and 6 SAR species. In our analysis, we used established supertree methods to generate phylogenies from 8,355 homologous oomycete and SAR gene families and have complemented those analyses with both phylogenomic network and concatenated supermatrix analyses. Our results show that a genome-scale approach to oomycete phylogeny resolves oomycete classes and individual clades within the problematic Phytophthora genus. Support for the resolution of the inferred relationships between individual Phytophthora clades varies depending on the methodology used. Our analysis represents an important first step in large-scale phylogenomic analysis of the oomycetes. IMPORTANCE The oomycetes are a class of eukaryotes and include ecologically significant animal and plant pathogens. Single-gene and multigene phylogenetic studies of individual oomycete genera and of members of the larger classes have resulted in conflicting conclusions concerning interspecies relationships among these species, particularly for the Phytophthora genus. The onset of next-generation sequencing techniques now means that a wealth of oomycete genomic data is available. For the first time, we have used genome-scale phylogenetic methods to resolve oomycete phylogenetic relationships. We used supertree methods to generate single-gene and multigene species phylogenies. Overall, our supertree analyses utilized phylogenetic data from 8,355 oomycete gene families. We have also complemented our analyses with superalignment phylogenies derived from 131 single-copy ubiquitous gene families. Our results show that a genome-scale approach to oomycete phylogeny resolves oomycete classes and clades. Our analysis represents an important first step in large-scale phylogenomic analysis of the oomycetes. PMID:28435885

Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens. | Office of Cancer Genomics

Cancer.gov

Protein complexes are assemblies of subunits that have co-evolved to execute one or many coordinated functions in the cellular environment. Functional annotation of mammalian protein complexes is critical to understanding biological processes, as well as disease mechanisms. Here, we used genetic co-essentiality derived from genome-scale RNAi- and CRISPR-Cas9-based fitness screens performed across hundreds of human cancer cell lines to assign measures of functional similarity.

iAK692: A genome-scale metabolic model of Spirulina platensis C1

PubMed Central

2012-01-01

Background Spirulina (Arthrospira) platensis is a well-known filamentous cyanobacterium used in the production of many industrial products, including high value compounds, healthy food supplements, animal feeds, pharmaceuticals and cosmetics, for example. It has been increasingly studied around the world for scientific purposes, especially for its genome, biology, physiology, and also for the analysis of its small-scale metabolic network. However, the overall description of the metabolic and biotechnological capabilities of S. platensis requires the development of a whole cellular metabolism model. Recently, the S. platensis C1 (Arthrospira sp. PCC9438) genome sequence has become available, allowing systems-level studies of this commercial cyanobacterium. Results In this work, we present the genome-scale metabolic network analysis of S. platensis C1, iAK692, its topological properties, and its metabolic capabilities and functions. The network was reconstructed from the S. platensis C1 annotated genomic sequence using Pathway Tools software to generate a preliminary network. Then, manual curation was performed based on a collective knowledge base and a combination of genomic, biochemical, and physiological information. The genome-scale metabolic model consists of 692 genes, 837 metabolites, and 875 reactions. We validated iAK692 by conducting fermentation experiments and simulating the model under autotrophic, heterotrophic, and mixotrophic growth conditions using COBRA toolbox. The model predictions under these growth conditions were consistent with the experimental results. The iAK692 model was further used to predict the unique active reactions and essential genes for each growth condition. Additionally, the metabolic states of iAK692 during autotrophic and mixotrophic growths were described by phenotypic phase plane (PhPP) analysis. Conclusions This study proposes the first genome-scale model of S. platensis C1, iAK692, which is a predictive metabolic platform for a global understanding of physiological behaviors and metabolic engineering. This platform could accelerate the integrative analysis of various “-omics” data, leading to strain improvement towards a diverse range of desired industrial products from Spirulina. PMID:22703714

iAK692: a genome-scale metabolic model of Spirulina platensis C1.

PubMed

Klanchui, Amornpan; Khannapho, Chiraphan; Phodee, Atchara; Cheevadhanarak, Supapon; Meechai, Asawin

2012-06-15

Spirulina (Arthrospira) platensis is a well-known filamentous cyanobacterium used in the production of many industrial products, including high value compounds, healthy food supplements, animal feeds, pharmaceuticals and cosmetics, for example. It has been increasingly studied around the world for scientific purposes, especially for its genome, biology, physiology, and also for the analysis of its small-scale metabolic network. However, the overall description of the metabolic and biotechnological capabilities of S. platensis requires the development of a whole cellular metabolism model. Recently, the S. platensis C1 (Arthrospira sp. PCC9438) genome sequence has become available, allowing systems-level studies of this commercial cyanobacterium. In this work, we present the genome-scale metabolic network analysis of S. platensis C1, iAK692, its topological properties, and its metabolic capabilities and functions. The network was reconstructed from the S. platensis C1 annotated genomic sequence using Pathway Tools software to generate a preliminary network. Then, manual curation was performed based on a collective knowledge base and a combination of genomic, biochemical, and physiological information. The genome-scale metabolic model consists of 692 genes, 837 metabolites, and 875 reactions. We validated iAK692 by conducting fermentation experiments and simulating the model under autotrophic, heterotrophic, and mixotrophic growth conditions using COBRA toolbox. The model predictions under these growth conditions were consistent with the experimental results. The iAK692 model was further used to predict the unique active reactions and essential genes for each growth condition. Additionally, the metabolic states of iAK692 during autotrophic and mixotrophic growths were described by phenotypic phase plane (PhPP) analysis. This study proposes the first genome-scale model of S. platensis C1, iAK692, which is a predictive metabolic platform for a global understanding of physiological behaviors and metabolic engineering. This platform could accelerate the integrative analysis of various "-omics" data, leading to strain improvement towards a diverse range of desired industrial products from Spirulina.

A high-resolution cattle CNV map by population-scale genome sequencing

USDA-ARS?s Scientific Manuscript database

Copy Number Variations (CNVs) are common genomic structural variations that have been linked to human diseases and phenotypic traits. Prior studies in cattle have produced low-resolution CNV maps. We constructed a draft, high-resolution map of cattle CNVs based on whole genome sequencing data from 7...

GIGGLE: a search engine for large-scale integrated genome analysis.

PubMed

Layer, Ryan M; Pedersen, Brent S; DiSera, Tonya; Marth, Gabor T; Gertz, Jason; Quinlan, Aaron R

2018-02-01

GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (https://github.com/ryanlayer/giggle) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation.

GIGGLE: a search engine for large-scale integrated genome analysis

PubMed Central

Layer, Ryan M; Pedersen, Brent S; DiSera, Tonya; Marth, Gabor T; Gertz, Jason; Quinlan, Aaron R

2018-01-01

GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (https://github.com/ryanlayer/giggle) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation. PMID:29309061

Genome-Wide Fine-Scale Recombination Rate Variation in Drosophila melanogaster

PubMed Central

Song, Yun S.

2012-01-01

Estimating fine-scale recombination maps of Drosophila from population genomic data is a challenging problem, in particular because of the high background recombination rate. In this paper, a new computational method is developed to address this challenge. Through an extensive simulation study, it is demonstrated that the method allows more accurate inference, and exhibits greater robustness to the effects of natural selection and noise, compared to a well-used previous method developed for studying fine-scale recombination rate variation in the human genome. As an application, a genome-wide analysis of genetic variation data is performed for two Drosophila melanogaster populations, one from North America (Raleigh, USA) and the other from Africa (Gikongoro, Rwanda). It is shown that fine-scale recombination rate variation is widespread throughout the D. melanogaster genome, across all chromosomes and in both populations. At the fine-scale, a conservative, systematic search for evidence of recombination hotspots suggests the existence of a handful of putative hotspots each with at least a tenfold increase in intensity over the background rate. A wavelet analysis is carried out to compare the estimated recombination maps in the two populations and to quantify the extent to which recombination rates are conserved. In general, similarity is observed at very broad scales, but substantial differences are seen at fine scales. The average recombination rate of the X chromosome appears to be higher than that of the autosomes in both populations, and this pattern is much more pronounced in the African population than the North American population. The correlation between various genomic features—including recombination rates, diversity, divergence, GC content, gene content, and sequence quality—is examined using the wavelet analysis, and it is shown that the most notable difference between D. melanogaster and humans is in the correlation between recombination and diversity. PMID:23284288

Translational bioinformatics in the cloud: an affordable alternative

PubMed Central

2010-01-01

With the continued exponential expansion of publicly available genomic data and access to low-cost, high-throughput molecular technologies for profiling patient populations, computational technologies and informatics are becoming vital considerations in genomic medicine. Although cloud computing technology is being heralded as a key enabling technology for the future of genomic research, available case studies are limited to applications in the domain of high-throughput sequence data analysis. The goal of this study was to evaluate the computational and economic characteristics of cloud computing in performing a large-scale data integration and analysis representative of research problems in genomic medicine. We find that the cloud-based analysis compares favorably in both performance and cost in comparison to a local computational cluster, suggesting that cloud computing technologies might be a viable resource for facilitating large-scale translational research in genomic medicine. PMID:20691073

Genome sequence of the progenitor of wheat A subgenome Triticum urartu.

PubMed

Ling, Hong-Qing; Ma, Bin; Shi, Xiaoli; Liu, Hui; Dong, Lingli; Sun, Hua; Cao, Yinghao; Gao, Qiang; Zheng, Shusong; Li, Ye; Yu, Ying; Du, Huilong; Qi, Ming; Li, Yan; Lu, Hongwei; Yu, Hua; Cui, Yan; Wang, Ning; Chen, Chunlin; Wu, Huilan; Zhao, Yan; Zhang, Juncheng; Li, Yiwen; Zhou, Wenjuan; Zhang, Bairu; Hu, Weijuan; van Eijk, Michiel J T; Tang, Jifeng; Witsenboer, Hanneke M A; Zhao, Shancen; Li, Zhensheng; Zhang, Aimin; Wang, Daowen; Liang, Chengzhi

2018-05-09

Triticum urartu (diploid, AA) is the progenitor of the A subgenome of tetraploid (Triticum turgidum, AABB) and hexaploid (Triticum aestivum, AABBDD) wheat 1,2 . Genomic studies of T. urartu have been useful for investigating the structure, function and evolution of polyploid wheat genomes. Here we report the generation of a high-quality genome sequence of T. urartu by combining bacterial artificial chromosome (BAC)-by-BAC sequencing, single molecule real-time whole-genome shotgun sequencing 3 , linked reads and optical mapping 4,5 . We assembled seven chromosome-scale pseudomolecules and identified protein-coding genes, and we suggest a model for the evolution of T. urartu chromosomes. Comparative analyses with genomes of other grasses showed gene loss and amplification in the numbers of transposable elements in the T. urartu genome. Population genomics analysis of 147 T. urartu accessions from across the Fertile Crescent showed clustering of three groups, with differences in altitude and biostress, such as powdery mildew disease. The T. urartu genome assembly provides a valuable resource for studying genetic variation in wheat and related grasses, and promises to facilitate the discovery of genes that could be useful for wheat improvement.

Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence.

PubMed

Savage, Jeanne E; Jansen, Philip R; Stringer, Sven; Watanabe, Kyoko; Bryois, Julien; de Leeuw, Christiaan A; Nagel, Mats; Awasthi, Swapnil; Barr, Peter B; Coleman, Jonathan R I; Grasby, Katrina L; Hammerschlag, Anke R; Kaminski, Jakob A; Karlsson, Robert; Krapohl, Eva; Lam, Max; Nygaard, Marianne; Reynolds, Chandra A; Trampush, Joey W; Young, Hannah; Zabaneh, Delilah; Hägg, Sara; Hansell, Narelle K; Karlsson, Ida K; Linnarsson, Sten; Montgomery, Grant W; Muñoz-Manchado, Ana B; Quinlan, Erin B; Schumann, Gunter; Skene, Nathan G; Webb, Bradley T; White, Tonya; Arking, Dan E; Avramopoulos, Dimitrios; Bilder, Robert M; Bitsios, Panos; Burdick, Katherine E; Cannon, Tyrone D; Chiba-Falek, Ornit; Christoforou, Andrea; Cirulli, Elizabeth T; Congdon, Eliza; Corvin, Aiden; Davies, Gail; Deary, Ian J; DeRosse, Pamela; Dickinson, Dwight; Djurovic, Srdjan; Donohoe, Gary; Conley, Emily Drabant; Eriksson, Johan G; Espeseth, Thomas; Freimer, Nelson A; Giakoumaki, Stella; Giegling, Ina; Gill, Michael; Glahn, David C; Hariri, Ahmad R; Hatzimanolis, Alex; Keller, Matthew C; Knowles, Emma; Koltai, Deborah; Konte, Bettina; Lahti, Jari; Le Hellard, Stephanie; Lencz, Todd; Liewald, David C; London, Edythe; Lundervold, Astri J; Malhotra, Anil K; Melle, Ingrid; Morris, Derek; Need, Anna C; Ollier, William; Palotie, Aarno; Payton, Antony; Pendleton, Neil; Poldrack, Russell A; Räikkönen, Katri; Reinvang, Ivar; Roussos, Panos; Rujescu, Dan; Sabb, Fred W; Scult, Matthew A; Smeland, Olav B; Smyrnis, Nikolaos; Starr, John M; Steen, Vidar M; Stefanis, Nikos C; Straub, Richard E; Sundet, Kjetil; Tiemeier, Henning; Voineskos, Aristotle N; Weinberger, Daniel R; Widen, Elisabeth; Yu, Jin; Abecasis, Goncalo; Andreassen, Ole A; Breen, Gerome; Christiansen, Lene; Debrabant, Birgit; Dick, Danielle M; Heinz, Andreas; Hjerling-Leffler, Jens; Ikram, M Arfan; Kendler, Kenneth S; Martin, Nicholas G; Medland, Sarah E; Pedersen, Nancy L; Plomin, Robert; Polderman, Tinca J C; Ripke, Stephan; van der Sluis, Sophie; Sullivan, Patrick F; Vrieze, Scott I; Wright, Margaret J; Posthuma, Danielle

2018-06-25

Intelligence is highly heritable 1 and a major determinant of human health and well-being 2 . Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence 3-7 , but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.

CanvasDB: a local database infrastructure for analysis of targeted- and whole genome re-sequencing projects

PubMed Central

Ameur, Adam; Bunikis, Ignas; Enroth, Stefan; Gyllensten, Ulf

2014-01-01

CanvasDB is an infrastructure for management and analysis of genetic variants from massively parallel sequencing (MPS) projects. The system stores SNP and indel calls in a local database, designed to handle very large datasets, to allow for rapid analysis using simple commands in R. Functional annotations are included in the system, making it suitable for direct identification of disease-causing mutations in human exome- (WES) or whole-genome sequencing (WGS) projects. The system has a built-in filtering function implemented to simultaneously take into account variant calls from all individual samples. This enables advanced comparative analysis of variant distribution between groups of samples, including detection of candidate causative mutations within family structures and genome-wide association by sequencing. In most cases, these analyses are executed within just a matter of seconds, even when there are several hundreds of samples and millions of variants in the database. We demonstrate the scalability of canvasDB by importing the individual variant calls from all 1092 individuals present in the 1000 Genomes Project into the system, over 4.4 billion SNPs and indels in total. Our results show that canvasDB makes it possible to perform advanced analyses of large-scale WGS projects on a local server. Database URL: https://github.com/UppsalaGenomeCenter/CanvasDB PMID:25281234

CanvasDB: a local database infrastructure for analysis of targeted- and whole genome re-sequencing projects.

PubMed

Ameur, Adam; Bunikis, Ignas; Enroth, Stefan; Gyllensten, Ulf

2014-01-01

CanvasDB is an infrastructure for management and analysis of genetic variants from massively parallel sequencing (MPS) projects. The system stores SNP and indel calls in a local database, designed to handle very large datasets, to allow for rapid analysis using simple commands in R. Functional annotations are included in the system, making it suitable for direct identification of disease-causing mutations in human exome- (WES) or whole-genome sequencing (WGS) projects. The system has a built-in filtering function implemented to simultaneously take into account variant calls from all individual samples. This enables advanced comparative analysis of variant distribution between groups of samples, including detection of candidate causative mutations within family structures and genome-wide association by sequencing. In most cases, these analyses are executed within just a matter of seconds, even when there are several hundreds of samples and millions of variants in the database. We demonstrate the scalability of canvasDB by importing the individual variant calls from all 1092 individuals present in the 1000 Genomes Project into the system, over 4.4 billion SNPs and indels in total. Our results show that canvasDB makes it possible to perform advanced analyses of large-scale WGS projects on a local server. Database URL: https://github.com/UppsalaGenomeCenter/CanvasDB. © The Author(s) 2014. Published by Oxford University Press.

Transposon diversity in Arabidopsis thaliana

PubMed Central

Le, Quang Hien; Wright, Stephen; Yu, Zhihui; Bureau, Thomas

2000-01-01

Recent availability of extensive genome sequence information offers new opportunities to analyze genome organization, including transposon diversity and accumulation, at a level of resolution that was previously unattainable. In this report, we used sequence similarity search and analysis protocols to perform a fine-scale analysis of a large sample (≈17.2 Mb) of the Arabidopsis thaliana (Columbia) genome for transposons. Consistent with previous studies, we report that the A. thaliana genome harbors diverse representatives of most known superfamilies of transposons. However, our survey reveals a higher density of transposons of which over one-fourth could be classified into a single novel transposon family designated as Basho, which appears unrelated to any previously known superfamily. We have also identified putative transposase-coding ORFs for miniature inverted-repeat transposable elements (MITEs), providing clues into the mechanism of mobility and origins of the most abundant transposons associated with plant genes. In addition, we provide evidence that most mined transposons have a clear distribution preference for A + T-rich sequences and show that structural variation for many mined transposons is partly due to interelement recombination. Taken together, these findings further underscore the complexity of transposons within the compact genome of A. thaliana. PMID:10861007

Evaluating phylogenetic congruence in the post-genomic era.

PubMed

Leigh, Jessica W; Lapointe, François-Joseph; Lopez, Philippe; Bapteste, Eric

2011-01-01

Congruence is a broadly applied notion in evolutionary biology used to justify multigene phylogeny or phylogenomics, as well as in studies of coevolution, lateral gene transfer, and as evidence for common descent. Existing methods for identifying incongruence or heterogeneity using character data were designed for data sets that are both small and expected to be rarely incongruent. At the same time, methods that assess incongruence using comparison of trees test a null hypothesis of uncorrelated tree structures, which may be inappropriate for phylogenomic studies. As such, they are ill-suited for the growing number of available genome sequences, most of which are from prokaryotes and viruses, either for phylogenomic analysis or for studies of the evolutionary forces and events that have shaped these genomes. Specifically, many existing methods scale poorly with large numbers of genes, cannot accommodate high levels of incongruence, and do not adequately model patterns of missing taxa for different markers. We propose the development of novel incongruence assessment methods suitable for the analysis of the molecular evolution of the vast majority of life and support the investigation of homogeneity of evolutionary process in cases where markers do not share identical tree structures.

Evaluating Phylogenetic Congruence in the Post-Genomic Era

PubMed Central

Leigh, Jessica W.; Lapointe, François-Joseph; Lopez, Philippe; Bapteste, Eric

2011-01-01

Congruence is a broadly applied notion in evolutionary biology used to justify multigene phylogeny or phylogenomics, as well as in studies of coevolution, lateral gene transfer, and as evidence for common descent. Existing methods for identifying incongruence or heterogeneity using character data were designed for data sets that are both small and expected to be rarely incongruent. At the same time, methods that assess incongruence using comparison of trees test a null hypothesis of uncorrelated tree structures, which may be inappropriate for phylogenomic studies. As such, they are ill-suited for the growing number of available genome sequences, most of which are from prokaryotes and viruses, either for phylogenomic analysis or for studies of the evolutionary forces and events that have shaped these genomes. Specifically, many existing methods scale poorly with large numbers of genes, cannot accommodate high levels of incongruence, and do not adequately model patterns of missing taxa for different markers. We propose the development of novel incongruence assessment methods suitable for the analysis of the molecular evolution of the vast majority of life and support the investigation of homogeneity of evolutionary process in cases where markers do not share identical tree structures. PMID:21712432

A case study for cloud based high throughput analysis of NGS data using the globus genomics system

PubMed Central

Bhuvaneshwar, Krithika; Sulakhe, Dinanath; Gauba, Robinder; Rodriguez, Alex; Madduri, Ravi; Dave, Utpal; Lacinski, Lukasz; Foster, Ian; Gusev, Yuriy; Madhavan, Subha

2014-01-01

Next generation sequencing (NGS) technologies produce massive amounts of data requiring a powerful computational infrastructure, high quality bioinformatics software, and skilled personnel to operate the tools. We present a case study of a practical solution to this data management and analysis challenge that simplifies terabyte scale data handling and provides advanced tools for NGS data analysis. These capabilities are implemented using the “Globus Genomics” system, which is an enhanced Galaxy workflow system made available as a service that offers users the capability to process and transfer data easily, reliably and quickly to address end-to-endNGS analysis requirements. The Globus Genomics system is built on Amazon 's cloud computing infrastructure. The system takes advantage of elastic scaling of compute resources to run multiple workflows in parallel and it also helps meet the scale-out analysis needs of modern translational genomics research. PMID:26925205

Major soybean maturity gene haplotypes revealed by SNPViz analysis of 72 sequenced soybean genomes

USDA-ARS?s Scientific Manuscript database

In this Genomics Era, vast amounts of next generation sequencing data have become publicly-available for multiple genomes across hundreds of species. Analysis of these large-scale datasets can become cumbersome, especially when comparing nucleotide polymorphisms across many samples within a dataset...

Chromatin Insulators and Topological Domains: Adding New Dimensions to 3D Genome Architecture

PubMed Central

Matharu, Navneet K.; Ahanger, Sajad H.

2015-01-01

The spatial organization of metazoan genomes has a direct influence on fundamental nuclear processes that include transcription, replication, and DNA repair. It is imperative to understand the mechanisms that shape the 3D organization of the eukaryotic genomes. Chromatin insulators have emerged as one of the central components of the genome organization tool-kit across species. Recent advancements in chromatin conformation capture technologies have provided important insights into the architectural role of insulators in genomic structuring. Insulators are involved in 3D genome organization at multiple spatial scales and are important for dynamic reorganization of chromatin structure during reprogramming and differentiation. In this review, we will discuss the classical view and our renewed understanding of insulators as global genome organizers. We will also discuss the plasticity of chromatin structure and its re-organization during pluripotency and differentiation and in situations of cellular stress. PMID:26340639

3D genomics imposes evolution of the domain model of eukaryotic genome organization.

PubMed

Razin, Sergey V; Vassetzky, Yegor S

2017-02-01

The hypothesis that the genome is composed of a patchwork of structural and functional domains (units) that may be either active or repressed was proposed almost 30 years ago. Here, we examine the evolution of the domain model of eukaryotic genome organization in view of the expansion of genome-scale techniques in the twenty-first century that have provided us with a wealth of information on genome organization, folding, and functioning.

BactoGeNIE: A large-scale comparative genome visualization for big displays

DOE PAGES

Aurisano, Jillian; Reda, Khairi; Johnson, Andrew; ...

2015-08-13

The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE throughmore » a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. In conclusion, BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics.« less

BactoGeNIE: a large-scale comparative genome visualization for big displays

PubMed Central

2015-01-01

Background The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. Results In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE through a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. Conclusions BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics. PMID:26329021

BactoGeNIE: A large-scale comparative genome visualization for big displays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aurisano, Jillian; Reda, Khairi; Johnson, Andrew

The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE throughmore » a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. In conclusion, BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics.« less

Computational complexity of algorithms for sequence comparison, short-read assembly and genome alignment.

PubMed

Baichoo, Shakuntala; Ouzounis, Christos A

A multitude of algorithms for sequence comparison, short-read assembly and whole-genome alignment have been developed in the general context of molecular biology, to support technology development for high-throughput sequencing, numerous applications in genome biology and fundamental research on comparative genomics. The computational complexity of these algorithms has been previously reported in original research papers, yet this often neglected property has not been reviewed previously in a systematic manner and for a wider audience. We provide a review of space and time complexity of key sequence analysis algorithms and highlight their properties in a comprehensive manner, in order to identify potential opportunities for further research in algorithm or data structure optimization. The complexity aspect is poised to become pivotal as we will be facing challenges related to the continuous increase of genomic data on unprecedented scales and complexity in the foreseeable future, when robust biological simulation at the cell level and above becomes a reality. Copyright © 2017 Elsevier B.V. All rights reserved.

Molecular epidemiology of Epizootic haematopoietic necrosis virus (EHNV).

PubMed

Hick, Paul M; Subramaniam, Kuttichantran; Thompson, Patrick M; Waltzek, Thomas B; Becker, Joy A; Whittington, Richard J

2017-11-01

Low genetic diversity of Epizootic haematopoietic necrosis virus (EHNV) was determined for the complete genome of 16 isolates spanning the natural range of hosts, geography and time since the first outbreaks of disease. Genomes ranged from 125,591-127,487 nucleotides with 97.47% pairwise identity and 106-109 genes. All isolates shared 101 core genes with 121 potential genes predicted within the pan-genome of this collection. There was high conservation within 90,181 nucleotides of the core genes with isolates separated by average genetic distance of 3.43 × 10 -4 substitutions per site. Evolutionary analysis of the core genome strongly supported historical epidemiological evidence of iatrogenic spread of EHNV to naïve hosts and establishment of endemic status in discrete ecological niches. There was no evidence of structural genome reorganization, however, the complement of non-core genes and variation in repeat elements enabled fine scale molecular epidemiological investigation of this unpredictable pathogen of fish. Copyright © 2017 Elsevier Inc. All rights reserved.

ScrumPy: metabolic modelling with Python.

PubMed

Poolman, M G

2006-09-01

ScrumPy is a software package used for the definition and analysis of metabolic models. It is written using the Python programming language that is also used as a user interface. ScrumPy has features for both kinetic and structural modelling, but the emphasis is on structural modelling and those features of most relevance to analysis of large (genome-scale) models. The aim is at describing ScrumPy's functionality to readers with some knowledge of metabolic modelling, but implementation, programming and other computational details are omitted. ScrumPy is released under the Gnu Public Licence, and available for download from http://mudshark.brookes.ac.uk/ ScrumPy.

Nonlinear Analysis of Time Series in Genome-Wide Linkage Disequilibrium Data

NASA Astrophysics Data System (ADS)

Hernández-Lemus, Enrique; Estrada-Gil, Jesús K.; Silva-Zolezzi, Irma; Fernández-López, J. Carlos; Hidalgo-Miranda, Alfredo; Jiménez-Sánchez, Gerardo

2008-02-01

The statistical study of large scale genomic data has turned out to be a very important tool in population genetics. Quantitative methods are essential to understand and implement association studies in the biomedical and health sciences. Nevertheless, the characterization of recently admixed populations has been an elusive problem due to the presence of a number of complex phenomena. For example, linkage disequilibrium structures are thought to be more complex than their non-recently admixed population counterparts, presenting the so-called ancestry blocks, admixed regions that are not yet smoothed by the effect of genetic recombination. In order to distinguish characteristic features for various populations we have implemented several methods, some of them borrowed or adapted from the analysis of nonlinear time series in statistical physics and quantitative physiology. We calculate the main fractal dimensions (Kolmogorov's capacity, information dimension and correlation dimension, usually named, D0, D1 and D2). We also have made detrended fluctuation analysis and information based similarity index calculations for the probability distribution of correlations of linkage disequilibrium coefficient of six recently admixed (mestizo) populations within the Mexican Genome Diversity Project [1] and for the non-recently admixed populations in the International HapMap Project [2]. Nonlinear correlations showed up as a consequence of internal structure within the haplotype distributions. The analysis of these correlations as well as the scope and limitations of these procedures within the biomedical sciences are discussed.

CoryneRegNet: An ontology-based data warehouse of corynebacterial transcription factors and regulatory networks

PubMed Central

Baumbach, Jan; Brinkrolf, Karina; Czaja, Lisa F; Rahmann, Sven; Tauch, Andreas

2006-01-01

Background The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. Description CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. Conclusion CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation. PMID:16478536

About TCGA - TCGA

Cancer.gov

Find out about The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to accelerate our understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing.

Discrimination of candidate subgenome-specific loci by linkage map construction with an S1 population of octoploid strawberry (Fragaria × ananassa).

PubMed

Nagano, Soichiro; Shirasawa, Kenta; Hirakawa, Hideki; Maeda, Fumi; Ishikawa, Masami; Isobe, Sachiko N

2017-05-12

The strawberry, Fragaria × ananassa, is an allo-octoploid (2n = 8x = 56) and outcrossing species. Although it is the most widely consumed berry crop in the world, its complex genome structure has hindered its genetic and genomic analysis, and thus discrimination of subgenome-specific loci among the homoeologous chromosomes is needed. In the present study, we identified candidate subgenome-specific single nucleotide polymorphism (SNP) and simple sequence repeat (SSR) loci, and constructed a linkage map using an S 1 mapping population of the cultivar 'Reikou' with an IStraw90 Axiom® SNP array and previously published SSR markers. The 'Reikou' linkage map consisted of 11,574 loci (11,002 SNPs and 572 SSR loci) spanning 2816.5 cM of 31 linkage groups. The 11,574 loci were located on 4738 unique positions (bin) on the linkage map. Of the mapped loci, 8999 (8588 SNPs and 411 SSR loci) showed a 1:2:1 segregation ratio of AA:AB:BB allele, which suggested the possibility of deriving loci from candidate subgenome-specific sequences. In addition, 2575 loci (2414 SNPs and 161 SSR loci) showed a 3:1 segregation of AB:BB allele, indicating they were derived from homoeologous genomic sequences. Comparative analysis of the homoeologous linkage groups revealed differences in genome structure among the subgenomes. Our results suggest that candidate subgenome-specific loci are randomly located across the genomes, and that there are small- to large-scale structural variations among the subgenomes. The mapped SNPs and SSR loci on the linkage map are expected to be seed points for the construction of pseudomolecules in the octoploid strawberry.

Theobroma cacao: A genetically integrated physical map and genome-scale comparative synteny analysis

USDA-ARS?s Scientific Manuscript database

A comprehensive integrated genomic framework is considered a centerpiece of genomic research. In collaboration with the USDA-ARS (SHRS) and Mars Inc., the Clemson University Genomics Institute (CUGI) has developed a genetically anchored physical map of the T. cacao genome. Three BAC libraries contai...

FGWAS: Functional genome wide association analysis.

PubMed

Huang, Chao; Thompson, Paul; Wang, Yalin; Yu, Yang; Zhang, Jingwen; Kong, Dehan; Colen, Rivka R; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-10-01

Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs. Copyright © 2017 Elsevier Inc. All rights reserved.

Measurement of replication structures at the nanometer scale using super-resolution light microscopy

PubMed Central

Baddeley, D.; Chagin, V. O.; Schermelleh, L.; Martin, S.; Pombo, A.; Carlton, P. M.; Gahl, A.; Domaing, P.; Birk, U.; Leonhardt, H.; Cremer, C.; Cardoso, M. C.

2010-01-01

DNA replication, similar to other cellular processes, occurs within dynamic macromolecular structures. Any comprehensive understanding ultimately requires quantitative data to establish and test models of genome duplication. We used two different super-resolution light microscopy techniques to directly measure and compare the size and numbers of replication foci in mammalian cells. This analysis showed that replication foci vary in size from 210 nm down to 40 nm. Remarkably, spatially modulated illumination (SMI) and 3D-structured illumination microscopy (3D-SIM) both showed an average size of 125 nm that was conserved throughout S-phase and independent of the labeling method, suggesting a basic unit of genome duplication. Interestingly, the improved optical 3D resolution identified 3- to 5-fold more distinct replication foci than previously reported. These results show that optical nanoscopy techniques enable accurate measurements of cellular structures at a level previously achieved only by electron microscopy and highlight the possibility of high-throughput, multispectral 3D analyses. PMID:19864256

Genome-Wide Association Study of Cardiac Structure and Systolic Function in African Americans: The Candidate Gene Association Resource (CARe) Study

PubMed Central

Fox, Ervin R.; Musani, Solomon K.; Barbalic, Maja; Lin, Honghuang; Yu, Bing; Ogunyankin, Kofo O.; Smith, Nicholas L.; Kutlar, Abdullah; Glazer, Nicole L.; Post, Wendy S.; Paltoo, Dina N.; Dries, Daniel L.; Farlow, Deborah N.; Duarte, Christine W.; Kardia, Sharon L.; Meyers, Kristin J.; Sun, Yan V.; Arnett, Donna K.; Patki, Amit A.; Sha, Jin; Cui, Xiangqui; Samdarshi, Tandaw E.; Penman, Alan D.; Bibbins-Domingo, Kirsten; Bůžková, Petra; Benjamin, Emelia J.; Bluemke, David A.; Morrison, Alanna C.; Heiss, Gerardo; Carr, J. Jeffrey; Tracy, Russell P.; Mosley, Thomas H.; Taylor, Herman A.; Psaty, Bruce M.; Heckbert, Susan R.; Cappola, Thomas P.; Vasan, Ramachandran S.

2013-01-01

Background Using data from four community-based cohorts of African Americans (AA), we tested the association between genome-wide markers (SNPs) and cardiac phenotypes in the Candidate-gene Association REsource (CARe) study. Methods and Results Among 6,765 AA, we related age, sex, height and weight-adjusted residuals for nine cardiac phenotypes (assessed by echocardiogram or MRI) to 2.5 million SNPs genotyped using Genome-Wide Affymetrix Human SNP Array 6.0 (Affy6.0) and the remainder imputed. Within cohort genome-wide association analysis was conducted followed by meta-analysis across cohorts using inverse variance weights (genome-wide significance threshold=4.0 ×10−07). Supplementary pathway analysis was performed. We attempted replication in 3 smaller cohorts of African ancestry and tested look-ups in one consortium of European ancestry (EchoGEN). Across the 9 phenotypes, variants in 4 genetic loci reached genome-wide significance: rs4552931 in UBE2V2 (p=1.43 × 10−07) for left ventricular mass (LVM); rs7213314 in WIPI1 (p=1.68 × 10−07) for LV internal diastolic diameter (LVIDD); rs1571099 in PPAPDC1A (p= 2.57 × 10−08) for interventricular septal wall thickness (IVST); and rs9530176 in KLF5 (p=4.02 × 10−07) for ejection fraction (EF). Associated variants were enriched in three signaling pathways involved in cardiac remodeling. None of the 4 loci replicated in cohorts of African ancestry were confirmed in look-ups in EchoGEN. Conclusions In the largest GWAS of cardiac structure and function to date in AA, we identified 4 genetic loci related to LVM, IVST, LVIDD and EF that reached genome-wide significance. Replication results suggest that these loci may represent unique to individuals of African ancestry. Additional large-scale studies are warranted for these complex phenotypes. PMID:23275298

Deppdb--DNA electrostatic potential properties database: electrostatic properties of genome DNA.

PubMed

Osypov, Alexander A; Krutinin, Gleb G; Kamzolova, Svetlana G

2010-06-01

The electrostatic properties of genome DNA influence its interactions with different proteins, in particular, the regulation of transcription by RNA-polymerases. DEPPDB--DNA Electrostatic Potential Properties Database--was developed to hold and provide all available information on the electrostatic properties of genome DNA combined with its sequence and annotation of biological and structural properties of genome elements and whole genomes. Genomes in DEPPDB are organized on a taxonomical basis. Currently, the database contains all the completely sequenced bacterial and viral genomes according to NCBI RefSeq. General properties of the genome DNA electrostatic potential profile and principles of its formation are revealed. This potential correlates with the GC content but does not correspond to it exactly and strongly depends on both the sequence arrangement and its context (flanking regions). Analysis of the promoter regions for bacterial and viral RNA polymerases revealed a correspondence between the scale of these proteins' physical properties and electrostatic profile patterns. We also discovered a direct correlation between the potential value and the binding frequency of RNA polymerase to DNA, supporting the idea of the role of electrostatics in these interactions. This matches a pronounced tendency of the promoter regions to possess higher values of the electrostatic potential.

Ensembl Genomes 2013: scaling up access to genome-wide data.

PubMed

Kersey, Paul Julian; Allen, James E; Christensen, Mikkel; Davis, Paul; Falin, Lee J; Grabmueller, Christoph; Hughes, Daniel Seth Toney; Humphrey, Jay; Kerhornou, Arnaud; Khobova, Julia; Langridge, Nicholas; McDowall, Mark D; Maheswari, Uma; Maslen, Gareth; Nuhn, Michael; Ong, Chuang Kee; Paulini, Michael; Pedro, Helder; Toneva, Iliana; Tuli, Mary Ann; Walts, Brandon; Williams, Gareth; Wilson, Derek; Youens-Clark, Ken; Monaco, Marcela K; Stein, Joshua; Wei, Xuehong; Ware, Doreen; Bolser, Daniel M; Howe, Kevin Lee; Kulesha, Eugene; Lawson, Daniel; Staines, Daniel Michael

2014-01-01

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species. The project exploits and extends technologies for genome annotation, analysis and dissemination, developed in the context of the vertebrate-focused Ensembl project, and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. This article provides an update to the previous publications about the resource, with a focus on recent developments. These include the addition of important new genomes (and related data sets) including crop plants, vectors of human disease and eukaryotic pathogens. In addition, the resource has scaled up its representation of bacterial genomes, and now includes the genomes of over 9000 bacteria. Specific extensions to the web and programmatic interfaces have been developed to support users in navigating these large data sets. Looking forward, analytic tools to allow targeted selection of data for visualization and download are likely to become increasingly important in future as the number of available genomes increases within all domains of life, and some of the challenges faced in representing bacterial data are likely to become commonplace for eukaryotes in future.

Globus | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Globus software services provide secure cancer research data transfer, synchronization, and sharing in distributed environments at large scale. These services can be integrated into applications and research data gateways, leveraging Globus identity management, single sign-on, search, and authorization capabilities. Globus Genomics integrates Globus with the Galaxy genomics workflow engine and Amazon Web Services to enable cancer genomics analysis that can elastically scale compute resources with demand.

Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function

PubMed Central

Wild, Philipp S.; Felix, Janine F.; Schillert, Arne; Chen, Ming-Huei; Leening, Maarten J.G.; Völker, Uwe; Großmann, Vera; Brody, Jennifer A.; Irvin, Marguerite R.; Shah, Sanjiv J.; Pramana, Setia; Lieb, Wolfgang; Schmidt, Reinhold; Stanton, Alice V.; Malzahn, Dörthe; Lyytikäinen, Leo-Pekka; Tiller, Daniel; Smith, J. Gustav; Di Tullio, Marco R.; Musani, Solomon K.; Morrison, Alanna C.; Pers, Tune H.; Morley, Michael; Kleber, Marcus E.; Aragam, Jayashri; Bis, Joshua C.; Bisping, Egbert; Broeckel, Ulrich; Cheng, Susan; Deckers, Jaap W.; Del Greco M, Fabiola; Edelmann, Frank; Fornage, Myriam; Franke, Lude; Friedrich, Nele; Harris, Tamara B.; Hofer, Edith; Hofman, Albert; Huang, Jie; Hughes, Alun D.; Kähönen, Mika; investigators, KNHI; Kruppa, Jochen; Lackner, Karl J.; Lannfelt, Lars; Laskowski, Rafael; Launer, Lenore J.; Lindgren, Cecilia M.; Loley, Christina; Mayet, Jamil; Medenwald, Daniel; Morris, Andrew P.; Müller, Christian; Müller-Nurasyid, Martina; Nappo, Stefania; Nilsson, Peter M.; Nuding, Sebastian; Nutile, Teresa; Peters, Annette; Pfeufer, Arne; Pietzner, Diana; Pramstaller, Peter P.; Raitakari, Olli T.; Rice, Kenneth M.; Rotter, Jerome I.; Ruohonen, Saku T.; Sacco, Ralph L.; Samdarshi, Tandaw E.; Sharp, Andrew S.P.; Shields, Denis C.; Sorice, Rossella; Sotoodehnia, Nona; Stricker, Bruno H.; Surendran, Praveen; Töglhofer, Anna M.; Uitterlinden, André G.; Völzke, Henry; Ziegler, Andreas; Münzel, Thomas; März, Winfried; Cappola, Thomas P.; Hirschhorn, Joel N.; Mitchell, Gary F.; Smith, Nicholas L.; Fox, Ervin R.; Dueker, Nicole D.; Jaddoe, Vincent W.V.; Melander, Olle; Lehtimäki, Terho; Ciullo, Marina; Hicks, Andrew A.; Lind, Lars; Gudnason, Vilmundur; Pieske, Burkert; Barron, Anthony J.; Zweiker, Robert; Schunkert, Heribert; Ingelsson, Erik; Liu, Kiang; Arnett, Donna K.; Psaty, Bruce M.; Blankenberg, Stefan; Larson, Martin G.; Felix, Stephan B.; Franco, Oscar H.; Zeller, Tanja; Vasan, Ramachandran S.; Dörr, Marcus

2017-01-01

BACKGROUND. Understanding the genetic architecture of cardiac structure and function may help to prevent and treat heart disease. This investigation sought to identify common genetic variations associated with inter-individual variability in cardiac structure and function. METHODS. A GWAS meta-analysis of echocardiographic traits was performed, including 46,533 individuals from 30 studies (EchoGen consortium). The analysis included 16 traits of left ventricular (LV) structure, and systolic and diastolic function. RESULTS. The discovery analysis included 21 cohorts for structural and systolic function traits (n = 32,212) and 17 cohorts for diastolic function traits (n = 21,852). Replication was performed in 5 cohorts (n = 14,321) and 6 cohorts (n = 16,308), respectively. Besides 5 previously reported loci, the combined meta-analysis identified 10 additional genome-wide significant SNPs: rs12541595 near MTSS1 and rs10774625 in ATXN2 for LV end-diastolic internal dimension; rs806322 near KCNRG, rs4765663 in CACNA1C, rs6702619 near PALMD, rs7127129 in TMEM16A, rs11207426 near FGGY, rs17608766 in GOSR2, and rs17696696 in CFDP1 for aortic root diameter; and rs12440869 in IQCH for Doppler transmitral A-wave peak velocity. Findings were in part validated in other cohorts and in GWAS of related disease traits. The genetic loci showed associations with putative signaling pathways, and with gene expression in whole blood, monocytes, and myocardial tissue. CONCLUSION. The additional genetic loci identified in this large meta-analysis of cardiac structure and function provide insights into the underlying genetic architecture of cardiac structure and warrant follow-up in future functional studies. FUNDING. For detailed information per study, see Acknowledgments. PMID:28394258

High throughput platforms for structural genomics of integral membrane proteins.

PubMed

Mancia, Filippo; Love, James

2011-08-01

Structural genomics approaches on integral membrane proteins have been postulated for over a decade, yet specific efforts are lagging years behind their soluble counterparts. Indeed, high throughput methodologies for production and characterization of prokaryotic integral membrane proteins are only now emerging, while large-scale efforts for eukaryotic ones are still in their infancy. Presented here is a review of recent literature on actively ongoing structural genomics of membrane protein initiatives, with a focus on those aimed at implementing interesting techniques aimed at increasing our rate of success for this class of macromolecules. Copyright © 2011 Elsevier Ltd. All rights reserved.

Using relational databases for improved sequence similarity searching and large-scale genomic analyses.

PubMed

Mackey, Aaron J; Pearson, William R

2004-10-01

Relational databases are designed to integrate diverse types of information and manage large sets of search results, greatly simplifying genome-scale analyses. Relational databases are essential for management and analysis of large-scale sequence analyses, and can also be used to improve the statistical significance of similarity searches by focusing on subsets of sequence libraries most likely to contain homologs. This unit describes using relational databases to improve the efficiency of sequence similarity searching and to demonstrate various large-scale genomic analyses of homology-related data. This unit describes the installation and use of a simple protein sequence database, seqdb_demo, which is used as a basis for the other protocols. These include basic use of the database to generate a novel sequence library subset, how to extend and use seqdb_demo for the storage of sequence similarity search results and making use of various kinds of stored search results to address aspects of comparative genomic analysis.

Guidelines for Genome-Scale Analysis of Biological Rhythms.

PubMed

Hughes, Michael E; Abruzzi, Katherine C; Allada, Ravi; Anafi, Ron; Arpat, Alaaddin Bulak; Asher, Gad; Baldi, Pierre; de Bekker, Charissa; Bell-Pedersen, Deborah; Blau, Justin; Brown, Steve; Ceriani, M Fernanda; Chen, Zheng; Chiu, Joanna C; Cox, Juergen; Crowell, Alexander M; DeBruyne, Jason P; Dijk, Derk-Jan; DiTacchio, Luciano; Doyle, Francis J; Duffield, Giles E; Dunlap, Jay C; Eckel-Mahan, Kristin; Esser, Karyn A; FitzGerald, Garret A; Forger, Daniel B; Francey, Lauren J; Fu, Ying-Hui; Gachon, Frédéric; Gatfield, David; de Goede, Paul; Golden, Susan S; Green, Carla; Harer, John; Harmer, Stacey; Haspel, Jeff; Hastings, Michael H; Herzel, Hanspeter; Herzog, Erik D; Hoffmann, Christy; Hong, Christian; Hughey, Jacob J; Hurley, Jennifer M; de la Iglesia, Horacio O; Johnson, Carl; Kay, Steve A; Koike, Nobuya; Kornacker, Karl; Kramer, Achim; Lamia, Katja; Leise, Tanya; Lewis, Scott A; Li, Jiajia; Li, Xiaodong; Liu, Andrew C; Loros, Jennifer J; Martino, Tami A; Menet, Jerome S; Merrow, Martha; Millar, Andrew J; Mockler, Todd; Naef, Felix; Nagoshi, Emi; Nitabach, Michael N; Olmedo, Maria; Nusinow, Dmitri A; Ptáček, Louis J; Rand, David; Reddy, Akhilesh B; Robles, Maria S; Roenneberg, Till; Rosbash, Michael; Ruben, Marc D; Rund, Samuel S C; Sancar, Aziz; Sassone-Corsi, Paolo; Sehgal, Amita; Sherrill-Mix, Scott; Skene, Debra J; Storch, Kai-Florian; Takahashi, Joseph S; Ueda, Hiroki R; Wang, Han; Weitz, Charles; Westermark, Pål O; Wijnen, Herman; Xu, Ying; Wu, Gang; Yoo, Seung-Hee; Young, Michael; Zhang, Eric Erquan; Zielinski, Tomasz; Hogenesch, John B

2017-10-01

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding "big data" that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them.

Guidelines for Genome-Scale Analysis of Biological Rhythms

PubMed Central

Hughes, Michael E.; Abruzzi, Katherine C.; Allada, Ravi; Anafi, Ron; Arpat, Alaaddin Bulak; Asher, Gad; Baldi, Pierre; de Bekker, Charissa; Bell-Pedersen, Deborah; Blau, Justin; Brown, Steve; Ceriani, M. Fernanda; Chen, Zheng; Chiu, Joanna C.; Cox, Juergen; Crowell, Alexander M.; DeBruyne, Jason P.; Dijk, Derk-Jan; DiTacchio, Luciano; Doyle, Francis J.; Duffield, Giles E.; Dunlap, Jay C.; Eckel-Mahan, Kristin; Esser, Karyn A.; FitzGerald, Garret A.; Forger, Daniel B.; Francey, Lauren J.; Fu, Ying-Hui; Gachon, Frédéric; Gatfield, David; de Goede, Paul; Golden, Susan S.; Green, Carla; Harer, John; Harmer, Stacey; Haspel, Jeff; Hastings, Michael H.; Herzel, Hanspeter; Herzog, Erik D.; Hoffmann, Christy; Hong, Christian; Hughey, Jacob J.; Hurley, Jennifer M.; de la Iglesia, Horacio O.; Johnson, Carl; Kay, Steve A.; Koike, Nobuya; Kornacker, Karl; Kramer, Achim; Lamia, Katja; Leise, Tanya; Lewis, Scott A.; Li, Jiajia; Li, Xiaodong; Liu, Andrew C.; Loros, Jennifer J.; Martino, Tami A.; Menet, Jerome S.; Merrow, Martha; Millar, Andrew J.; Mockler, Todd; Naef, Felix; Nagoshi, Emi; Nitabach, Michael N.; Olmedo, Maria; Nusinow, Dmitri A.; Ptáček, Louis J.; Rand, David; Reddy, Akhilesh B.; Robles, Maria S.; Roenneberg, Till; Rosbash, Michael; Ruben, Marc D.; Rund, Samuel S.C.; Sancar, Aziz; Sassone-Corsi, Paolo; Sehgal, Amita; Sherrill-Mix, Scott; Skene, Debra J.; Storch, Kai-Florian; Takahashi, Joseph S.; Ueda, Hiroki R.; Wang, Han; Weitz, Charles; Westermark, Pål O.; Wijnen, Herman; Xu, Ying; Wu, Gang; Yoo, Seung-Hee; Young, Michael; Zhang, Eric Erquan; Zielinski, Tomasz; Hogenesch, John B.

2017-01-01

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them. PMID:29098954

TCGA4U: A Web-Based Genomic Analysis Platform To Explore And Mine TCGA Genomic Data For Translational Research.

PubMed

Huang, Zhenzhen; Duan, Huilong; Li, Haomin

2015-01-01

Large-scale human cancer genomics projects, such as TCGA, generated large genomics data for further study. Exploring and mining these data to obtain meaningful analysis results can help researchers find potential genomics alterations that intervene the development and metastasis of tumors. We developed a web-based gene analysis platform, named TCGA4U, which used statistics methods and models to help translational investigators explore, mine and visualize human cancer genomic characteristic information from the TCGA datasets. Furthermore, through Gene Ontology (GO) annotation and clinical data integration, the genomic data were transformed into biological process, molecular function, cellular component and survival curves to help researchers identify potential driver genes. Clinical researchers without expertise in data analysis will benefit from such a user-friendly genomic analysis platform.

The genome of black cottonwood, Populus trichocarpa (Torr. & Gray)

Treesearch

G.A. Tuskan; S. DiFazio; S. Jansson; J. Bohlmann; I. Grigoriev; U. Hellsten; N. Putnam; S. Ralph; S. Rombauts; A. Salamov; J. Schein; L. Sterck; A. Aerts; R.R. Bhalerao; R.P. Bhalerao; D. Blaudez; W. Boerjan; A. Brun; A. Brunner; V. Busov; M. Campbell; J. Carlson; M. Chalot; J. Chapman; G.-L. Chen; D. Cooper; P.M. Coutinho; J. Couturier; S. Covert; Q. Cronk; R. Cunningham; J. Davis; S. Degroeve; A. Dejardin; C. dePamphilis; J. Detter; B. Dirks; U. Dubchak; S. Duplessis; J. Ehlting; B. Ellis; K. Gendler; D. Goodstein; M. Gribskov; J. Grimwood; A. Groover; L. Gunter; B. Hamberger; B. Heinze; Y. Helariutta; B. Henrissat; D. Holligan; R. Holt; W. Huang; N. Islam-Faridi; S. Jones; M. Jones-Rhoades; R. Jorgensen; C. Joshi; J. Kangasjarvi; J. Karlsson; C. Kelleher; R. Kirkpatrick; M. Kirst; A. Kohler; U. Kalluri; F. Larimer; J. Leebens-Mack; J.-C. Leple; P. Locascio; Y. Lou; S. Lucas; F. Martin; B. Montanini; C. Napoli; D.R. Nelson; C. Nelson; K. Nieminen; O. Nilsson; V. Pereda; G. Peter; R. Philippe; G. Pilate; A. Poliakov; J. Razumovskaya; P. Richardson; C. Rinaldi; K. Ritland; P. Rouze; D. Ryaboy; J. Schumtz; J. Schrader; B. Segerman; H. Shin; A. Siddiqui; F. Sterky; A. Terry; C.-J. Tsai; E. Uberbacher; P. Unneberg; J. Vahala; K. Wall; S. Wessler; G. Yang; T. Yin; C. Douglas; M. Marra; G. Sandberg; Y. Van de Peer; D. Rokhsar

2006-01-01

We report the draft genome of the black cottonwood tree, Populus trichocarpa. Integration of shotgun sequence assembly with genetic mapping enabled chromosome-scale reconstruction of the genome. More than 45,000 putative protein-coding genes were identified. Analysis of the assembled genome revealed a whole-genome duplication event; about 8000 pairs...

Analysis of Plasmodium falciparum diversity in natural infections by deep sequencing

PubMed Central

Manske, Magnus; Miotto, Olivo; Campino, Susana; Auburn, Sarah; Almagro-Garcia, Jacob; Maslen, Gareth; O’Brien, Jack; Djimde, Abdoulaye; Doumbo, Ogobara; Zongo, Issaka; Ouedraogo, Jean-Bosco; Michon, Pascal; Mueller, Ivo; Siba, Peter; Nzila, Alexis; Borrmann, Steffen; Kiara, Steven M.; Marsh, Kevin; Jiang, Hongying; Su, Xin-Zhuan; Amaratunga, Chanaki; Fairhurst, Rick; Socheat, Duong; Nosten, Francois; Imwong, Mallika; White, Nicholas J.; Sanders, Mandy; Anastasi, Elisa; Alcock, Dan; Drury, Eleanor; Oyola, Samuel; Quail, Michael A.; Turner, Daniel J.; Rubio, Valentin Ruano; Jyothi, Dushyanth; Amenga-Etego, Lucas; Hubbart, Christina; Jeffreys, Anna; Rowlands, Kate; Sutherland, Colin; Roper, Cally; Mangano, Valentina; Modiano, David; Tan, John C.; Ferdig, Michael T.; Amambua-Ngwa, Alfred; Conway, David J.; Takala-Harrison, Shannon; Plowe, Christopher V.; Rayner, Julian C.; Rockett, Kirk A.; Clark, Taane G.; Newbold, Chris I.; Berriman, Matthew; MacInnis, Bronwyn; Kwiatkowski, Dominic P.

2013-01-01

Malaria elimination strategies require surveillance of the parasite population for genetic changes that demand a public health response, such as new forms of drug resistance. 1,2 Here we describe methods for large-scale analysis of genetic variation in Plasmodium falciparum by deep sequencing of parasite DNA obtained from the blood of patients with malaria, either directly or after short term culture. Analysis of 86,158 exonic SNPs that passed genotyping quality control in 227 samples from Africa, Asia and Oceania provides genome-wide estimates of allele frequency distribution, population structure and linkage disequilibrium. By comparing the genetic diversity of individual infections with that of the local parasite population, we derive a metric of within-host diversity that is related to the level of inbreeding in the population. An open-access web application has been established for exploration of regional differences in allele frequency and of highly differentiated loci in the P. falciparum genome. PMID:22722859

Chemical biology on the genome.

PubMed

Balasubramanian, Shankar

2014-08-15

In this article I discuss studies towards understanding the structure and function of DNA in the context of genomes from the perspective of a chemist. The first area I describe concerns the studies that led to the invention and subsequent development of a method for sequencing DNA on a genome scale at high speed and low cost, now known as Solexa/Illumina sequencing. The second theme will feature the four-stranded DNA structure known as a G-quadruplex with a focus on its fundamental properties, its presence in cellular genomic DNA and the prospects for targeting such a structure in cels with small molecules. The final topic for discussion is naturally occurring chemically modified DNA bases with an emphasis on chemistry for decoding (or sequencing) such modifications in genomic DNA. The genome is a fruitful topic to be further elucidated by the creation and application of chemical approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.

Identifying structural variation in haploid microbial genomes from short-read resequencing data using breseq.

PubMed

Barrick, Jeffrey E; Colburn, Geoffrey; Deatherage, Daniel E; Traverse, Charles C; Strand, Matthew D; Borges, Jordan J; Knoester, David B; Reba, Aaron; Meyer, Austin G

2014-11-29

Mutations that alter chromosomal structure play critical roles in evolution and disease, including in the origin of new lifestyles and pathogenic traits in microbes. Large-scale rearrangements in genomes are often mediated by recombination events involving new or existing copies of mobile genetic elements, recently duplicated genes, or other repetitive sequences. Most current software programs for predicting structural variation from short-read DNA resequencing data are intended primarily for use on human genomes. They typically disregard information in reads mapping to repeat sequences, and significant post-processing and manual examination of their output is often required to rule out false-positive predictions and precisely describe mutational events. We have implemented an algorithm for identifying structural variation from DNA resequencing data as part of the breseq computational pipeline for predicting mutations in haploid microbial genomes. Our method evaluates the support for new sequence junctions present in a clonal sample from split-read alignments to a reference genome, including matches to repeat sequences. Then, it uses a statistical model of read coverage evenness to accept or reject these predictions. Finally, breseq combines predictions of new junctions and deleted chromosomal regions to output biologically relevant descriptions of mutations and their effects on genes. We demonstrate the performance of breseq on simulated Escherichia coli genomes with deletions generating unique breakpoint sequences, new insertions of mobile genetic elements, and deletions mediated by mobile elements. Then, we reanalyze data from an E. coli K-12 mutation accumulation evolution experiment in which structural variation was not previously identified. Transposon insertions and large-scale chromosomal changes detected by breseq account for ~25% of spontaneous mutations in this strain. In all cases, we find that breseq is able to reliably predict structural variation with modest read-depth coverage of the reference genome (>40-fold). Using breseq to predict structural variation should be useful for studies of microbial epidemiology, experimental evolution, synthetic biology, and genetics when a reference genome for a closely related strain is available. In these cases, breseq can discover mutations that may be responsible for important or unintended changes in genomes that might otherwise go undetected.

Newborn Sequencing in Genomic Medicine and Public Health

PubMed Central

Agrawal, Pankaj B.; Bailey, Donald B.; Beggs, Alan H.; Brenner, Steven E.; Brower, Amy M.; Cakici, Julie A.; Ceyhan-Birsoy, Ozge; Chan, Kee; Chen, Flavia; Currier, Robert J.; Dukhovny, Dmitry; Green, Robert C.; Harris-Wai, Julie; Holm, Ingrid A.; Iglesias, Brenda; Joseph, Galen; Kingsmore, Stephen F.; Koenig, Barbara A.; Kwok, Pui-Yan; Lantos, John; Leeder, Steven J.; Lewis, Megan A.; McGuire, Amy L.; Milko, Laura V.; Mooney, Sean D.; Parad, Richard B.; Pereira, Stacey; Petrikin, Joshua; Powell, Bradford C.; Powell, Cynthia M.; Puck, Jennifer M.; Rehm, Heidi L.; Risch, Neil; Roche, Myra; Shieh, Joseph T.; Veeraraghavan, Narayanan; Watson, Michael S.; Willig, Laurel; Yu, Timothy W.; Urv, Tiina; Wise, Anastasia L.

2017-01-01

The rapid development of genomic sequencing technologies has decreased the cost of genetic analysis to the extent that it seems plausible that genome-scale sequencing could have widespread availability in pediatric care. Genomic sequencing provides a powerful diagnostic modality for patients who manifest symptoms of monogenic disease and an opportunity to detect health conditions before their development. However, many technical, clinical, ethical, and societal challenges should be addressed before such technology is widely deployed in pediatric practice. This article provides an overview of the Newborn Sequencing in Genomic Medicine and Public Health Consortium, which is investigating the application of genome-scale sequencing in newborns for both diagnosis and screening. PMID:28096516

A New Perspective on Polyploid Fragaria (Strawberry) Genome Composition Based on Large-Scale, Multi-Locus Phylogenetic Analysis.

PubMed

Yang, Yilong; Davis, Thomas M

2017-12-01

The subgenomic compositions of the octoploid (2n = 8× = 56) strawberry (Fragaria) species, including the economically important cultivated species Fragaria x ananassa, have been a topic of long-standing interest. Phylogenomic approaches utilizing next-generation sequencing technologies offer a new window into species relationships and the subgenomic compositions of polyploids. We have conducted a large-scale phylogenetic analysis of Fragaria (strawberry) species using the Fluidigm Access Array system and 454 sequencing platform. About 24 single-copy or low-copy nuclear genes distributed across the genome were amplified and sequenced from 96 genomic DNA samples representing 16 Fragaria species from diploid (2×) to decaploid (10×), including the most extensive sampling of octoploid taxa yet reported. Individual gene trees were constructed by different tree-building methods. Mosaic genomic structures of diploid Fragaria species consisting of sequences at different phylogenetic positions were observed. Our findings support the presence in octoploid species of genetic signatures from at least five diploid ancestors (F. vesca, F. iinumae, F. bucharica, F. viridis, and at least one additional allele contributor of unknown identity), and questions the extent to which distinct subgenomes are preserved over evolutionary time in the allopolyploid Fragaria species. In addition, our data support divergence between the two wild octoploid species, F. virginiana and F. chiloensis. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Tomato functional genomics database (TFGD): a comprehensive collection and analysis package for tomato functional genomics

USDA-ARS?s Scientific Manuscript database

Tomato Functional Genomics Database (TFGD; http://ted.bti.cornell.edu) provides a comprehensive systems biology resource to store, mine, analyze, visualize and integrate large-scale tomato functional genomics datasets. The database is expanded from the previously described Tomato Expression Database...

An integrated 3-Dimensional Genome Modeling Engine for data-driven simulation of spatial genome organization.

PubMed

Szałaj, Przemysław; Tang, Zhonghui; Michalski, Paul; Pietal, Michal J; Luo, Oscar J; Sadowski, Michał; Li, Xingwang; Radew, Kamen; Ruan, Yijun; Plewczynski, Dariusz

2016-12-01

ChIA-PET is a high-throughput mapping technology that reveals long-range chromatin interactions and provides insights into the basic principles of spatial genome organization and gene regulation mediated by specific protein factors. Recently, we showed that a single ChIA-PET experiment provides information at all genomic scales of interest, from the high-resolution locations of binding sites and enriched chromatin interactions mediated by specific protein factors, to the low resolution of nonenriched interactions that reflect topological neighborhoods of higher-order chromosome folding. This multilevel nature of ChIA-PET data offers an opportunity to use multiscale 3D models to study structural-functional relationships at multiple length scales, but doing so requires a structural modeling platform. Here, we report the development of 3D-GNOME (3-Dimensional Genome Modeling Engine), a complete computational pipeline for 3D simulation using ChIA-PET data. 3D-GNOME consists of three integrated components: a graph-distance-based heat map normalization tool, a 3D modeling platform, and an interactive 3D visualization tool. Using ChIA-PET and Hi-C data derived from human B-lymphocytes, we demonstrate the effectiveness of 3D-GNOME in building 3D genome models at multiple levels, including the entire genome, individual chromosomes, and specific segments at megabase (Mb) and kilobase (kb) resolutions of single average and ensemble structures. Further incorporation of CTCF-motif orientation and high-resolution looping patterns in 3D simulation provided additional reliability of potential biologically plausible topological structures. © 2016 Szałaj et al.; Published by Cold Spring Harbor Laboratory Press.

Global Organization of a Positive-strand RNA Virus Genome

PubMed Central

Wu, Baodong; Grigull, Jörg; Ore, Moriam O.; Morin, Sylvie; White, K. Andrew

2013-01-01

The genomes of plus-strand RNA viruses contain many regulatory sequences and structures that direct different viral processes. The traditional view of these RNA elements are as local structures present in non-coding regions. However, this view is changing due to the discovery of regulatory elements in coding regions and functional long-range intra-genomic base pairing interactions. The ∼4.8 kb long RNA genome of the tombusvirus tomato bushy stunt virus (TBSV) contains these types of structural features, including six different functional long-distance interactions. We hypothesized that to achieve these multiple interactions this viral genome must utilize a large-scale organizational strategy and, accordingly, we sought to assess the global conformation of the entire TBSV genome. Atomic force micrographs of the genome indicated a mostly condensed structure composed of interconnected protrusions extending from a central hub. This configuration was consistent with the genomic secondary structure model generated using high-throughput selective 2′-hydroxyl acylation analysed by primer extension (i.e. SHAPE), which predicted different sized RNA domains originating from a central region. Known RNA elements were identified in both domain and inter-domain regions, and novel structural features were predicted and functionally confirmed. Interestingly, only two of the six long-range interactions known to form were present in the structural model. However, for those interactions that did not form, complementary partner sequences were positioned relatively close to each other in the structure, suggesting that the secondary structure level of viral genome structure could provide a basic scaffold for the formation of different long-range interactions. The higher-order structural model for the TBSV RNA genome provides a snapshot of the complex framework that allows multiple functional components to operate in concert within a confined context. PMID:23717202

Predicting chromatin architecture from models of polymer physics.

PubMed

Bianco, Simona; Chiariello, Andrea M; Annunziatella, Carlo; Esposito, Andrea; Nicodemi, Mario

2017-03-01

We review the picture of chromatin large-scale 3D organization emerging from the analysis of Hi-C data and polymer modeling. In higher mammals, Hi-C contact maps reveal a complex higher-order organization, extending from the sub-Mb to chromosomal scales, hierarchically folded in a structure of domains-within-domains (metaTADs). The domain folding hierarchy is partially conserved throughout differentiation, and deeply correlated to epigenomic features. Rearrangements in the metaTAD topology relate to gene expression modifications: in particular, in neuronal differentiation models, topologically associated domains (TADs) tend to have coherent expression changes within architecturally conserved metaTAD niches. To identify the nature of architectural domains and their molecular determinants within a principled approach, we discuss models based on polymer physics. We show that basic concepts of interacting polymer physics explain chromatin spatial organization across chromosomal scales and cell types. The 3D structure of genomic loci can be derived with high accuracy and its molecular determinants identified by crossing information with epigenomic databases. In particular, we illustrate the case of the Sox9 locus, linked to human congenital disorders. The model in-silico predictions on the effects of genomic rearrangements are confirmed by available 5C data. That can help establishing new diagnostic tools for diseases linked to chromatin mis-folding, such as congenital disorders and cancer.

A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation

PubMed Central

2012-01-01

Background Efficient, robust, and accurate genotype imputation algorithms make large-scale application of genomic selection cost effective. An algorithm that imputes alleles or allele probabilities for all animals in the pedigree and for all genotyped single nucleotide polymorphisms (SNP) provides a framework to combine all pedigree, genomic, and phenotypic information into a single-stage genomic evaluation. Methods An algorithm was developed for imputation of genotypes in pedigreed populations that allows imputation for completely ungenotyped animals and for low-density genotyped animals, accommodates a wide variety of pedigree structures for genotyped animals, imputes unmapped SNP, and works for large datasets. The method involves simple phasing rules, long-range phasing and haplotype library imputation and segregation analysis. Results Imputation accuracy was high and computational cost was feasible for datasets with pedigrees of up to 25 000 animals. The resulting single-stage genomic evaluation increased the accuracy of estimated genomic breeding values compared to a scenario in which phenotypes on relatives that were not genotyped were ignored. Conclusions The developed imputation algorithm and software and the resulting single-stage genomic evaluation method provide powerful new ways to exploit imputation and to obtain more accurate genetic evaluations. PMID:22462519

Comparative Analysis of Genome Diversity in Bullmastiff Dogs

PubMed Central

Mortlock, Sally-Anne; Khatkar, Mehar S.; Williamson, Peter

2016-01-01

Management and preservation of genomic diversity in dog breeds is a major objective for maintaining health. The present study was undertaken to characterise genomic diversity in Bullmastiff dogs using both genealogical and molecular analysis. Genealogical analysis of diversity was conducted using a database consisting of 16,378 Bullmastiff pedigrees from year 1980 to 2013. Additionally, a total of 188 Bullmastiff dogs were genotyped using the 170,000 SNP Illumina CanineHD Beadchip. Genealogical parameters revealed a mean inbreeding coefficient of 0.047; 142 total founders (f); an effective number of founders (fe) of 79; an effective number of ancestors (fa) of 62; and an effective population size of the reference population of 41. Genetic diversity and the degree of genome-wide homogeneity within the breed were also investigated using molecular data. Multiple-locus heterozygosity (MLH) was equal to 0.206; runs of homozygosity (ROH) as proportion of the genome, averaged 16.44%; effective population size was 29.1, with an average inbreeding coefficient of 0.035, all estimated using SNP Data. Fine-scale population structure was analysed using NETVIEW, a population analysis pipeline. Visualisation of the high definition network captured relationships among individuals within and between subpopulations. Effects of unequal founder use, and ancestral inbreeding and selection, were evident. While current levels of Bullmastiff heterozygosity, inbreeding and homozygosity are not unusual, a relatively small effective population size indicates that a breeding strategy to reduce the inbreeding rate may be beneficial. PMID:26824579

Exploring metabolic pathways in genome-scale networks via generating flux modes.

PubMed

Rezola, A; de Figueiredo, L F; Brock, M; Pey, J; Podhorski, A; Wittmann, C; Schuster, S; Bockmayr, A; Planes, F J

2011-02-15

The reconstruction of metabolic networks at the genome scale has allowed the analysis of metabolic pathways at an unprecedented level of complexity. Elementary flux modes (EFMs) are an appropriate concept for such analysis. However, their number grows in a combinatorial fashion as the size of the metabolic network increases, which renders the application of EFMs approach to large metabolic networks difficult. Novel methods are expected to deal with such complexity. In this article, we present a novel optimization-based method for determining a minimal generating set of EFMs, i.e. a convex basis. We show that a subset of elements of this convex basis can be effectively computed even in large metabolic networks. Our method was applied to examine the structure of pathways producing lysine in Escherichia coli. We obtained a more varied and informative set of pathways in comparison with existing methods. In addition, an alternative pathway to produce lysine was identified using a detour via propionyl-CoA, which shows the predictive power of our novel approach. The source code in C++ is available upon request.

Optimization of oligonucleotide arrays and RNA amplification protocols for analysis of transcript structure and alternative splicing.

PubMed

Castle, John; Garrett-Engele, Phil; Armour, Christopher D; Duenwald, Sven J; Loerch, Patrick M; Meyer, Michael R; Schadt, Eric E; Stoughton, Roland; Parrish, Mark L; Shoemaker, Daniel D; Johnson, Jason M

2003-01-01

Microarrays offer a high-resolution means for monitoring pre-mRNA splicing on a genomic scale. We have developed a novel, unbiased amplification protocol that permits labeling of entire transcripts. Also, hybridization conditions, probe characteristics, and analysis algorithms were optimized for detection of exons, exon-intron edges, and exon junctions. These optimized protocols can be used to detect small variations and isoform mixtures, map the tissue specificity of known human alternative isoforms, and provide a robust, scalable platform for high-throughput discovery of alternative splicing.

Optimization of oligonucleotide arrays and RNA amplification protocols for analysis of transcript structure and alternative splicing

PubMed Central

Castle, John; Garrett-Engele, Phil; Armour, Christopher D; Duenwald, Sven J; Loerch, Patrick M; Meyer, Michael R; Schadt, Eric E; Stoughton, Roland; Parrish, Mark L; Shoemaker, Daniel D; Johnson, Jason M

2003-01-01

Microarrays offer a high-resolution means for monitoring pre-mRNA splicing on a genomic scale. We have developed a novel, unbiased amplification protocol that permits labeling of entire transcripts. Also, hybridization conditions, probe characteristics, and analysis algorithms were optimized for detection of exons, exon-intron edges, and exon junctions. These optimized protocols can be used to detect small variations and isoform mixtures, map the tissue specificity of known human alternative isoforms, and provide a robust, scalable platform for high-throughput discovery of alternative splicing. PMID:14519201

The role of internal duplication in the evolution of multi-domain proteins.

PubMed

Nacher, J C; Hayashida, M; Akutsu, T

2010-08-01

Many proteins consist of several structural domains. These multi-domain proteins have likely been generated by selective genome growth dynamics during evolution to perform new functions as well as to create structures that fold on a biologically feasible time scale. Domain units frequently evolved through a variety of genetic shuffling mechanisms. Here we examine the protein domain statistics of more than 1000 organisms including eukaryotic, archaeal and bacterial species. The analysis extends earlier findings on asymmetric statistical laws for proteome to a wider variety of species. While proteins are composed of a wide range of domains, displaying a power-law decay, the computation of domain families for each protein reveals an exponential distribution, characterizing a protein universe composed of a thin number of unique families. Structural studies in proteomics have shown that domain repeats, or internal duplicated domains, represent a small but significant fraction of genome. In spite of its importance, this observation has been largely overlooked until recently. We model the evolutionary dynamics of proteome and demonstrate that these distinct distributions are in fact rooted in an internal duplication mechanism. This process generates the contemporary protein structural domain universe, determines its reduced thickness, and tames its growth. These findings have important implications, ranging from protein interaction network modeling to evolutionary studies based on fundamental mechanisms governing genome expansion.

Pattern Analysis and Decision Support for Cancer through Clinico-Genomic Profiles

NASA Astrophysics Data System (ADS)

Exarchos, Themis P.; Giannakeas, Nikolaos; Goletsis, Yorgos; Papaloukas, Costas; Fotiadis, Dimitrios I.

Advances in genome technology are playing a growing role in medicine and healthcare. With the development of new technologies and opportunities for large-scale analysis of the genome, genomic data have a clear impact on medicine. Cancer prognostics and therapeutics are among the first major test cases for genomic medicine, given that all types of cancer are related with genomic instability. In this paper we present a novel system for pattern analysis and decision support in cancer. The system integrates clinical data from electronic health records and genomic data. Pattern analysis and data mining methods are applied to these integrated data and the discovered knowledge is used for cancer decision support. Through this integration, conclusions can be drawn for early diagnosis, staging and cancer treatment.

Multiscale Embedded Gene Co-expression Network Analysis

PubMed Central

Song, Won-Min; Zhang, Bin

2015-01-01

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma. PMID:26618778

Multiscale Embedded Gene Co-expression Network Analysis.

PubMed

Song, Won-Min; Zhang, Bin

2015-11-01

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

Studies on cattle genomic structural variation provide insights into ruminant speciation and adaptation

USDA-ARS?s Scientific Manuscript database

Genomic structural variations, including segmental duplications (SD) and copy number variations (CNV), contribute significantly to individual health and disease in primates and rodents. As a part of the bovine genome annotation effort, we performed the first genome-wide analysis of SD in cattle usin...

The Dockstore: enabling modular, community-focused sharing of Docker-based genomics tools and workflows

PubMed Central

O'Connor, Brian D.; Yuen, Denis; Chung, Vincent; Duncan, Andrew G.; Liu, Xiang Kun; Patricia, Janice; Paten, Benedict; Stein, Lincoln; Ferretti, Vincent

2017-01-01

As genomic datasets continue to grow, the feasibility of downloading data to a local organization and running analysis on a traditional compute environment is becoming increasingly problematic. Current large-scale projects, such as the ICGC PanCancer Analysis of Whole Genomes (PCAWG), the Data Platform for the U.S. Precision Medicine Initiative, and the NIH Big Data to Knowledge Center for Translational Genomics, are using cloud-based infrastructure to both host and perform analysis across large data sets. In PCAWG, over 5,800 whole human genomes were aligned and variant called across 14 cloud and HPC environments; the processed data was then made available on the cloud for further analysis and sharing. If run locally, an operation at this scale would have monopolized a typical academic data centre for many months, and would have presented major challenges for data storage and distribution. However, this scale is increasingly typical for genomics projects and necessitates a rethink of how analytical tools are packaged and moved to the data. For PCAWG, we embraced the use of highly portable Docker images for encapsulating and sharing complex alignment and variant calling workflows across highly variable environments. While successful, this endeavor revealed a limitation in Docker containers, namely the lack of a standardized way to describe and execute the tools encapsulated inside the container. As a result, we created the Dockstore ( https://dockstore.org), a project that brings together Docker images with standardized, machine-readable ways of describing and running the tools contained within. This service greatly improves the sharing and reuse of genomics tools and promotes interoperability with similar projects through emerging web service standards developed by the Global Alliance for Genomics and Health (GA4GH). PMID:28344774

The Dockstore: enabling modular, community-focused sharing of Docker-based genomics tools and workflows.

PubMed

O'Connor, Brian D; Yuen, Denis; Chung, Vincent; Duncan, Andrew G; Liu, Xiang Kun; Patricia, Janice; Paten, Benedict; Stein, Lincoln; Ferretti, Vincent

2017-01-01

As genomic datasets continue to grow, the feasibility of downloading data to a local organization and running analysis on a traditional compute environment is becoming increasingly problematic. Current large-scale projects, such as the ICGC PanCancer Analysis of Whole Genomes (PCAWG), the Data Platform for the U.S. Precision Medicine Initiative, and the NIH Big Data to Knowledge Center for Translational Genomics, are using cloud-based infrastructure to both host and perform analysis across large data sets. In PCAWG, over 5,800 whole human genomes were aligned and variant called across 14 cloud and HPC environments; the processed data was then made available on the cloud for further analysis and sharing. If run locally, an operation at this scale would have monopolized a typical academic data centre for many months, and would have presented major challenges for data storage and distribution. However, this scale is increasingly typical for genomics projects and necessitates a rethink of how analytical tools are packaged and moved to the data. For PCAWG, we embraced the use of highly portable Docker images for encapsulating and sharing complex alignment and variant calling workflows across highly variable environments. While successful, this endeavor revealed a limitation in Docker containers, namely the lack of a standardized way to describe and execute the tools encapsulated inside the container. As a result, we created the Dockstore ( https://dockstore.org), a project that brings together Docker images with standardized, machine-readable ways of describing and running the tools contained within. This service greatly improves the sharing and reuse of genomics tools and promotes interoperability with similar projects through emerging web service standards developed by the Global Alliance for Genomics and Health (GA4GH).

An object model and database for functional genomics.

PubMed

Jones, Andrew; Hunt, Ela; Wastling, Jonathan M; Pizarro, Angel; Stoeckert, Christian J

2004-07-10

Large-scale functional genomics analysis is now feasible and presents significant challenges in data analysis, storage and querying. Data standards are required to enable the development of public data repositories and to improve data sharing. There is an established data format for microarrays (microarray gene expression markup language, MAGE-ML) and a draft standard for proteomics (PEDRo). We believe that all types of functional genomics experiments should be annotated in a consistent manner, and we hope to open up new ways of comparing multiple datasets used in functional genomics. We have created a functional genomics experiment object model (FGE-OM), developed from the microarray model, MAGE-OM and two models for proteomics, PEDRo and our own model (Gla-PSI-Glasgow Proposal for the Proteomics Standards Initiative). FGE-OM comprises three namespaces representing (i) the parts of the model common to all functional genomics experiments; (ii) microarray-specific components; and (iii) proteomics-specific components. We believe that FGE-OM should initiate discussion about the contents and structure of the next version of MAGE and the future of proteomics standards. A prototype database called RNA And Protein Abundance Database (RAPAD), based on FGE-OM, has been implemented and populated with data from microbial pathogenesis. FGE-OM and the RAPAD schema are available from http://www.gusdb.org/fge.html, along with a set of more detailed diagrams. RAPAD can be accessed by registration at the site.

The pangenome of the genus Clostridium.

PubMed

Udaondo, Zulema; Duque, Estrella; Ramos, Juan-Luis

2017-07-01

The pangenome for the genus Clostridium sensu stricto, which was obtained using highly curated and annotated genomes from 16 species is presented; some of these cause disease, while others are used for the production of added-value chemicals. Multilocus sequencing analysis revealed that species of this genus group into at least two clades that include non-pathogenic and pathogenic strains, suggesting that pathogenicity is dispersed across the phylogenetic tree. The core genome of the genus includes 546 protein families, which mainly comprise those involved in protein translation and DNA repair. The GS-GOGAT may represent the central pathway for generating organic nitrogen from inorganic nitrogen sources. Glycerol and glucose metabolism genes are well represented in the core genome together with a set of energy conservation systems. A metabolic network comprising proteins/enzymes, RNAs and metabolites, whose topological structure is a non-random and scale-free network with hierarchically structured modules was built. These modules shed light on the interactions between RNAs, proteins and metabolites, revealing biological features of transcription and translation, cell wall biosynthesis, C1 metabolism and N metabolism. Network analysis identified four nodes that function as hubs and bottlenecks, namely, coenzyme A, HPr kinases, S-adenosylmethionine and the ribonuclease P-protein, suggesting pivotal roles for them in Clostridium. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

Newborn Sequencing in Genomic Medicine and Public Health.

PubMed

Berg, Jonathan S; Agrawal, Pankaj B; Bailey, Donald B; Beggs, Alan H; Brenner, Steven E; Brower, Amy M; Cakici, Julie A; Ceyhan-Birsoy, Ozge; Chan, Kee; Chen, Flavia; Currier, Robert J; Dukhovny, Dmitry; Green, Robert C; Harris-Wai, Julie; Holm, Ingrid A; Iglesias, Brenda; Joseph, Galen; Kingsmore, Stephen F; Koenig, Barbara A; Kwok, Pui-Yan; Lantos, John; Leeder, Steven J; Lewis, Megan A; McGuire, Amy L; Milko, Laura V; Mooney, Sean D; Parad, Richard B; Pereira, Stacey; Petrikin, Joshua; Powell, Bradford C; Powell, Cynthia M; Puck, Jennifer M; Rehm, Heidi L; Risch, Neil; Roche, Myra; Shieh, Joseph T; Veeraraghavan, Narayanan; Watson, Michael S; Willig, Laurel; Yu, Timothy W; Urv, Tiina; Wise, Anastasia L

2017-02-01

The rapid development of genomic sequencing technologies has decreased the cost of genetic analysis to the extent that it seems plausible that genome-scale sequencing could have widespread availability in pediatric care. Genomic sequencing provides a powerful diagnostic modality for patients who manifest symptoms of monogenic disease and an opportunity to detect health conditions before their development. However, many technical, clinical, ethical, and societal challenges should be addressed before such technology is widely deployed in pediatric practice. This article provides an overview of the Newborn Sequencing in Genomic Medicine and Public Health Consortium, which is investigating the application of genome-scale sequencing in newborns for both diagnosis and screening. Copyright © 2017 by the American Academy of Pediatrics.

Producing genome structure populations with the dynamic and automated PGS software.

PubMed

Hua, Nan; Tjong, Harianto; Shin, Hanjun; Gong, Ke; Zhou, Xianghong Jasmine; Alber, Frank

2018-05-01

Chromosome conformation capture technologies such as Hi-C are widely used to investigate the spatial organization of genomes. Because genome structures can vary considerably between individual cells of a population, interpreting ensemble-averaged Hi-C data can be challenging, in particular for long-range and interchromosomal interactions. We pioneered a probabilistic approach for the generation of a population of distinct diploid 3D genome structures consistent with all the chromatin-chromatin interaction probabilities from Hi-C experiments. Each structure in the population is a physical model of the genome in 3D. Analysis of these models yields new insights into the causes and the functional properties of the genome's organization in space and time. We provide a user-friendly software package, called PGS, which runs on local machines (for practice runs) and high-performance computing platforms. PGS takes a genome-wide Hi-C contact frequency matrix, along with information about genome segmentation, and produces an ensemble of 3D genome structures entirely consistent with the input. The software automatically generates an analysis report, and provides tools to extract and analyze the 3D coordinates of specific domains. Basic Linux command-line knowledge is sufficient for using this software. A typical running time of the pipeline is ∼3 d with 300 cores on a computer cluster to generate a population of 1,000 diploid genome structures at topological-associated domain (TAD)-level resolution.

Scalable and cost-effective NGS genotyping in the cloud.

PubMed

Souilmi, Yassine; Lancaster, Alex K; Jung, Jae-Yoon; Rizzo, Ettore; Hawkins, Jared B; Powles, Ryan; Amzazi, Saaïd; Ghazal, Hassan; Tonellato, Peter J; Wall, Dennis P

2015-10-15

While next-generation sequencing (NGS) costs have plummeted in recent years, cost and complexity of computation remain substantial barriers to the use of NGS in routine clinical care. The clinical potential of NGS will not be realized until robust and routine whole genome sequencing data can be accurately rendered to medically actionable reports within a time window of hours and at scales of economy in the 10's of dollars. We take a step towards addressing this challenge, by using COSMOS, a cloud-enabled workflow management system, to develop GenomeKey, an NGS whole genome analysis workflow. COSMOS implements complex workflows making optimal use of high-performance compute clusters. Here we show that the Amazon Web Service (AWS) implementation of GenomeKey via COSMOS provides a fast, scalable, and cost-effective analysis of both public benchmarking and large-scale heterogeneous clinical NGS datasets. Our systematic benchmarking reveals important new insights and considerations to produce clinical turn-around of whole genome analysis optimization and workflow management including strategic batching of individual genomes and efficient cluster resource configuration.

Co-evolutionary Analysis of Domains in Interacting Proteins Reveals Insights into Domain–Domain Interactions Mediating Protein–Protein Interactions

PubMed Central

Jothi, Raja; Cherukuri, Praveen F.; Tasneem, Asba; Przytycka, Teresa M.

2006-01-01

Recent advances in functional genomics have helped generate large-scale high-throughput protein interaction data. Such networks, though extremely valuable towards molecular level understanding of cells, do not provide any direct information about the regions (domains) in the proteins that mediate the interaction. Here, we performed co-evolutionary analysis of domains in interacting proteins in order to understand the degree of co-evolution of interacting and non-interacting domains. Using a combination of sequence and structural analysis, we analyzed protein–protein interactions in F1-ATPase, Sec23p/Sec24p, DNA-directed RNA polymerase and nuclear pore complexes, and found that interacting domain pair(s) for a given interaction exhibits higher level of co-evolution than the noninteracting domain pairs. Motivated by this finding, we developed a computational method to test the generality of the observed trend, and to predict large-scale domain–domain interactions. Given a protein–protein interaction, the proposed method predicts the domain pair(s) that is most likely to mediate the protein interaction. We applied this method on the yeast interactome to predict domain–domain interactions, and used known domain–domain interactions found in PDB crystal structures to validate our predictions. Our results show that the prediction accuracy of the proposed method is statistically significant. Comparison of our prediction results with those from two other methods reveals that only a fraction of predictions are shared by all the three methods, indicating that the proposed method can detect known interactions missed by other methods. We believe that the proposed method can be used with other methods to help identify previously unrecognized domain–domain interactions on a genome scale, and could potentially help reduce the search space for identifying interaction sites. PMID:16949097

Complete Genomic Sequence and Comparative Analysis of the Genome Segments of Sweet Potato Chlorotic Stunt Virus in China

PubMed Central

Qin, Yanhong; Wang, Li; Zhang, Zhenchen; Qiao, Qi; Zhang, Desheng; Tian, Yuting; Wang, Shuang; Wang, Yongjiang; Yan, Zhaoling

2014-01-01

Background Sweet potato chlorotic stunt virus (family Closteroviridae, genus Crinivirus) features a large bipartite, single-stranded, positive-sense RNA genome. To date, only three complete genomic sequences of SPCSV can be accessed through GenBank. SPCSV was first detected from China in 2011, only partial genomic sequences have been determined in the country. No report on the complete genomic sequence and genome structure of Chinese SPCSV isolates or the genetic relation between isolates from China and other countries is available. Methodology/Principal Findings The complete genomic sequences of five isolates from different areas in China were characterized. This study is the first to report the complete genome sequences of SPCSV from whitefly vectors. Genome structure analysis showed that isolates of WA and EA strains from China have the same coding protein as isolates Can181-9 and m2-47, respectively. Twenty cp genes and four RNA1 partial segments were sequenced and analyzed, and the nucleotide identities of complete genomic, cp, and RNA1 partial sequences were determined. Results indicated high conservation among strains and significant differences between WA and EA strains. Genetic analysis demonstrated that, except for isolates from Guangdong Province, SPCSVs from other areas belong to the WA strain. Genome organization analysis showed that the isolates in this study lack the p22 gene. Conclusions/Significance We presented the complete genome sequences of SPCSV in China. Comparison of nucleotide identities and genome structures between these isolates and previously reported isolates showed slight differences. The nucleotide identities of different SPCSV isolates showed high conservation among strains and significant differences between strains. All nine isolates in this study lacked p22 gene. WA strains were more extensively distributed than EA strains in China. These data provide important insights into the molecular variation and genomic structure of SPCSV in China as well as genetic relationships among isolates from China and other countries. PMID:25170926

Large-Scale Genomic Analysis of Codon Usage in Dengue Virus and Evaluation of Its Phylogenetic Dependence

PubMed Central

Lara-Ramírez, Edgar E.; Salazar, Ma Isabel; López-López, María de Jesús; Salas-Benito, Juan Santiago; Sánchez-Varela, Alejandro

2014-01-01

The increasing number of dengue virus (DENV) genome sequences available allows identifying the contributing factors to DENV evolution. In the present study, the codon usage in serotypes 1–4 (DENV1–4) has been explored for 3047 sequenced genomes using different statistics methods. The correlation analysis of total GC content (GC) with GC content at the three nucleotide positions of codons (GC1, GC2, and GC3) as well as the effective number of codons (ENC, ENCp) versus GC3 plots revealed mutational bias and purifying selection pressures as the major forces influencing the codon usage, but with distinct pressure on specific nucleotide position in the codon. The correspondence analysis (CA) and clustering analysis on relative synonymous codon usage (RSCU) within each serotype showed similar clustering patterns to the phylogenetic analysis of nucleotide sequences for DENV1–4. These clustering patterns are strongly related to the virus geographic origin. The phylogenetic dependence analysis also suggests that stabilizing selection acts on the codon usage bias. Our analysis of a large scale reveals new feature on DENV genomic evolution. PMID:25136631

Efficient population-scale variant analysis and prioritization with VAPr.

PubMed

Birmingham, Amanda; Mark, Adam M; Mazzaferro, Carlo; Xu, Guorong; Fisch, Kathleen M

2018-04-06

With the growing availability of population-scale whole-exome and whole-genome sequencing, demand for reproducible, scalable variant analysis has spread within genomic research communities. To address this need, we introduce the Python package VAPr (Variant Analysis and Prioritization). VAPr leverages existing annotation tools ANNOVAR and MyVariant.info with MongoDB-based flexible storage and filtering functionality. It offers biologists and bioinformatics generalists easy-to-use and scalable analysis and prioritization of genomic variants from large cohort studies. VAPr is developed in Python and is available for free use and extension under the MIT License. An install package is available on PyPi at https://pypi.python.org/pypi/VAPr, while source code and extensive documentation are on GitHub at https://github.com/ucsd-ccbb/VAPr. kfisch@ucsd.edu.

Visualization of RNA structure models within the Integrative Genomics Viewer.

PubMed

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.

Quantitative phenotyping via deep barcode sequencing.

PubMed

Smith, Andrew M; Heisler, Lawrence E; Mellor, Joseph; Kaper, Fiona; Thompson, Michael J; Chee, Mark; Roth, Frederick P; Giaever, Guri; Nislow, Corey

2009-10-01

Next-generation DNA sequencing technologies have revolutionized diverse genomics applications, including de novo genome sequencing, SNP detection, chromatin immunoprecipitation, and transcriptome analysis. Here we apply deep sequencing to genome-scale fitness profiling to evaluate yeast strain collections in parallel. This method, Barcode analysis by Sequencing, or "Bar-seq," outperforms the current benchmark barcode microarray assay in terms of both dynamic range and throughput. When applied to a complex chemogenomic assay, Bar-seq quantitatively identifies drug targets, with performance superior to the benchmark microarray assay. We also show that Bar-seq is well-suited for a multiplex format. We completely re-sequenced and re-annotated the yeast deletion collection using deep sequencing, found that approximately 20% of the barcodes and common priming sequences varied from expectation, and used this revised list of barcode sequences to improve data quality. Together, this new assay and analysis routine provide a deep-sequencing-based toolkit for identifying gene-environment interactions on a genome-wide scale.

Launching genomics into the cloud: deployment of Mercury, a next generation sequence analysis pipeline.

PubMed

Reid, Jeffrey G; Carroll, Andrew; Veeraraghavan, Narayanan; Dahdouli, Mahmoud; Sundquist, Andreas; English, Adam; Bainbridge, Matthew; White, Simon; Salerno, William; Buhay, Christian; Yu, Fuli; Muzny, Donna; Daly, Richard; Duyk, Geoff; Gibbs, Richard A; Boerwinkle, Eric

2014-01-29

Massively parallel DNA sequencing generates staggering amounts of data. Decreasing cost, increasing throughput, and improved annotation have expanded the diversity of genomics applications in research and clinical practice. This expanding scale creates analytical challenges: accommodating peak compute demand, coordinating secure access for multiple analysts, and sharing validated tools and results. To address these challenges, we have developed the Mercury analysis pipeline and deployed it in local hardware and the Amazon Web Services cloud via the DNAnexus platform. Mercury is an automated, flexible, and extensible analysis workflow that provides accurate and reproducible genomic results at scales ranging from individuals to large cohorts. By taking advantage of cloud computing and with Mercury implemented on the DNAnexus platform, we have demonstrated a powerful combination of a robust and fully validated software pipeline and a scalable computational resource that, to date, we have applied to more than 10,000 whole genome and whole exome samples.

Deep ancestry of programmed genome rearrangement in lampreys.

PubMed

Timoshevskiy, Vladimir A; Lampman, Ralph T; Hess, Jon E; Porter, Laurie L; Smith, Jeramiah J

2017-09-01

In most multicellular organisms, the structure and content of the genome is rigorously maintained over the course of development. However some species have evolved genome biologies that permit, or require, developmentally regulated changes in the physical structure and content of the genome (programmed genome rearrangement: PGR). Relatively few vertebrates are known to undergo PGR, although all agnathans surveyed to date (several hagfish and one lamprey: Petromyzon marinus) show evidence of large scale PGR. To further resolve the ancestry of PGR within vertebrates, we developed probes that allow simultaneous tracking of nearly all sequences eliminated by PGR in P. marinus and a second lamprey species (Entosphenus tridentatus). These comparative analyses reveal conserved subcellular structures (lagging chromatin and micronuclei) associated with PGR and provide the first comparative embryological evidence in support of the idea that PGR represents an ancient and evolutionarily stable strategy for regulating inherent developmental/genetic conflicts between germline and soma. Copyright © 2017 Elsevier Inc. All rights reserved.

Biogeography of the Sulfolobus islandicus pan-genome

PubMed Central

Reno, Michael L.; Held, Nicole L.; Fields, Christopher J.; Burke, Patricia V.; Whitaker, Rachel J.

2009-01-01

Variation in gene content has been hypothesized to be the primary mode of adaptive evolution in microorganisms; however, very little is known about the spatial and temporal distribution of variable genes. Through population-scale comparative genomics of 7 Sulfolobus islandicus genomes from 3 locations, we demonstrate the biogeographical structure of the pan-genome of this species, with no evidence of gene flow between geographically isolated populations. The evolutionary independence of each population allowed us to assess genome dynamics over very recent evolutionary time, beginning ≈910,000 years ago. On this time scale, genome variation largely consists of recent strain-specific integration of mobile elements. Localized sectors of parallel gene loss are identified; however, the balance between the gain and loss of genetic material suggests that S. islandicus genomes acquire material slowly over time, primarily from closely related Sulfolobus species. Examination of the genome dynamics through population genomics in S. islandicus exposes the process of allopatric speciation in thermophilic Archaea and brings us closer to a generalized framework for understanding microbial genome evolution in a spatial context. PMID:19435847

Evidence for Sequential and Increasing Activation of Replication Origins along Replication Timing Gradients in the Human Genome

PubMed Central

Guilbaud, Guillaume; Rappailles, Aurélien; Baker, Antoine; Chen, Chun-Long; Arneodo, Alain; Goldar, Arach; d'Aubenton-Carafa, Yves; Thermes, Claude; Audit, Benjamin; Hyrien, Olivier

2011-01-01

Genome-wide replication timing studies have suggested that mammalian chromosomes consist of megabase-scale domains of coordinated origin firing separated by large originless transition regions. Here, we report a quantitative genome-wide analysis of DNA replication kinetics in several human cell types that contradicts this view. DNA combing in HeLa cells sorted into four temporal compartments of S phase shows that replication origins are spaced at 40 kb intervals and fire as small clusters whose synchrony increases during S phase and that replication fork velocity (mean 0.7 kb/min, maximum 2.0 kb/min) remains constant and narrowly distributed through S phase. However, multi-scale analysis of a genome-wide replication timing profile shows a broad distribution of replication timing gradients with practically no regions larger than 100 kb replicating at less than 2 kb/min. Therefore, HeLa cells lack large regions of unidirectional fork progression. Temporal transition regions are replicated by sequential activation of origins at a rate that increases during S phase and replication timing gradients are set by the delay and the spacing between successive origin firings rather than by the velocity of single forks. Activation of internal origins in a specific temporal transition region is directly demonstrated by DNA combing of the IGH locus in HeLa cells. Analysis of published origin maps in HeLa cells and published replication timing and DNA combing data in several other cell types corroborate these findings, with the interesting exception of embryonic stem cells where regions of unidirectional fork progression seem more abundant. These results can be explained if origins fire independently of each other but under the control of long-range chromatin structure, or if replication forks progressing from early origins stimulate initiation in nearby unreplicated DNA. These findings shed a new light on the replication timing program of mammalian genomes and provide a general model for their replication kinetics. PMID:22219720

Genome-scale rates of evolutionary change in bacteria

PubMed Central

Duchêne, Sebastian; Holt, Kathryn E.; Weill, François-Xavier; Le Hello, Simon; Hawkey, Jane; Edwards, David J.; Fourment, Mathieu

2016-01-01

Estimating the rates at which bacterial genomes evolve is critical to understanding major evolutionary and ecological processes such as disease emergence, long-term host–pathogen associations and short-term transmission patterns. The surge in bacterial genomic data sets provides a new opportunity to estimate these rates and reveal the factors that shape bacterial evolutionary dynamics. For many organisms estimates of evolutionary rate display an inverse association with the time-scale over which the data are sampled. However, this relationship remains unexplored in bacteria due to the difficulty in estimating genome-wide evolutionary rates, which are impacted by the extent of temporal structure in the data and the prevalence of recombination. We collected 36 whole genome sequence data sets from 16 species of bacterial pathogens to systematically estimate and compare their evolutionary rates and assess the extent of temporal structure in the absence of recombination. The majority (28/36) of data sets possessed sufficient clock-like structure to robustly estimate evolutionary rates. However, in some species reliable estimates were not possible even with ‘ancient DNA’ data sampled over many centuries, suggesting that they evolve very slowly or that they display extensive rate variation among lineages. The robustly estimated evolutionary rates spanned several orders of magnitude, from approximately 10−5 to 10−8 nucleotide substitutions per site year−1. This variation was negatively associated with sampling time, with this relationship best described by an exponential decay curve. To avoid potential estimation biases, such time-dependency should be considered when inferring evolutionary time-scales in bacteria. PMID:28348834

Effective normalization for copy number variation detection from whole genome sequencing.

PubMed

Janevski, Angel; Varadan, Vinay; Kamalakaran, Sitharthan; Banerjee, Nilanjana; Dimitrova, Nevenka

2012-01-01

Whole genome sequencing enables a high resolution view of the human genome and provides unique insights into genome structure at an unprecedented scale. There have been a number of tools to infer copy number variation in the genome. These tools, while validated, also include a number of parameters that are configurable to genome data being analyzed. These algorithms allow for normalization to account for individual and population-specific effects on individual genome CNV estimates but the impact of these changes on the estimated CNVs is not well characterized. We evaluate in detail the effect of normalization methodologies in two CNV algorithms FREEC and CNV-seq using whole genome sequencing data from 8 individuals spanning four populations. We apply FREEC and CNV-seq to a sequencing data set consisting of 8 genomes. We use multiple configurations corresponding to different read-count normalization methodologies in FREEC, and statistically characterize the concordance of the CNV calls between FREEC configurations and the analogous output from CNV-seq. The normalization methodologies evaluated in FREEC are: GC content, mappability and control genome. We further stratify the concordance analysis within genic, non-genic, and a collection of validated variant regions. The GC content normalization methodology generates the highest number of altered copy number regions. Both mappability and control genome normalization reduce the total number and length of copy number regions. Mappability normalization yields Jaccard indices in the 0.07 - 0.3 range, whereas using a control genome normalization yields Jaccard index values around 0.4 with normalization based on GC content. The most critical impact of using mappability as a normalization factor is substantial reduction of deletion CNV calls. The output of another method based on control genome normalization, CNV-seq, resulted in comparable CNV call profiles, and substantial agreement in variable gene and CNV region calls. Choice of read-count normalization methodology has a substantial effect on CNV calls and the use of genomic mappability or an appropriately chosen control genome can optimize the output of CNV analysis.

The role of parasite-driven selection in shaping landscape genomic structure in red grouse (Lagopus lagopus scotica).

PubMed

Wenzel, Marius A; Douglas, Alex; James, Marianne C; Redpath, Steve M; Piertney, Stuart B

2016-01-01

Landscape genomics promises to provide novel insights into how neutral and adaptive processes shape genome-wide variation within and among populations. However, there has been little emphasis on examining whether individual-based phenotype-genotype relationships derived from approaches such as genome-wide association (GWAS) manifest themselves as a population-level signature of selection in a landscape context. The two may prove irreconcilable as individual-level patterns become diluted by high levels of gene flow and complex phenotypic or environmental heterogeneity. We illustrate this issue with a case study that examines the role of the highly prevalent gastrointestinal nematode Trichostrongylus tenuis in shaping genomic signatures of selection in red grouse (Lagopus lagopus scotica). Individual-level GWAS involving 384 SNPs has previously identified five SNPs that explain variation in T. tenuis burden. Here, we examine whether these same SNPs display population-level relationships between T. tenuis burden and genetic structure across a small-scale landscape of 21 sites with heterogeneous parasite pressure. Moreover, we identify adaptive SNPs showing signatures of directional selection using F(ST) outlier analysis and relate population- and individual-level patterns of multilocus neutral and adaptive genetic structure to T. tenuis burden. The five candidate SNPs for parasite-driven selection were neither associated with T. tenuis burden on a population level, nor under directional selection. Similarly, there was no evidence of parasite-driven selection in SNPs identified as candidates for directional selection. We discuss these results in the context of red grouse ecology and highlight the broader consequences for the utility of landscape genomics approaches for identifying signatures of selection. © 2015 John Wiley & Sons Ltd.

A high-resolution cattle CNV map by population-scale genome sequencing

USDA-ARS?s Scientific Manuscript database

Copy Number Variations (CNVs) are common genomic structural variations that have been linked to human diseases and phenotypic traits. CNVs represent an important type of genetic variation among cattle breeds and even individual animals; however, only low-resolution maps of cattle CNVs currently exis...

Metabolic network visualization eliminating node redundance and preserving metabolic pathways

PubMed Central

Bourqui, Romain; Cottret, Ludovic; Lacroix, Vincent; Auber, David; Mary, Patrick; Sagot, Marie-France; Jourdan, Fabien

2007-01-01

Background The tools that are available to draw and to manipulate the representations of metabolism are usually restricted to metabolic pathways. This limitation becomes problematic when studying processes that span several pathways. The various attempts that have been made to draw genome-scale metabolic networks are confronted with two shortcomings: 1- they do not use contextual information which leads to dense, hard to interpret drawings, 2- they impose to fit to very constrained standards, which implies, in particular, duplicating nodes making topological analysis considerably more difficult. Results We propose a method, called MetaViz, which enables to draw a genome-scale metabolic network and that also takes into account its structuration into pathways. This method consists in two steps: a clustering step which addresses the pathway overlapping problem and a drawing step which consists in drawing the clustered graph and each cluster. Conclusion The method we propose is original and addresses new drawing issues arising from the no-duplication constraint. We do not propose a single drawing but rather several alternative ways of presenting metabolism depending on the pathway on which one wishes to focus. We believe that this provides a valuable tool to explore the pathway structure of metabolism. PMID:17608928

Genome scale engineering techniques for metabolic engineering.

PubMed

Liu, Rongming; Bassalo, Marcelo C; Zeitoun, Ramsey I; Gill, Ryan T

2015-11-01

Metabolic engineering has expanded from a focus on designs requiring a small number of genetic modifications to increasingly complex designs driven by advances in genome-scale engineering technologies. Metabolic engineering has been generally defined by the use of iterative cycles of rational genome modifications, strain analysis and characterization, and a synthesis step that fuels additional hypothesis generation. This cycle mirrors the Design-Build-Test-Learn cycle followed throughout various engineering fields that has recently become a defining aspect of synthetic biology. This review will attempt to summarize recent genome-scale design, build, test, and learn technologies and relate their use to a range of metabolic engineering applications. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

SWARM : a scientific workflow for supporting Bayesian approaches to improve metabolic models.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, X.; Stevens, R.; Mathematics and Computer Science

2008-01-01

With the exponential growth of complete genome sequences, the analysis of these sequences is becoming a powerful approach to build genome-scale metabolic models. These models can be used to study individual molecular components and their relationships, and eventually study cells as systems. However, constructing genome-scale metabolic models manually is time-consuming and labor-intensive. This property of manual model-building process causes the fact that much fewer genome-scale metabolic models are available comparing to hundreds of genome sequences available. To tackle this problem, we design SWARM, a scientific workflow that can be utilized to improve genome-scale metabolic models in high-throughput fashion. SWARM dealsmore » with a range of issues including the integration of data across distributed resources, data format conversions, data update, and data provenance. Putting altogether, SWARM streamlines the whole modeling process that includes extracting data from various resources, deriving training datasets to train a set of predictors and applying Bayesian techniques to assemble the predictors, inferring on the ensemble of predictors to insert missing data, and eventually improving draft metabolic networks automatically. By the enhancement of metabolic model construction, SWARM enables scientists to generate many genome-scale metabolic models within a short period of time and with less effort.« less

Genomic Analysis of the Necrotrophic Fungal Pathogens Sclerotinia sclerotiorum and Botrytis cinerea

PubMed Central

Benito, Ernesto P.; Couloux, Arnaud; Coutinho, Pedro M.; de Vries, Ronald P.; Dyer, Paul S.; Fillinger, Sabine; Fournier, Elisabeth; Gout, Lilian; Hahn, Matthias; Kohn, Linda; Lapalu, Nicolas; Plummer, Kim M.; Pradier, Jean-Marc; Quévillon, Emmanuel; Sharon, Amir; Simon, Adeline; ten Have, Arjen; Tudzynski, Bettina; Tudzynski, Paul; Wincker, Patrick; Andrew, Marion; Anthouard, Véronique; Beffa, Rolland; Benoit, Isabelle; Bouzid, Ourdia; Brault, Baptiste; Chen, Zehua; Choquer, Mathias; Collémare, Jérome; Cotton, Pascale; Danchin, Etienne G.; Da Silva, Corinne; Gautier, Angélique; Giraud, Corinne; Giraud, Tatiana; Gonzalez, Celedonio; Grossetete, Sandrine; Güldener, Ulrich; Henrissat, Bernard; Howlett, Barbara J.; Kodira, Chinnappa; Kretschmer, Matthias; Lappartient, Anne; Leroch, Michaela; Levis, Caroline; Mauceli, Evan; Neuvéglise, Cécile; Oeser, Birgitt; Pearson, Matthew; Poulain, Julie; Poussereau, Nathalie; Quesneville, Hadi; Rascle, Christine; Schumacher, Julia; Ségurens, Béatrice; Sexton, Adrienne; Silva, Evelyn; Sirven, Catherine; Soanes, Darren M.; Talbot, Nicholas J.; Templeton, Matt; Yandava, Chandri; Yarden, Oded; Zeng, Qiandong; Rollins, Jeffrey A.; Lebrun, Marc-Henri; Dickman, Marty

2011-01-01

Sclerotinia sclerotiorum and Botrytis cinerea are closely related necrotrophic plant pathogenic fungi notable for their wide host ranges and environmental persistence. These attributes have made these species models for understanding the complexity of necrotrophic, broad host-range pathogenicity. Despite their similarities, the two species differ in mating behaviour and the ability to produce asexual spores. We have sequenced the genomes of one strain of S. sclerotiorum and two strains of B. cinerea. The comparative analysis of these genomes relative to one another and to other sequenced fungal genomes is provided here. Their 38–39 Mb genomes include 11,860–14,270 predicted genes, which share 83% amino acid identity on average between the two species. We have mapped the S. sclerotiorum assembly to 16 chromosomes and found large-scale co-linearity with the B. cinerea genomes. Seven percent of the S. sclerotiorum genome comprises transposable elements compared to <1% of B. cinerea. The arsenal of genes associated with necrotrophic processes is similar between the species, including genes involved in plant cell wall degradation and oxalic acid production. Analysis of secondary metabolism gene clusters revealed an expansion in number and diversity of B. cinerea–specific secondary metabolites relative to S. sclerotiorum. The potential diversity in secondary metabolism might be involved in adaptation to specific ecological niches. Comparative genome analysis revealed the basis of differing sexual mating compatibility systems between S. sclerotiorum and B. cinerea. The organization of the mating-type loci differs, and their structures provide evidence for the evolution of heterothallism from homothallism. These data shed light on the evolutionary and mechanistic bases of the genetically complex traits of necrotrophic pathogenicity and sexual mating. This resource should facilitate the functional studies designed to better understand what makes these fungi such successful and persistent pathogens of agronomic crops. PMID:21876677

Genome-wide analysis of tandem repeats in plants and green algae

Treesearch

Zhixin Zhao; Cheng Guo; Sreeskandarajan Sutharzan; Pei Li; Craig Echt; Jie Zhang; Chun Liang

2014-01-01

Tandem repeats (TRs) extensively exist in the genomes of prokaryotes and eukaryotes. Based on the sequenced genomes and gene annotations of 31 plant and algal species in Phytozome version 8.0 (http://www.phytozome.net/), we examined TRs in a genome-wide scale, characterized their distributions and motif features, and explored their putative biological functions. Among...

A high-quality carrot genome assembly provides new insights into carotenoid accumulation and asterid genome evolution

USDA-ARS?s Scientific Manuscript database

We report a chromosome-scale assembly and analysis of the Daucus carota genome, an important source of provitamin A in the human diet and the first sequenced genome among members of the Euasterid II clade. We characterized two new polyploidization events, both occurring after the divergence of carro...

The Mobile Element Locator Tool (MELT): population-scale mobile element discovery and biology

PubMed Central

Gardner, Eugene J.; Lam, Vincent K.; Harris, Daniel N.; Chuang, Nelson T.; Scott, Emma C.; Pittard, W. Stephen; Mills, Ryan E.; Devine, Scott E.

2017-01-01

Mobile element insertions (MEIs) represent ∼25% of all structural variants in human genomes. Moreover, when they disrupt genes, MEIs can influence human traits and diseases. Therefore, MEIs should be fully discovered along with other forms of genetic variation in whole genome sequencing (WGS) projects involving population genetics, human diseases, and clinical genomics. Here, we describe the Mobile Element Locator Tool (MELT), which was developed as part of the 1000 Genomes Project to perform MEI discovery on a population scale. Using both Illumina WGS data and simulations, we demonstrate that MELT outperforms existing MEI discovery tools in terms of speed, scalability, specificity, and sensitivity, while also detecting a broader spectrum of MEI-associated features. Several run modes were developed to perform MEI discovery on local and cloud systems. In addition to using MELT to discover MEIs in modern humans as part of the 1000 Genomes Project, we also used it to discover MEIs in chimpanzees and ancient (Neanderthal and Denisovan) hominids. We detected diverse patterns of MEI stratification across these populations that likely were caused by (1) diverse rates of MEI production from source elements, (2) diverse patterns of MEI inheritance, and (3) the introgression of ancient MEIs into modern human genomes. Overall, our study provides the most comprehensive map of MEIs to date spanning chimpanzees, ancient hominids, and modern humans and reveals new aspects of MEI biology in these lineages. We also demonstrate that MELT is a robust platform for MEI discovery and analysis in a variety of experimental settings. PMID:28855259

Phylogeographic separation and formation of sexually discrete lineages in a global population of Yersinia pseudotuberculosis

PubMed Central

Seecharran, Tristan; Kalin-Manttari, Laura; Koskela, Katja; Nikkari, Simo; Dickins, Benjamin; Corander, Jukka; Skurnik, Mikael

2017-01-01

Yersinia pseudotuberculosis is a Gram-negative intestinal pathogen of humans and has been responsible for several nationwide gastrointestinal outbreaks. Large-scale population genomic studies have been performed on the other human pathogenic species of the genus Yersinia, Yersinia pestis and Yersinia enterocolitica allowing a high-resolution understanding of the ecology, evolution and dissemination of these pathogens. However, to date no purpose-designed large-scale global population genomic analysis of Y. pseudotuberculosis has been performed. Here we present analyses of the genomes of 134 strains of Y. pseudotuberculosis isolated from around the world, from multiple ecosystems since the 1960s. Our data display a phylogeographic split within the population, with an Asian ancestry and subsequent dispersal of successful clonal lineages into Europe and the rest of the world. These lineages can be differentiated by CRISPR cluster arrays, and we show that the lineages are limited with respect to inter-lineage genetic exchange. This restriction of genetic exchange maintains the discrete lineage structure in the population despite co-existence of lineages for thousands of years in multiple countries. Our data highlights how CRISPR can be informative of the evolutionary trajectory of bacterial lineages, and merits further study across bacteria. PMID:29177091

Comparative sequence analysis of Sordaria macrospora and Neurospora crassa as a means to improve genome annotation.

PubMed

Nowrousian, Minou; Würtz, Christian; Pöggeler, Stefanie; Kück, Ulrich

2004-03-01

One of the most challenging parts of large scale sequencing projects is the identification of functional elements encoded in a genome. Recently, studies of genomes of up to six different Saccharomyces species have demonstrated that a comparative analysis of genome sequences from closely related species is a powerful approach to identify open reading frames and other functional regions within genomes [Science 301 (2003) 71, Nature 423 (2003) 241]. Here, we present a comparison of selected sequences from Sordaria macrospora to their corresponding Neurospora crassa orthologous regions. Our analysis indicates that due to the high degree of sequence similarity and conservation of overall genomic organization, S. macrospora sequence information can be used to simplify the annotation of the N. crassa genome.

Fungal Genomics for Energy and Environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grigoriev, Igor V.

2013-03-11

Genomes of fungi relevant to energy and environment are in focus of the Fungal Genomic Program at the US Department of Energy Joint Genome Institute (JGI). One of its projects, the Genomics Encyclopedia of Fungi, targets fungi related to plant health (symbionts, pathogens, and biocontrol agents) and biorefinery processes (cellulose degradation, sugar fermentation, industrial hosts) by means of genome sequencing and analysis. New chapters of the Encyclopedia can be opened with user proposals to the JGI Community Sequencing Program (CSP). Another JGI project, the 1000 fungal genomes, explores fungal diversity on genome level at scale and is open for usersmore » to nominate new species for sequencing. Over 200 fungal genomes have been sequenced by JGI to date and released through MycoCosm (www.jgi.doe.gov/fungi), a fungal web-portal, which integrates sequence and functional data with genome analysis tools for user community. Sequence analysis supported by functional genomics leads to developing parts list for complex systems ranging from ecosystems of biofuel crops to biorefineries. Recent examples of such parts suggested by comparative genomics and functional analysis in these areas are presented here.« less

Toward the automated generation of genome-scale metabolic networks in the SEED.

PubMed

DeJongh, Matthew; Formsma, Kevin; Boillot, Paul; Gould, John; Rycenga, Matthew; Best, Aaron

2007-04-26

Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis). We have implemented our tools and database within the SEED, an open-source software environment for comparative genome annotation and analysis. Our method sets the stage for the automated generation of substantially complete metabolic networks for over 400 complete genome sequences currently in the SEED. With each genome that is processed using our tools, the database of common components grows to cover more of the diversity of metabolic pathways. This increases the likelihood that components of reaction networks for subsequently processed genomes can be retrieved from the database, rather than assembled and verified manually.

G23D: Online tool for mapping and visualization of genomic variants on 3D protein structures.

PubMed

Solomon, Oz; Kunik, Vered; Simon, Amos; Kol, Nitzan; Barel, Ortal; Lev, Atar; Amariglio, Ninette; Somech, Raz; Rechavi, Gidi; Eyal, Eran

2016-08-26

Evaluation of the possible implications of genomic variants is an increasingly important task in the current high throughput sequencing era. Structural information however is still not routinely exploited during this evaluation process. The main reasons can be attributed to the partial structural coverage of the human proteome and the lack of tools which conveniently convert genomic positions, which are the frequent output of genomic pipelines, to proteins and structure coordinates. We present G23D, a tool for conversion of human genomic coordinates to protein coordinates and protein structures. G23D allows mapping of genomic positions/variants on evolutionary related (and not only identical) protein three dimensional (3D) structures as well as on theoretical models. By doing so it significantly extends the space of variants for which structural insight is feasible. To facilitate interpretation of the variant consequence, pathogenic variants, functional sites and polymorphism sites are displayed on protein sequence and structure diagrams alongside the input variants. G23D also provides modeling of the mutant structure, analysis of intra-protein contacts and instant access to functional predictions and predictions of thermo-stability changes. G23D is available at http://www.sheba-cancer.org.il/G23D . G23D extends the fraction of variants for which structural analysis is applicable and provides better and faster accessibility for structural data to biologists and geneticists who routinely work with genomic information.

Statistical Significance of Optical Map Alignments

PubMed Central

Sarkar, Deepayan; Goldstein, Steve; Schwartz, David C.

2012-01-01

Abstract The Optical Mapping System constructs ordered restriction maps spanning entire genomes through the assembly and analysis of large datasets comprising individually analyzed genomic DNA molecules. Such restriction maps uniquely reveal mammalian genome structure and variation, but also raise computational and statistical questions beyond those that have been solved in the analysis of smaller, microbial genomes. We address the problem of how to filter maps that align poorly to a reference genome. We obtain map-specific thresholds that control errors and improve iterative assembly. We also show how an optimal self-alignment score provides an accurate approximation to the probability of alignment, which is useful in applications seeking to identify structural genomic abnormalities. PMID:22506568

Substantial genome synteny preservation among woody angiosperm species: comparative genomics of Chinese chestnut (Castanea mollissima) and plant reference genomes.

PubMed

Staton, Margaret; Zhebentyayeva, Tetyana; Olukolu, Bode; Fang, Guang Chen; Nelson, Dana; Carlson, John E; Abbott, Albert G

2015-10-05

Chinese chestnut (Castanea mollissima) has emerged as a model species for the Fagaceae family with extensive genomic resources including a physical map, a dense genetic map and quantitative trait loci (QTLs) for chestnut blight resistance. These resources enable comparative genomics analyses relative to model plants. We assessed the degree of conservation between the chestnut genome and other well annotated and assembled plant genomic sequences, focusing on the QTL regions of most interest to the chestnut breeding community. The integrated physical and genetic map of Chinese chestnut has been improved to now include 858 shared sequence-based markers. The utility of the integrated map has also been improved through the addition of 42,970 BAC (bacterial artificial chromosome) end sequences spanning over 26 million bases of the estimated 800 Mb chestnut genome. Synteny between chestnut and ten model plant species was conducted on a macro-syntenic scale using sequences from both individual probes and BAC end sequences across the chestnut physical map. Blocks of synteny with chestnut were found in all ten reference species, with the percent of the chestnut physical map that could be aligned ranging from 10 to 39 %. The integrated genetic and physical map was utilized to identify BACs that spanned the three previously identified QTL regions conferring blight resistance. The clones were pooled and sequenced, yielding 396 sequence scaffolds covering 13.9 Mbp. Comparative genomic analysis on a microsytenic scale, using the QTL-associated genomic sequence, identified synteny from chestnut to other plant genomes ranging from 5.4 to 12.9 % of the genome sequences aligning. On both the macro- and micro-synteny levels, the peach, grape and poplar genomes were found to be the most structurally conserved with chestnut. Interestingly, these results did not strictly follow the expectation that decreased phylogenetic distance would correspond to increased levels of genome preservation, but rather suggest the additional influence of life-history traits on preservation of synteny. The regions of synteny that were detected provide an important tool for defining and cataloging genes in the QTL regions for advancing chestnut blight resistance research.

Covering complete proteomes with X-ray structures: A current snapshot

DOE PAGES

Mizianty, Marcin J.; Fan, Xiao; Yan, Jing; ...

2014-10-23

Structural genomics programs have developed and applied structure-determination pipelines to a wide range of protein targets, facilitating the visualization of macromolecular interactions and the understanding of their molecular and biochemical functions. The fundamental question of whether three-dimensional structures of all proteins and all functional annotations can be determined using X-ray crystallography is investigated. A first-of-its-kind large-scale analysis of crystallization propensity for all proteins encoded in 1953 fully sequenced genomes was performed. It is shown that current X-ray crystallographic knowhow combined with homology modeling can provide structures for 25% of modeling families (protein clusters for which structural models can be obtainedmore » through homology modeling), with at least one structural model produced for each Gene Ontology functional annotation. The coverage varies between superkingdoms, with 19% for eukaryotes, 35% for bacteria and 49% for archaea, and with those of viruses following the coverage values of their hosts. It is shown that the crystallization propensities of proteomes from the taxonomic superkingdoms are distinct. The use of knowledge-based target selection is shown to substantially increase the ability to produce X-ray structures. It is demonstrated that the human proteome has one of the highest attainable coverage values among eukaryotes, and GPCR membrane proteins suitable for X-ray structure determination were determined.« less

TARGET Publication Guidelines | Office of Cancer Genomics

Cancer.gov

Like other NCI large-scale genomics initiatives, TARGET is a community resource project and data are made available rapidly after validation for use by other researchers. To act in accord with the Fort Lauderdale principles and support the continued prompt public release of large-scale genomic data prior to publication, researchers who plan to prepare manuscripts containing descriptions of TARGET pediatric cancer data that would be of comparable scope to an initial TARGET disease-specific comprehensive, global analysis publication, and journal editors who receive such manuscripts, are

Comparative analysis and visualization of multiple collinear genomes

PubMed Central

2012-01-01

Background Genome browsers are a common tool used by biologists to visualize genomic features including genes, polymorphisms, and many others. However, existing genome browsers and visualization tools are not well-suited to perform meaningful comparative analysis among a large number of genomes. With the increasing quantity and availability of genomic data, there is an increased burden to provide useful visualization and analysis tools for comparison of multiple collinear genomes such as the large panels of model organisms which are the basis for much of the current genetic research. Results We have developed a novel web-based tool for visualizing and analyzing multiple collinear genomes. Our tool illustrates genome-sequence similarity through a mosaic of intervals representing local phylogeny, subspecific origin, and haplotype identity. Comparative analysis is facilitated through reordering and clustering of tracks, which can vary throughout the genome. In addition, we provide local phylogenetic trees as an alternate visualization to assess local variations. Conclusions Unlike previous genome browsers and viewers, ours allows for simultaneous and comparative analysis. Our browser provides intuitive selection and interactive navigation about features of interest. Dynamic visualizations adjust to scale and data content making analysis at variable resolutions and of multiple data sets more informative. We demonstrate our genome browser for an extensive set of genomic data sets composed of almost 200 distinct mouse laboratory strains. PMID:22536897

2b-RAD genotyping for population genomic studies of Chagas disease vectors: Rhodnius ecuadoriensis in Ecuador.

PubMed

Hernandez-Castro, Luis E; Paterno, Marta; Villacís, Anita G; Andersson, Björn; Costales, Jaime A; De Noia, Michele; Ocaña-Mayorga, Sofía; Yumiseva, Cesar A; Grijalva, Mario J; Llewellyn, Martin S

2017-07-01

Rhodnius ecuadoriensis is the main triatomine vector of Chagas disease, American trypanosomiasis, in Southern Ecuador and Northern Peru. Genomic approaches and next generation sequencing technologies have become powerful tools for investigating population diversity and structure which is a key consideration for vector control. Here we assess the effectiveness of three different 2b restriction site-associated DNA (2b-RAD) genotyping strategies in R. ecuadoriensis to provide sufficient genomic resolution to tease apart microevolutionary processes and undertake some pilot population genomic analyses. The 2b-RAD protocol was carried out in-house at a non-specialized laboratory using 20 R. ecuadoriensis adults collected from the central coast and southern Andean region of Ecuador, from June 2006 to July 2013. 2b-RAD sequencing data was performed on an Illumina MiSeq instrument and analyzed with the STACKS de novo pipeline for loci assembly and Single Nucleotide Polymorphism (SNP) discovery. Preliminary population genomic analyses (global AMOVA and Bayesian clustering) were implemented. Our results showed that the 2b-RAD genotyping protocol is effective for R. ecuadoriensis and likely for other triatomine species. However, only BcgI and CspCI restriction enzymes provided a number of markers suitable for population genomic analysis at the read depth we generated. Our preliminary genomic analyses detected a signal of genetic structuring across the study area. Our findings suggest that 2b-RAD genotyping is both a cost effective and methodologically simple approach for generating high resolution genomic data for Chagas disease vectors with the power to distinguish between different vector populations at epidemiologically relevant scales. As such, 2b-RAD represents a powerful tool in the hands of medical entomologists with limited access to specialized molecular biological equipment.

Sequence Analysis of Leuconostoc mesenteroides Bacteriophage Φ1-A4 Isolated from an Industrial Vegetable Fermentation▿

PubMed Central

Lu, Z.; Altermann, E.; Breidt, F.; Kozyavkin, S.

2010-01-01

Vegetable fermentations rely on the proper succession of a variety of lactic acid bacteria (LAB). Leuconostoc mesenteroides initiates fermentation. As fermentation proceeds, L. mesenteroides dies off and other LAB complete the fermentation. Phages infecting L. mesenteroides may significantly influence the die-off of L. mesenteroides. However, no L. mesenteroides phages have been previously genetically characterized. Knowledge of more phage genome sequences may provide new insights into phage genomics, phage evolution, and phage-host interactions. We have determined the complete genome sequence of L. mesenteroides phage Φ1-A4, isolated from an industrial sauerkraut fermentation. The phage possesses a linear, double-stranded DNA genome consisting of 29,508 bp with a G+C content of 36%. Fifty open reading frames (ORFs) were predicted. Putative functions were assigned to 26 ORFs (52%), including 5 ORFs of structural proteins. The phage genome was modularly organized, containing DNA replication, DNA-packaging, head and tail morphogenesis, cell lysis, and DNA regulation/modification modules. In silico analyses showed that Φ1-A4 is a unique lytic phage with a large-scale genome inversion (∼30% of the genome). The genome inversion encompassed the lysis module, part of the structural protein module, and a cos site. The endolysin gene was flanked by two holin genes. The tail morphogenesis module was interspersed with cell lysis genes and other genes with unknown functions. The predicted amino acid sequences of the phage proteins showed little similarity to other phages, but functional analyses showed that Φ1-A4 clusters with several Lactococcus phages. To our knowledge, Φ1-A4 is the first genetically characterized L. mesenteroides phage. PMID:20118355

2b-RAD genotyping for population genomic studies of Chagas disease vectors: Rhodnius ecuadoriensis in Ecuador

PubMed Central

Villacís, Anita G.; Andersson, Björn; Costales, Jaime A.; De Noia, Michele; Ocaña-Mayorga, Sofía; Yumiseva, Cesar A.; Grijalva, Mario J.; Llewellyn, Martin S.

2017-01-01

Background Rhodnius ecuadoriensis is the main triatomine vector of Chagas disease, American trypanosomiasis, in Southern Ecuador and Northern Peru. Genomic approaches and next generation sequencing technologies have become powerful tools for investigating population diversity and structure which is a key consideration for vector control. Here we assess the effectiveness of three different 2b restriction site-associated DNA (2b-RAD) genotyping strategies in R. ecuadoriensis to provide sufficient genomic resolution to tease apart microevolutionary processes and undertake some pilot population genomic analyses. Methodology/Principal findings The 2b-RAD protocol was carried out in-house at a non-specialized laboratory using 20 R. ecuadoriensis adults collected from the central coast and southern Andean region of Ecuador, from June 2006 to July 2013. 2b-RAD sequencing data was performed on an Illumina MiSeq instrument and analyzed with the STACKS de novo pipeline for loci assembly and Single Nucleotide Polymorphism (SNP) discovery. Preliminary population genomic analyses (global AMOVA and Bayesian clustering) were implemented. Our results showed that the 2b-RAD genotyping protocol is effective for R. ecuadoriensis and likely for other triatomine species. However, only BcgI and CspCI restriction enzymes provided a number of markers suitable for population genomic analysis at the read depth we generated. Our preliminary genomic analyses detected a signal of genetic structuring across the study area. Conclusions/Significance Our findings suggest that 2b-RAD genotyping is both a cost effective and methodologically simple approach for generating high resolution genomic data for Chagas disease vectors with the power to distinguish between different vector populations at epidemiologically relevant scales. As such, 2b-RAD represents a powerful tool in the hands of medical entomologists with limited access to specialized molecular biological equipment. PMID:28723901

Trends in structural coverage of the protein universe and the impact of the Protein Structure Initiative

PubMed Central

Khafizov, Kamil; Madrid-Aliste, Carlos; Almo, Steven C.; Fiser, Andras

2014-01-01

The exponential growth of protein sequence data provides an ever-expanding body of unannotated and misannotated proteins. The National Institutes of Health-supported Protein Structure Initiative and related worldwide structural genomics efforts facilitate functional annotation of proteins through structural characterization. Recently there have been profound changes in the taxonomic composition of sequence databases, which are effectively redefining the scope and contribution of these large-scale structure-based efforts. The faster-growing bacterial genomic entries have overtaken the eukaryotic entries over the last 5 y, but also have become more redundant. Despite the enormous increase in the number of sequences, the overall structural coverage of proteins—including proteins for which reliable homology models can be generated—on the residue level has increased from 30% to 40% over the last 10 y. Structural genomics efforts contributed ∼50% of this new structural coverage, despite determining only ∼10% of all new structures. Based on current trends, it is expected that ∼55% structural coverage (the level required for significant functional insight) will be achieved within 15 y, whereas without structural genomics efforts, realizing this goal will take approximately twice as long. PMID:24567391

Trends in structural coverage of the protein universe and the impact of the Protein Structure Initiative.

PubMed

Khafizov, Kamil; Madrid-Aliste, Carlos; Almo, Steven C; Fiser, Andras

2014-03-11

The exponential growth of protein sequence data provides an ever-expanding body of unannotated and misannotated proteins. The National Institutes of Health-supported Protein Structure Initiative and related worldwide structural genomics efforts facilitate functional annotation of proteins through structural characterization. Recently there have been profound changes in the taxonomic composition of sequence databases, which are effectively redefining the scope and contribution of these large-scale structure-based efforts. The faster-growing bacterial genomic entries have overtaken the eukaryotic entries over the last 5 y, but also have become more redundant. Despite the enormous increase in the number of sequences, the overall structural coverage of proteins--including proteins for which reliable homology models can be generated--on the residue level has increased from 30% to 40% over the last 10 y. Structural genomics efforts contributed ∼50% of this new structural coverage, despite determining only ∼10% of all new structures. Based on current trends, it is expected that ∼55% structural coverage (the level required for significant functional insight) will be achieved within 15 y, whereas without structural genomics efforts, realizing this goal will take approximately twice as long.

Genomic diversity in switchgrass (Panicum virgatum): from the continental scale to a dune landscape

PubMed Central

Morris, Geoffrey P.; Grabowski, Paul; Borevitz, Justin O.

2011-01-01

Connecting broad-scale patterns of genetic variation and population structure to genetic diversity on a landscape is a key step towards understanding historical processes of migration and adaptation. New genomic approaches can be used to increase the resolution of phylogeographic studies while reducing locus sampling effects and circumventing ascertainment bias. Here, we use a novel approach based on high-throughput sequencing to characterize genetic diversity in complete chloroplast genomes and >10,000 nuclear loci in switchgrass, across a continental and landscape scale. Switchgrass is a North American tallgrass species, which is widely used in conservation and perennial biomass production, and shows strong ecotypic adaptation and population structure across the continental range. We sequenced 40.9 billion base pairs from 24 individuals from across the species’ range and 20 individuals from the Indiana Dunes. Analysis of plastome sequence revealed 203 variable SNP sites that define eight haplogroups, which are differentiated by 4 to 127 SNPs and confirmed by patterns of indel variation. These include three deeply divergent haplogroups, which correspond to the previously described lowland-upland ecotypic split and a novel upland haplogroup split that dates to the mid-Pleistoscene. Most of the plastome haplogroup diversity present in the northern switchgrass range, including in the Indiana Dunes, originated in the mid- or upper-Pleistocene prior to the most recent postglacial recolonization. Furthermore, a recently colonized landscape feature (~150 ya) in the Indiana Dunes contains several deeply divergent upland haplogroups. Nuclear markers also support a deep lowland-upland split, followed by limited gene flow, and show extensive gene flow in the local population of the Indiana Dunes. PMID:22060816

Large-Scale Phylogenetic Classification of Fungal Chitin Synthases and Identification of a Putative Cell-Wall Metabolism Gene Cluster in Aspergillus Genomes

PubMed Central

Pacheco-Arjona, Jose Ramon; Ramirez-Prado, Jorge Humberto

2014-01-01

The cell wall is a protective and versatile structure distributed in all fungi. The component responsible for its rigidity is chitin, a product of chitin synthase (Chsp) enzymes. There are seven classes of chitin synthase genes (CHS) and the amount and type encoded in fungal genomes varies considerably from one species to another. Previous Chsp sequence analyses focused on their study as individual units, regardless of genomic context. The identification of blocks of conserved genes between genomes can provide important clues about the interactions and localization of chitin synthases. On the present study, we carried out an in silico search of all putative Chsp encoded in 54 full fungal genomes, encompassing 21 orders from five phyla. Phylogenetic studies of these Chsp were able to confidently classify 347 out of the 369 Chsp identified (94%). Patterns in the distribution of Chsp related to taxonomy were identified, the most prominent being related to the type of fungal growth. More importantly, a synteny analysis for genomic blocks centered on class IV Chsp (the most abundant and widely distributed Chsp class) identified a putative cell wall metabolism gene cluster in members of the genus Aspergillus, the first such association reported for any fungal genome. PMID:25148134

Progress towards mapping the universe of protein folds

PubMed Central

Grant, Alastair; Lee, David; Orengo, Christine

2004-01-01

Although the precise aims differ between the various international structural genomics initiatives currently aiming to illuminate the universe of protein folds, many selectively target protein families for which the fold is unknown. How well can the current set of known protein families and folds be used to estimate the total number of folds in nature, and will structural genomics initiatives yield representatives for all the major protein families within a reasonable time scale? PMID:15128436

Fueling the Future with Fungal Genomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grigoriev, Igor V.

2014-10-27

Genomes of fungi relevant to energy and environment are in focus of the JGI Fungal Genomic Program. One of its projects, the Genomics Encyclopedia of Fungi, targets fungi related to plant health (symbionts and pathogens) and biorefinery processes (cellulose degradation and sugar fermentation) by means of genome sequencing and analysis. New chapters of the Encyclopedia can be opened with user proposals to the JGI Community Science Program (CSP). Another JGI project, the 1000 fungal genomes, explores fungal diversity on genome level at scale and is open for users to nominate new species for sequencing. Over 400 fungal genomes have beenmore » sequenced by JGI to date and released through MycoCosm (www.jgi.doe.gov/fungi), a fungal web-portal, which integrates sequence and functional data with genome analysis tools for user community. Sequence analysis supported by functional genomics will lead to developing parts list for complex systems ranging from ecosystems of biofuel crops to biorefineries. Recent examples of such ‘parts’ suggested by comparative genomics and functional analysis in these areas are presented here.« less

Sequences of 95 human MHC haplotypes reveal extreme coding variation in genes other than highly polymorphic HLA class I and II

PubMed Central

Norman, Paul J.; Norberg, Steven J.; Guethlein, Lisbeth A.; Nemat-Gorgani, Neda; Royce, Thomas; Wroblewski, Emily E.; Dunn, Tamsen; Mann, Tobias; Alicata, Claudia; Hollenbach, Jill A.; Chang, Weihua; Shults Won, Melissa; Gunderson, Kevin L.; Abi-Rached, Laurent; Ronaghi, Mostafa; Parham, Peter

2017-01-01

The most polymorphic part of the human genome, the MHC, encodes over 160 proteins of diverse function. Half of them, including the HLA class I and II genes, are directly involved in immune responses. Consequently, the MHC region strongly associates with numerous diseases and clinical therapies. Notoriously, the MHC region has been intractable to high-throughput analysis at complete sequence resolution, and current reference haplotypes are inadequate for large-scale studies. To address these challenges, we developed a method that specifically captures and sequences the 4.8-Mbp MHC region from genomic DNA. For 95 MHC homozygous cell lines we assembled, de novo, a set of high-fidelity contigs and a sequence scaffold, representing a mean 98% of the target region. Included are six alternative MHC reference sequences of the human genome that we completed and refined. Characterization of the sequence and structural diversity of the MHC region shows the approach accurately determines the sequences of the highly polymorphic HLA class I and HLA class II genes and the complex structural diversity of complement factor C4A/C4B. It has also uncovered extensive and unexpected diversity in other MHC genes; an example is MUC22, which encodes a lung mucin and exhibits more coding sequence alleles than any HLA class I or II gene studied here. More than 60% of the coding sequence alleles analyzed were previously uncharacterized. We have created a substantial database of robust reference MHC haplotype sequences that will enable future population scale studies of this complicated and clinically important region of the human genome. PMID:28360230

Efficient HIV-1 inhibition by a 16 nt-long RNA aptamer designed by combining in vitro selection and in silico optimisation strategies

PubMed Central

Sánchez-Luque, Francisco J.; Stich, Michael; Manrubia, Susanna; Briones, Carlos; Berzal-Herranz, Alfredo

2014-01-01

The human immunodeficiency virus type-1 (HIV-1) genome contains multiple, highly conserved structural RNA domains that play key roles in essential viral processes. Interference with the function of these RNA domains either by disrupting their structures or by blocking their interaction with viral or cellular factors may seriously compromise HIV-1 viability. RNA aptamers are amongst the most promising synthetic molecules able to interact with structural domains of viral genomes. However, aptamer shortening up to their minimal active domain is usually necessary for scaling up production, what requires very time-consuming, trial-and-error approaches. Here we report on the in vitro selection of 64 nt-long specific aptamers against the complete 5′-untranslated region of HIV-1 genome, which inhibit more than 75% of HIV-1 production in a human cell line. The analysis of the selected sequences and structures allowed for the identification of a highly conserved 16 nt-long stem-loop motif containing a common 8 nt-long apical loop. Based on this result, an in silico designed 16 nt-long RNA aptamer, termed RNApt16, was synthesized, with sequence 5′-CCCCGGCAAGGAGGGG-3′. The HIV-1 inhibition efficiency of such an aptamer was close to 85%, thus constituting the shortest RNA molecule so far described that efficiently interferes with HIV-1 replication. PMID:25175101

Conditional Random Fields for Fast, Large-Scale Genome-Wide Association Studies

PubMed Central

Huang, Jim C.; Meek, Christopher; Kadie, Carl; Heckerman, David

2011-01-01

Understanding the role of genetic variation in human diseases remains an important problem to be solved in genomics. An important component of such variation consist of variations at single sites in DNA, or single nucleotide polymorphisms (SNPs). Typically, the problem of associating particular SNPs to phenotypes has been confounded by hidden factors such as the presence of population structure, family structure or cryptic relatedness in the sample of individuals being analyzed. Such confounding factors lead to a large number of spurious associations and missed associations. Various statistical methods have been proposed to account for such confounding factors such as linear mixed-effect models (LMMs) or methods that adjust data based on a principal components analysis (PCA), but these methods either suffer from low power or cease to be tractable for larger numbers of individuals in the sample. Here we present a statistical model for conducting genome-wide association studies (GWAS) that accounts for such confounding factors. Our method scales in runtime quadratic in the number of individuals being studied with only a modest loss in statistical power as compared to LMM-based and PCA-based methods when testing on synthetic data that was generated from a generalized LMM. Applying our method to both real and synthetic human genotype/phenotype data, we demonstrate the ability of our model to correct for confounding factors while requiring significantly less runtime relative to LMMs. We have implemented methods for fitting these models, which are available at http://www.microsoft.com/science. PMID:21765897

Genome-wide computational prediction and analysis of core promoter elements across plant monocots and dicots

USDA-ARS?s Scientific Manuscript database

Transcription initiation, essential to gene expression regulation, involves recruitment of basal transcription factors to the core promoter elements (CPEs). The distribution of currently known CPEs across plant genomes is largely unknown. This is the first large scale genome-wide report on the compu...

FULL-GENOME ANALYSIS OF ALTERNATIVE SPLICING IN MOUSE LIVER AFTER HEPATOTOXICANT EXPOSURE

EPA Science Inventory

Alternative splicing plays a role in determining gene function and protein diversity. We have employed whole genome exon profiling using Affymetrix Mouse Exon 1.0 ST arrays to understand the significance of alternative splicing on a genome-wide scale in response to multiple toxic...

BIOMONITORING THE TOXICOGENOMIC RESPONSE TO ENDOCRINE DISRUPTING CHEMICALS IN HUMANS, LABORATORY SPECIES AND WILDLIFE

EPA Science Inventory

With the advent of sequence information for entire eukaryotic genomes, it is now possible to analyze gene expression on a genomic scale. The primary tool for genomic analysis of gene expression is the gene microarray. We have used commercially available and custom cDNA microarray...

ScreenBEAM: a novel meta-analysis algorithm for functional genomics screens via Bayesian hierarchical modeling | Office of Cancer Genomics

Cancer.gov

Functional genomics (FG) screens, using RNAi or CRISPR technology, have become a standard tool for systematic, genome-wide loss-of-function studies for therapeutic target discovery. As in many large-scale assays, however, off-target effects, variable reagents' potency and experimental noise must be accounted for appropriately control for false positives.

Natural Allelic Diversity, Genetic Structure and Linkage Disequilibrium Pattern in Wild Chickpea

PubMed Central

Kujur, Alice; Das, Shouvik; Badoni, Saurabh; Kumar, Vinod; Singh, Mohar; Bansal, Kailash C.; Tyagi, Akhilesh K.; Parida, Swarup K.

2014-01-01

Characterization of natural allelic diversity and understanding the genetic structure and linkage disequilibrium (LD) pattern in wild germplasm accessions by large-scale genotyping of informative microsatellite and single nucleotide polymorphism (SNP) markers is requisite to facilitate chickpea genetic improvement. Large-scale validation and high-throughput genotyping of genome-wide physically mapped 478 genic and genomic microsatellite markers and 380 transcription factor gene-derived SNP markers using gel-based assay, fluorescent dye-labelled automated fragment analyser and matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass array have been performed. Outcome revealed their high genotyping success rate (97.5%) and existence of a high level of natural allelic diversity among 94 wild and cultivated Cicer accessions. High intra- and inter-specific polymorphic potential and wider molecular diversity (11–94%) along with a broader genetic base (13–78%) specifically in the functional genic regions of wild accessions was assayed by mapped markers. It suggested their utility in monitoring introgression and transferring target trait-specific genomic (gene) regions from wild to cultivated gene pool for the genetic enhancement. Distinct species/gene pool-wise differentiation, admixed domestication pattern, and differential genome-wide recombination and LD estimates/decay observed in a six structured population of wild and cultivated accessions using mapped markers further signifies their usefulness in chickpea genetics, genomics and breeding. PMID:25222488

[Comparative analysis of ISSR markers polymorphism in populations of yak (Bos mutus) and in F1 hybrids between yak and cattle in the Sayan-Altai region].

PubMed

Stolpovsky, Yu A; Kol, N V; Evsyukov, A N; Nesteruk, L V; Dorzhu, Ch M; Tsendsuren, Ts; Sulimova, G E

2014-10-01

The genetic variability in seven yak populations from the Sayan-Altai region and in F1 hybrids between yak and cattle (khainags) was investigated with the help of a technique that involves the use of inter simple sequence repeat (ISSR) markers generated with PCR primers (AG)9C and (GA)9C. Samples for the analysis were collected in Mongolia, Tuva, and Altai from 2008 through 2012. The examined yak populations differed in in the presence/absence of ISSR fragments, as well as in their frequency. In total, 46 ISSR fragments were identified using two marker systems; the proportion of polymorphic loci constituted 76% and 90% for the AG-ISSR and GA-ISSR markers, respectively. For the total sample of yaks, total genetic diversity (Ht), within-population diversity (Hs), and interpopulation diversity (Gst) constituted 0.081, 0.044, and 0.459 for the AG-ISSR and 0.137, 0.057, and 0.582 for the GA-ISSR markers, respectively. Based on ISSR finger printing, species- and breed-specific DNA patterns were described for the three groups of animals (yaks, cattle, khainags). For the domestic yak, the species-specific profile was represented by eight ISSR fragments. Genetic relationships between the yak populations, cattle breeds, and khainags were examined with the help of four different approaches used in the analysis of population structure: estimation of phylogenetic similarity, multidimensional scaling, principal component analysis, and cluster analysis. Clear evidence on the differentiation of the populations examined at the interspecific, as well as at intraspecific, level were obtained. Similar (relative); as well as remote (isolated), yak populations were identified. Khainags occupy an intermediate position between yak and cattle. However, the data on the ISSR-PCR marker polymorphism (genome polymorphism, population structure).indicate that part of the analyzed khainag genome was more similar to the yak genome than to the cattle genome.

MEGANTE: A Web-Based System for Integrated Plant Genome Annotation

PubMed Central

Numa, Hisataka; Itoh, Takeshi

2014-01-01

The recent advancement of high-throughput genome sequencing technologies has resulted in a considerable increase in demands for large-scale genome annotation. While annotation is a crucial step for downstream data analyses and experimental studies, this process requires substantial expertise and knowledge of bioinformatics. Here we present MEGANTE, a web-based annotation system that makes plant genome annotation easy for researchers unfamiliar with bioinformatics. Without any complicated configuration, users can perform genomic sequence annotations simply by uploading a sequence and selecting the species to query. MEGANTE automatically runs several analysis programs and integrates the results to select the appropriate consensus exon–intron structures and to predict open reading frames (ORFs) at each locus. Functional annotation, including a similarity search against known proteins and a functional domain search, are also performed for the predicted ORFs. The resultant annotation information is visualized with a widely used genome browser, GBrowse. For ease of analysis, the results can be downloaded in Microsoft Excel format. All of the query sequences and annotation results are stored on the server side so that users can access their own data from virtually anywhere on the web. The current release of MEGANTE targets 24 plant species from the Brassicaceae, Fabaceae, Musaceae, Poaceae, Salicaceae, Solanaceae, Rosaceae and Vitaceae families, and it allows users to submit a sequence up to 10 Mb in length and to save up to 100 sequences with the annotation information on the server. The MEGANTE web service is available at https://megante.dna.affrc.go.jp/. PMID:24253915

The emerging biofuel crop Camelina sativa retains a highly undifferentiated hexaploid genome structure

PubMed Central

Kagale, Sateesh; Koh, Chushin; Nixon, John; Bollina, Venkatesh; Clarke, Wayne E.; Tuteja, Reetu; Spillane, Charles; Robinson, Stephen J.; Links, Matthew G.; Clarke, Carling; Higgins, Erin E.; Huebert, Terry; Sharpe, Andrew G.; Parkin, Isobel A. P.

2014-01-01

Camelina sativa is an oilseed with desirable agronomic and oil-quality attributes for a viable industrial oil platform crop. Here we generate the first chromosome-scale high-quality reference genome sequence for C. sativa and annotated 89,418 protein-coding genes, representing a whole-genome triplication event relative to the crucifer model Arabidopsis thaliana. C. sativa represents the first crop species to be sequenced from lineage I of the Brassicaceae. The well-preserved hexaploid genome structure of C. sativa surprisingly mirrors those of economically important amphidiploid Brassica crop species from lineage II as well as wheat and cotton. The three genomes of C. sativa show no evidence of fractionation bias and limited expression-level bias, both characteristics commonly associated with polyploid evolution. The highly undifferentiated polyploid genome of C. sativa presents significant consequences for breeding and genetic manipulation of this industrial oil crop. PMID:24759634

Analysis of copy number variations among cattle breeds

USDA-ARS?s Scientific Manuscript database

Genomic structural variation is an important and abundant source of genetic and phenotypic variation. Here we describe the first systematic and genome-wide analysis of copy number variations (CNVs) in the modern domesticated cattle using array comparative genomic hybridization (array CGH) and quanti...

Development of constraint-based system-level models of microbial metabolism.

PubMed

Navid, Ali

2012-01-01

Genome-scale models of metabolism are valuable tools for using genomic information to predict microbial phenotypes. System-level mathematical models of metabolic networks have been developed for a number of microbes and have been used to gain new insights into the biochemical conversions that occur within organisms and permit their survival and proliferation. Utilizing these models, computational biologists can (1) examine network structures, (2) predict metabolic capabilities and resolve unexplained experimental observations, (3) generate and test new hypotheses, (4) assess the nutritional requirements of the organism and approximate its environmental niche, (5) identify missing enzymatic functions in the annotated genome, and (6) engineer desired metabolic capabilities in model organisms. This chapter details the protocol for developing genome-scale models of metabolism in microbes as well as tips for accelerating the model building process.

Investigating host-pathogen behavior and their interaction using genome-scale metabolic network models.

PubMed

Sadhukhan, Priyanka P; Raghunathan, Anu

2014-01-01

Genome Scale Metabolic Modeling methods represent one way to compute whole cell function starting from the genome sequence of an organism and contribute towards understanding and predicting the genotype-phenotype relationship. About 80 models spanning all the kingdoms of life from archaea to eukaryotes have been built till date and used to interrogate cell phenotype under varying conditions. These models have been used to not only understand the flux distribution in evolutionary conserved pathways like glycolysis and the Krebs cycle but also in applications ranging from value added product formation in Escherichia coli to predicting inborn errors of Homo sapiens metabolism. This chapter describes a protocol that delineates the process of genome scale metabolic modeling for analysing host-pathogen behavior and interaction using flux balance analysis (FBA). The steps discussed in the process include (1) reconstruction of a metabolic network from the genome sequence, (2) its representation in a precise mathematical framework, (3) its translation to a model, and (4) the analysis using linear algebra and optimization. The methods for biological interpretations of computed cell phenotypes in the context of individual host and pathogen models and their integration are also discussed.

Age distribution of human gene families shows significant roles of both large- and small-scale duplications in vertebrate evolution.

PubMed

Gu, Xun; Wang, Yufeng; Gu, Jianying

2002-06-01

The classical (two-round) hypothesis of vertebrate genome duplication proposes two successive whole-genome duplication(s) (polyploidizations) predating the origin of fishes, a view now being seriously challenged. As the debate largely concerns the relative merits of the 'big-bang mode' theory (large-scale duplication) and the 'continuous mode' theory (constant creation by small-scale duplications), we tested whether a significant proportion of paralogous genes in the contemporary human genome was indeed generated in the early stage of vertebrate evolution. After an extensive search of major databases, we dated 1,739 gene duplication events from the phylogenetic analysis of 749 vertebrate gene families. We found a pattern characterized by two waves (I, II) and an ancient component. Wave I represents a recent gene family expansion by tandem or segmental duplications, whereas wave II, a rapid paralogous gene increase in the early stage of vertebrate evolution, supports the idea of genome duplication(s) (the big-bang mode). Further analysis indicated that large- and small-scale gene duplications both make a significant contribution during the early stage of vertebrate evolution to build the current hierarchy of the human proteome.

Genome-scale metabolic modeling of Mucor circinelloides and comparative analysis with other oleaginous species.

PubMed

Vongsangnak, Wanwipa; Klanchui, Amornpan; Tawornsamretkit, Iyarest; Tatiyaborwornchai, Witthawin; Laoteng, Kobkul; Meechai, Asawin

2016-06-01

We present a novel genome-scale metabolic model iWV1213 of Mucor circinelloides, which is an oleaginous fungus for industrial applications. The model contains 1213 genes, 1413 metabolites and 1326 metabolic reactions across different compartments. We demonstrate that iWV1213 is able to accurately predict the growth rates of M. circinelloides on various nutrient sources and culture conditions using Flux Balance Analysis and Phenotypic Phase Plane analysis. Comparative analysis of three oleaginous genome-scale models, including M. circinelloides (iWV1213), Mortierella alpina (iCY1106) and Yarrowia lipolytica (iYL619_PCP) revealed that iWV1213 possesses a higher number of genes involved in carbohydrate, amino acid, and lipid metabolisms that might contribute to its versatility in nutrient utilization. Moreover, the identification of unique and common active reactions among the Zygomycetes oleaginous models using Flux Variability Analysis unveiled a set of gene/enzyme candidates as metabolic engineering targets for cellular improvement. Thus, iWV1213 offers a powerful metabolic engineering tool for multi-level omics analysis, enabling strain optimization as a cell factory platform of lipid-based production. Copyright © 2016 Elsevier B.V. All rights reserved.

An exact arithmetic toolbox for a consistent and reproducible structural analysis of metabolic network models

PubMed Central

Chindelevitch, Leonid; Trigg, Jason; Regev, Aviv; Berger, Bonnie

2014-01-01

Constraint-based models are currently the only methodology that allows the study of metabolism at the whole-genome scale. Flux balance analysis is commonly used to analyse constraint-based models. Curiously, the results of this analysis vary with the software being run, a situation that we show can be remedied by using exact rather than floating-point arithmetic. Here we introduce MONGOOSE, a toolbox for analysing the structure of constraint-based metabolic models in exact arithmetic. We apply MONGOOSE to the analysis of 98 existing metabolic network models and find that the biomass reaction is surprisingly blocked (unable to sustain non-zero flux) in nearly half of them. We propose a principled approach for unblocking these reactions and extend it to the problems of identifying essential and synthetic lethal reactions and minimal media. Our structural insights enable a systematic study of constraint-based metabolic models, yielding a deeper understanding of their possibilities and limitations. PMID:25291352

Genome wide analysis of flowering time trait in multiple environments via high-throughput genotyping technique in Brassica napus L.

PubMed

Li, Lun; Long, Yan; Zhang, Libin; Dalton-Morgan, Jessica; Batley, Jacqueline; Yu, Longjiang; Meng, Jinling; Li, Maoteng

2015-01-01

The prediction of the flowering time (FT) trait in Brassica napus based on genome-wide markers and the detection of underlying genetic factors is important not only for oilseed producers around the world but also for the other crop industry in the rotation system in China. In previous studies the low density and mixture of biomarkers used obstructed genomic selection in B. napus and comprehensive mapping of FT related loci. In this study, a high-density genome-wide SNP set was genotyped from a double-haploid population of B. napus. We first performed genomic prediction of FT traits in B. napus using SNPs across the genome under ten environments of three geographic regions via eight existing genomic predictive models. The results showed that all the models achieved comparably high accuracies, verifying the feasibility of genomic prediction in B. napus. Next, we performed a large-scale mapping of FT related loci among three regions, and found 437 associated SNPs, some of which represented known FT genes, such as AP1 and PHYE. The genes tagged by the associated SNPs were enriched in biological processes involved in the formation of flowers. Epistasis analysis showed that significant interactions were found between detected loci, even among some known FT related genes. All the results showed that our large scale and high-density genotype data are of great practical and scientific values for B. napus. To our best knowledge, this is the first evaluation of genomic selection models in B. napus based on a high-density SNP dataset and large-scale mapping of FT loci.

Stepwise identification of HLA-A*0201-restricted CD8+ T-cell epitope peptides from herpes simplex virus type 1 genome boosted by a StepRank scheme.

PubMed

Bi, Jianjun; Song, Rengang; Yang, Huilan; Li, Bingling; Fan, Jianyong; Liu, Zhongrong; Long, Chaoqin

2011-01-01

Identification of immunodominant epitopes is the first step in the rational design of peptide vaccines aimed at T-cell immunity. To date, however, it is yet a great challenge for accurately predicting the potent epitope peptides from a pool of large-scale candidates with an efficient manner. In this study, a method that we named StepRank has been developed for the reliable and rapid prediction of binding capabilities/affinities between proteins and genome-wide peptides. In this procedure, instead of single strategy used in most traditional epitope identification algorithms, four steps with different purposes and thus different computational demands are employed in turn to screen the large-scale peptide candidates that are normally generated from, for example, pathogenic genome. The steps 1 and 2 aim at qualitative exclusion of typical nonbinders by using empirical rule and linear statistical approach, while the steps 3 and 4 focus on quantitative examination and prediction of the interaction energy profile and binding affinity of peptide to target protein via quantitative structure-activity relationship (QSAR) and structure-based free energy analysis. We exemplify this method through its application to binding predictions of the peptide segments derived from the 76 known open-reading frames (ORFs) of herpes simplex virus type 1 (HSV-1) genome with or without affinity to human major histocompatibility complex class I (MHC I) molecule HLA-A*0201, and find that the predictive results are well compatible with the classical anchor residue theory and perfectly match for the extended motif pattern of MHC I-binding peptides. The putative epitopes are further confirmed by comparisons with 11 experimentally measured HLA-A*0201-restrcited peptides from the HSV-1 glycoproteins D and K. We expect that this well-designed scheme can be applied in the computational screening of other viral genomes as well.

Genetic Classification of Populations Using Supervised Learning

PubMed Central

Bridges, Michael; Heron, Elizabeth A.; O'Dushlaine, Colm; Segurado, Ricardo; Morris, Derek; Corvin, Aiden; Gill, Michael; Pinto, Carlos

2011-01-01

There are many instances in genetics in which we wish to determine whether two candidate populations are distinguishable on the basis of their genetic structure. Examples include populations which are geographically separated, case–control studies and quality control (when participants in a study have been genotyped at different laboratories). This latter application is of particular importance in the era of large scale genome wide association studies, when collections of individuals genotyped at different locations are being merged to provide increased power. The traditional method for detecting structure within a population is some form of exploratory technique such as principal components analysis. Such methods, which do not utilise our prior knowledge of the membership of the candidate populations. are termed unsupervised. Supervised methods, on the other hand are able to utilise this prior knowledge when it is available. In this paper we demonstrate that in such cases modern supervised approaches are a more appropriate tool for detecting genetic differences between populations. We apply two such methods, (neural networks and support vector machines) to the classification of three populations (two from Scotland and one from Bulgaria). The sensitivity exhibited by both these methods is considerably higher than that attained by principal components analysis and in fact comfortably exceeds a recently conjectured theoretical limit on the sensitivity of unsupervised methods. In particular, our methods can distinguish between the two Scottish populations, where principal components analysis cannot. We suggest, on the basis of our results that a supervised learning approach should be the method of choice when classifying individuals into pre-defined populations, particularly in quality control for large scale genome wide association studies. PMID:21589856

Analysis of copy number variations reveals differences among cattle breeds

USDA-ARS?s Scientific Manuscript database

Genomic structural variation is an important and abundant source of genetic and phenotypic variation. Here we describe the first systematic and genome-wide analysis of copy number variations (CNVs) in the modern domesticated cattle using array comparative genomic hybridization (array CGH) and quanti...

Genetic diversity and structure of elite cotton germplasm (Gossypium hirsutum L.) using genome-wide SNP data.

PubMed

Ai, XianTao; Liang, YaJun; Wang, JunDuo; Zheng, JuYun; Gong, ZhaoLong; Guo, JiangPing; Li, XueYuan; Qu, YanYing

2017-10-01

Cotton (Gossypium spp.) is the most important natural textile fiber crop, and Gossypium hirsutum L. is responsible for 90% of the annual cotton crop in the world. Information on cotton genetic diversity and population structure is essential for new breeding lines. In this study, we analyzed population structure and genetic diversity of 288 elite Gossypium hirsutum cultivar accessions collected from around the world, and especially from China, using genome-wide single nucleotide polymorphisms (SNP) markers. The average polymorphsim information content (PIC) was 0.25, indicating a relatively low degree of genetic diversity. Population structure analysis revealed extensive admixture and identified three subgroups. Phylogenetic analysis supported the subgroups identified by STRUCTURE. The results from both population structure and phylogenetic analysis were, for the most part, in agreement with pedigree information. Analysis of molecular variance revealed a larger amount of variation was due to diversity within the groups. Establishment of genetic diversity and population structure from this study could be useful for genetic and genomic analysis and systematic utilization of the standing genetic variation in upland cotton.

Insights into the noncoding RNome of nitrogen-fixing endosymbiotic α-proteobacteria.

PubMed

Jiménez-Zurdo, José I; Valverde, Claudio; Becker, Anke

2013-02-01

Symbiotic chronic infection of legumes by rhizobia involves transition of invading bacteria from a free-living environment in soil to an intracellular state as differentiated nitrogen-fixing bacteroids within the nodules elicited in the host plant. The adaptive flexibility demanded by this complex lifestyle is likely facilitated by the large set of regulatory proteins encoded by rhizobial genomes. However, proteins are not the only relevant players in the regulation of gene expression in bacteria. Large-scale high-throughput analysis of prokaryotic genomes is evidencing the expression of an unexpected plethora of small untranslated transcripts (sRNAs) with housekeeping or regulatory roles. sRNAs mostly act in response to environmental cues as post-transcriptional regulators of gene expression through protein-assisted base-pairing interactions with target mRNAs. Riboregulation contributes to fine-tune a wide range of bacterial processes which, in intracellular animal pathogens, largely compromise virulence traits. Here, we summarize the incipient knowledge about the noncoding RNome structure of nitrogen-fixing endosymbiotic bacteria as inferred from genome-wide searches for sRNA genes in the alfalfa partner Sinorhizobium meliloti and further comparative genomics analysis. The biology of relevant S. meliloti RNA chaperones (e.g., Hfq) is also reviewed as a first global indicator of the impact of riboregulation in the establishment of the symbiotic interaction.

Quantitative phenotyping via deep barcode sequencing

PubMed Central

Smith, Andrew M.; Heisler, Lawrence E.; Mellor, Joseph; Kaper, Fiona; Thompson, Michael J.; Chee, Mark; Roth, Frederick P.; Giaever, Guri; Nislow, Corey

2009-01-01

Next-generation DNA sequencing technologies have revolutionized diverse genomics applications, including de novo genome sequencing, SNP detection, chromatin immunoprecipitation, and transcriptome analysis. Here we apply deep sequencing to genome-scale fitness profiling to evaluate yeast strain collections in parallel. This method, Barcode analysis by Sequencing, or “Bar-seq,” outperforms the current benchmark barcode microarray assay in terms of both dynamic range and throughput. When applied to a complex chemogenomic assay, Bar-seq quantitatively identifies drug targets, with performance superior to the benchmark microarray assay. We also show that Bar-seq is well-suited for a multiplex format. We completely re-sequenced and re-annotated the yeast deletion collection using deep sequencing, found that ∼20% of the barcodes and common priming sequences varied from expectation, and used this revised list of barcode sequences to improve data quality. Together, this new assay and analysis routine provide a deep-sequencing-based toolkit for identifying gene–environment interactions on a genome-wide scale. PMID:19622793

Launching genomics into the cloud: deployment of Mercury, a next generation sequence analysis pipeline

PubMed Central

2014-01-01

Background Massively parallel DNA sequencing generates staggering amounts of data. Decreasing cost, increasing throughput, and improved annotation have expanded the diversity of genomics applications in research and clinical practice. This expanding scale creates analytical challenges: accommodating peak compute demand, coordinating secure access for multiple analysts, and sharing validated tools and results. Results To address these challenges, we have developed the Mercury analysis pipeline and deployed it in local hardware and the Amazon Web Services cloud via the DNAnexus platform. Mercury is an automated, flexible, and extensible analysis workflow that provides accurate and reproducible genomic results at scales ranging from individuals to large cohorts. Conclusions By taking advantage of cloud computing and with Mercury implemented on the DNAnexus platform, we have demonstrated a powerful combination of a robust and fully validated software pipeline and a scalable computational resource that, to date, we have applied to more than 10,000 whole genome and whole exome samples. PMID:24475911

Alignment of Common Wheat and Other Grass Genomes Establishes a Comparative Genomics Research Platform

PubMed Central

Sun, Sangrong; Wang, Jinpeng; Yu, Jigao; Meng, Fanbo; Xia, Ruiyan; Wang, Li; Wang, Zhenyi; Ge, Weina; Liu, Xiaojian; Li, Yuxian; Liu, Yinzhe; Yang, Nanshan; Wang, Xiyin

2017-01-01

Grass genomes are complicated structures as they share a common tetraploidization, and particular genomes have been further affected by extra polyploidizations. These events and the following genomic re-patternings have resulted in a complex, interweaving gene homology both within a genome, and between genomes. Accurately deciphering the structure of these complicated plant genomes would help us better understand their compositional and functional evolution at multiple scales. Here, we build on our previous research by performing a hierarchical alignment of the common wheat genome vis-à-vis eight other sequenced grass genomes with most up-to-date assemblies, and annotations. With this data, we constructed a list of the homologous genes, and then, in a layer-by-layer process, separated their orthology, and paralogy that were established by speciations and recursive polyploidizations, respectively. Compared with the other grasses, the far fewer collinear outparalogous genes within each of three subgenomes of common wheat suggest that homoeologous recombination, and genomic fractionation should have occurred after its formation. In sum, this work contributes to the establishment of an important and timely comparative genomics platform for researchers in the grass community and possibly beyond. Homologous gene list can be found in Supplemental material. PMID:28912789

Comparative genomic analysis of Genlisea (corkscrew plants—Lentibulariaceae) chloroplast genomes reveals an increasing loss of the ndh genes

PubMed Central

Silva, Saura R.; Michael, Todd P.; Meer, Elliott J.; Pinheiro, Daniel G.; Miranda, Vitor F. O.

2018-01-01

In the carnivorous plant family Lentibulariaceae, all three genome compartments (nuclear, chloroplast, and mitochondria) have some of the highest rates of nucleotide substitutions across angiosperms. While the genera Genlisea and Utricularia have the smallest known flowering plant nuclear genomes, the chloroplast genomes (cpDNA) are mostly structurally conserved except for deletion and/or pseudogenization of the NAD(P)H-dehydrogenase complex (ndh) genes known to be involved in stress conditions of low light or CO2 concentrations. In order to determine how the cpDNA are changing, and to better understand the evolutionary history within the Genlisea genus, we sequenced, assembled and analyzed complete cpDNA from six species (G. aurea, G. filiformis, G. pygmaea, G. repens, G. tuberosa and G. violacea) together with the publicly available G. margaretae cpDNA. In general, the cpDNA structure among the analyzed Genlisea species is highly similar. However, we found that the plastidial ndh genes underwent a progressive process of degradation similar to the other terrestrial Lentibulariaceae cpDNA analyzed to date, but in contrast to the aquatic species. Contrary to current thinking that the terrestrial environment is a more stressful environment and thus requiring the ndh genes, we provide evidence that in the Lentibulariaceae the terrestrial forms have progressive loss while the aquatic forms have the eleven plastidial ndh genes intact. Therefore, the Lentibulariaceae system provides an important opportunity to understand the evolutionary forces that govern the transition to an aquatic environment and may provide insight into how plants manage water stress at a genome scale. PMID:29293597

Comparative genomic analysis of Genlisea (corkscrew plants-Lentibulariaceae) chloroplast genomes reveals an increasing loss of the ndh genes.

PubMed

Silva, Saura R; Michael, Todd P; Meer, Elliott J; Pinheiro, Daniel G; Varani, Alessandro M; Miranda, Vitor F O

2018-01-01

In the carnivorous plant family Lentibulariaceae, all three genome compartments (nuclear, chloroplast, and mitochondria) have some of the highest rates of nucleotide substitutions across angiosperms. While the genera Genlisea and Utricularia have the smallest known flowering plant nuclear genomes, the chloroplast genomes (cpDNA) are mostly structurally conserved except for deletion and/or pseudogenization of the NAD(P)H-dehydrogenase complex (ndh) genes known to be involved in stress conditions of low light or CO2 concentrations. In order to determine how the cpDNA are changing, and to better understand the evolutionary history within the Genlisea genus, we sequenced, assembled and analyzed complete cpDNA from six species (G. aurea, G. filiformis, G. pygmaea, G. repens, G. tuberosa and G. violacea) together with the publicly available G. margaretae cpDNA. In general, the cpDNA structure among the analyzed Genlisea species is highly similar. However, we found that the plastidial ndh genes underwent a progressive process of degradation similar to the other terrestrial Lentibulariaceae cpDNA analyzed to date, but in contrast to the aquatic species. Contrary to current thinking that the terrestrial environment is a more stressful environment and thus requiring the ndh genes, we provide evidence that in the Lentibulariaceae the terrestrial forms have progressive loss while the aquatic forms have the eleven plastidial ndh genes intact. Therefore, the Lentibulariaceae system provides an important opportunity to understand the evolutionary forces that govern the transition to an aquatic environment and may provide insight into how plants manage water stress at a genome scale.

Cell-free translational screening of an expression sequence tag library of Clonorchis sinensis for novel antigen discovery.

PubMed

Kasi, Devi; Catherine, Christy; Lee, Seung-Won; Lee, Kyung-Ho; Kim, Yu Jung; Ro Lee, Myeong; Ju, Jung Won; Kim, Dong-Myung

2017-05-01

The rapidly evolving cloning and sequencing technologies have enabled understanding of genomic structure of parasite genomes, opening up new ways of combatting parasite-related diseases. To make the most of the exponentially accumulating genomic data, however, it is crucial to analyze the proteins encoded by these genomic sequences. In this study, we adopted an engineered cell-free protein synthesis system for large-scale expression screening of an expression sequence tag (EST) library of Clonorchis sinensis to identify potential antigens that can be used for diagnosis and treatment of clonorchiasis. To allow high-throughput expression and identification of individual genes comprising the library, a cell-free synthesis reaction was designed such that both the template DNA and the expressed proteins were co-immobilized on the same microbeads, leading to microbead-based linkage of the genotype and phenotype. This reaction configuration allowed streamlined expression, recovery, and analysis of proteins. This approach enabled us to identify 21 antigenic proteins. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:832-837, 2017. © 2017 American Institute of Chemical Engineers.

The opportunities and challenges of large-scale molecular approaches to songbird neurobiology

PubMed Central

Mello, C.V.; Clayton, D.F.

2014-01-01

High-through put methods for analyzing genome structure and function are having a large impact in song-bird neurobiology. Methods include genome sequencing and annotation, comparative genomics, DNA microarrays and transcriptomics, and the development of a brain atlas of gene expression. Key emerging findings include the identification of complex transcriptional programs active during singing, the robust brain expression of non-coding RNAs, evidence of profound variations in gene expression across brain regions, and the identification of molecular specializations within song production and learning circuits. Current challenges include the statistical analysis of large datasets, effective genome curations, the efficient localization of gene expression changes to specific neuronal circuits and cells, and the dissection of behavioral and environmental factors that influence brain gene expression. The field requires efficient methods for comparisons with organisms like chicken, which offer important anatomical, functional and behavioral contrasts. As sequencing costs plummet, opportunities emerge for comparative approaches that may help reveal evolutionary transitions contributing to vocal learning, social behavior and other properties that make songbirds such compelling research subjects. PMID:25280907

Compactness of viral genomes: effect of disperse and localized random mutations

NASA Astrophysics Data System (ADS)

Lošdorfer Božič, Anže; Micheletti, Cristian; Podgornik, Rudolf; Tubiana, Luca

2018-02-01

Genomes of single-stranded RNA viruses have evolved to optimize several concurrent properties. One of them is the architecture of their genomic folds, which must not only feature precise structural elements at specific positions, but also allow for overall spatial compactness. The latter was shown to be disrupted by random synonymous mutations, a disruption which can consequently negatively affect genome encapsidation. In this study, we use three mutation schemes with different degrees of locality to mutate the genomes of phage MS2 and Brome Mosaic virus in order to understand the observed sensitivity of the global compactness of their folds. We find that mutating local stretches of their genomes’ sequence or structure is less disruptive to their compactness compared to inducing randomly-distributed mutations. Our findings are indicative of a mechanism for the conservation of compactness acting on a global scale of the genomes, and have several implications for understanding the interplay between local and global architecture of viral RNA genomes.

AlgaGEM – a genome-scale metabolic reconstruction of algae based on the Chlamydomonas reinhardtii genome

PubMed Central

2011-01-01

Background Microalgae have the potential to deliver biofuels without the associated competition for land resources. In order to realise the rates and titres necessary for commercial production, however, system-level metabolic engineering will be required. Genome scale metabolic reconstructions have revolutionized microbial metabolic engineering and are used routinely for in silico analysis and design. While genome scale metabolic reconstructions have been developed for many prokaryotes and model eukaryotes, the application to less well characterized eukaryotes such as algae is challenging not at least due to a lack of compartmentalization data. Results We have developed a genome-scale metabolic network model (named AlgaGEM) covering the metabolism for a compartmentalized algae cell based on the Chlamydomonas reinhardtii genome. AlgaGEM is a comprehensive literature-based genome scale metabolic reconstruction that accounts for the functions of 866 unique ORFs, 1862 metabolites, 2249 gene-enzyme-reaction-association entries, and 1725 unique reactions. The reconstruction was compartmentalized into the cytoplasm, mitochondrion, plastid and microbody using available data for algae complemented with compartmentalisation data for Arabidopsis thaliana. AlgaGEM describes a functional primary metabolism of Chlamydomonas and significantly predicts distinct algal behaviours such as the catabolism or secretion rather than recycling of phosphoglycolate in photorespiration. AlgaGEM was validated through the simulation of growth and algae metabolic functions inferred from literature. Using efficient resource utilisation as the optimality criterion, AlgaGEM predicted observed metabolic effects under autotrophic, heterotrophic and mixotrophic conditions. AlgaGEM predicts increased hydrogen production when cyclic electron flow is disrupted as seen in a high producing mutant derived from mutational studies. The model also predicted the physiological pathway for H2 production and identified new targets to further improve H2 yield. Conclusions AlgaGEM is a viable and comprehensive framework for in silico functional analysis and can be used to derive new, non-trivial hypotheses for exploring this metabolically versatile organism. Flux balance analysis can be used to identify bottlenecks and new targets to metabolically engineer microalgae for production of biofuels. PMID:22369158

mySyntenyPortal: an application package to construct websites for synteny block analysis.

PubMed

Lee, Jongin; Lee, Daehwan; Sim, Mikang; Kwon, Daehong; Kim, Juyeon; Ko, Younhee; Kim, Jaebum

2018-06-05

Advances in sequencing technologies have facilitated large-scale comparative genomics based on whole genome sequencing. Constructing and investigating conserved genomic regions among multiple species (called synteny blocks) are essential in the comparative genomics. However, they require significant amounts of computational resources and time in addition to bioinformatics skills. Many web interfaces have been developed to make such tasks easier. However, these web interfaces cannot be customized for users who want to use their own set of genome sequences or definition of synteny blocks. To resolve this limitation, we present mySyntenyPortal, a stand-alone application package to construct websites for synteny block analyses by using users' own genome data. mySyntenyPortal provides both command line and web-based interfaces to build and manage websites for large-scale comparative genomic analyses. The websites can be also easily published and accessed by other users. To demonstrate the usability of mySyntenyPortal, we present an example study for building websites to compare genomes of three mammalian species (human, mouse, and cow) and show how they can be easily utilized to identify potential genes affected by genome rearrangements. mySyntenyPortal will contribute for extended comparative genomic analyses based on large-scale whole genome sequences by providing unique functionality to support the easy creation of interactive websites for synteny block analyses from user's own genome data.

In Situ Hi-C Library Preparation for Plants to Study Their Three-Dimensional Chromatin Interactions on a Genome-Wide Scale.

PubMed

Liu, Chang

2017-01-01

The spatial organization of the genome in the nucleus is critical for many cellular processes. It has been broadly accepted that the packing of chromatin inside the nucleus is not random, but structured at several hierarchical levels. The Hi-C method combines Chromatin Conformation Capture and high-throughput sequencing, which allows interrogating genome-wide chromatin interactions. Depending on the sequencing depth, chromatin packing patterns derived from Hi-C experiments can be viewed on a chromosomal scale or at a local genic level. Here, I describe a protocol of plant in situ Hi-C library preparation, which covers procedures starting from tissue fixation to library amplification.

Using the Saccharomyces Genome Database (SGD) for analysis of genomic information

PubMed Central

Skrzypek, Marek S.; Hirschman, Jodi

2011-01-01

Analysis of genomic data requires access to software tools that place the sequence-derived information in the context of biology. The Saccharomyces Genome Database (SGD) integrates functional information about budding yeast genes and their products with a set of analysis tools that facilitate exploring their biological details. This unit describes how the various types of functional data available at SGD can be searched, retrieved, and analyzed. Starting with the guided tour of the SGD Home page and Locus Summary page, this unit highlights how to retrieve data using YeastMine, how to visualize genomic information with GBrowse, how to explore gene expression patterns with SPELL, and how to use Gene Ontology tools to characterize large-scale datasets. PMID:21901739

Are there ergodic limits to evolution? Ergodic exploration of genome space and convergence

PubMed Central

McLeish, Tom C. B.

2015-01-01

We examine the analogy between evolutionary dynamics and statistical mechanics to include the fundamental question of ergodicity—the representative exploration of the space of possible states (in the case of evolution this is genome space). Several properties of evolutionary dynamics are identified that allow a generalization of the ergodic dynamics, familiar in dynamical systems theory, to evolution. Two classes of evolved biological structure then arise, differentiated by the qualitative duration of their evolutionary time scales. The first class has an ergodicity time scale (the time required for representative genome exploration) longer than available evolutionary time, and has incompletely explored the genotypic and phenotypic space of its possibilities. This case generates no expectation of convergence to an optimal phenotype or possibility of its prediction. The second, more interesting, class exhibits an evolutionary form of ergodicity—essentially all of the structural space within the constraints of slower evolutionary variables have been sampled; the ergodicity time scale for the system evolution is less than the evolutionary time. In this case, some convergence towards similar optima may be expected for equivalent systems in different species where both possess ergodic evolutionary dynamics. When the fitness maximum is set by physical, rather than co-evolved, constraints, it is additionally possible to make predictions of some properties of the evolved structures and systems. We propose four structures that emerge from evolution within genotypes whose fitness is induced from their phenotypes. Together, these result in an exponential speeding up of evolution, when compared with complete exploration of genomic space. We illustrate a possible case of application and a prediction of convergence together with attaining a physical fitness optimum in the case of invertebrate compound eye resolution. PMID:26640648

Are there ergodic limits to evolution? Ergodic exploration of genome space and convergence.

PubMed

McLeish, Tom C B

2015-12-06

We examine the analogy between evolutionary dynamics and statistical mechanics to include the fundamental question of ergodicity-the representative exploration of the space of possible states (in the case of evolution this is genome space). Several properties of evolutionary dynamics are identified that allow a generalization of the ergodic dynamics, familiar in dynamical systems theory, to evolution. Two classes of evolved biological structure then arise, differentiated by the qualitative duration of their evolutionary time scales. The first class has an ergodicity time scale (the time required for representative genome exploration) longer than available evolutionary time, and has incompletely explored the genotypic and phenotypic space of its possibilities. This case generates no expectation of convergence to an optimal phenotype or possibility of its prediction. The second, more interesting, class exhibits an evolutionary form of ergodicity-essentially all of the structural space within the constraints of slower evolutionary variables have been sampled; the ergodicity time scale for the system evolution is less than the evolutionary time. In this case, some convergence towards similar optima may be expected for equivalent systems in different species where both possess ergodic evolutionary dynamics. When the fitness maximum is set by physical, rather than co-evolved, constraints, it is additionally possible to make predictions of some properties of the evolved structures and systems. We propose four structures that emerge from evolution within genotypes whose fitness is induced from their phenotypes. Together, these result in an exponential speeding up of evolution, when compared with complete exploration of genomic space. We illustrate a possible case of application and a prediction of convergence together with attaining a physical fitness optimum in the case of invertebrate compound eye resolution.

Inference of Population Structure using Dense Haplotype Data

PubMed Central

Lawson, Daniel John; Hellenthal, Garrett

2012-01-01

The advent of genome-wide dense variation data provides an opportunity to investigate ancestry in unprecedented detail, but presents new statistical challenges. We propose a novel inference framework that aims to efficiently capture information on population structure provided by patterns of haplotype similarity. Each individual in a sample is considered in turn as a recipient, whose chromosomes are reconstructed using chunks of DNA donated by the other individuals. Results of this “chromosome painting” can be summarized as a “coancestry matrix,” which directly reveals key information about ancestral relationships among individuals. If markers are viewed as independent, we show that this matrix almost completely captures the information used by both standard Principal Components Analysis (PCA) and model-based approaches such as STRUCTURE in a unified manner. Furthermore, when markers are in linkage disequilibrium, the matrix combines information across successive markers to increase the ability to discern fine-scale population structure using PCA. In parallel, we have developed an efficient model-based approach to identify discrete populations using this matrix, which offers advantages over PCA in terms of interpretability and over existing clustering algorithms in terms of speed, number of separable populations, and sensitivity to subtle population structure. We analyse Human Genome Diversity Panel data for 938 individuals and 641,000 markers, and we identify 226 populations reflecting differences on continental, regional, local, and family scales. We present multiple lines of evidence that, while many methods capture similar information among strongly differentiated groups, more subtle population structure in human populations is consistently present at a much finer level than currently available geographic labels and is only captured by the haplotype-based approach. The software used for this article, ChromoPainter and fineSTRUCTURE, is available from http://www.paintmychromosomes.com/. PMID:22291602

Company profile: Complete Genomics Inc.

PubMed

Reid, Clifford

2011-02-01

Complete Genomics Inc. is a life sciences company that focuses on complete human genome sequencing. It is taking a completely different approach to DNA sequencing than other companies in the industry. Rather than building a general-purpose platform for sequencing all organisms and all applications, it has focused on a single application - complete human genome sequencing. The company's Complete Genomics Analysis Platform (CGA™ Platform) comprises an integrated package of biochemistry, instrumentation and software that sequences human genomes at the highest quality, lowest cost and largest scale available. Complete Genomics offers a turnkey service that enables customers to outsource their human genome sequencing to the company's genome sequencing center in Mountain View, CA, USA. Customers send in their DNA samples, the company does all the library preparation, DNA sequencing, assembly and variant analysis, and customers receive research-ready data that they can use for biological discovery.

Genome-scale metabolic network of Cordyceps militaris useful for comparative analysis of entomopathogenic fungi.

PubMed

Vongsangnak, Wanwipa; Raethong, Nachon; Mujchariyakul, Warasinee; Nguyen, Nam Ninh; Leong, Hon Wai; Laoteng, Kobkul

2017-08-30

The first genome-scale metabolic network of Cordyceps militaris (iWV1170) was constructed representing its whole metabolisms, which consisted of 894 metabolites and 1,267 metabolic reactions across five compartments, including the plasma membrane, cytoplasm, mitochondria, peroxisome and extracellular space. The iWV1170 could be exploited to explain its phenotypes of growth ability, cordycepin and other metabolites production on various substrates. A high number of genes encoding extracellular enzymes for degradation of complex carbohydrates, lipids and proteins were existed in C. militaris genome. By comparative genome-scale analysis, the adenine metabolic pathway towards putative cordycepin biosynthesis was reconstructed, indicating their evolutionary relationships across eleven species of entomopathogenic fungi. The overall metabolic routes involved in the putative cordycepin biosynthesis were also identified in C. militaris, including central carbon metabolism, amino acid metabolism (glycine, l-glutamine and l-aspartate) and nucleotide metabolism (adenosine and adenine). Interestingly, a lack of the sequence coding for ribonucleotide reductase inhibitor was observed in C. militaris that might contribute to its over-production of cordycepin. Copyright © 2017. Published by Elsevier B.V.

Whole Genome Amplification and Reduced-Representation Genome Sequencing of Schistosoma japonicum Miracidia.

PubMed

Shortt, Jonathan A; Card, Daren C; Schield, Drew R; Liu, Yang; Zhong, Bo; Castoe, Todd A; Carlton, Elizabeth J; Pollock, David D

2017-01-01

In areas where schistosomiasis control programs have been implemented, morbidity and prevalence have been greatly reduced. However, to sustain these reductions and move towards interruption of transmission, new tools for disease surveillance are needed. Genomic methods have the potential to help trace the sources of new infections, and allow us to monitor drug resistance. Large-scale genotyping efforts for schistosome species have been hindered by cost, limited numbers of established target loci, and the small amount of DNA obtained from miracidia, the life stage most readily acquired from humans. Here, we present a method using next generation sequencing to provide high-resolution genomic data from S. japonicum for population-based studies. We applied whole genome amplification followed by double digest restriction site associated DNA sequencing (ddRADseq) to individual S. japonicum miracidia preserved on Whatman FTA cards. We found that we could effectively and consistently survey hundreds of thousands of variants from 10,000 to 30,000 loci from archived miracidia as old as six years. An analysis of variation from eight miracidia obtained from three hosts in two villages in Sichuan showed clear population structuring by village and host even within this limited sample. This high-resolution sequencing approach yields three orders of magnitude more information than microsatellite genotyping methods that have been employed over the last decade, creating the potential to answer detailed questions about the sources of human infections and to monitor drug resistance. Costs per sample range from $50-$200, depending on the amount of sequence information desired, and we expect these costs can be reduced further given continued reductions in sequencing costs, improvement of protocols, and parallelization. This approach provides new promise for using modern genome-scale sampling to S. japonicum surveillance, and could be applied to other schistosome species and other parasitic helminthes.

An integrated map of structural variation in 2,504 human genomes.

PubMed

Sudmant, Peter H; Rausch, Tobias; Gardner, Eugene J; Handsaker, Robert E; Abyzov, Alexej; Huddleston, John; Zhang, Yan; Ye, Kai; Jun, Goo; Fritz, Markus Hsi-Yang; Konkel, Miriam K; Malhotra, Ankit; Stütz, Adrian M; Shi, Xinghua; Casale, Francesco Paolo; Chen, Jieming; Hormozdiari, Fereydoun; Dayama, Gargi; Chen, Ken; Malig, Maika; Chaisson, Mark J P; Walter, Klaudia; Meiers, Sascha; Kashin, Seva; Garrison, Erik; Auton, Adam; Lam, Hugo Y K; Mu, Xinmeng Jasmine; Alkan, Can; Antaki, Danny; Bae, Taejeong; Cerveira, Eliza; Chines, Peter; Chong, Zechen; Clarke, Laura; Dal, Elif; Ding, Li; Emery, Sarah; Fan, Xian; Gujral, Madhusudan; Kahveci, Fatma; Kidd, Jeffrey M; Kong, Yu; Lameijer, Eric-Wubbo; McCarthy, Shane; Flicek, Paul; Gibbs, Richard A; Marth, Gabor; Mason, Christopher E; Menelaou, Androniki; Muzny, Donna M; Nelson, Bradley J; Noor, Amina; Parrish, Nicholas F; Pendleton, Matthew; Quitadamo, Andrew; Raeder, Benjamin; Schadt, Eric E; Romanovitch, Mallory; Schlattl, Andreas; Sebra, Robert; Shabalin, Andrey A; Untergasser, Andreas; Walker, Jerilyn A; Wang, Min; Yu, Fuli; Zhang, Chengsheng; Zhang, Jing; Zheng-Bradley, Xiangqun; Zhou, Wanding; Zichner, Thomas; Sebat, Jonathan; Batzer, Mark A; McCarroll, Steven A; Mills, Ryan E; Gerstein, Mark B; Bashir, Ali; Stegle, Oliver; Devine, Scott E; Lee, Charles; Eichler, Evan E; Korbel, Jan O

2015-10-01

Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

The complete chloroplast genome sequence of the CAM epiphyte Spanish moss (Tillandsia usneoides, Bromeliaceae) and its comparative analysis.

PubMed

Poczai, Péter; Hyvönen, Jaakko

2017-01-01

Spanish moss (Tillandsia usneoides) is an epiphytic bromeliad widely distributed throughout tropical and warm temperate America. This plant is highly adapted to extreme environmental conditions. Striking features of this species include specialized trichomes (scales) covering the surface of its shoots aiding the absorption of water and nutrients directly from the atmosphere and a specific photosynthesis using crassulacean acid metabolism (CAM). Here we report the plastid genome of Spanish moss and present the comparison of genome organization and sequence evolution within Poales. The plastome of Spanish moss has a quadripartite structure consisting of a large single copy (LSC, 87,439 bp), two inverted regions (IRa and IRb, 26,803 bp) and short single copy (SSC, 18,612 bp) region. The plastid genome had 37.2% GC content and 134 genes with 88 being unique protein-coding genes and 20 of these are duplicated in the IR, similar to other reported bromeliads. Our study shows that early diverging lineages of Poales do not have high substitution rates as compared to grasses, and plastid genomes of bromeliads show structural features considered to be ancestral in graminids. These include the loss of the introns in the clpP and rpoC1 genes and the complete loss or partial degradation of accD and ycf genes in the Graminid clade. Further structural rearrangements appeared in the graminids lacking in Spanish moss, which include a 28-kb inversion between the trnG-UCC-rps14 region and 6-kb in the trnG-UCC-psbD, followed by a third <1kb inversion in the trnT sequence.

The complete chloroplast genome sequence of the CAM epiphyte Spanish moss (Tillandsia usneoides, Bromeliaceae) and its comparative analysis

PubMed Central

Hyvönen, Jaakko

2017-01-01

Spanish moss (Tillandsia usneoides) is an epiphytic bromeliad widely distributed throughout tropical and warm temperate America. This plant is highly adapted to extreme environmental conditions. Striking features of this species include specialized trichomes (scales) covering the surface of its shoots aiding the absorption of water and nutrients directly from the atmosphere and a specific photosynthesis using crassulacean acid metabolism (CAM). Here we report the plastid genome of Spanish moss and present the comparison of genome organization and sequence evolution within Poales. The plastome of Spanish moss has a quadripartite structure consisting of a large single copy (LSC, 87,439 bp), two inverted regions (IRa and IRb, 26,803 bp) and short single copy (SSC, 18,612 bp) region. The plastid genome had 37.2% GC content and 134 genes with 88 being unique protein-coding genes and 20 of these are duplicated in the IR, similar to other reported bromeliads. Our study shows that early diverging lineages of Poales do not have high substitution rates as compared to grasses, and plastid genomes of bromeliads show structural features considered to be ancestral in graminids. These include the loss of the introns in the clpP and rpoC1 genes and the complete loss or partial degradation of accD and ycf genes in the Graminid clade. Further structural rearrangements appeared in the graminids lacking in Spanish moss, which include a 28-kb inversion between the trnG-UCC–rps14 region and 6-kb in the trnG-UCC–psbD, followed by a third <1kb inversion in the trnT sequence. PMID:29095905

CPTAC researchers report first large-scale integrated proteomic and genomic analysis of a human cancer | Office of Cancer Clinical Proteomics Research

Cancer.gov

Investigators from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) who comprehensively analyzed 95 human colorectal tumor samples, have determined how gene alterations identified in previous analyses of the same samples are expressed at the protein level. The integration of proteomic and genomic data, or proteogenomics, provides a more comprehensive view of the biological features that drive cancer than genomic analysis alone and may help identify the most important targets for cancer detection and intervention.

Techniques for Large-Scale Bacterial Genome Manipulation and Characterization of the Mutants with Respect to In Silico Metabolic Reconstructions.

PubMed

diCenzo, George C; Finan, Turlough M

2018-01-01

The rate at which all genes within a bacterial genome can be identified far exceeds the ability to characterize these genes. To assist in associating genes with cellular functions, a large-scale bacterial genome deletion approach can be employed to rapidly screen tens to thousands of genes for desired phenotypes. Here, we provide a detailed protocol for the generation of deletions of large segments of bacterial genomes that relies on the activity of a site-specific recombinase. In this procedure, two recombinase recognition target sequences are introduced into known positions of a bacterial genome through single cross-over plasmid integration. Subsequent expression of the site-specific recombinase mediates recombination between the two target sequences, resulting in the excision of the intervening region and its loss from the genome. We further illustrate how this deletion system can be readily adapted to function as a large-scale in vivo cloning procedure, in which the region excised from the genome is captured as a replicative plasmid. We next provide a procedure for the metabolic analysis of bacterial large-scale genome deletion mutants using the Biolog Phenotype MicroArray™ system. Finally, a pipeline is described, and a sample Matlab script is provided, for the integration of the obtained data with a draft metabolic reconstruction for the refinement of the reactions and gene-protein-reaction relationships in a metabolic reconstruction.

Cloud computing for genomic data analysis and collaboration.

PubMed

Langmead, Ben; Nellore, Abhinav

2018-04-01

Next-generation sequencing has made major strides in the past decade. Studies based on large sequencing data sets are growing in number, and public archives for raw sequencing data have been doubling in size every 18 months. Leveraging these data requires researchers to use large-scale computational resources. Cloud computing, a model whereby users rent computers and storage from large data centres, is a solution that is gaining traction in genomics research. Here, we describe how cloud computing is used in genomics for research and large-scale collaborations, and argue that its elasticity, reproducibility and privacy features make it ideally suited for the large-scale reanalysis of publicly available archived data, including privacy-protected data.

A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure.

PubMed

Sung, Yun J; Winkler, Thomas W; de Las Fuentes, Lisa; Bentley, Amy R; Brown, Michael R; Kraja, Aldi T; Schwander, Karen; Ntalla, Ioanna; Guo, Xiuqing; Franceschini, Nora; Lu, Yingchang; Cheng, Ching-Yu; Sim, Xueling; Vojinovic, Dina; Marten, Jonathan; Musani, Solomon K; Li, Changwei; Feitosa, Mary F; Kilpeläinen, Tuomas O; Richard, Melissa A; Noordam, Raymond; Aslibekyan, Stella; Aschard, Hugues; Bartz, Traci M; Dorajoo, Rajkumar; Liu, Yongmei; Manning, Alisa K; Rankinen, Tuomo; Smith, Albert Vernon; Tajuddin, Salman M; Tayo, Bamidele O; Warren, Helen R; Zhao, Wei; Zhou, Yanhua; Matoba, Nana; Sofer, Tamar; Alver, Maris; Amini, Marzyeh; Boissel, Mathilde; Chai, Jin Fang; Chen, Xu; Divers, Jasmin; Gandin, Ilaria; Gao, Chuan; Giulianini, Franco; Goel, Anuj; Harris, Sarah E; Hartwig, Fernando Pires; Horimoto, Andrea R V R; Hsu, Fang-Chi; Jackson, Anne U; Kähönen, Mika; Kasturiratne, Anuradhani; Kühnel, Brigitte; Leander, Karin; Lee, Wen-Jane; Lin, Keng-Hung; 'an Luan, Jian; McKenzie, Colin A; Meian, He; Nelson, Christopher P; Rauramaa, Rainer; Schupf, Nicole; Scott, Robert A; Sheu, Wayne H H; Stančáková, Alena; Takeuchi, Fumihiko; van der Most, Peter J; Varga, Tibor V; Wang, Heming; Wang, Yajuan; Ware, Erin B; Weiss, Stefan; Wen, Wanqing; Yanek, Lisa R; Zhang, Weihua; Zhao, Jing Hua; Afaq, Saima; Alfred, Tamuno; Amin, Najaf; Arking, Dan; Aung, Tin; Barr, R Graham; Bielak, Lawrence F; Boerwinkle, Eric; Bottinger, Erwin P; Braund, Peter S; Brody, Jennifer A; Broeckel, Ulrich; Cabrera, Claudia P; Cade, Brian; Caizheng, Yu; Campbell, Archie; Canouil, Mickaël; Chakravarti, Aravinda; Chauhan, Ganesh; Christensen, Kaare; Cocca, Massimiliano; Collins, Francis S; Connell, John M; de Mutsert, Renée; de Silva, H Janaka; Debette, Stephanie; Dörr, Marcus; Duan, Qing; Eaton, Charles B; Ehret, Georg; Evangelou, Evangelos; Faul, Jessica D; Fisher, Virginia A; Forouhi, Nita G; Franco, Oscar H; Friedlander, Yechiel; Gao, He; Gigante, Bruna; Graff, Misa; Gu, C Charles; Gu, Dongfeng; Gupta, Preeti; Hagenaars, Saskia P; Harris, Tamara B; He, Jiang; Heikkinen, Sami; Heng, Chew-Kiat; Hirata, Makoto; Hofman, Albert; Howard, Barbara V; Hunt, Steven; Irvin, Marguerite R; Jia, Yucheng; Joehanes, Roby; Justice, Anne E; Katsuya, Tomohiro; Kaufman, Joel; Kerrison, Nicola D; Khor, Chiea Chuen; Koh, Woon-Puay; Koistinen, Heikki A; Komulainen, Pirjo; Kooperberg, Charles; Krieger, Jose E; Kubo, Michiaki; Kuusisto, Johanna; Langefeld, Carl D; Langenberg, Claudia; Launer, Lenore J; Lehne, Benjamin; Lewis, Cora E; Li, Yize; Lim, Sing Hui; Lin, Shiow; Liu, Ching-Ti; Liu, Jianjun; Liu, Jingmin; Liu, Kiang; Liu, Yeheng; Loh, Marie; Lohman, Kurt K; Long, Jirong; Louie, Tin; Mägi, Reedik; Mahajan, Anubha; Meitinger, Thomas; Metspalu, Andres; Milani, Lili; Momozawa, Yukihide; Morris, Andrew P; Mosley, Thomas H; Munson, Peter; Murray, Alison D; Nalls, Mike A; Nasri, Ubaydah; Norris, Jill M; North, Kari; Ogunniyi, Adesola; Padmanabhan, Sandosh; Palmas, Walter R; Palmer, Nicholette D; Pankow, James S; Pedersen, Nancy L; Peters, Annette; Peyser, Patricia A; Polasek, Ozren; Raitakari, Olli T; Renström, Frida; Rice, Treva K; Ridker, Paul M; Robino, Antonietta; Robinson, Jennifer G; Rose, Lynda M; Rudan, Igor; Sabanayagam, Charumathi; Salako, Babatunde L; Sandow, Kevin; Schmidt, Carsten O; Schreiner, Pamela J; Scott, William R; Seshadri, Sudha; Sever, Peter; Sitlani, Colleen M; Smith, Jennifer A; Snieder, Harold; Starr, John M; Strauch, Konstantin; Tang, Hua; Taylor, Kent D; Teo, Yik Ying; Tham, Yih Chung; Uitterlinden, André G; Waldenberger, Melanie; Wang, Lihua; Wang, Ya X; Wei, Wen Bin; Williams, Christine; Wilson, Gregory; Wojczynski, Mary K; Yao, Jie; Yuan, Jian-Min; Zonderman, Alan B; Becker, Diane M; Boehnke, Michael; Bowden, Donald W; Chambers, John C; Chen, Yii-Der Ida; de Faire, Ulf; Deary, Ian J; Esko, Tõnu; Farrall, Martin; Forrester, Terrence; Franks, Paul W; Freedman, Barry I; Froguel, Philippe; Gasparini, Paolo; Gieger, Christian; Horta, Bernardo Lessa; Hung, Yi-Jen; Jonas, Jost B; Kato, Norihiro; Kooner, Jaspal S; Laakso, Markku; Lehtimäki, Terho; Liang, Kae-Woei; Magnusson, Patrik K E; Newman, Anne B; Oldehinkel, Albertine J; Pereira, Alexandre C; Redline, Susan; Rettig, Rainer; Samani, Nilesh J; Scott, James; Shu, Xiao-Ou; van der Harst, Pim; Wagenknecht, Lynne E; Wareham, Nicholas J; Watkins, Hugh; Weir, David R; Wickremasinghe, Ananda R; Wu, Tangchun; Zheng, Wei; Kamatani, Yoichiro; Laurie, Cathy C; Bouchard, Claude; Cooper, Richard S; Evans, Michele K; Gudnason, Vilmundur; Kardia, Sharon L R; Kritchevsky, Stephen B; Levy, Daniel; O'Connell, Jeff R; Psaty, Bruce M; van Dam, Rob M; Sims, Mario; Arnett, Donna K; Mook-Kanamori, Dennis O; Kelly, Tanika N; Fox, Ervin R; Hayward, Caroline; Fornage, Myriam; Rotimi, Charles N; Province, Michael A; van Duijn, Cornelia M; Tai, E Shyong; Wong, Tien Yin; Loos, Ruth J F; Reiner, Alex P; Rotter, Jerome I; Zhu, Xiaofeng; Bierut, Laura J; Gauderman, W James; Caulfield, Mark J; Elliott, Paul; Rice, Kenneth; Munroe, Patricia B; Morrison, Alanna C; Cupples, L Adrienne; Rao, Dabeeru C; Chasman, Daniel I

2018-03-01

Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined ∼18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p < 5 × 10 -8 ) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p < 5 × 10 -8 ). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling (MSRA, EBF2). Copyright © 2018 American Society of Human Genetics. All rights reserved.

Consistency Analysis of Genome-Scale Models of Bacterial Metabolism: A Metamodel Approach

PubMed Central

Ponce-de-Leon, Miguel; Calle-Espinosa, Jorge; Peretó, Juli; Montero, Francisco

2015-01-01

Genome-scale metabolic models usually contain inconsistencies that manifest as blocked reactions and gap metabolites. With the purpose to detect recurrent inconsistencies in metabolic models, a large-scale analysis was performed using a previously published dataset of 130 genome-scale models. The results showed that a large number of reactions (~22%) are blocked in all the models where they are present. To unravel the nature of such inconsistencies a metamodel was construed by joining the 130 models in a single network. This metamodel was manually curated using the unconnected modules approach, and then, it was used as a reference network to perform a gap-filling on each individual genome-scale model. Finally, a set of 36 models that had not been considered during the construction of the metamodel was used, as a proof of concept, to extend the metamodel with new biochemical information, and to assess its impact on gap-filling results. The analysis performed on the metamodel allowed to conclude: 1) the recurrent inconsistencies found in the models were already present in the metabolic database used during the reconstructions process; 2) the presence of inconsistencies in a metabolic database can be propagated to the reconstructed models; 3) there are reactions not manifested as blocked which are active as a consequence of some classes of artifacts, and; 4) the results of an automatic gap-filling are highly dependent on the consistency and completeness of the metamodel or metabolic database used as the reference network. In conclusion the consistency analysis should be applied to metabolic databases in order to detect and fill gaps as well as to detect and remove artifacts and redundant information. PMID:26629901

Genomic Hypomethylation in the Human Germline Associates with Selective Structural Mutability in the Human Genome

PubMed Central

Li, Jian; Harris, R. Alan; Cheung, Sau Wai; Coarfa, Cristian; Jeong, Mira; Goodell, Margaret A.; White, Lisa D.; Patel, Ankita; Kang, Sung-Hae; Shaw, Chad; Chinault, A. Craig; Gambin, Tomasz; Gambin, Anna; Lupski, James R.; Milosavljevic, Aleksandar

2012-01-01

The hotspots of structural polymorphisms and structural mutability in the human genome remain to be explained mechanistically. We examine associations of structural mutability with germline DNA methylation and with non-allelic homologous recombination (NAHR) mediated by low-copy repeats (LCRs). Combined evidence from four human sperm methylome maps, human genome evolution, structural polymorphisms in the human population, and previous genomic and disease studies consistently points to a strong association of germline hypomethylation and genomic instability. Specifically, methylation deserts, the ∼1% fraction of the human genome with the lowest methylation in the germline, show a tenfold enrichment for structural rearrangements that occurred in the human genome since the branching of chimpanzee and are highly enriched for fast-evolving loci that regulate tissue-specific gene expression. Analysis of copy number variants (CNVs) from 400 human samples identified using a custom-designed array comparative genomic hybridization (aCGH) chip, combined with publicly available structural variation data, indicates that association of structural mutability with germline hypomethylation is comparable in magnitude to the association of structural mutability with LCR–mediated NAHR. Moreover, rare CNVs occurring in the genomes of individuals diagnosed with schizophrenia, bipolar disorder, and developmental delay and de novo CNVs occurring in those diagnosed with autism are significantly more concentrated within hypomethylated regions. These findings suggest a new connection between the epigenome, selective mutability, evolution, and human disease. PMID:22615578

Comparison of codon usage bias across Leishmania and Trypanosomatids to understand mRNA secondary structure, relative protein abundance and pathway functions.

PubMed

Subramanian, Abhishek; Sarkar, Ram Rup

2015-10-01

Understanding the variations in gene organization and its effect on the phenotype across different Leishmania species, and to study differential clinical manifestations of parasite within the host, we performed large scale analysis of codon usage patterns between Leishmania and other known Trypanosomatid species. We present the causes and consequences of codon usage bias in Leishmania genomes with respect to mutational pressure, translational selection and amino acid composition bias. We establish GC bias at wobble position that governs codon usage bias across Leishmania species, rather than amino acid composition bias. We found that, within Leishmania, homogenous codon context coding for less frequent amino acid pairs and codons avoiding formation of folding structures in mRNA are essentially chosen. We predicted putative differences in global expression between genes belonging to specific pathways across Leishmania. This explains the role of evolution in shaping the otherwise conserved genome to demonstrate species-specific function-level differences for efficient survival. Copyright © 2015 Elsevier Inc. All rights reserved.

Image Analysis of DNA Fiber and Nucleus in Plants.

PubMed

Ohmido, Nobuko; Wako, Toshiyuki; Kato, Seiji; Fukui, Kiichi

2016-01-01

Advances in cytology have led to the application of a wide range of visualization methods in plant genome studies. Image analysis methods are indispensable tools where morphology, density, and color play important roles in the biological systems. Visualization and image analysis methods are useful techniques in the analyses of the detailed structure and function of extended DNA fibers (EDFs) and interphase nuclei. The EDF is the highest in the spatial resolving power to reveal genome structure and it can be used for physical mapping, especially for closely located genes and tandemly repeated sequences. One the other hand, analyzing nuclear DNA and proteins would reveal nuclear structure and functions. In this chapter, we describe the image analysis protocol for quantitatively analyzing different types of plant genome, EDFs and interphase nuclei.

A case study for cloud based high throughput analysis of NGS data using the globus genomics system

DOE PAGES

Bhuvaneshwar, Krithika; Sulakhe, Dinanath; Gauba, Robinder; ...

2015-01-01

Next generation sequencing (NGS) technologies produce massive amounts of data requiring a powerful computational infrastructure, high quality bioinformatics software, and skilled personnel to operate the tools. We present a case study of a practical solution to this data management and analysis challenge that simplifies terabyte scale data handling and provides advanced tools for NGS data analysis. These capabilities are implemented using the “Globus Genomics” system, which is an enhanced Galaxy workflow system made available as a service that offers users the capability to process and transfer data easily, reliably and quickly to address end-to-end NGS analysis requirements. The Globus Genomicsmore » system is built on Amazon's cloud computing infrastructure. The system takes advantage of elastic scaling of compute resources to run multiple workflows in parallel and it also helps meet the scale-out analysis needs of modern translational genomics research.« less

The mitochondrial genome of the pathogenic yeast Candida subhashii: GC-rich linear DNA with a protein covalently attached to the 5′ termini

PubMed Central

Fricova, Dominika; Valach, Matus; Farkas, Zoltan; Pfeiffer, Ilona; Kucsera, Judit; Tomaska, Lubomir; Nosek, Jozef

2010-01-01

As a part of our initiative aimed at a large-scale comparative analysis of fungal mitochondrial genomes, we determined the complete DNA sequence of the mitochondrial genome of the yeast Candida subhashii and found that it exhibits a number of peculiar features. First, the mitochondrial genome is represented by linear dsDNA molecules of uniform length (29 795 bp), with an unusually high content of guanine and cytosine residues (52.7 %). Second, the coding sequences lack introns; thus, the genome has a relatively compact organization. Third, the termini of the linear molecules consist of long inverted repeats and seem to contain a protein covalently bound to terminal nucleotides at the 5′ ends. This architecture resembles the telomeres in a number of linear viral and plasmid DNA genomes classified as invertrons, in which the terminal proteins serve as specific primers for the initiation of DNA synthesis. Finally, although the mitochondrial genome of C. subhashii contains essentially the same set of genes as other closely related pathogenic Candida species, we identified additional ORFs encoding two homologues of the family B protein-priming DNA polymerases and an unknown protein. The terminal structures and the genes for DNA polymerases are reminiscent of linear mitochondrial plasmids, indicating that this genome architecture might have emerged from fortuitous recombination between an ancestral, presumably circular, mitochondrial genome and an invertron-like element. PMID:20395267

A Chromosome-Scale Assembly of the Bactrocera cucurbitae Genome Provides Insight to the Genetic Basis of white pupae

PubMed Central

Sim, Sheina B.; Geib, Scott M.

2017-01-01

Genetic sexing strains (GSS) used in sterile insect technique (SIT) programs are textbook examples of how classical Mendelian genetics can be directly implemented in the management of agricultural insect pests. Although the foundation of traditionally developed GSS are single locus, autosomal recessive traits, their genetic basis are largely unknown. With the advent of modern genomic techniques, the genetic basis of sexing traits in GSS can now be further investigated. This study is the first of its kind to integrate traditional genetic techniques with emerging genomics to characterize a GSS using the tephritid fruit fly pest Bactrocera cucurbitae as a model. These techniques include whole-genome sequencing, the development of a mapping population and linkage map, and quantitative trait analysis. The experiment designed to map the genetic sexing trait in B. cucurbitae, white pupae (wp), also enabled the generation of a chromosome-scale genome assembly by integrating the linkage map with the assembly. Quantitative trait loci analysis revealed SNP loci near position 42 MB on chromosome 3 to be tightly linked to wp. Gene annotation and synteny analysis show a near perfect relationship between chromosomes in B. cucurbitae and Muller elements A–E in Drosophila melanogaster. This chromosome-scale genome assembly is complete, has high contiguity, was generated using a minimal input DNA, and will be used to further characterize the genetic mechanisms underlying wp. Knowledge of the genetic basis of genetic sexing traits can be used to improve SIT in this species and expand it to other economically important Diptera. PMID:28450369

A Parallel Population Genomic and Hydrodynamic Approach to Fishery Management of Highly-Dispersive Marine Invertebrates: The Case of the Fijian Black-Lip Pearl Oyster Pinctada margaritifera.

PubMed

Lal, Monal M; Southgate, Paul C; Jerry, Dean R; Bosserelle, Cyprien; Zenger, Kyall R

2016-01-01

Fishery management and conservation of marine species increasingly relies on genetic data to delineate biologically relevant stock boundaries. Unfortunately for high gene flow species which may display low, but statistically significant population structure, there is no clear consensus on the level of differentiation required to resolve distinct stocks. The use of fine-scale neutral and adaptive variation, considered together with environmental data can offer additional insights to this problem. Genome-wide genetic data (4,123 SNPs), together with an independent hydrodynamic particle dispersal model were used to inform farm and fishery management in the Fijian black-lip pearl oyster Pinctada margaritifera, where comprehensive fishery management is lacking, and the sustainability of exploitation uncertain. Weak fine-scale patterns of population structure were detected, indicative of broad-scale panmixia among wild oysters, while a hatchery-sourced farmed population exhibited a higher degree of genetic divergence (Fst = 0.0850-0.102). This hatchery-produced population had also experienced a bottleneck (NeLD = 5.1; 95% C.I. = [5.1-5.3]); compared to infinite NeLD estimates for all wild oysters. Simulation of larval transport pathways confirmed the existence of broad-scale mixture by surface ocean currents, correlating well with fine-scale patterns of population structuring. Fst outlier tests failed to detect large numbers of loci supportive of selection, with 2-5 directional outlier SNPs identified (average Fst = 0.116). The lack of biologically significant population genetic structure, absence of evidence for local adaptation and larval dispersal simulation, all indicate the existence of a single genetic stock of P. margaritifera in the Fiji Islands. This approach using independent genomic and oceanographic tools has allowed fundamental insights into stock structure in this species, with transferability to other highly-dispersive marine taxa for their conservation and management.

Genome Structure of the Legume, Lotus japonicus

PubMed Central

Sato, Shusei; Nakamura, Yasukazu; Kaneko, Takakazu; Asamizu, Erika; Kato, Tomohiko; Nakao, Mitsuteru; Sasamoto, Shigemi; Watanabe, Akiko; Ono, Akiko; Kawashima, Kumiko; Fujishiro, Tsunakazu; Katoh, Midori; Kohara, Mitsuyo; Kishida, Yoshie; Minami, Chiharu; Nakayama, Shinobu; Nakazaki, Naomi; Shimizu, Yoshimi; Shinpo, Sayaka; Takahashi, Chika; Wada, Tsuyuko; Yamada, Manabu; Ohmido, Nobuko; Hayashi, Makoto; Fukui, Kiichi; Baba, Tomoya; Nakamichi, Tomoko; Mori, Hirotada; Tabata, Satoshi

2008-01-01

The legume Lotus japonicus has been widely used as a model system to investigate the genetic background of legume-specific phenomena such as symbiotic nitrogen fixation. Here, we report structural features of the L. japonicus genome. The 315.1-Mb sequences determined in this and previous studies correspond to 67% of the genome (472 Mb), and are likely to cover 91.3% of the gene space. Linkage mapping anchored 130-Mb sequences onto the six linkage groups. A total of 10 951 complete and 19 848 partial structures of protein-encoding genes were assigned to the genome. Comparative analysis of these genes revealed the expansion of several functional domains and gene families that are characteristic of L. japonicus. Synteny analysis detected traces of whole-genome duplication and the presence of synteny blocks with other plant genomes to various degrees. This study provides the first opportunity to look into the complex and unique genetic system of legumes. PMID:18511435

RNA structural constraints in the evolution of the influenza A virus genome NP segment

PubMed Central

Gultyaev, Alexander P; Tsyganov-Bodounov, Anton; Spronken, Monique IJ; van der Kooij, Sander; Fouchier, Ron AM; Olsthoorn, René CL

2014-01-01

Conserved RNA secondary structures were predicted in the nucleoprotein (NP) segment of the influenza A virus genome using comparative sequence and structure analysis. A number of structural elements exhibiting nucleotide covariations were identified over the whole segment length, including protein-coding regions. Calculations of mutual information values at the paired nucleotide positions demonstrate that these structures impose considerable constraints on the virus genome evolution. Functional importance of a pseudoknot structure, predicted in the NP packaging signal region, was confirmed by plaque assays of the mutant viruses with disrupted structure and those with restored folding using compensatory substitutions. Possible functions of the conserved RNA folding patterns in the influenza A virus genome are discussed. PMID:25180940

Ensembl Genomes 2016: more genomes, more complexity.

PubMed

Kersey, Paul Julian; Allen, James E; Armean, Irina; Boddu, Sanjay; Bolt, Bruce J; Carvalho-Silva, Denise; Christensen, Mikkel; Davis, Paul; Falin, Lee J; Grabmueller, Christoph; Humphrey, Jay; Kerhornou, Arnaud; Khobova, Julia; Aranganathan, Naveen K; Langridge, Nicholas; Lowy, Ernesto; McDowall, Mark D; Maheswari, Uma; Nuhn, Michael; Ong, Chuang Kee; Overduin, Bert; Paulini, Michael; Pedro, Helder; Perry, Emily; Spudich, Giulietta; Tapanari, Electra; Walts, Brandon; Williams, Gareth; Tello-Ruiz, Marcela; Stein, Joshua; Wei, Sharon; Ware, Doreen; Bolser, Daniel M; Howe, Kevin L; Kulesha, Eugene; Lawson, Daniel; Maslen, Gareth; Staines, Daniel M

2016-01-04

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of programmatic and interactive interfaces to a rich range of data including reference sequence, gene models, transcriptional data, genetic variation and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments. These include the development of new analyses and views to represent polyploid genomes (of which bread wheat is the primary exemplar); and the continued up-scaling of the resource, which now includes over 23 000 bacterial genomes, 400 fungal genomes and 100 protist genomes, in addition to 55 genomes from invertebrate metazoa and 39 genomes from plants. This dramatic increase in the number of included genomes is one part of a broader effort to automate the integration of archival data (genome sequence, but also associated RNA sequence data and variant calls) within the context of reference genomes and make it available through the Ensembl user interfaces. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Ensembl Genomes 2016: more genomes, more complexity

PubMed Central

Kersey, Paul Julian; Allen, James E.; Armean, Irina; Boddu, Sanjay; Bolt, Bruce J.; Carvalho-Silva, Denise; Christensen, Mikkel; Davis, Paul; Falin, Lee J.; Grabmueller, Christoph; Humphrey, Jay; Kerhornou, Arnaud; Khobova, Julia; Aranganathan, Naveen K.; Langridge, Nicholas; Lowy, Ernesto; McDowall, Mark D.; Maheswari, Uma; Nuhn, Michael; Ong, Chuang Kee; Overduin, Bert; Paulini, Michael; Pedro, Helder; Perry, Emily; Spudich, Giulietta; Tapanari, Electra; Walts, Brandon; Williams, Gareth; Tello–Ruiz, Marcela; Stein, Joshua; Wei, Sharon; Ware, Doreen; Bolser, Daniel M.; Howe, Kevin L.; Kulesha, Eugene; Lawson, Daniel; Maslen, Gareth; Staines, Daniel M.

2016-01-01

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of programmatic and interactive interfaces to a rich range of data including reference sequence, gene models, transcriptional data, genetic variation and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments. These include the development of new analyses and views to represent polyploid genomes (of which bread wheat is the primary exemplar); and the continued up-scaling of the resource, which now includes over 23 000 bacterial genomes, 400 fungal genomes and 100 protist genomes, in addition to 55 genomes from invertebrate metazoa and 39 genomes from plants. This dramatic increase in the number of included genomes is one part of a broader effort to automate the integration of archival data (genome sequence, but also associated RNA sequence data and variant calls) within the context of reference genomes and make it available through the Ensembl user interfaces. PMID:26578574

Neandertal admixture in Eurasia confirmed by maximum-likelihood analysis of three genomes.

PubMed

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.

Neandertal Admixture in Eurasia Confirmed by Maximum-Likelihood Analysis of Three Genomes

PubMed Central

Lohse, Konrad; Frantz, Laurent A. F.

2014-01-01

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. PMID:24532731

[Comparative analysis of clustered regularly interspaced short palindromic repeats (CRISPRs) loci in the genomes of halophilic archaea].

PubMed

Zhang, Fan; Zhang, Bing; Xiang, Hua; Hu, Songnian

2009-11-01

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) is a widespread system that provides acquired resistance against phages in bacteria and archaea. Here we aim to genome-widely analyze the CRISPR in extreme halophilic archaea, of which the whole genome sequences are available at present time. We used bioinformatics methods including alignment, conservation analysis, GC content and RNA structure prediction to analyze the CRISPR structures of 7 haloarchaeal genomes. We identified the CRISPR structures in 5 halophilic archaea and revealed a conserved palindromic motif in the flanking regions of these CRISPR structures. In addition, we found that the repeat sequences of large CRISPR structures in halophilic archaea were greatly conserved, and two types of predicted RNA secondary structures derived from the repeat sequences were likely determined by the fourth base of the repeat sequence. Our results support the proposal that the leader sequence may function as recognition site by having palindromic structures in flanking regions, and the stem-loop secondary structure formed by repeat sequences may function in mediating the interaction between foreign genetic elements and CAS-encoded proteins.

Genome-wide association analysis based on multiple imputation with low-depth GBS data: application to biofuel traits in reed canarygrass

USDA-ARS?s Scientific Manuscript database

Genotyping-by-sequencing allows for large-scale genetic analyses in plant species with no reference genome, creating the challenge of sound inference in the presence of uncertain genotypes. Here we report an imputation-based genome-wide association study (GWAS) in reed canarygrass (Phalaris arundina...

Genome-scale characterization of RNA tertiary structures and their functional impact by RNA solvent accessibility prediction.

PubMed

Yang, Yuedong; Li, Xiaomei; Zhao, Huiying; Zhan, Jian; Wang, Jihua; Zhou, Yaoqi

2017-01-01

As most RNA structures are elusive to structure determination, obtaining solvent accessible surface areas (ASAs) of nucleotides in an RNA structure is an important first step to characterize potential functional sites and core structural regions. Here, we developed RNAsnap, the first machine-learning method trained on protein-bound RNA structures for solvent accessibility prediction. Built on sequence profiles from multiple sequence alignment (RNAsnap-prof), the method provided robust prediction in fivefold cross-validation and an independent test (Pearson correlation coefficients, r, between predicted and actual ASA values are 0.66 and 0.63, respectively). Application of the method to 6178 mRNAs revealed its positive correlation to mRNA accessibility by dimethyl sulphate (DMS) experimentally measured in vivo (r = 0.37) but not in vitro (r = 0.07), despite the lack of training on mRNAs and the fact that DMS accessibility is only an approximation to solvent accessibility. We further found strong association across coding and noncoding regions between predicted solvent accessibility of the mutation site of a single nucleotide variant (SNV) and the frequency of that variant in the population for 2.2 million SNVs obtained in the 1000 Genomes Project. Moreover, mapping solvent accessibility of RNAs to the human genome indicated that introns, 5' cap of 5' and 3' cap of 3' untranslated regions, are more solvent accessible, consistent with their respective functional roles. These results support conformational selections as the mechanism for the formation of RNA-protein complexes and highlight the utility of genome-scale characterization of RNA tertiary structures by RNAsnap. The server and its stand-alone downloadable version are available at http://sparks-lab.org. © 2016 Yang et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Gene Expression Analysis: Teaching Students to Do 30,000 Experiments at Once with Microarray

ERIC Educational Resources Information Center

Carvalho, Felicia I.; Johns, Christopher; Gillespie, Marc E.

2012-01-01

Genome scale experiments routinely produce large data sets that require computational analysis, yet there are few student-based labs that illustrate the design and execution of these experiments. In order for students to understand and participate in the genomic world, teaching labs must be available where students generate and analyze large data…

Rapid isolation of microsatellite DNAs and identification of polymorphic mitochondrial DNA regions in the fish rotan (Perccottus glenii) invading European Russia

USGS Publications Warehouse

King, Timothy L.; Eackles, Michael S.; Reshetnikov, Andrey N.

2015-01-01

Human-mediated translocations and subsequent large-scale colonization by the invasive fish rotan (Perccottus glenii Dybowski, 1877; Perciformes, Odontobutidae), also known as Amur or Chinese sleeper, has resulted in dramatic transformations of small lentic ecosystems. However, no detailed genetic information exists on population structure, levels of effective movement, or relatedness among geographic populations of P. glenii within the European part of the range. We used massively parallel genomic DNA shotgun sequencing on the semiconductor-based Ion Torrent Personal Genome Machine (PGM) sequencing platform to identify nuclear microsatellite and mitochondrial DNA sequences in P. glenii from European Russia. Here we describe the characterization of nine nuclear microsatellite loci, ascertain levels of allelic diversity, heterozygosity, and demographic status of P. glenii collected from Ilev, Russia, one of several initial introduction points in European Russia. In addition, we mapped sequence reads to the complete P. glenii mitochondrial DNA sequence to identify polymorphic regions. Nuclear microsatellite markers developed for P. glenii yielded sufficient genetic diversity to: (1) produce unique multilocus genotypes; (2) elucidate structure among geographic populations; and (3) provide unique perspectives for analysis of population sizes and historical demographics. Among 4.9 million filtered P. glenii Ion Torrent PGM sequence reads, 11,304 mapped to the mitochondrial genome (NC_020350). This resulted in 100 % coverage of this genome to a mean coverage depth of 102X. A total of 130 variable sites were observed between the publicly available genome from China and the studied composite mitochondrial genome. Among these, 82 were diagnostic and monomorphic between the mitochondrial genomes and distributed among 15 genome regions. The polymorphic sites (N = 48) were distributed among 11 mitochondrial genome regions. Our results also indicate that sequence reads generated from two three-hour runs on the Ion Torrent PGM can generate a sufficient number of nuclear and mitochondrial markers to improve understanding of the evolutionary and ecological dynamics of non-model and in particular, invasive species.

Genome-scale CRISPR-Cas9 Knockout and Transcriptional Activation Screening

PubMed Central

Joung, Julia; Konermann, Silvana; Gootenberg, Jonathan S.; Abudayyeh, Omar O.; Platt, Randall J.; Brigham, Mark D.; Sanjana, Neville E.; Zhang, Feng

2017-01-01

Forward genetic screens are powerful tools for the unbiased discovery and functional characterization of specific genetic elements associated with a phenotype of interest. Recently, the RNA-guided endonuclease Cas9 from the microbial CRISPR (clustered regularly interspaced short palindromic repeats) immune system has been adapted for genome-scale screening by combining Cas9 with pooled guide RNA libraries. Here we describe a protocol for genome-scale knockout and transcriptional activation screening using the CRISPR-Cas9 system. Custom- or ready-made guide RNA libraries are constructed and packaged into lentiviral vectors for delivery into cells for screening. As each screen is unique, we provide guidelines for determining screening parameters and maintaining sufficient coverage. To validate candidate genes identified from the screen, we further describe strategies for confirming the screening phenotype as well as genetic perturbation through analysis of indel rate and transcriptional activation. Beginning with library design, a genome-scale screen can be completed in 9–15 weeks followed by 4–5 weeks of validation. PMID:28333914

Genome-scale CRISPR-Cas9 knockout and transcriptional activation screening.

PubMed

Joung, Julia; Konermann, Silvana; Gootenberg, Jonathan S; Abudayyeh, Omar O; Platt, Randall J; Brigham, Mark D; Sanjana, Neville E; Zhang, Feng

2017-04-01

Forward genetic screens are powerful tools for the unbiased discovery and functional characterization of specific genetic elements associated with a phenotype of interest. Recently, the RNA-guided endonuclease Cas9 from the microbial CRISPR (clustered regularly interspaced short palindromic repeats) immune system has been adapted for genome-scale screening by combining Cas9 with pooled guide RNA libraries. Here we describe a protocol for genome-scale knockout and transcriptional activation screening using the CRISPR-Cas9 system. Custom- or ready-made guide RNA libraries are constructed and packaged into lentiviral vectors for delivery into cells for screening. As each screen is unique, we provide guidelines for determining screening parameters and maintaining sufficient coverage. To validate candidate genes identified by the screen, we further describe strategies for confirming the screening phenotype, as well as genetic perturbation, through analysis of indel rate and transcriptional activation. Beginning with library design, a genome-scale screen can be completed in 9-15 weeks, followed by 4-5 weeks of validation.

CGCI Investigators Reveal Comprehensive Landscape of Diffuse Large B-Cell Lymphoma (DLBCL) Genomes | Office of Cancer Genomics

Cancer.gov

Researchers from British Columbia Cancer Agency used whole genome sequencing to analyze 40 DLBCL cases and 13 cell lines in order to fill in the gaps of the complex landscape of DLBCL genomes. Their analysis, “Mutational and structural analysis of diffuse large B-cell lymphoma using whole genome sequencing,” was published online in Blood on May 22. The authors are Ryan Morin, Marco Marra, and colleagues.  

Genome-wide identification and characterisation of F-box family in maize.

PubMed

Jia, Fengjuan; Wu, Bingjiang; Li, Hui; Huang, Jinguang; Zheng, Chengchao

2013-11-01

F-box-containing proteins, as the key components of the protein degradation machinery, are widely distributed in higher plants and are considered as one of the largest known families of regulatory proteins. The F-box protein family plays a crucial role in plant growth and development and in response to biotic and abiotic stresses. However, systematic analysis of the F-box family in maize (Zea mays) has not been reported yet. In this paper, we identified and characterised the maize F-box genes in a genome-wide scale, including phylogenetic analysis, chromosome distribution, gene structure, promoter analysis and gene expression profiles. A total of 359 F-box genes were identified and divided into 15 subgroups by phylogenetic analysis. The F-box domain was relatively conserved, whereas additional motifs outside the F-box domain may indicate the functional diversification of maize F-box genes. These genes were unevenly distributed in ten maize chromosomes, suggesting that they expanded in the maize genome because of tandem and segmental duplication events. The expression profiles suggested that the maize F-box genes had temporal and spatial expression patterns. Putative cis-acting regulatory DNA elements involved in abiotic stresses were observed in maize F-box gene promoters. The gene expression profiles under abiotic stresses also suggested that some genes participated in stress responsive pathways. Furthermore, ten genes were chosen for quantitative real-time PCR analysis under drought stress and the results were consistent with the microarray data. This study has produced a comparative genomics analysis of the maize ZmFBX gene family that can be used in further studies to uncover their roles in maize growth and development.

A High-Resolution InDel (Insertion–Deletion) Markers-Anchored Consensus Genetic Map Identifies Major QTLs Governing Pod Number and Seed Yield in Chickpea

PubMed Central

Srivastava, Rishi; Singh, Mohar; Bajaj, Deepak; Parida, Swarup K.

2016-01-01

Development and large-scale genotyping of user-friendly informative genome/gene-derived InDel markers in natural and mapping populations is vital for accelerating genomics-assisted breeding applications of chickpea with minimal resource expenses. The present investigation employed a high-throughput whole genome next-generation resequencing strategy in low and high pod number parental accessions and homozygous individuals constituting the bulks from each of two inter-specific mapping populations [(Pusa 1103 × ILWC 46) and (Pusa 256 × ILWC 46)] to develop non-erroneous InDel markers at a genome-wide scale. Comparing these high-quality genomic sequences, 82,360 InDel markers with reference to kabuli genome and 13,891 InDel markers exhibiting differentiation between low and high pod number parental accessions and bulks of aforementioned mapping populations were developed. These informative markers were structurally and functionally annotated in diverse coding and non-coding sequence components of genome/genes of kabuli chickpea. The functional significance of regulatory and coding (frameshift and large-effect mutations) InDel markers for establishing marker-trait linkages through association/genetic mapping was apparent. The markers detected a greater amplification (97%) and intra-specific polymorphic potential (58–87%) among a diverse panel of cultivated desi, kabuli, and wild accessions even by using a simpler cost-efficient agarose gel-based assay implicating their utility in large-scale genetic analysis especially in domesticated chickpea with narrow genetic base. Two high-density inter-specific genetic linkage maps generated using aforesaid mapping populations were integrated to construct a consensus 1479 InDel markers-anchored high-resolution (inter-marker distance: 0.66 cM) genetic map for efficient molecular mapping of major QTLs governing pod number and seed yield per plant in chickpea. Utilizing these high-density genetic maps as anchors, three major genomic regions harboring each of pod number and seed yield robust QTLs (15–28% phenotypic variation explained) were identified on chromosomes 2, 4, and 6. The integration of genetic and physical maps at these QTLs mapped on chromosomes scaled-down the long major QTL intervals into high-resolution short pod number and seed yield robust QTL physical intervals (0.89–2.94 Mb) which were essentially got validated in multiple genetic backgrounds of two chickpea mapping populations. The genome-wide InDel markers including natural allelic variants and genomic loci/genes delineated at major six especially in one colocalized novel congruent robust pod number and seed yield robust QTLs mapped on a high-density consensus genetic map were found most promising in chickpea. These functionally relevant molecular tags can drive marker-assisted genetic enhancement to develop high-yielding cultivars with increased seed/pod number and yield in chickpea. PMID:27695461

Three-dimensional reconstruction of single-cell chromosome structure using recurrence plots.

PubMed

Hirata, Yoshito; Oda, Arisa; Ohta, Kunihiro; Aihara, Kazuyuki

2016-10-11

Single-cell analysis of the three-dimensional (3D) chromosome structure can reveal cell-to-cell variability in genome activities. Here, we propose to apply recurrence plots, a mathematical method of nonlinear time series analysis, to reconstruct the 3D chromosome structure of a single cell based on information of chromosomal contacts from genome-wide chromosome conformation capture (Hi-C) data. This recurrence plot-based reconstruction (RPR) method enables rapid reconstruction of a unique structure in single cells, even from incomplete Hi-C information.

Three-dimensional reconstruction of single-cell chromosome structure using recurrence plots

NASA Astrophysics Data System (ADS)

Hirata, Yoshito; Oda, Arisa; Ohta, Kunihiro; Aihara, Kazuyuki

2016-10-01

Single-cell analysis of the three-dimensional (3D) chromosome structure can reveal cell-to-cell variability in genome activities. Here, we propose to apply recurrence plots, a mathematical method of nonlinear time series analysis, to reconstruct the 3D chromosome structure of a single cell based on information of chromosomal contacts from genome-wide chromosome conformation capture (Hi-C) data. This recurrence plot-based reconstruction (RPR) method enables rapid reconstruction of a unique structure in single cells, even from incomplete Hi-C information.

Leveraging unsupervised training sets for multi-scale compartmentalization in renal pathology

NASA Astrophysics Data System (ADS)

Lutnick, Brendon; Tomaszewski, John E.; Sarder, Pinaki

2017-03-01

Clinical pathology relies on manual compartmentalization and quantification of biological structures, which is time consuming and often error-prone. Application of computer vision segmentation algorithms to histopathological image analysis, in contrast, can offer fast, reproducible, and accurate quantitative analysis to aid pathologists. Algorithms tunable to different biologically relevant structures can allow accurate, precise, and reproducible estimates of disease states. In this direction, we have developed a fast, unsupervised computational method for simultaneously separating all biologically relevant structures from histopathological images in multi-scale. Segmentation is achieved by solving an energy optimization problem. Representing the image as a graph, nodes (pixels) are grouped by minimizing a Potts model Hamiltonian, adopted from theoretical physics, modeling interacting electron spins. Pixel relationships (modeled as edges) are used to update the energy of the partitioned graph. By iteratively improving the clustering, the optimal number of segments is revealed. To reduce computational time, the graph is simplified using a Cantor pairing function to intelligently reduce the number of included nodes. The classified nodes are then used to train a multiclass support vector machine to apply the segmentation over the full image. Accurate segmentations of images with as many as 106 pixels can be completed only in 5 sec, allowing for attainable multi-scale visualization. To establish clinical potential, we employed our method in renal biopsies to quantitatively visualize for the first time scale variant compartments of heterogeneous intra- and extraglomerular structures simultaneously. Implications of the utility of our method extend to fields such as oncology, genomics, and non-biological problems.

Identification of both copy number variation-type and constant-type core elements in a large segmental duplication region of the mouse genome

PubMed Central

2013-01-01

Background Copy number variation (CNV), an important source of diversity in genomic structure, is frequently found in clusters called CNV regions (CNVRs). CNVRs are strongly associated with segmental duplications (SDs), but the composition of these complex repetitive structures remains unclear. Results We conducted self-comparative-plot analysis of all mouse chromosomes using the high-speed and large-scale-homology search algorithm SHEAP. For eight chromosomes, we identified various types of large SD as tartan-checked patterns within the self-comparative plots. A complex arrangement of diagonal split lines in the self-comparative-plots indicated the presence of large homologous repetitive sequences. We focused on one SD on chromosome 13 (SD13M), and developed SHEPHERD, a stepwise ab initio method, to extract longer repetitive elements and to characterize repetitive structures in this region. Analysis using SHEPHERD showed the existence of 60 core elements, which were expected to be the basic units that form SDs within the repetitive structure of SD13M. The demonstration that sequences homologous to the core elements (>70% homology) covered approximately 90% of the SD13M region indicated that our method can characterize the repetitive structure of SD13M effectively. Core elements were composed largely of fragmented repeats of a previously identified type, such as long interspersed nuclear elements (LINEs), together with partial genic regions. Comparative genome hybridization array analysis showed that whereas 42 core elements were components of CNVR that varied among mouse strains, 8 did not vary among strains (constant type), and the status of the others could not be determined. The CNV-type core elements contained significantly larger proportions of long terminal repeat (LTR) types of retrotransposon than the constant-type core elements, which had no CNV. The higher divergence rates observed in the CNV-type core elements than in the constant type indicate that the CNV-type core elements have a longer evolutionary history than constant-type core elements in SD13M. Conclusions Our methodology for the identification of repetitive core sequences simplifies characterization of the structures of large SDs and detailed analysis of CNV. The results of detailed structural and quantitative analyses in this study might help to elucidate the biological role of one of the SDs on chromosome 13. PMID:23834397

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

PubMed

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.

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

PubMed Central

Bhadra, Anindya; Rao, Arvind; Baladandayuthapani, Veerabhadran

2017-01-01

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. PMID:28437848

The Adoption of Cloud Computing in the Field of Genomics Research: The Influence of Ethical and Legal Issues

PubMed Central

Charlebois, Kathleen; Palmour, Nicole; Knoppers, Bartha Maria

2016-01-01

This study aims to understand the influence of the ethical and legal issues on cloud computing adoption in the field of genomics research. To do so, we adapted Diffusion of Innovation (DoI) theory to enable understanding of how key stakeholders manage the various ethical and legal issues they encounter when adopting cloud computing. Twenty semi-structured interviews were conducted with genomics researchers, patient advocates and cloud service providers. Thematic analysis generated five major themes: 1) Getting comfortable with cloud computing; 2) Weighing the advantages and the risks of cloud computing; 3) Reconciling cloud computing with data privacy; 4) Maintaining trust and 5) Anticipating the cloud by creating the conditions for cloud adoption. Our analysis highlights the tendency among genomics researchers to gradually adopt cloud technology. Efforts made by cloud service providers to promote cloud computing adoption are confronted by researchers’ perpetual cost and security concerns, along with a lack of familiarity with the technology. Further underlying those fears are researchers’ legal responsibility with respect to the data that is stored on the cloud. Alternative consent mechanisms aimed at increasing patients’ control over the use of their data also provide a means to circumvent various institutional and jurisdictional hurdles that restrict access by creating siloed databases. However, the risk of creating new, cloud-based silos may run counter to the goal in genomics research to increase data sharing on a global scale. PMID:27755563

The Adoption of Cloud Computing in the Field of Genomics Research: The Influence of Ethical and Legal Issues.

PubMed

Charlebois, Kathleen; Palmour, Nicole; Knoppers, Bartha Maria

2016-01-01

This study aims to understand the influence of the ethical and legal issues on cloud computing adoption in the field of genomics research. To do so, we adapted Diffusion of Innovation (DoI) theory to enable understanding of how key stakeholders manage the various ethical and legal issues they encounter when adopting cloud computing. Twenty semi-structured interviews were conducted with genomics researchers, patient advocates and cloud service providers. Thematic analysis generated five major themes: 1) Getting comfortable with cloud computing; 2) Weighing the advantages and the risks of cloud computing; 3) Reconciling cloud computing with data privacy; 4) Maintaining trust and 5) Anticipating the cloud by creating the conditions for cloud adoption. Our analysis highlights the tendency among genomics researchers to gradually adopt cloud technology. Efforts made by cloud service providers to promote cloud computing adoption are confronted by researchers' perpetual cost and security concerns, along with a lack of familiarity with the technology. Further underlying those fears are researchers' legal responsibility with respect to the data that is stored on the cloud. Alternative consent mechanisms aimed at increasing patients' control over the use of their data also provide a means to circumvent various institutional and jurisdictional hurdles that restrict access by creating siloed databases. However, the risk of creating new, cloud-based silos may run counter to the goal in genomics research to increase data sharing on a global scale.

Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database.

PubMed

Winsor, Geoffrey L; Griffiths, Emma J; Lo, Raymond; Dhillon, Bhavjinder K; Shay, Julie A; Brinkman, Fiona S L

2016-01-04

The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

The next generation of melanocyte data: Genetic, epigenetic, and transcriptional resource datasets and analysis tools.

PubMed

Loftus, Stacie K

2018-05-01

The number of melanocyte- and melanoma-derived next generation sequence genome-scale datasets have rapidly expanded over the past several years. This resource guide provides a summary of publicly available sources of melanocyte cell derived whole genome, exome, mRNA and miRNA transcriptome, chromatin accessibility and epigenetic datasets. Also highlighted are bioinformatic resources and tools for visualization and data queries which allow researchers a genome-scale view of the melanocyte. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

PubMed

Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien

2017-01-01

Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.

Systematic Determination of Replication Activity Type Highlights Interconnections between Replication, Chromatin Structure and Nuclear Localization

PubMed Central

Polten, Andreas; Hezroni, Hadas; Eldar, Yonina C.; Meshorer, Eran; Yakhini, Zohar; Simon, Itamar

2012-01-01

DNA replication is a highly regulated process, with each genomic locus replicating at a distinct time of replication (ToR). Advances in ToR measurement technology enabled several genome-wide profiling studies that revealed tight associations between ToR and general genomic features and a remarkable ToR conservation in mammals. Genome wide studies further showed that at the hundreds kb-to-megabase scale the genome can be divided into constant ToR regions (CTRs) in which the replication process propagates at a faster pace due to the activation of multiple origins and temporal transition regions (TTRs) in which the replication process propagates at a slower pace. We developed a computational tool that assigns a ToR to every measured locus and determines its replication activity type (CTR versus TTR). Our algorithm, ARTO (Analysis of Replication Timing and Organization), uses signal processing methods to fit a constant piece-wise linear curve to the measured raw data. We tested our algorithm and provide performance and usability results. A Matlab implementation of ARTO is available at http://bioinfo.cs.technion.ac.il/people/zohar/ARTO/. Applying our algorithm to ToR data measured in multiple mouse and human samples allowed precise genome-wide ToR determination and replication activity type characterization. Analysis of the results highlighted the plasticity of the replication program. For example, we observed significant ToR differences in 10–25% of the genome when comparing different tissue types. Our analyses also provide evidence for activity type differences in up to 30% of the probes. Integration of the ToR data with multiple aspects of chromosome organization characteristics suggests that ToR plays a role in shaping the regional chromatin structure. Namely, repressive chromatin marks, are associated with late ToR both in TTRs and CTRs. Finally, characterization of the differences between TTRs and CTRs, with matching ToR, revealed that TTRs are associated with compact chromatin and are located significantly closer to the nuclear envelope. Supplementary material is available. Raw and processed data were deposited in Geo (GSE17236). PMID:23145042

Genomic characterization of a core set of the USDA-NPGS Ethiopian sorghum germplasm collection: implications for germplasm conservation, evaluation, and utilization in crop improvement.

PubMed

Cuevas, Hugo E; Rosa-Valentin, Giseiry; Hayes, Chad M; Rooney, William L; Hoffmann, Leo

2017-01-26

The USDA Agriculture Research Service National Plant Germplasm System (NPGS) preserves the largest sorghum germplasm collection in the world, which includes 7,217 accessions from the center of diversity in Ethiopia. The characterization of this exotic germplasm at a genome-wide scale will improve conservation efforts and its utilization in research and breeding programs. Therefore, we phenotyped a representative core set of 374 Ethiopian accessions at two locations for agronomic traits and characterized the genomes. Using genotyping-by-sequencing, we identified 148,476 single-nucleotide polymorphism (SNP) markers distributed across the entire genome. Over half of the alleles were rare (frequency < 0.05). The genetic profile of each accession was unique (i.e., no duplicates), and the average genetic distance among accessions was 0.70. Based on population structure and cluster analyses, we separated the collection into 11 populations with pairwise F ST values ranging from 0.11 to 0.47. In total, 198 accessions (53%) were assigned to one of these populations with an ancestry membership coefficient of larger than 0.60; these covered 90% of the total genomic variation. We characterized these populations based on agronomic and seed compositional traits. We performed a cluster analysis with the sorghum association panel based on 26,026 SNPs and determined that nine of the Ethiopian populations expanded the genetic diversity in the panel. Genome-wide association analysis demonstrated that these low-coverage data and the observed population structure could be employed for the genomic dissection of important phenotypes in this core set of Ethiopian sorghum germplasm. The NPGS Ethiopian sorghum germplasm is a genetically and phenotypically diverse collection comprising 11 populations with high levels of admixture. Genetic associations with agronomic traits can be used to improve the screening of exotic germplasm for selection of specific populations. We detected many rare alleles, suggesting that this germplasm contains potentially useful undiscovered alleles, but their discovery and characterization will require extensive effort. The genotypic data available for these accessions provide a valuable resource for sorghum breeders and geneticists to effectively improve crops.

Genetic variability of mutans streptococci revealed by wide whole-genome sequencing

PubMed Central

2013-01-01

Background Mutans streptococci are a group of bacteria significantly contributing to tooth decay. Their genetic variability is however still not well understood. Results Genomes of 6 clinical S. mutans isolates of different origins, one isolate of S. sobrinus (DSM 20742) and one isolate of S. ratti (DSM 20564) were sequenced and comparatively analyzed. Genome alignment revealed a mosaic-like structure of genome arrangement. Genes related to pathogenicity are found to have high variations among the strains, whereas genes for oxidative stress resistance are well conserved, indicating the importance of this trait in the dental biofilm community. Analysis of genome-scale metabolic networks revealed significant differences in 42 pathways. A striking dissimilarity is the unique presence of two lactate oxidases in S. sobrinus DSM 20742, probably indicating an unusual capability of this strain in producing H2O2 and expanding its ecological niche. In addition, lactate oxidases may form with other enzymes a novel energetic pathway in S. sobrinus DSM 20742 that can remedy its deficiency in citrate utilization pathway. Using 67 S. mutans genomes currently available including the strains sequenced in this study, we estimates the theoretical core genome size of S. mutans, and performed modeling of S. mutans pan-genome by applying different fitting models. An “open” pan-genome was inferred. Conclusions The comparative genome analyses revealed diversities in the mutans streptococci group, especially with respect to the virulence related genes and metabolic pathways. The results are helpful for better understanding the evolution and adaptive mechanisms of these oral pathogen microorganisms and for combating them. PMID:23805886

Deep transcriptome sequencing provides new insights into the structural and functional organization of the wheat genome.

PubMed

Pingault, Lise; Choulet, Frédéric; Alberti, Adriana; Glover, Natasha; Wincker, Patrick; Feuillet, Catherine; Paux, Etienne

2015-02-10

Because of its size, allohexaploid nature, and high repeat content, the bread wheat genome is a good model to study the impact of the genome structure on gene organization, function, and regulation. However, because of the lack of a reference genome sequence, such studies have long been hampered and our knowledge of the wheat gene space is still limited. The access to the reference sequence of the wheat chromosome 3B provided us with an opportunity to study the wheat transcriptome and its relationships to genome and gene structure at a level that has never been reached before. By combining this sequence with RNA-seq data, we construct a fine transcriptome map of the chromosome 3B. More than 8,800 transcription sites are identified, that are distributed throughout the entire chromosome. Expression level, expression breadth, alternative splicing as well as several structural features of genes, including transcript length, number of exons, and cumulative intron length are investigated. Our analysis reveals a non-monotonic relationship between gene expression and structure and leads to the hypothesis that gene structure is determined by its function, whereas gene expression is subject to energetic cost. Moreover, we observe a recombination-based partitioning at the gene structure and function level. Our analysis provides new insights into the relationships between gene and genome structure and function. It reveals mechanisms conserved with other plant species as well as superimposed evolutionary forces that shaped the wheat gene space, likely participating in wheat adaptation.

Community annotation and bioinformatics workforce development in concert--Little Skate Genome Annotation Workshops and Jamborees.

PubMed

Wang, Qinghua; Arighi, Cecilia N; King, Benjamin L; Polson, Shawn W; Vincent, James; Chen, Chuming; Huang, Hongzhan; Kingham, Brewster F; Page, Shallee T; Rendino, Marc Farnum; Thomas, William Kelley; Udwary, Daniel W; Wu, Cathy H

2012-01-01

Recent advances in high-throughput DNA sequencing technologies have equipped biologists with a powerful new set of tools for advancing research goals. The resulting flood of sequence data has made it critically important to train the next generation of scientists to handle the inherent bioinformatic challenges. The North East Bioinformatics Collaborative (NEBC) is undertaking the genome sequencing and annotation of the little skate (Leucoraja erinacea) to promote advancement of bioinformatics infrastructure in our region, with an emphasis on practical education to create a critical mass of informatically savvy life scientists. In support of the Little Skate Genome Project, the NEBC members have developed several annotation workshops and jamborees to provide training in genome sequencing, annotation and analysis. Acting as a nexus for both curation activities and dissemination of project data, a project web portal, SkateBase (http://skatebase.org) has been developed. As a case study to illustrate effective coupling of community annotation with workforce development, we report the results of the Mitochondrial Genome Annotation Jamborees organized to annotate the first completely assembled element of the Little Skate Genome Project, as a culminating experience for participants from our three prior annotation workshops. We are applying the physical/virtual infrastructure and lessons learned from these activities to enhance and streamline the genome annotation workflow, as we look toward our continuing efforts for larger-scale functional and structural community annotation of the L. erinacea genome.

Community annotation and bioinformatics workforce development in concert—Little Skate Genome Annotation Workshops and Jamborees

PubMed Central

Wang, Qinghua; Arighi, Cecilia N.; King, Benjamin L.; Polson, Shawn W.; Vincent, James; Chen, Chuming; Huang, Hongzhan; Kingham, Brewster F.; Page, Shallee T.; Farnum Rendino, Marc; Thomas, William Kelley; Udwary, Daniel W.; Wu, Cathy H.

2012-01-01

Recent advances in high-throughput DNA sequencing technologies have equipped biologists with a powerful new set of tools for advancing research goals. The resulting flood of sequence data has made it critically important to train the next generation of scientists to handle the inherent bioinformatic challenges. The North East Bioinformatics Collaborative (NEBC) is undertaking the genome sequencing and annotation of the little skate (Leucoraja erinacea) to promote advancement of bioinformatics infrastructure in our region, with an emphasis on practical education to create a critical mass of informatically savvy life scientists. In support of the Little Skate Genome Project, the NEBC members have developed several annotation workshops and jamborees to provide training in genome sequencing, annotation and analysis. Acting as a nexus for both curation activities and dissemination of project data, a project web portal, SkateBase (http://skatebase.org) has been developed. As a case study to illustrate effective coupling of community annotation with workforce development, we report the results of the Mitochondrial Genome Annotation Jamborees organized to annotate the first completely assembled element of the Little Skate Genome Project, as a culminating experience for participants from our three prior annotation workshops. We are applying the physical/virtual infrastructure and lessons learned from these activities to enhance and streamline the genome annotation workflow, as we look toward our continuing efforts for larger-scale functional and structural community annotation of the L. erinacea genome. PMID:22434832

Toward Repurposing Metformin as a Precision Anti-Cancer Therapy Using Structural Systems Pharmacology

PubMed Central

Hart, Thomas; Dider, Shihab; Han, Weiwei; Xu, Hua; Zhao, Zhongming; Xie, Lei

2016-01-01

Metformin, a drug prescribed to treat type-2 diabetes, exhibits anti-cancer effects in a portion of patients, but the direct molecular and genetic interactions leading to this pleiotropic effect have not yet been fully explored. To repurpose metformin as a precision anti-cancer therapy, we have developed a novel structural systems pharmacology approach to elucidate metformin’s molecular basis and genetic biomarkers of action. We integrated structural proteome-scale drug target identification with network biology analysis by combining structural genomic, functional genomic, and interactomic data. Through searching the human structural proteome, we identified twenty putative metformin binding targets and their interaction models. We experimentally verified the interactions between metformin and our top-ranked kinase targets. Notably, kinases, particularly SGK1 and EGFR were identified as key molecular targets of metformin. Subsequently, we linked these putative binding targets to genes that do not directly bind to metformin but whose expressions are altered by metformin through protein-protein interactions, and identified network biomarkers of phenotypic response of metformin. The molecular targets and the key nodes in genetic networks are largely consistent with the existing experimental evidence. Their interactions can be affected by the observed cancer mutations. This study will shed new light into repurposing metformin for safe, effective, personalized therapies. PMID:26841718

modPDZpep: a web resource for structure based analysis of human PDZ-mediated interaction networks.

PubMed

Sain, Neetu; Mohanty, Debasisa

2016-09-21

PDZ domains recognize short sequence stretches usually present in C-terminal of their interaction partners. Because of the involvement of PDZ domains in many important biological processes, several attempts have been made for developing bioinformatics tools for genome-wide identification of PDZ interaction networks. Currently available tools for prediction of interaction partners of PDZ domains utilize machine learning approach. Since, they have been trained using experimental substrate specificity data for specific PDZ families, their applicability is limited to PDZ families closely related to the training set. These tools also do not allow analysis of PDZ-peptide interaction interfaces. We have used a structure based approach to develop modPDZpep, a program to predict the interaction partners of human PDZ domains and analyze structural details of PDZ interaction interfaces. modPDZpep predicts interaction partners by using structural models of PDZ-peptide complexes and evaluating binding energy scores using residue based statistical pair potentials. Since, it does not require training using experimental data on peptide binding affinity, it can predict substrates for diverse PDZ families. Because of the use of simple scoring function for binding energy, it is also fast enough for genome scale structure based analysis of PDZ interaction networks. Benchmarking using artificial as well as real negative datasets indicates good predictive power with ROC-AUC values in the range of 0.7 to 0.9 for a large number of human PDZ domains. Another novel feature of modPDZpep is its ability to map novel PDZ mediated interactions in human protein-protein interaction networks, either by utilizing available experimental phage display data or by structure based predictions. In summary, we have developed modPDZpep, a web-server for structure based analysis of human PDZ domains. It is freely available at http://www.nii.ac.in/modPDZpep.html or http://202.54.226.235/modPDZpep.html . This article was reviewed by Michael Gromiha and Zoltán Gáspári.

GWAMA: software for genome-wide association meta-analysis.

PubMed

Mägi, Reedik; Morris, Andrew P

2010-05-28

Despite the recent success of genome-wide association studies in identifying novel loci contributing effects to complex human traits, such as type 2 diabetes and obesity, much of the genetic component of variation in these phenotypes remains unexplained. One way to improving power to detect further novel loci is through meta-analysis of studies from the same population, increasing the sample size over any individual study. Although statistical software analysis packages incorporate routines for meta-analysis, they are ill equipped to meet the challenges of the scale and complexity of data generated in genome-wide association studies. We have developed flexible, open-source software for the meta-analysis of genome-wide association studies. The software incorporates a variety of error trapping facilities, and provides a range of meta-analysis summary statistics. The software is distributed with scripts that allow simple formatting of files containing the results of each association study and generate graphical summaries of genome-wide meta-analysis results. The GWAMA (Genome-Wide Association Meta-Analysis) software has been developed to perform meta-analysis of summary statistics generated from genome-wide association studies of dichotomous phenotypes or quantitative traits. Software with source files, documentation and example data files are freely available online at http://www.well.ox.ac.uk/GWAMA.

Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism

DTIC Science & Technology

2016-03-15

mutants hisC1 (PA4447), hisD (PA4448), hutH (PA5098), and PA0006. We predicted that uro - canate was depleted in these high biofilm-producing mutants and...Lam DK, Fleming L, Lo R, Whiteside MD, Yu NY, et al. PseudomonasGenome Database: improved comparative analysis and population genomics capability for

Metalloproteomics: Forward and Reverse Approaches in Metalloprotein Structural and Functional Characterization

PubMed Central

Shi, Wuxian; Chance, Mark R.

2010-01-01

About one-third of all proteins are associated with a metal. Metalloproteomics is defined as the structural and functional characterization of metalloproteins on a genome-wide scale. The methodologies utilized in metalloproteomics, including both forward (bottom-up) and reverse (top-down) technologies, to provide information on the identity, quantity and function of metalloproteins are discussed. Important techniques frequently employed in metalloproteomics include classical proteomics tools such as mass spectrometry and 2-D gels, immobilized-metal affinity chromatography, bioinformatics sequence analysis and homology modeling, X-ray absorption spectroscopy and other synchrotron radiation based tools. Combinative applications of these techniques provide a powerful approach to understand the function of metalloproteins. PMID:21130021

Elucidating the role of transcription in shaping the 3D structure of the bacterial genome

NASA Astrophysics Data System (ADS)

Brandao, Hugo B.; Wang, Xindan; Rudner, David Z.; Mirny, Leonid

Active transcription has been linked to several genome conformation changes in bacteria, including the recruitment of chromosomal DNA to the cell membrane and formation of nucleoid clusters. Using genomic and imaging data as input into mathematical models and polymer simulations, we sought to explore the extent to which bacterial 3D genome structure could be explained by 1D transcription tracks. Using B. subtilis as a model organism, we investigated via polymer simulations the role of loop extrusion and DNA super-coiling on the formation of interaction domains and other fine-scale features that are visible in chromosome conformation capture (Hi-C) data. We then explored the role of the condensin structural maintenance of chromosome complex on the alignment of chromosomal arms. A parameter-free transcription traffic model demonstrated that mean chromosomal arm alignment can be quantitatively explained, and the effects on arm alignment in genomically rearranged strains of B. subtilis were accurately predicted. H.B. acknowledges support from the Natural Sciences and Engineering Research Council of Canada for a PGS-D fellowship.

Finding the Genomic Basis of Local Adaptation: Pitfalls, Practical Solutions, and Future Directions.

PubMed

Hoban, Sean; Kelley, Joanna L; Lotterhos, Katie E; Antolin, Michael F; Bradburd, Gideon; Lowry, David B; Poss, Mary L; Reed, Laura K; Storfer, Andrew; Whitlock, Michael C

2016-10-01

Uncovering the genetic and evolutionary basis of local adaptation is a major focus of evolutionary biology. The recent development of cost-effective methods for obtaining high-quality genome-scale data makes it possible to identify some of the loci responsible for adaptive differences among populations. Two basic approaches for identifying putatively locally adaptive loci have been developed and are broadly used: one that identifies loci with unusually high genetic differentiation among populations (differentiation outlier methods) and one that searches for correlations between local population allele frequencies and local environments (genetic-environment association methods). Here, we review the promises and challenges of these genome scan methods, including correcting for the confounding influence of a species' demographic history, biases caused by missing aspects of the genome, matching scales of environmental data with population structure, and other statistical considerations. In each case, we make suggestions for best practices for maximizing the accuracy and efficiency of genome scans to detect the underlying genetic basis of local adaptation. With attention to their current limitations, genome scan methods can be an important tool in finding the genetic basis of adaptive evolutionary change.

Large-Scale Bioinformatics Analysis of Bacillus Genomes Uncovers Conserved Roles of Natural Products in Bacterial Physiology.

PubMed

Grubbs, Kirk J; Bleich, Rachel M; Santa Maria, Kevin C; Allen, Scott E; Farag, Sherif; Shank, Elizabeth A; Bowers, Albert A

2017-01-01

Bacteria possess an amazing capacity to synthesize a diverse range of structurally complex, bioactive natural products known as specialized (or secondary) metabolites. Many of these specialized metabolites are used as clinical therapeutics, while others have important ecological roles in microbial communities. The biosynthetic gene clusters (BGCs) that generate these metabolites can be identified in bacterial genome sequences using their highly conserved genetic features. We analyzed an unprecedented 1,566 bacterial genomes from Bacillus species and identified nearly 20,000 BGCs. By comparing these BGCs to one another as well as a curated set of known specialized metabolite BGCs, we discovered that the majority of Bacillus natural products are comprised of a small set of highly conserved, well-distributed, known natural product compounds. Most of these metabolites have important roles influencing the physiology and development of Bacillus species. We identified, in addition to these characterized compounds, many unique, weakly conserved BGCs scattered across the genus that are predicted to encode unknown natural products. Many of these "singleton" BGCs appear to have been acquired via horizontal gene transfer. Based on this large-scale characterization of metabolite production in the Bacilli , we go on to connect the alkylpyrones, natural products that are highly conserved but previously biologically uncharacterized, to a role in Bacillus physiology: inhibiting spore development. IMPORTANCE Bacilli are capable of producing a diverse array of specialized metabolites, many of which have gained attention for their roles as signals that affect bacterial physiology and development. Up to this point, however, the Bacillus genus's metabolic capacity has been underexplored. We undertook a deep genomic analysis of 1,566 Bacillus genomes to understand the full spectrum of metabolites that this bacterial group can make. We discovered that the majority of the specialized metabolites produced by Bacillus species are highly conserved, known compounds with important signaling roles in the physiology and development of this bacterium. Additionally, there is significant unique biosynthetic machinery distributed across the genus that might lead to new, unknown metabolites with diverse biological functions. Inspired by the findings of our genomic analysis, we speculate that the highly conserved alkylpyrones might have an important biological activity within this genus. We go on to validate this prediction by demonstrating that these natural products are developmental signals in Bacillus and act by inhibiting sporulation.

Family-specific scaling laws in bacterial genomes.

PubMed

De Lazzari, Eleonora; Grilli, Jacopo; Maslov, Sergei; Cosentino Lagomarsino, Marco

2017-07-27

Among several quantitative invariants found in evolutionary genomics, one of the most striking is the scaling of the overall abundance of proteins, or protein domains, sharing a specific functional annotation across genomes of given size. The size of these functional categories change, on average, as power-laws in the total number of protein-coding genes. Here, we show that such regularities are not restricted to the overall behavior of high-level functional categories, but also exist systematically at the level of single evolutionary families of protein domains. Specifically, the number of proteins within each family follows family-specific scaling laws with genome size. Functionally similar sets of families tend to follow similar scaling laws, but this is not always the case. To understand this systematically, we provide a comprehensive classification of families based on their scaling properties. Additionally, we develop a quantitative score for the heterogeneity of the scaling of families belonging to a given category or predefined group. Under the common reasonable assumption that selection is driven solely or mainly by biological function, these findings point to fine-tuned and interdependent functional roles of specific protein domains, beyond our current functional annotations. This analysis provides a deeper view on the links between evolutionary expansion of protein families and the functional constraints shaping the gene repertoire of bacterial genomes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Factors affecting reproducibility between genome-scale siRNA-based screens

PubMed Central

Barrows, Nicholas J.; Le Sommer, Caroline; Garcia-Blanco, Mariano A.; Pearson, James L.

2011-01-01

RNA interference-based screening is a powerful new genomic technology which addresses gene function en masse. To evaluate factors influencing hit list composition and reproducibility, we performed two identically designed small interfering RNA (siRNA)-based, whole genome screens for host factors supporting yellow fever virus infection. These screens represent two separate experiments completed five months apart and allow the direct assessment of the reproducibility of a given siRNA technology when performed in the same environment. Candidate hit lists generated by sum rank, median absolute deviation, z-score, and strictly standardized mean difference were compared within and between whole genome screens. Application of these analysis methodologies within a single screening dataset using a fixed threshold equivalent to a p-value ≤ 0.001 resulted in hit lists ranging from 82 to 1,140 members and highlighted the tremendous impact analysis methodology has on hit list composition. Intra- and inter-screen reproducibility was significantly influenced by the analysis methodology and ranged from 32% to 99%. This study also highlighted the power of testing at least two independent siRNAs for each gene product in primary screens. To facilitate validation we conclude by suggesting methods to reduce false discovery at the primary screening stage. In this study we present the first comprehensive comparison of multiple analysis strategies, and demonstrate the impact of the analysis methodology on the composition of the “hit list”. Therefore, we propose that the entire dataset derived from functional genome-scale screens, especially if publicly funded, should be made available as is done with data derived from gene expression and genome-wide association studies. PMID:20625183

Efficient analysis of large-scale genome-wide data with two R packages: bigstatsr and bigsnpr.

PubMed

Privé, Florian; Aschard, Hugues; Ziyatdinov, Andrey; Blum, Michael G B

2017-03-30

Genome-wide datasets produced for association studies have dramatically increased in size over the past few years, with modern datasets commonly including millions of variants measured in dozens of thousands of individuals. This increase in data size is a major challenge severely slowing down genomic analyses, leading to some software becoming obsolete and researchers having limited access to diverse analysis tools. Here we present two R packages, bigstatsr and bigsnpr, allowing for the analysis of large scale genomic data to be performed within R. To address large data size, the packages use memory-mapping for accessing data matrices stored on disk instead of in RAM. To perform data pre-processing and data analysis, the packages integrate most of the tools that are commonly used, either through transparent system calls to existing software, or through updated or improved implementation of existing methods. In particular, the packages implement fast and accurate computations of principal component analysis and association studies, functions to remove SNPs in linkage disequilibrium and algorithms to learn polygenic risk scores on millions of SNPs. We illustrate applications of the two R packages by analyzing a case-control genomic dataset for celiac disease, performing an association study and computing Polygenic Risk Scores. Finally, we demonstrate the scalability of the R packages by analyzing a simulated genome-wide dataset including 500,000 individuals and 1 million markers on a single desktop computer. https://privefl.github.io/bigstatsr/ & https://privefl.github.io/bigsnpr/. florian.prive@univ-grenoble-alpes.fr & michael.blum@univ-grenoble-alpes.fr. Supplementary materials are available at Bioinformatics online.

A Genomic Survey of SCPP Family Genes in Fishes Provides Novel Insights into the Evolution of Fish Scales.

PubMed

Lv, Yunyun; Kawasaki, Kazuhiko; Li, Jia; Li, Yanping; Bian, Chao; Huang, Yu; You, Xinxin; Shi, Qiong

2017-11-16

The family of secretory calcium-binding phosphoproteins (SCPPs) have been considered vital to skeletal tissue mineralization. However, most previous SCPP studies focused on phylogenetically distant animals but not on those closely related species. Here we provide novel insights into the coevolution of SCPP genes and fish scales in 10 species from Otophysi . According to their scale phenotypes, these fishes can be divided into three groups, i.e., scaled, sparsely scaled, and scaleless. We identified homologous SCPP genes in the genomes of these species and revealed an absence of some SCPP members in some genomes, suggesting an uneven evolutionary history of SCPP genes in fishes. In addition, most of these SCPP genes, with the exception of SPP1 , individually form one or two gene cluster(s) on each corresponding genome. Furthermore, we constructed phylogenetic trees using maximum likelihood method to estimate their evolution. The phylogenetic topology mostly supports two subclasses in some species, such as Cyprinus carpio , Sinocyclocheilus anshuiensis , S. grahamin , and S. rhinocerous , but not in the other examined fishes. By comparing the gene structures of recently reported candidate genes, SCPP1 and SCPP5 , for determining scale phenotypes, we found that the hypothesis is suitable for Astyanax mexicanus , but denied by S. anshuiensis , even though they are both sparsely scaled for cave adaptation. Thus, we conclude that, although different fish species display similar scale phenotypes, the underlying genetic changes however might be diverse. In summary, this paper accelerates the recognition of the SCPP family in teleosts for potential scale evolution.

Genome alignment with graph data structures: a comparison

PubMed Central

2014-01-01

Background Recent advances in rapid, low-cost sequencing have opened up the opportunity to study complete genome sequences. The computational approach of multiple genome alignment allows investigation of evolutionarily related genomes in an integrated fashion, providing a basis for downstream analyses such as rearrangement studies and phylogenetic inference. Graphs have proven to be a powerful tool for coping with the complexity of genome-scale sequence alignments. The potential of graphs to intuitively represent all aspects of genome alignments led to the development of graph-based approaches for genome alignment. These approaches construct a graph from a set of local alignments, and derive a genome alignment through identification and removal of graph substructures that indicate errors in the alignment. Results We compare the structures of commonly used graphs in terms of their abilities to represent alignment information. We describe how the graphs can be transformed into each other, and identify and classify graph substructures common to one or more graphs. Based on previous approaches, we compile a list of modifications that remove these substructures. Conclusion We show that crucial pieces of alignment information, associated with inversions and duplications, are not visible in the structure of all graphs. If we neglect vertex or edge labels, the graphs differ in their information content. Still, many ideas are shared among all graph-based approaches. Based on these findings, we outline a conceptual framework for graph-based genome alignment that can assist in the development of future genome alignment tools. PMID:24712884

Genome-based microbial ecology of anammox granules in a full-scale wastewater treatment system.

PubMed

Speth, Daan R; In 't Zandt, Michiel H; Guerrero-Cruz, Simon; Dutilh, Bas E; Jetten, Mike S M

2016-03-31

Partial-nitritation anammox (PNA) is a novel wastewater treatment procedure for energy-efficient ammonium removal. Here we use genome-resolved metagenomics to build a genome-based ecological model of the microbial community in a full-scale PNA reactor. Sludge from the bioreactor examined here is used to seed reactors in wastewater treatment plants around the world; however, the role of most of its microbial community in ammonium removal remains unknown. Our analysis yielded 23 near-complete draft genomes that together represent the majority of the microbial community. We assign these genomes to distinct anaerobic and aerobic microbial communities. In the aerobic community, nitrifying organisms and heterotrophs predominate. In the anaerobic community, widespread potential for partial denitrification suggests a nitrite loop increases treatment efficiency. Of our genomes, 19 have no previously cultivated or sequenced close relatives and six belong to bacterial phyla without any cultivated members, including the most complete Omnitrophica (formerly OP3) genome to date.

Genome-based microbial ecology of anammox granules in a full-scale wastewater treatment system

PubMed Central

Speth, Daan R.; in 't Zandt, Michiel H.; Guerrero-Cruz, Simon; Dutilh, Bas E.; Jetten, Mike S. M.

2016-01-01

Partial-nitritation anammox (PNA) is a novel wastewater treatment procedure for energy-efficient ammonium removal. Here we use genome-resolved metagenomics to build a genome-based ecological model of the microbial community in a full-scale PNA reactor. Sludge from the bioreactor examined here is used to seed reactors in wastewater treatment plants around the world; however, the role of most of its microbial community in ammonium removal remains unknown. Our analysis yielded 23 near-complete draft genomes that together represent the majority of the microbial community. We assign these genomes to distinct anaerobic and aerobic microbial communities. In the aerobic community, nitrifying organisms and heterotrophs predominate. In the anaerobic community, widespread potential for partial denitrification suggests a nitrite loop increases treatment efficiency. Of our genomes, 19 have no previously cultivated or sequenced close relatives and six belong to bacterial phyla without any cultivated members, including the most complete Omnitrophica (formerly OP3) genome to date. PMID:27029554

gmos: Rapid Detection of Genome Mosaicism over Short Evolutionary Distances.

PubMed

Domazet-Lošo, Mirjana; Domazet-Lošo, Tomislav

2016-01-01

Prokaryotic and viral genomes are often altered by recombination and horizontal gene transfer. The existing methods for detecting recombination are primarily aimed at viral genomes or sets of loci, since the expensive computation of underlying statistical models often hinders the comparison of complete prokaryotic genomes. As an alternative, alignment-free solutions are more efficient, but cannot map (align) a query to subject genomes. To address this problem, we have developed gmos (Genome MOsaic Structure), a new program that determines the mosaic structure of query genomes when compared to a set of closely related subject genomes. The program first computes local alignments between query and subject genomes and then reconstructs the query mosaic structure by choosing the best local alignment for each query region. To accomplish the analysis quickly, the program mostly relies on pairwise alignments and constructs multiple sequence alignments over short overlapping subject regions only when necessary. This fine-tuned implementation achieves an efficiency comparable to an alignment-free tool. The program performs well for simulated and real data sets of closely related genomes and can be used for fast recombination detection; for instance, when a new prokaryotic pathogen is discovered. As an example, gmos was used to detect genome mosaicism in a pathogenic Enterococcus faecium strain compared to seven closely related genomes. The analysis took less than two minutes on a single 2.1 GHz processor. The output is available in fasta format and can be visualized using an accessory program, gmosDraw (freely available with gmos).

gmos: Rapid Detection of Genome Mosaicism over Short Evolutionary Distances

PubMed Central

Domazet-Lošo, Mirjana; Domazet-Lošo, Tomislav

2016-01-01

Prokaryotic and viral genomes are often altered by recombination and horizontal gene transfer. The existing methods for detecting recombination are primarily aimed at viral genomes or sets of loci, since the expensive computation of underlying statistical models often hinders the comparison of complete prokaryotic genomes. As an alternative, alignment-free solutions are more efficient, but cannot map (align) a query to subject genomes. To address this problem, we have developed gmos (Genome MOsaic Structure), a new program that determines the mosaic structure of query genomes when compared to a set of closely related subject genomes. The program first computes local alignments between query and subject genomes and then reconstructs the query mosaic structure by choosing the best local alignment for each query region. To accomplish the analysis quickly, the program mostly relies on pairwise alignments and constructs multiple sequence alignments over short overlapping subject regions only when necessary. This fine-tuned implementation achieves an efficiency comparable to an alignment-free tool. The program performs well for simulated and real data sets of closely related genomes and can be used for fast recombination detection; for instance, when a new prokaryotic pathogen is discovered. As an example, gmos was used to detect genome mosaicism in a pathogenic Enterococcus faecium strain compared to seven closely related genomes. The analysis took less than two minutes on a single 2.1 GHz processor. The output is available in fasta format and can be visualized using an accessory program, gmosDraw (freely available with gmos). PMID:27846272

Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens.

PubMed

Pan, Joshua; Meyers, Robin M; Michel, Brittany C; Mashtalir, Nazar; Sizemore, Ann E; Wells, Jonathan N; Cassel, Seth H; Vazquez, Francisca; Weir, Barbara A; Hahn, William C; Marsh, Joseph A; Tsherniak, Aviad; Kadoch, Cigall

2018-05-23

Protein complexes are assemblies of subunits that have co-evolved to execute one or many coordinated functions in the cellular environment. Functional annotation of mammalian protein complexes is critical to understanding biological processes, as well as disease mechanisms. Here, we used genetic co-essentiality derived from genome-scale RNAi- and CRISPR-Cas9-based fitness screens performed across hundreds of human cancer cell lines to assign measures of functional similarity. From these measures, we systematically built and characterized functional similarity networks that recapitulate known structural and functional features of well-studied protein complexes and resolve novel functional modules within complexes lacking structural resolution, such as the mammalian SWI/SNF complex. Finally, by integrating functional networks with large protein-protein interaction networks, we discovered novel protein complexes involving recently evolved genes of unknown function. Taken together, these findings demonstrate the utility of genetic perturbation screens alone, and in combination with large-scale biophysical data, to enhance our understanding of mammalian protein complexes in normal and disease states. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Metabolic Network Modeling of Microbial Communities

PubMed Central

Biggs, Matthew B.; Medlock, Gregory L.; Kolling, Glynis L.

2015-01-01

Genome-scale metabolic network reconstructions and constraint-based analysis are powerful methods that have the potential to make functional predictions about microbial communities. Current use of genome-scale metabolic networks to characterize the metabolic functions of microbial communities includes species compartmentalization, separating species-level and community-level objectives, dynamic analysis, the “enzyme-soup” approach, multi-scale modeling, and others. There are many challenges inherent to the field, including a need for tools that accurately assign high-level omics signals to individual community members, new automated reconstruction methods that rival manual curation, and novel algorithms for integrating omics data and engineering communities. As technologies and modeling frameworks improve, we expect that there will be proportional advances in the fields of ecology, health science, and microbial community engineering. PMID:26109480

Genome-scale analysis of positionally relocated genes

PubMed Central

Bhutkar, Arjun; Russo, Susan M.; Smith, Temple F.; Gelbart, William M.

2007-01-01

During evolution, genome reorganization includes large-scale events such as inversions, translocations, and segmental or even whole-genome duplications, as well as fine-scale events such as the relocation of individual genes. This latter category, which we will refer to as positionally relocated genes (PRGs), is the subject of this report. Assessment of the magnitude of such PRGs and of possible contributing mechanisms is aided by a comparative analysis of related genomes, where conserved chromosomal organization can aid in identifying genes that have acquired a new location in a lineage of these genomes. Here we utilize two methods to comprehensively identify relocated protein-coding genes in the recently sequenced genomes of 12 species of genus Drosophila. We use exceptions to the general rule of maintenance of chromosome arm (Muller element) association for most Drosophila genes to identify one major class of PRGs. We also identify a partially overlapping set of PRGs among “embedded genes,” located within the extents of other surrounding genes. We provide evidence that PRG movements have at least two different origins: Some events occur via retrotransposition of processed RNAs and others via a DNA-based transposition mechanism. Overall, we identify several hundred PRGs that arose within a lineage of the genus Drosophila phylogeny and provide suggestive evidence that a few thousand such events have occurred within the radiation of the insect order Diptera, thereby illustrating the magnitude of the contribution of PRG movement to chromosomal reorganization during evolution. PMID:17989252

[The human variome project and its progress].

PubMed

Gao, Shan; Zhang, Ning; Zhang, Lei; Duan, Guang-You; Zhang, Tao

2010-11-01

The main goal of post genomics is to explain how the genome, the map of which has been constructed in the Human Genome Project, affacts activities of life. This leads to generate multiple "omics": structural genomics, functional genomics, proteomics, metabonomics, et al. In Jun. 2006, Melbourne, Australia, Human Genome Variation Society (HGVS) initiated the Human Variome Project (HVP) to collect all the sequence variation and polymorphism data worldwidely. HVP is to search and determine those mutations related with human diseases by association study between genetype and phenotype on the scale of genome level and other methods. Those results will be translated into clinical application. Considering the potential effects of this project on human health, this paper introduced its origin and main content in detail and discussed its meaning and prospect.

The amphioxus genome and the evolution of the chordate karyotype

DOE Office of Scientific and Technical Information (OSTI.GOV)

Putnam, Nicholas H.; Butts, Thomas; Ferrier, David E.K.

2008-04-01

Lancelets ('amphioxus') are the modern survivors of an ancient chordate lineage with a fossil record dating back to the Cambrian. We describe the structure and gene content of the highly polymorphic {approx}520 million base pair genome of the Florida lancelet Branchiostoma floridae, and analyze it in the context of chordate evolution. Whole genome comparisons illuminate the murky relationships among the three chordate groups (tunicates, lancelets, and vertebrates), and allow reconstruction of not only the gene complement of the last common chordate ancestor, but also a partial reconstruction of its genomic organization, as well as a description of two genome-wide duplicationsmore » and subsequent reorganizations in the vertebrate lineage. These genome-scale events shaped the vertebrate genome and provided additional genetic variation for exploitation during vertebrate evolution.« less

The Jujube Genome Provides Insights into Genome Evolution and the Domestication of Sweetness/Acidity Taste in Fruit Trees

PubMed Central

Wan, KangKang; Zhang, Zhong; Pang, Xiaoming; Yin, Xiao; Bai, Yang; Sun, Xiaoqing; Gao, Lizhi; Li, Ruiqiang; Zhang, Jinbo

2016-01-01

Jujube (Ziziphus jujuba Mill.) belongs to the Rhamnaceae family and is a popular fruit tree species with immense economic and nutritional value. Here, we report a draft genome of the dry jujube cultivar ‘Junzao’ and the genome resequencing of 31 geographically diverse accessions of cultivated and wild jujubes (Ziziphus jujuba var. spinosa). Comparative analysis revealed that the genome of ‘Dongzao’, a fresh jujube, was ~86.5 Mb larger than that of the ‘Junzao’, partially due to the recent insertions of transposable elements in the ‘Dongzao’ genome. We constructed eight proto-chromosomes of the common ancestor of Rhamnaceae and Rosaceae, two sister families in the order Rosales, and elucidated the evolutionary processes that have shaped the genome structures of modern jujubes. Population structure analysis revealed the complex genetic background of jujubes resulting from extensive hybridizations between jujube and its wild relatives. Notably, several key genes that control fruit organic acid metabolism and sugar content were identified in the selective sweep regions. We also identified S-locus genes controlling gametophytic self-incompatibility and investigated haplotype patterns of the S locus in the jujube genomes, which would provide a guideline for parent selection for jujube crossbreeding. This study provides valuable genomic resources for jujube improvement, and offers insights into jujube genome evolution and its population structure and domestication. PMID:28005948

The Jujube Genome Provides Insights into Genome Evolution and the Domestication of Sweetness/Acidity Taste in Fruit Trees.

PubMed

Huang, Jian; Zhang, Chunmei; Zhao, Xing; Fei, Zhangjun; Wan, KangKang; Zhang, Zhong; Pang, Xiaoming; Yin, Xiao; Bai, Yang; Sun, Xiaoqing; Gao, Lizhi; Li, Ruiqiang; Zhang, Jinbo; Li, Xingang

2016-12-01

Jujube (Ziziphus jujuba Mill.) belongs to the Rhamnaceae family and is a popular fruit tree species with immense economic and nutritional value. Here, we report a draft genome of the dry jujube cultivar 'Junzao' and the genome resequencing of 31 geographically diverse accessions of cultivated and wild jujubes (Ziziphus jujuba var. spinosa). Comparative analysis revealed that the genome of 'Dongzao', a fresh jujube, was ~86.5 Mb larger than that of the 'Junzao', partially due to the recent insertions of transposable elements in the 'Dongzao' genome. We constructed eight proto-chromosomes of the common ancestor of Rhamnaceae and Rosaceae, two sister families in the order Rosales, and elucidated the evolutionary processes that have shaped the genome structures of modern jujubes. Population structure analysis revealed the complex genetic background of jujubes resulting from extensive hybridizations between jujube and its wild relatives. Notably, several key genes that control fruit organic acid metabolism and sugar content were identified in the selective sweep regions. We also identified S-locus genes controlling gametophytic self-incompatibility and investigated haplotype patterns of the S locus in the jujube genomes, which would provide a guideline for parent selection for jujube crossbreeding. This study provides valuable genomic resources for jujube improvement, and offers insights into jujube genome evolution and its population structure and domestication.

BAMSI: a multi-cloud service for scalable distributed filtering of massive genome data.

PubMed

Ausmees, Kristiina; John, Aji; Toor, Salman Z; Hellander, Andreas; Nettelblad, Carl

2018-06-26

The advent of next-generation sequencing (NGS) has made whole-genome sequencing of cohorts of individuals a reality. Primary datasets of raw or aligned reads of this sort can get very large. For scientific questions where curated called variants are not sufficient, the sheer size of the datasets makes analysis prohibitively expensive. In order to make re-analysis of such data feasible without the need to have access to a large-scale computing facility, we have developed a highly scalable, storage-agnostic framework, an associated API and an easy-to-use web user interface to execute custom filters on large genomic datasets. We present BAMSI, a Software as-a Service (SaaS) solution for filtering of the 1000 Genomes phase 3 set of aligned reads, with the possibility of extension and customization to other sets of files. Unique to our solution is the capability of simultaneously utilizing many different mirrors of the data to increase the speed of the analysis. In particular, if the data is available in private or public clouds - an increasingly common scenario for both academic and commercial cloud providers - our framework allows for seamless deployment of filtering workers close to data. We show results indicating that such a setup improves the horizontal scalability of the system, and present a possible use case of the framework by performing an analysis of structural variation in the 1000 Genomes data set. BAMSI constitutes a framework for efficient filtering of large genomic data sets that is flexible in the use of compute as well as storage resources. The data resulting from the filter is assumed to be greatly reduced in size, and can easily be downloaded or routed into e.g. a Hadoop cluster for subsequent interactive analysis using Hive, Spark or similar tools. In this respect, our framework also suggests a general model for making very large datasets of high scientific value more accessible by offering the possibility for organizations to share the cost of hosting data on hot storage, without compromising the scalability of downstream analysis.

Genome sequence, comparative analysis and haplotype structure of the domestic dog.

PubMed

Lindblad-Toh, Kerstin; Wade, Claire M; Mikkelsen, Tarjei S; Karlsson, Elinor K; Jaffe, David B; Kamal, Michael; Clamp, Michele; Chang, Jean L; Kulbokas, Edward J; Zody, Michael C; Mauceli, Evan; Xie, Xiaohui; Breen, Matthew; Wayne, Robert K; Ostrander, Elaine A; Ponting, Chris P; Galibert, Francis; Smith, Douglas R; DeJong, Pieter J; Kirkness, Ewen; Alvarez, Pablo; Biagi, Tara; Brockman, William; Butler, Jonathan; Chin, Chee-Wye; Cook, April; Cuff, James; Daly, Mark J; DeCaprio, David; Gnerre, Sante; Grabherr, Manfred; Kellis, Manolis; Kleber, Michael; Bardeleben, Carolyne; Goodstadt, Leo; Heger, Andreas; Hitte, Christophe; Kim, Lisa; Koepfli, Klaus-Peter; Parker, Heidi G; Pollinger, John P; Searle, Stephen M J; Sutter, Nathan B; Thomas, Rachael; Webber, Caleb; Baldwin, Jennifer; Abebe, Adal; Abouelleil, Amr; Aftuck, Lynne; Ait-Zahra, Mostafa; Aldredge, Tyler; Allen, Nicole; An, Peter; Anderson, Scott; Antoine, Claudel; Arachchi, Harindra; Aslam, Ali; Ayotte, Laura; Bachantsang, Pasang; Barry, Andrew; Bayul, Tashi; Benamara, Mostafa; Berlin, Aaron; Bessette, Daniel; Blitshteyn, Berta; Bloom, Toby; Blye, Jason; Boguslavskiy, Leonid; Bonnet, Claude; Boukhgalter, Boris; Brown, Adam; Cahill, Patrick; Calixte, Nadia; Camarata, Jody; Cheshatsang, Yama; Chu, Jeffrey; Citroen, Mieke; Collymore, Alville; Cooke, Patrick; Dawoe, Tenzin; Daza, Riza; Decktor, Karin; DeGray, Stuart; Dhargay, Norbu; Dooley, Kimberly; Dooley, Kathleen; Dorje, Passang; Dorjee, Kunsang; Dorris, Lester; Duffey, Noah; Dupes, Alan; Egbiremolen, Osebhajajeme; Elong, Richard; Falk, Jill; Farina, Abderrahim; Faro, Susan; Ferguson, Diallo; Ferreira, Patricia; Fisher, Sheila; FitzGerald, Mike; Foley, Karen; Foley, Chelsea; Franke, Alicia; Friedrich, Dennis; Gage, Diane; Garber, Manuel; Gearin, Gary; Giannoukos, Georgia; Goode, Tina; Goyette, Audra; Graham, Joseph; Grandbois, Edward; Gyaltsen, Kunsang; Hafez, Nabil; Hagopian, Daniel; Hagos, Birhane; Hall, Jennifer; Healy, Claire; Hegarty, Ryan; Honan, Tracey; Horn, Andrea; Houde, Nathan; Hughes, Leanne; Hunnicutt, Leigh; Husby, M; Jester, Benjamin; Jones, Charlien; Kamat, Asha; Kanga, Ben; Kells, Cristyn; Khazanovich, Dmitry; Kieu, Alix Chinh; Kisner, Peter; Kumar, Mayank; Lance, Krista; Landers, Thomas; Lara, Marcia; Lee, William; Leger, Jean-Pierre; Lennon, Niall; Leuper, Lisa; LeVine, Sarah; Liu, Jinlei; Liu, Xiaohong; Lokyitsang, Yeshi; Lokyitsang, Tashi; Lui, Annie; Macdonald, Jan; Major, John; Marabella, Richard; Maru, Kebede; Matthews, Charles; McDonough, Susan; Mehta, Teena; Meldrim, James; Melnikov, Alexandre; Meneus, Louis; Mihalev, Atanas; Mihova, Tanya; Miller, Karen; Mittelman, Rachel; Mlenga, Valentine; Mulrain, Leonidas; Munson, Glen; Navidi, Adam; Naylor, Jerome; Nguyen, Tuyen; Nguyen, Nga; Nguyen, Cindy; Nguyen, Thu; Nicol, Robert; Norbu, Nyima; Norbu, Choe; Novod, Nathaniel; Nyima, Tenchoe; Olandt, Peter; O'Neill, Barry; O'Neill, Keith; Osman, Sahal; Oyono, Lucien; Patti, Christopher; Perrin, Danielle; Phunkhang, Pema; Pierre, Fritz; Priest, Margaret; Rachupka, Anthony; Raghuraman, Sujaa; Rameau, Rayale; Ray, Verneda; Raymond, Christina; Rege, Filip; Rise, Cecil; Rogers, Julie; Rogov, Peter; Sahalie, Julie; Settipalli, Sampath; Sharpe, Theodore; Shea, Terrance; Sheehan, Mechele; Sherpa, Ngawang; Shi, Jianying; Shih, Diana; Sloan, Jessie; Smith, Cherylyn; Sparrow, Todd; Stalker, John; Stange-Thomann, Nicole; Stavropoulos, Sharon; Stone, Catherine; Stone, Sabrina; Sykes, Sean; Tchuinga, Pierre; Tenzing, Pema; Tesfaye, Senait; Thoulutsang, Dawa; Thoulutsang, Yama; Topham, Kerri; Topping, Ira; Tsamla, Tsamla; Vassiliev, Helen; Venkataraman, Vijay; Vo, Andy; Wangchuk, Tsering; Wangdi, Tsering; Weiand, Michael; Wilkinson, Jane; Wilson, Adam; Yadav, Shailendra; Yang, Shuli; Yang, Xiaoping; Young, Geneva; Yu, Qing; Zainoun, Joanne; Zembek, Lisa; Zimmer, Andrew; Lander, Eric S

2005-12-08

Here we report a high-quality draft genome sequence of the domestic dog (Canis familiaris), together with a dense map of single nucleotide polymorphisms (SNPs) across breeds. The dog is of particular interest because it provides important evolutionary information and because existing breeds show great phenotypic diversity for morphological, physiological and behavioural traits. We use sequence comparison with the primate and rodent lineages to shed light on the structure and evolution of genomes and genes. Notably, the majority of the most highly conserved non-coding sequences in mammalian genomes are clustered near a small subset of genes with important roles in development. Analysis of SNPs reveals long-range haplotypes across the entire dog genome, and defines the nature of genetic diversity within and across breeds. The current SNP map now makes it possible for genome-wide association studies to identify genes responsible for diseases and traits, with important consequences for human and companion animal health.

The Large Mitochondrial Genome of Symbiodinium minutum Reveals Conserved Noncoding Sequences between Dinoflagellates and Apicomplexans

PubMed Central

Shoguchi, Eiichi; Shinzato, Chuya; Hisata, Kanako; Satoh, Nori; Mungpakdee, Sutada

2015-01-01

Even though mitochondrial genomes, which characterize eukaryotic cells, were first discovered more than 50 years ago, mitochondrial genomics remains an important topic in molecular biology and genome sciences. The Phylum Alveolata comprises three major groups (ciliates, apicomplexans, and dinoflagellates), the mitochondrial genomes of which have diverged widely. Even though the gene content of dinoflagellate mitochondrial genomes is reportedly comparable to that of apicomplexans, the highly fragmented and rearranged genome structures of dinoflagellates have frustrated whole genomic analysis. Consequently, noncoding sequences and gene arrangements of dinoflagellate mitochondrial genomes have not been well characterized. Here we report that the continuous assembled genome (∼326 kb) of the dinoflagellate, Symbiodinium minutum, is AT-rich (∼64.3%) and that it contains three protein-coding genes. Based upon in silico analysis, the remaining 99% of the genome comprises transcriptomic noncoding sequences. RNA edited sites and unique, possible start and stop codons clarify conserved regions among dinoflagellates. Our massive transcriptome analysis shows that almost all regions of the genome are transcribed, including 27 possible fragmented ribosomal RNA genes and 12 uncharacterized small RNAs that are similar to mitochondrial RNA genes of the malarial parasite, Plasmodium falciparum. Gene map comparisons show that gene order is only slightly conserved between S. minutum and P. falciparum. However, small RNAs and intergenic sequences share sequence similarities with P. falciparum, suggesting that the function of noncoding sequences has been preserved despite development of very different genome structures. PMID:26199191

Rose spring dwarf-associated virus has RNA structural and gene-expression features like those of Barley yellow dwarf virus

PubMed Central

Salem, Nida’ M.; Miller, W. Allen; Rowhani, Adib; Golino, Deborah A.; Moyne, Anne-Laure; Falk, Bryce W.

2015-01-01

We determined the complete nucleotide sequence of the Rose spring dwarf-associated virus (RSDaV) genomic RNA (GenBank accession no. EU024678) and compared its predicted RNA structural characteristics affecting gene expression. A cDNA library was derived from RSDaV double-stranded RNAs (dsRNAs) purified from infected tissue. Nucleotide sequence analysis of the cloned cDNAs, plus for clones generated by 5′- and 3′-RACE showed the RSDaV genomic RNA to be 5,808 nucleotides. The genomic RNA contains five major open reading frames (ORFs), and three small ORFs in the 3′-terminal 800 nucleotides, typical for viruses of genus Luteovirus in the family Luteoviridae. Northern blot hybridization analysis revealed the genomic RNA and two prominent subgenomic RNAs of approximately 3 kb and 1 kb. Putative 5′ ends of the sgRNAs were predicted by identification of conserved sequences and secondary structures which resembled the Barley yellow dwarf virus (BYDV) genomic RNA 5′ end and subgenomic RNA promoter sequences. Secondary structures of the BYDV-like ribosomal frameshift elements and cap-independent translation elements, including long-distance base pairing spanning four kb were identified. These contain similarities but also informative differences with the BYDV structures, including a strikingly different structure predicted for the 3′ cap-independent translation element. These analyses of the RSDaV genomic RNA show more complexity for the RNA structural elements for members of the Luteoviridae. PMID:18329064

Rose spring dwarf-associated virus has RNA structural and gene-expression features like those of Barley yellow dwarf virus.

PubMed

Salem, Nida' M; Miller, W Allen; Rowhani, Adib; Golino, Deborah A; Moyne, Anne-Laure; Falk, Bryce W

2008-06-05

We determined the complete nucleotide sequence of the Rose spring dwarf-associated virus (RSDaV) genomic RNA (GenBank accession no. EU024678) and compared its predicted RNA structural characteristics affecting gene expression. A cDNA library was derived from RSDaV double-stranded RNAs (dsRNAs) purified from infected tissue. Nucleotide sequence analysis of the cloned cDNAs, plus for clones generated by 5'- and 3'-RACE showed the RSDaV genomic RNA to be 5808 nucleotides. The genomic RNA contains five major open reading frames (ORFs), and three small ORFs in the 3'-terminal 800 nucleotides, typical for viruses of genus Luteovirus in the family Luteoviridae. Northern blot hybridization analysis revealed the genomic RNA and two prominent subgenomic RNAs of approximately 3 kb and 1 kb. Putative 5' ends of the sgRNAs were predicted by identification of conserved sequences and secondary structures which resembled the Barley yellow dwarf virus (BYDV) genomic RNA 5' end and subgenomic RNA promoter sequences. Secondary structures of the BYDV-like ribosomal frameshift elements and cap-independent translation elements, including long-distance base pairing spanning four kb were identified. These contain similarities but also informative differences with the BYDV structures, including a strikingly different structure predicted for the 3' cap-independent translation element. These analyses of the RSDaV genomic RNA show more complexity for the RNA structural elements for members of the Luteoviridae.

Design of a 9K illumina BeadChip for polar bears (Ursus maritimus) from RAD and transcriptome sequencing.

PubMed

Malenfant, René M; Coltman, David W; Davis, Corey S

2015-05-01

Single-nucleotide polymorphisms (SNPs) offer numerous advantages over anonymous markers such as microsatellites, including improved estimation of population parameters, finer-scale resolution of population structure and more precise genomic dissection of quantitative traits. However, many SNPs are needed to equal the resolution of a single microsatellite, and reliable large-scale genotyping of SNPs remains a challenge in nonmodel species. Here, we document the creation of a 9K Illumina Infinium BeadChip for polar bears (Ursus maritimus), which will be used to investigate: (i) the fine-scale population structure among Canadian polar bears and (ii) the genomic architecture of phenotypic traits in the Western Hudson Bay subpopulation. To this end, we used restriction-site associated DNA (RAD) sequencing from 38 bears across their circumpolar range, as well as blood/fat transcriptome sequencing of 10 individuals from Western Hudson Bay. Six-thousand RAD SNPs and 3000 transcriptomic SNPs were selected for the chip, based primarily on genomic spacing and gene function respectively. Of the 9000 SNPs ordered from Illumina, 8042 were successfully printed, and - after genotyping 1450 polar bears - 5441 of these SNPs were found to be well clustered and polymorphic. Using this array, we show rapid linkage disequilibrium decay among polar bears, we demonstrate that in a subsample of 78 individuals, our SNPs detect known genetic structure more clearly than 24 microsatellites genotyped for the same individuals and that these results are not driven by the SNP ascertainment scheme. Here, we present one of the first large-scale genotyping resources designed for a threatened species. © 2014 John Wiley & Sons Ltd.

Outlier analysis of functional genomic profiles enriches for oncology targets and enables precision medicine.

PubMed

Zhu, Zhou; Ihle, Nathan T; Rejto, Paul A; Zarrinkar, Patrick P

2016-06-13

Genome-scale functional genomic screens across large cell line panels provide a rich resource for discovering tumor vulnerabilities that can lead to the next generation of targeted therapies. Their data analysis typically has focused on identifying genes whose knockdown enhances response in various pre-defined genetic contexts, which are limited by biological complexities as well as the incompleteness of our knowledge. We thus introduce a complementary data mining strategy to identify genes with exceptional sensitivity in subsets, or outlier groups, of cell lines, allowing an unbiased analysis without any a priori assumption about the underlying biology of dependency. Genes with outlier features are strongly and specifically enriched with those known to be associated with cancer and relevant biological processes, despite no a priori knowledge being used to drive the analysis. Identification of exceptional responders (outliers) may not lead only to new candidates for therapeutic intervention, but also tumor indications and response biomarkers for companion precision medicine strategies. Several tumor suppressors have an outlier sensitivity pattern, supporting and generalizing the notion that tumor suppressors can play context-dependent oncogenic roles. The novel application of outlier analysis described here demonstrates a systematic and data-driven analytical strategy to decipher large-scale functional genomic data for oncology target and precision medicine discoveries.

Comparative Reannotation of 21 Aspergillus Genomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Salamov, Asaf; Riley, Robert; Kuo, Alan

2013-03-08

We used comparative gene modeling to reannotate 21 Aspergillus genomes. Initial automatic annotation of individual genomes may contain some errors of different nature, e.g. missing genes, incorrect exon-intron structures, 'chimeras', which fuse 2 or more real genes or alternatively splitting some real genes into 2 or more models. The main premise behind the comparative modeling approach is that for closely related genomes most orthologous families have the same conserved gene structure. The algorithm maps all gene models predicted in each individual Aspergillus genome to the other genomes and, for each locus, selects from potentially many competing models, the one whichmore » most closely resembles the orthologous genes from other genomes. This procedure is iterated until no further change in gene models is observed. For Aspergillus genomes we predicted in total 4503 new gene models ( ~;;2percent per genome), supported by comparative analysis, additionally correcting ~;;18percent of old gene models. This resulted in a total of 4065 more genes with annotated PFAM domains (~;;3percent increase per genome). Analysis of a few genomes with EST/transcriptomics data shows that the new annotation sets also have a higher number of EST-supported splice sites at exon-intron boundaries.« less

Genomic characterisation of the effector complement of the potato cyst nematode Globodera pallida.

PubMed

Thorpe, Peter; Mantelin, Sophie; Cock, Peter Ja; Blok, Vivian C; Coke, Mirela C; Eves-van den Akker, Sebastian; Guzeeva, Elena; Lilley, Catherine J; Smant, Geert; Reid, Adam J; Wright, Kathryn M; Urwin, Peter E; Jones, John T

2014-10-23

The potato cyst nematode Globodera pallida has biotrophic interactions with its host. The nematode induces a feeding structure - the syncytium - which it keeps alive for the duration of the life cycle and on which it depends for all nutrients required to develop to the adult stage. Interactions of G. pallida with the host are mediated by effectors, which are produced in two sets of gland cells. These effectors suppress host defences, facilitate migration and induce the formation of the syncytium. The recent completion of the G. pallida genome sequence has allowed us to identify the effector complement from this species. We identify 128 orthologues of effectors from other nematodes as well as 117 novel effector candidates. We have used in situ hybridisation to confirm gland cell expression of a subset of these effectors, demonstrating the validity of our effector identification approach. We have examined the expression profiles of all effector candidates using RNAseq; this analysis shows that the majority of effectors fall into one of three clusters of sequences showing conserved expression characteristics (invasive stage nematode only, parasitic stage only or invasive stage and adult male only). We demonstrate that further diversity in the effector pool is generated by alternative splicing. In addition, we show that effectors target a diverse range of structures in plant cells, including the peroxisome. This is the first identification of effectors from any plant pathogen that target this structure. This is the first genome scale search for effectors, combined to a life-cycle expression analysis, for any plant-parasitic nematode. We show that, like other phylogenetically unrelated plant pathogens, plant parasitic nematodes deploy hundreds of effectors in order to parasitise plants, with different effectors required for different phases of the infection process.

VirtualPlant: A Software Platform to Support Systems Biology Research1[W][OA

PubMed Central

Katari, Manpreet S.; Nowicki, Steve D.; Aceituno, Felipe F.; Nero, Damion; Kelfer, Jonathan; Thompson, Lee Parnell; Cabello, Juan M.; Davidson, Rebecca S.; Goldberg, Arthur P.; Shasha, Dennis E.; Coruzzi, Gloria M.; Gutiérrez, Rodrigo A.

2010-01-01

Data generation is no longer the limiting factor in advancing biological research. In addition, data integration, analysis, and interpretation have become key bottlenecks and challenges that biologists conducting genomic research face daily. To enable biologists to derive testable hypotheses from the increasing amount of genomic data, we have developed the VirtualPlant software platform. VirtualPlant enables scientists to visualize, integrate, and analyze genomic data from a systems biology perspective. VirtualPlant integrates genome-wide data concerning the known and predicted relationships among genes, proteins, and molecules, as well as genome-scale experimental measurements. VirtualPlant also provides visualization techniques that render multivariate information in visual formats that facilitate the extraction of biological concepts. Importantly, VirtualPlant helps biologists who are not trained in computer science to mine lists of genes, microarray experiments, and gene networks to address questions in plant biology, such as: What are the molecular mechanisms by which internal or external perturbations affect processes controlling growth and development? We illustrate the use of VirtualPlant with three case studies, ranging from querying a gene of interest to the identification of gene networks and regulatory hubs that control seed development. Whereas the VirtualPlant software was developed to mine Arabidopsis (Arabidopsis thaliana) genomic data, its data structures, algorithms, and visualization tools are designed in a species-independent way. VirtualPlant is freely available at www.virtualplant.org. PMID:20007449

Plastid genome structure and loss of photosynthetic ability in the parasitic genus Cuscuta.

PubMed

Revill, Meredith J W; Stanley, Susan; Hibberd, Julian M

2005-09-01

The genus Cuscuta (dodder) is composed of parasitic plants, some species of which appear to be losing the ability to photosynthesize. A molecular phylogeny was constructed using 15 species of Cuscuta in order to assess whether changes in photosynthetic ability and alterations in structure of the plastid genome relate to phylogenetic position within the genus. The molecular phylogeny provides evidence for four major clades within Cuscuta. Although DNA blot analysis showed that Cuscuta species have smaller plastid genomes than tobacco, and that plastome size varied significantly even within one Cuscuta clade, dot blot analysis indicated that the dodders possess homologous sequence to 101 genes from the tobacco plastome. Evidence is provided for significant rates of DNA transfer from plastid to nucleus in Cuscuta. Size and structure of Cuscuta plastid genomes, as well as photosynthetic ability, appear to vary independently of position within the phylogeny, thus supporting the hypothesis that within Cuscuta photosynthetic ability and organization of the plastid genome are changing in an unco-ordinated manner.

People of the British Isles: preliminary analysis of genotypes and surnames in a UK-control population

PubMed Central

Winney, Bruce; Boumertit, Abdelhamid; Day, Tammy; Davison, Dan; Echeta, Chikodi; Evseeva, Irina; Hutnik, Katarzyna; Leslie, Stephen; Nicodemus, Kristin; Royrvik, Ellen C; Tonks, Susan; Yang, Xiaofeng; Cheshire, James; Longley, Paul; Mateos, Pablo; Groom, Alexandra; Relton, Caroline; Bishop, D Tim; Black, Kathryn; Northwood, Emma; Parkinson, Louise; Frayling, Timothy M; Steele, Anna; Sampson, Julian R; King, Turi; Dixon, Ron; Middleton, Derek; Jennings, Barbara; Bowden, Rory; Donnelly, Peter; Bodmer, Walter

2012-01-01

There is a great deal of interest in a fine-scale population structure in the UK, both as a signature of historical immigration events and because of the effect population structure may have on disease association studies. Although population structure appears to have a minor impact on the current generation of genome-wide association studies, it is likely to have a significant part in the next generation of studies designed to search for rare variants. A powerful way of detecting such structure is to control and document carefully the provenance of the samples involved. In this study, we describe the collection of a cohort of rural UK samples (The People of the British Isles), aimed at providing a well-characterised UK-control population that can be used as a resource by the research community, as well as providing a fine-scale genetic information on the British population. So far, some 4000 samples have been collected, the majority of which fit the criteria of coming from a rural area and having all four grandparents from approximately the same area. Analysis of the first 3865 samples that have been geocoded indicates that 75% have a mean distance between grandparental places of birth of 37.3 km, and that about 70% of grandparental places of birth can be classed as rural. Preliminary genotyping of 1057 samples demonstrates the value of these samples for investigating a fine-scale population structure within the UK, and shows how this can be enhanced by the use of surnames. PMID:21829225

People of the British Isles: preliminary analysis of genotypes and surnames in a UK-control population.

PubMed

Winney, Bruce; Boumertit, Abdelhamid; Day, Tammy; Davison, Dan; Echeta, Chikodi; Evseeva, Irina; Hutnik, Katarzyna; Leslie, Stephen; Nicodemus, Kristin; Royrvik, Ellen C; Tonks, Susan; Yang, Xiaofeng; Cheshire, James; Longley, Paul; Mateos, Pablo; Groom, Alexandra; Relton, Caroline; Bishop, D Tim; Black, Kathryn; Northwood, Emma; Parkinson, Louise; Frayling, Timothy M; Steele, Anna; Sampson, Julian R; King, Turi; Dixon, Ron; Middleton, Derek; Jennings, Barbara; Bowden, Rory; Donnelly, Peter; Bodmer, Walter

2012-02-01

There is a great deal of interest in a fine-scale population structure in the UK, both as a signature of historical immigration events and because of the effect population structure may have on disease association studies. Although population structure appears to have a minor impact on the current generation of genome-wide association studies, it is likely to have a significant part in the next generation of studies designed to search for rare variants. A powerful way of detecting such structure is to control and document carefully the provenance of the samples involved. In this study, we describe the collection of a cohort of rural UK samples (The People of the British Isles), aimed at providing a well-characterised UK-control population that can be used as a resource by the research community, as well as providing a fine-scale genetic information on the British population. So far, some 4000 samples have been collected, the majority of which fit the criteria of coming from a rural area and having all four grandparents from approximately the same area. Analysis of the first 3865 samples that have been geocoded indicates that 75% have a mean distance between grandparental places of birth of 37.3 km, and that about 70% of grandparental places of birth can be classed as rural. Preliminary genotyping of 1057 samples demonstrates the value of these samples for investigating a fine-scale population structure within the UK, and shows how this can be enhanced by the use of surnames.

Genome-scale metabolic model for Lactococcus lactis MG1363 and its application to the analysis of flavor formation.

PubMed

Flahaut, Nicolas A L; Wiersma, Anne; van de Bunt, Bert; Martens, Dirk E; Schaap, Peter J; Sijtsma, Lolke; Dos Santos, Vitor A Martins; de Vos, Willem M

2013-10-01

Lactococcus lactis subsp. cremoris MG1363 is a paradigm strain for lactococci used in industrial dairy fermentations. However, despite of its importance for process development, no genome-scale metabolic model has been reported thus far. Moreover, current models for other lactococci only focus on growth and sugar degradation. A metabolic model that includes nitrogen metabolism and flavor-forming pathways is instrumental for the understanding and designing new industrial applications of these lactic acid bacteria. A genome-scale, constraint-based model of the metabolism and transport in L. lactis MG1363, accounting for 518 genes, 754 reactions, and 650 metabolites, was developed and experimentally validated. Fifty-nine reactions are directly or indirectly involved in flavor formation. Flux Balance Analysis and Flux Variability Analysis were used to investigate flux distributions within the whole metabolic network. Anaerobic carbon-limited continuous cultures were used for estimating the energetic parameters. A thorough model-driven analysis showing a highly flexible nitrogen metabolism, e.g., branched-chain amino acid catabolism which coupled with the redox balance, is pivotal for the prediction of the formation of different flavor compounds. Furthermore, the model predicted the formation of volatile sulfur compounds as a result of the fermentation. These products were subsequently identified in the experimental fermentations carried out. Thus, the genome-scale metabolic model couples the carbon and nitrogen metabolism in L. lactis MG1363 with complete known catabolic pathways leading to flavor formation. The model provided valuable insights into the metabolic networks underlying flavor formation and has the potential to contribute to new developments in dairy industries and cheese-flavor research.

Large-Scale Collection and Analysis of Full-Length cDNAs from Brachypodium distachyon and Integration with Pooideae Sequence Resources

PubMed Central

Mochida, Keiichi; Uehara-Yamaguchi, Yukiko; Takahashi, Fuminori; Yoshida, Takuhiro; Sakurai, Tetsuya; Shinozaki, Kazuo

2013-01-01

A comprehensive collection of full-length cDNAs is essential for correct structural gene annotation and functional analyses of genes. We constructed a mixed full-length cDNA library from 21 different tissues of Brachypodium distachyon Bd21, and obtained 78,163 high quality expressed sequence tags (ESTs) from both ends of ca. 40,000 clones (including 16,079 contigs). We updated gene structure annotations of Brachypodium genes based on full-length cDNA sequences in comparison with the latest publicly available annotations. About 10,000 non-redundant gene models were supported by full-length cDNAs; ca. 6,000 showed some transcription unit modifications. We also found ca. 580 novel gene models, including 362 newly identified in Bd21. Using the updated transcription start sites, we searched a total of 580 plant cis-motifs in the −3 kb promoter regions and determined a genome-wide Brachypodium promoter architecture. Furthermore, we integrated the Brachypodium full-length cDNAs and updated gene structures with available sequence resources in wheat and barley in a web-accessible database, the RIKEN Brachypodium FL cDNA database. The database represents a “one-stop” information resource for all genomic information in the Pooideae, facilitating functional analysis of genes in this model grass plant and seamless knowledge transfer to the Triticeae crops. PMID:24130698

Three Infectious Viral Species Lying in Wait in the Banana Genome

PubMed Central

Chabannes, Matthieu; Baurens, Franc-Christophe; Duroy, Pierre-Olivier; Bocs, Stéphanie; Vernerey, Marie-Stéphanie; Rodier-Goud, Marguerite; Barbe, Valérie; Gayral, Philippe

2013-01-01

Plant pararetroviruses integrate serendipitously into their host genomes. The banana genome harbors integrated copies of banana streak virus (BSV) named endogenous BSV (eBSV) that are able to release infectious pararetrovirus. In this investigation, we characterized integrants of three BSV species—Goldfinger (eBSGFV), Imove (eBSImV), and Obino l'Ewai (eBSOLV)—in the seedy Musa balbisiana Pisang klutuk wulung (PKW) by studying their molecular structure, genomic organization, genomic landscape, and infectious capacity. All eBSVs exhibit extensive viral genome duplications and rearrangements. eBSV segregation analysis on an F1 population of PKW combined with fluorescent in situ hybridization analysis showed that eBSImV, eBSOLV, and eBSGFV are each present at a single locus. eBSOLV and eBSGFV contain two distinct alleles, whereas eBSImV has two structurally identical alleles. Genotyping of both eBSV and viral particles expressed in the progeny demonstrated that only one allele for each species is infectious. The infectious allele of eBSImV could not be identified since the two alleles are identical. Finally, we demonstrate that eBSGFV and eBSOLV are located on chromosome 1 and eBSImV is located on chromosome 2 of the reference Musa genome published recently. The structure and evolution of eBSVs suggest sequential integration into the plant genome, and haplotype divergence analysis confirms that the three loci display differential evolution. Based on our data, we propose a model for BSV integration and eBSV evolution in the Musa balbisiana genome. The mutual benefits of this unique host-pathogen association are also discussed. PMID:23720724

Whole genome sequencing of the monomorphic pathogen Mycobacterium bovis reveals local differentiation of cattle clinical isolates.

PubMed

Lasserre, Moira; Fresia, Pablo; Greif, Gonzalo; Iraola, Gregorio; Castro-Ramos, Miguel; Juambeltz, Arturo; Nuñez, Álvaro; Naya, Hugo; Robello, Carlos; Berná, Luisa

2018-01-02

Bovine tuberculosis (bTB) poses serious risks to animal welfare and economy, as well as to public health as a zoonosis. Its etiological agent, Mycobacterium bovis, belongs to the Mycobacterium tuberculosis complex (MTBC), a group of genetically monomorphic organisms featured by a remarkably high overall nucleotide identity (99.9%). Indeed, this characteristic is of major concern for correct typing and determination of strain-specific traits based on sequence diversity. Due to its historical economic dependence on cattle production, Uruguay is deeply affected by the prevailing incidence of Mycobacterium bovis. With the world's highest number of cattle per human, and its intensive cattle production, Uruguay represents a particularly suited setting to evaluate genomic variability among isolates, and the diversity traits associated to this pathogen. We compared 186 genomes from MTBC strains isolated worldwide, and found a highly structured population in M. bovis. The analysis of 23 new M. bovis genomes, belonging to strains isolated in Uruguay evidenced three groups present in the country. Despite presenting an expected highly conserved genomic structure and sequence, these strains segregate into a clustered manner within the worldwide phylogeny. Analysis of the non-pe/ppe differential areas against a reference genome defined four main sources of variability, namely: regions of difference (RD), variable genes, duplications and novel genes. RDs and variant analysis segregated the strains into clusters that are concordant with their spoligotype identities. Due to its high homoplasy rate, spoligotyping failed to reflect the true genomic diversity among worldwide representative strains, however, it remains a good indicator for closely related populations. This study introduces a comprehensive population structure analysis of worldwide M. bovis isolates. The incorporation and analysis of 23 novel Uruguayan M. bovis genomes, sheds light onto the genomic diversity of this pathogen, evidencing the existence of greater genetic variability among strains than previously contemplated.

RNA-Seq Based Transcriptional Map of Bovine Respiratory Disease Pathogen “Histophilus somni 2336”

PubMed Central

Kumar, Ranjit; Lawrence, Mark L.; Watt, James; Cooksey, Amanda M.; Burgess, Shane C.; Nanduri, Bindu

2012-01-01

Genome structural annotation, i.e., identification and demarcation of the boundaries for all the functional elements in a genome (e.g., genes, non-coding RNAs, proteins and regulatory elements), is a prerequisite for systems level analysis. Current genome annotation programs do not identify all of the functional elements of the genome, especially small non-coding RNAs (sRNAs). Whole genome transcriptome analysis is a complementary method to identify “novel” genes, small RNAs, regulatory regions, and operon structures, thus improving the structural annotation in bacteria. In particular, the identification of non-coding RNAs has revealed their widespread occurrence and functional importance in gene regulation, stress and virulence. However, very little is known about non-coding transcripts in Histophilus somni, one of the causative agents of Bovine Respiratory Disease (BRD) as well as bovine infertility, abortion, septicemia, arthritis, myocarditis, and thrombotic meningoencephalitis. In this study, we report a single nucleotide resolution transcriptome map of H. somni strain 2336 using RNA-Seq method. The RNA-Seq based transcriptome map identified 94 sRNAs in the H. somni genome of which 82 sRNAs were never predicted or reported in earlier studies. We also identified 38 novel potential protein coding open reading frames that were absent in the current genome annotation. The transcriptome map allowed the identification of 278 operon (total 730 genes) structures in the genome. When compared with the genome sequence of a non-virulent strain 129Pt, a disproportionate number of sRNAs (∼30%) were located in genomic region unique to strain 2336 (∼18% of the total genome). This observation suggests that a number of the newly identified sRNAs in strain 2336 may be involved in strain-specific adaptations. PMID:22276113

RNA-seq based transcriptional map of bovine respiratory disease pathogen "Histophilus somni 2336".

PubMed

Kumar, Ranjit; Lawrence, Mark L; Watt, James; Cooksey, Amanda M; Burgess, Shane C; Nanduri, Bindu

2012-01-01

Genome structural annotation, i.e., identification and demarcation of the boundaries for all the functional elements in a genome (e.g., genes, non-coding RNAs, proteins and regulatory elements), is a prerequisite for systems level analysis. Current genome annotation programs do not identify all of the functional elements of the genome, especially small non-coding RNAs (sRNAs). Whole genome transcriptome analysis is a complementary method to identify "novel" genes, small RNAs, regulatory regions, and operon structures, thus improving the structural annotation in bacteria. In particular, the identification of non-coding RNAs has revealed their widespread occurrence and functional importance in gene regulation, stress and virulence. However, very little is known about non-coding transcripts in Histophilus somni, one of the causative agents of Bovine Respiratory Disease (BRD) as well as bovine infertility, abortion, septicemia, arthritis, myocarditis, and thrombotic meningoencephalitis. In this study, we report a single nucleotide resolution transcriptome map of H. somni strain 2336 using RNA-Seq method.The RNA-Seq based transcriptome map identified 94 sRNAs in the H. somni genome of which 82 sRNAs were never predicted or reported in earlier studies. We also identified 38 novel potential protein coding open reading frames that were absent in the current genome annotation. The transcriptome map allowed the identification of 278 operon (total 730 genes) structures in the genome. When compared with the genome sequence of a non-virulent strain 129Pt, a disproportionate number of sRNAs (∼30%) were located in genomic region unique to strain 2336 (∼18% of the total genome). This observation suggests that a number of the newly identified sRNAs in strain 2336 may be involved in strain-specific adaptations.

The Aspergillus Genome Database: multispecies curation and incorporation of RNA-Seq data to improve structural gene annotations.

PubMed

Cerqueira, Gustavo C; Arnaud, Martha B; Inglis, Diane O; Skrzypek, Marek S; Binkley, Gail; Simison, Matt; Miyasato, Stuart R; Binkley, Jonathan; Orvis, Joshua; Shah, Prachi; Wymore, Farrell; Sherlock, Gavin; Wortman, Jennifer R

2014-01-01

The Aspergillus Genome Database (AspGD; http://www.aspgd.org) is a freely available web-based resource that was designed for Aspergillus researchers and is also a valuable source of information for the entire fungal research community. In addition to being a repository and central point of access to genome, transcriptome and polymorphism data, AspGD hosts a comprehensive comparative genomics toolbox that facilitates the exploration of precomputed orthologs among the 20 currently available Aspergillus genomes. AspGD curators perform gene product annotation based on review of the literature for four key Aspergillus species: Aspergillus nidulans, Aspergillus oryzae, Aspergillus fumigatus and Aspergillus niger. We have iteratively improved the structural annotation of Aspergillus genomes through the analysis of publicly available transcription data, mostly expressed sequenced tags, as described in a previous NAR Database article (Arnaud et al. 2012). In this update, we report substantive structural annotation improvements for A. nidulans, A. oryzae and A. fumigatus genomes based on recently available RNA-Seq data. Over 26 000 loci were updated across these species; although those primarily comprise the addition and extension of untranslated regions (UTRs), the new analysis also enabled over 1000 modifications affecting the coding sequence of genes in each target genome.

Identification and Characterization of Genomic Amplifications in Ovarian Serous Carcinoma

DTIC Science & Technology

2009-07-01

oncogenes, Rsf1 and Notch3, which were up-regulated in both genomic DNA and transcript levels in ovarian cancer. In a large- scale FISH analysis, Rsf1...associated with worse disease outcome, suggesting that Rsf1 could be potentially used as a prognostic marker in the future (Appendix #1). For the...over- expressed in a recurrent carcinoma. Although the follow-up study in a larger- scale sample size did not demonstrate clear amplification in NAC1

Cloud-Scale Genomic Signals Processing for Robust Large-Scale Cancer Genomic Microarray Data Analysis.

PubMed

Harvey, Benjamin Simeon; Ji, Soo-Yeon

2017-01-01

As microarray data available to scientists continues to increase in size and complexity, it has become overwhelmingly important to find multiple ways to bring forth oncological inference to the bioinformatics community through the analysis of large-scale cancer genomic (LSCG) DNA and mRNA microarray data that is useful to scientists. Though there have been many attempts to elucidate the issue of bringing forth biological interpretation by means of wavelet preprocessing and classification, there has not been a research effort that focuses on a cloud-scale distributed parallel (CSDP) separable 1-D wavelet decomposition technique for denoising through differential expression thresholding and classification of LSCG microarray data. This research presents a novel methodology that utilizes a CSDP separable 1-D method for wavelet-based transformation in order to initialize a threshold which will retain significantly expressed genes through the denoising process for robust classification of cancer patients. Additionally, the overall study was implemented and encompassed within CSDP environment. The utilization of cloud computing and wavelet-based thresholding for denoising was used for the classification of samples within the Global Cancer Map, Cancer Cell Line Encyclopedia, and The Cancer Genome Atlas. The results proved that separable 1-D parallel distributed wavelet denoising in the cloud and differential expression thresholding increased the computational performance and enabled the generation of higher quality LSCG microarray datasets, which led to more accurate classification results.

Genome scale transcriptomics of baculovirus-insect interactions.

PubMed

Nguyen, Quan; Nielsen, Lars K; Reid, Steven

2013-11-12

Baculovirus-insect cell technologies are applied in the production of complex proteins, veterinary and human vaccines, gene delivery vectors' and biopesticides. Better understanding of how baculoviruses and insect cells interact would facilitate baculovirus-based production. While complete genomic sequences are available for over 58 baculovirus species, little insect genomic information is known. The release of the Bombyx mori and Plutella xylostella genomes, the accumulation of EST sequences for several Lepidopteran species, and especially the availability of two genome-scale analysis tools, namely oligonucleotide microarrays and next generation sequencing (NGS), have facilitated expression studies to generate a rich picture of insect gene responses to baculovirus infections. This review presents current knowledge on the interaction dynamics of the baculovirus-insect system' which is relatively well studied in relation to nucleocapsid transportation, apoptosis, and heat shock responses, but is still poorly understood regarding responses involved in pro-survival pathways, DNA damage pathways, protein degradation, translation, signaling pathways, RNAi pathways, and importantly metabolic pathways for energy, nucleotide and amino acid production. We discuss how the two genome-scale transcriptomic tools can be applied for studying such pathways and suggest that proteomics and metabolomics can produce complementary findings to transcriptomic studies.

VESPA: Software to Facilitate Genomic Annotation of Prokaryotic Organisms Through Integration of Proteomic and Transcriptomic Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peterson, Elena S.; McCue, Lee Ann; Rutledge, Alexandra C.

2012-04-25

Visual Exploration and Statistics to Promote Annotation (VESPA) is an interactive visual analysis software tool that facilitates the discovery of structural mis-annotations in prokaryotic genomes. VESPA integrates high-throughput peptide-centric proteomics data and oligo-centric or RNA-Seq transcriptomics data into a genomic context. The data may be interrogated via visual analysis across multiple levels of genomic resolution, linked searches, exports and interaction with BLAST to rapidly identify location of interest within the genome and evaluate potential mis-annotations.

Joint scaling laws in functional and evolutionary categories in prokaryotic genomes

PubMed Central

Grilli, J.; Bassetti, B.; Maslov, S.; Cosentino Lagomarsino, M.

2012-01-01

We propose and study a class-expansion/innovation/loss model of genome evolution taking into account biological roles of genes and their constituent domains. In our model, numbers of genes in different functional categories are coupled to each other. For example, an increase in the number of metabolic enzymes in a genome is usually accompanied by addition of new transcription factors regulating these enzymes. Such coupling can be thought of as a proportional ‘recipe’ for genome composition of the type ‘a spoonful of sugar for each egg yolk’. The model jointly reproduces two known empirical laws: the distribution of family sizes and the non-linear scaling of the number of genes in certain functional categories (e.g. transcription factors) with genome size. In addition, it allows us to derive a novel relation between the exponents characterizing these two scaling laws, establishing a direct quantitative connection between evolutionary and functional categories. It predicts that functional categories that grow faster-than-linearly with genome size to be characterized by flatter-than-average family size distributions. This relation is confirmed by our bioinformatics analysis of prokaryotic genomes. This proves that the joint quantitative trends of functional and evolutionary classes can be understood in terms of evolutionary growth with proportional recipes. PMID:21937509

First Insights into the Large Genome of Epimedium sagittatum (Sieb. et Zucc) Maxim, a Chinese Traditional Medicinal Plant

PubMed Central

Liu, Di; Zeng, Shao-Hua; Chen, Jian-Jun; Zhang, Yan-Jun; Xiao, Gong; Zhu, Lin-Yao; Wang, Ying

2013-01-01

Epimedium sagittatum (Sieb. et Zucc) Maxim is a member of the Berberidaceae family of basal eudicot plants, widely distributed and used as a traditional medicinal plant in China for therapeutic effects on many diseases with a long history. Recent data shows that E. sagittatum has a relatively large genome, with a haploid genome size of ~4496 Mbp, divided into a small number of only 12 diploid chromosomes (2n = 2x = 12). However, little is known about Epimedium genome structure and composition. Here we present the analysis of 691 kb of high-quality genomic sequence derived from 672 randomly selected plasmid clones of E. sagittatum genomic DNA, representing ~0.0154% of the genome. The sampled sequences comprised at least 78.41% repetitive DNA elements and 2.51% confirmed annotated gene sequences, with a total GC% content of 39%. Retrotransposons represented the major class of transposable element (TE) repeats identified (65.37% of all TE repeats), particularly LTR (Long Terminal Repeat) retrotransposons (52.27% of all TE repeats). Chromosome analysis and Fluorescence in situ Hybridization of Gypsy-Ty3 retrotransposons were performed to survey the E. sagittatum genome at the cytological level. Our data provide the first insights into the composition and structure of the E. sagittatum genome, and will facilitate the functional genomic analysis of this valuable medicinal plant. PMID:23807511

Genetic testing and genomic analysis: a debate on ethical, social and legal issues in the Arab world with a focus on Qatar.

PubMed

El Shanti, Hatem; Chouchane, Lotfi; Badii, Ramin; Gallouzi, Imed Eddine; Gasparini, Paolo

2015-11-14

In 2013 both Saudi Arabia and Qatar launched genome projects with the aim of providing information for better diagnosis, treatment and prevention of diseases and, ultimately to realize personalized medicine by sequencing hundred thousands samples. These population based genome activities raise a series of relevant ethical, legal and social issues general, related to the specific population structure as well as to the Islamic perspective on genomic analysis and genetic testing. To contribute to the debate, the Authors after reviewing the existing literature and taking advantage of their professional experience in the field and in the geographic area, discuss and provide their opinions. In particular, the Authors focus on the impact of consanguinity on population structure and disease frequency in the Arab world, on genetic testing and genomic analysis (i.e. technical aspects, impact, etc.) and on their regulations. A comparison between the Islamic perspective and the ethical, social and legal issues raised in other population contexts is also carried. In conclusion, this opinion article with an up-to-date contribution to the discussion on the relevance and impact of genomic analysis and genetic testing in the Arab world, might help in producing specific national guidelines on genetic testing and genomic analysis and help accelerate the implementation and roll out of genome projects in Muslim countries and more specifically in Qatar, and other countries of the Gulf.

An ethnically relevant consensus Korean reference genome is a step towards personal reference genomes

PubMed Central

Cho, Yun Sung; Kim, Hyunho; Kim, Hak-Min; Jho, Sungwoong; Jun, JeHoon; Lee, Yong Joo; Chae, Kyun Shik; Kim, Chang Geun; Kim, Sangsoo; Eriksson, Anders; Edwards, Jeremy S.; Lee, Semin; Kim, Byung Chul; Manica, Andrea; Oh, Tae-Kwang; Church, George M.; Bhak, Jong

2016-01-01

Human genomes are routinely compared against a universal reference. However, this strategy could miss population-specific and personal genomic variations, which may be detected more efficiently using an ethnically relevant or personal reference. Here we report a hybrid assembly of a Korean reference genome (KOREF) for constructing personal and ethnic references by combining sequencing and mapping methods. We also build its consensus variome reference, providing information on millions of variants from 40 additional ethnically homogeneous genomes from the Korean Personal Genome Project. We find that the ethnically relevant consensus reference can be beneficial for efficient variant detection. Systematic comparison of human assemblies shows the importance of assembly quality, suggesting the necessity of new technologies to comprehensively map ethnic and personal genomic structure variations. In the era of large-scale population genome projects, the leveraging of ethnicity-specific genome assemblies as well as the human reference genome will accelerate mapping all human genome diversity. PMID:27882922

Evaluation of Targeted Sequencing for Transcriptional Analysis of Archival Formalin-Fixed Paraffin-Embedded (FFPE) Samples

EPA Science Inventory

Next-generation sequencing provides unprecedented access to genomic information in archival FFPE tissue samples. However, costs and technical challenges related to RNA isolation and enrichment limit use of whole-genome RNA-sequencing for large-scale studies of FFPE specimens. Rec...

Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

PubMed

Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

2016-09-19

Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

Employing genome-wide SNP discovery and genotyping strategy to extrapolate the natural allelic diversity and domestication patterns in chickpea

PubMed Central

Kujur, Alice; Bajaj, Deepak; Upadhyaya, Hari D.; Das, Shouvik; Ranjan, Rajeev; Shree, Tanima; Saxena, Maneesha S.; Badoni, Saurabh; Kumar, Vinod; Tripathi, Shailesh; Gowda, C. L. L.; Sharma, Shivali; Singh, Sube; Tyagi, Akhilesh K.; Parida, Swarup K.

2015-01-01

The genome-wide discovery and high-throughput genotyping of SNPs in chickpea natural germplasm lines is indispensable to extrapolate their natural allelic diversity, domestication, and linkage disequilibrium (LD) patterns leading to the genetic enhancement of this vital legume crop. We discovered 44,844 high-quality SNPs by sequencing of 93 diverse cultivated desi, kabuli, and wild chickpea accessions using reference genome- and de novo-based GBS (genotyping-by-sequencing) assays that were physically mapped across eight chromosomes of desi and kabuli. Of these, 22,542 SNPs were structurally annotated in different coding and non-coding sequence components of genes. Genes with 3296 non-synonymous and 269 regulatory SNPs could functionally differentiate accessions based on their contrasting agronomic traits. A high experimental validation success rate (92%) and reproducibility (100%) along with strong sensitivity (93–96%) and specificity (99%) of GBS-based SNPs was observed. This infers the robustness of GBS as a high-throughput assay for rapid large-scale mining and genotyping of genome-wide SNPs in chickpea with sub-optimal use of resources. With 23,798 genome-wide SNPs, a relatively high intra-specific polymorphic potential (49.5%) and broader molecular diversity (13–89%)/functional allelic diversity (18–77%) was apparent among 93 chickpea accessions, suggesting their tremendous applicability in rapid selection of desirable diverse accessions/inter-specific hybrids in chickpea crossbred varietal improvement program. The genome-wide SNPs revealed complex admixed domestication pattern, extensive LD estimates (0.54–0.68) and extended LD decay (400–500 kb) in a structured population inclusive of 93 accessions. These findings reflect the utility of our identified SNPs for subsequent genome-wide association study (GWAS) and selective sweep-based domestication trait dissection analysis to identify potential genomic loci (gene-associated targets) specifically regulating important complex quantitative agronomic traits in chickpea. The numerous informative genome-wide SNPs, natural allelic diversity-led domestication pattern, and LD-based information generated in our study have got multidimensional applicability with respect to chickpea genomics-assisted breeding. PMID:25873920

Evaluation of a Genome-Scale In Silico Metabolic Model for Geobacter metallireducens Using Proteomic Data from a Field Biostimulation Experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fang, Yilin; Wilkins, Michael J.; Yabusaki, Steven B.

2012-12-12

Biomass and shotgun global proteomics data that reflected relative protein abundances from samples collected during the 2008 experiment at the U.S. Department of Energy Integrated Field-Scale Subsurface Research Challenge site in Rifle, Colorado, provided an unprecedented opportunity to validate a genome-scale metabolic model of Geobacter metallireducens and assess its performance with respect to prediction of metal reduction, biomass yield, and growth rate under dynamic field conditions. Reconstructed from annotated genomic sequence, biochemical, and physiological data, the constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes.more » Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low fluxes through amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.« less

Dating and functional characterization of duplicated genes in the apple (Malus domestica Borkh.) by analyzing EST data.

PubMed

Sanzol, Javier

2010-05-14

Gene duplication is central to genome evolution. In plants, genes can be duplicated through small-scale events and large-scale duplications often involving polyploidy. The apple belongs to the subtribe Pyrinae (Rosaceae), a diverse lineage that originated via allopolyploidization. Both small-scale duplications and polyploidy may have been important mechanisms shaping the genome of this species. This study evaluates the gene duplication and polyploidy history of the apple by characterizing duplicated genes in this species using EST data. Overall, 68% of the apple genes were clustered into families with a mean copy-number of 4.6. Analysis of the age distribution of gene duplications supported a continuous mode of small-scale duplications, plus two episodes of large-scale duplicates of vastly different ages. The youngest was consistent with the polyploid origin of the Pyrinae 37-48 MYBP, whereas the older may be related to gamma-triplication; an ancient hexapolyploidization previously characterized in the four sequenced eurosid genomes and basal to the eurosid-asterid divergence. Duplicated genes were studied for functional diversification with an emphasis on young paralogs; those originated during or after the formation of the Pyrinae lineage. Unequal assignment of single-copy genes and gene families to Gene Ontology categories suggested functional bias in the pattern of gene retention of paralogs. Young paralogs related to signal transduction, metabolism, and energy pathways have been preferentially retained. Non-random retention of duplicated genes seems to have mediated the expansion of gene families, some of which may have substantially increased their members after the origin of the Pyrinae. The joint analysis of over-duplicated functional categories and phylogenies, allowed evaluation of the role of both polyploidy and small-scale duplications during this process. Finally, gene expression analysis indicated that 82% of duplicated genes, including 80% of young paralogs, showed uncorrelated expression profiles, suggesting extensive subfunctionalization and a role of gene duplication in the acquisition of novel patterns of gene expression. This study reports a genome-wide analysis of the mode of gene duplication in the apple, and provides evidence for its role in genome functional diversification by characterising three major processes: selective retention of paralogs, amplification of gene families, and changes in gene expression.

Population-based structural variation discovery with Hydra-Multi.

PubMed

Lindberg, Michael R; Hall, Ira M; Quinlan, Aaron R

2015-04-15

Current strategies for SNP and INDEL discovery incorporate sequence alignments from multiple individuals to maximize sensitivity and specificity. It is widely accepted that this approach also improves structural variant (SV) detection. However, multisample SV analysis has been stymied by the fundamental difficulties of SV calling, e.g. library insert size variability, SV alignment signal integration and detecting long-range genomic rearrangements involving disjoint loci. Extant tools suffer from poor scalability, which limits the number of genomes that can be co-analyzed and complicates analysis workflows. We have developed an approach that enables multisample SV analysis in hundreds to thousands of human genomes using commodity hardware. Here, we describe Hydra-Multi and measure its accuracy, speed and scalability using publicly available datasets provided by The 1000 Genomes Project and by The Cancer Genome Atlas (TCGA). Hydra-Multi is written in C++ and is freely available at https://github.com/arq5x/Hydra. aaronquinlan@gmail.com or ihall@genome.wustl.edu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Whole-Genome Analysis of a Novel Fish Reovirus (MsReV) Discloses Aquareovirus Genomic Structure Relationship with Host in Saline Environments.

PubMed

Chen, Zhong-Yuan; Gao, Xiao-Chan; Zhang, Qi-Ya

2015-08-03

Aquareoviruses are serious pathogens of aquatic animals. Here, genome characterization and functional gene analysis of a novel aquareovirus, largemouth bass Micropterus salmoides reovirus (MsReV), was described. It comprises 11 dsRNA segments (S1-S11) covering 24,024 bp, and encodes 12 putative proteins including the inclusion forming-related protein NS87 and the fusion-associated small transmembrane (FAST) protein NS22. The function of NS22 was confirmed by expression in fish cells. Subsequently, MsReV was compared with two representative aquareoviruses, saltwater fish turbot Scophthalmus maximus reovirus (SMReV) and freshwater fish grass carp reovirus strain 109 (GCReV-109). MsReV NS87 and NS22 genes have the same structure and function with those of SMReV, whereas GCReV-109 is either missing the coiled-coil region in NS79 or the gene-encoding NS22. Significant similarities are also revealed among equivalent genome segments between MsReV and SMReV, but a difference is found between MsReV and GCReV-109. Furthermore, phylogenetic analysis showed that 13 aquareoviruses could be divided into freshwater and saline environments subgroups, and MsReV was closely related to SMReV in saline environments. Consequently, these viruses from hosts in saline environments have more genomic structural similarities than the viruses from hosts in freshwater. This is the first study of the relationships between aquareovirus genomic structure and their host environments.

Dichlorvos Exposure Results in Large Scale Disruption of Energy Metabolism in the Liver of the Zebra Fish, Danio Rerio

DTIC Science & Technology

2015-10-24

zebrafish reference genome sequence and its relationship to the human genome . Nature. 2013;496(7446):498–503. 21. Linney E, Upchurch L, Donerly S. Zebrafish...To obtain a broader understanding of the effects of dichlorvos on liver metabolism, we per- formed a genome -wide analysis of gene expression in the ...condition) for whole genome transcript ana- lysis, and fixed another set of fish for histological evaluation (n = 5/condition). We determined the target

IMG 4 version of the integrated microbial genomes comparative analysis system

PubMed Central

Markowitz, Victor M.; Chen, I-Min A.; Palaniappan, Krishna; Chu, Ken; Szeto, Ernest; Pillay, Manoj; Ratner, Anna; Huang, Jinghua; Woyke, Tanja; Huntemann, Marcel; Anderson, Iain; Billis, Konstantinos; Varghese, Neha; Mavromatis, Konstantinos; Pati, Amrita; Ivanova, Natalia N.; Kyrpides, Nikos C.

2014-01-01

The Integrated Microbial Genomes (IMG) data warehouse integrates genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG provides tools for analyzing and reviewing the structural and functional annotations of genomes in a comparative context. IMG’s data content and analytical capabilities have increased continuously since its first version released in 2005. Since the last report published in the 2012 NAR Database Issue, IMG’s annotation and data integration pipelines have evolved while new tools have been added for recording and analyzing single cell genomes, RNA Seq and biosynthetic cluster data. Different IMG datamarts provide support for the analysis of publicly available genomes (IMG/W: http://img.jgi.doe.gov/w), expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er) and teaching and training in the area of microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu). PMID:24165883

IMG 4 version of the integrated microbial genomes comparative analysis system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Markowitz, Victor M.; Chen, I-Min A.; Palaniappan, Krishna

The Integrated Microbial Genomes (IMG) data warehouse integrates genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG provides tools for analyzing and reviewing the structural and functional annotations of genomes in a comparative context. IMG’s data content and analytical capabilities have increased continuously since its first version released in 2005. Since the last report published in the 2012 NAR Database Issue, IMG’s annotation and data integration pipelines have evolved while new tools have been added for recording and analyzing single cell genomes, RNA Seq and biosynthetic cluster data. Finally, different IMG datamarts providemore » support for the analysis of publicly available genomes (IMG/W: http://img.jgi.doe.gov/w), expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er) and teaching and training in the area of microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu).« less

IMG 4 version of the integrated microbial genomes comparative analysis system.

PubMed

Markowitz, Victor M; Chen, I-Min A; Palaniappan, Krishna; Chu, Ken; Szeto, Ernest; Pillay, Manoj; Ratner, Anna; Huang, Jinghua; Woyke, Tanja; Huntemann, Marcel; Anderson, Iain; Billis, Konstantinos; Varghese, Neha; Mavromatis, Konstantinos; Pati, Amrita; Ivanova, Natalia N; Kyrpides, Nikos C

2014-01-01

The Integrated Microbial Genomes (IMG) data warehouse integrates genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG provides tools for analyzing and reviewing the structural and functional annotations of genomes in a comparative context. IMG's data content and analytical capabilities have increased continuously since its first version released in 2005. Since the last report published in the 2012 NAR Database Issue, IMG's annotation and data integration pipelines have evolved while new tools have been added for recording and analyzing single cell genomes, RNA Seq and biosynthetic cluster data. Different IMG datamarts provide support for the analysis of publicly available genomes (IMG/W: http://img.jgi.doe.gov/w), expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er) and teaching and training in the area of microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu).

Organizational heterogeneity of vertebrate genomes.

PubMed

Frenkel, Svetlana; Kirzhner, Valery; Korol, Abraham

2012-01-01

Genomes of higher eukaryotes are mosaics of segments with various structural, functional, and evolutionary properties. The availability of whole-genome sequences allows the investigation of their structure as "texts" using different statistical and computational methods. One such method, referred to as Compositional Spectra (CS) analysis, is based on scoring the occurrences of fixed-length oligonucleotides (k-mers) in the target DNA sequence. CS analysis allows generating species- or region-specific characteristics of the genome, regardless of their length and the presence of coding DNA. In this study, we consider the heterogeneity of vertebrate genomes as a joint effect of regional variation in sequence organization superimposed on the differences in nucleotide composition. We estimated compositional and organizational heterogeneity of genome and chromosome sequences separately and found that both heterogeneity types vary widely among genomes as well as among chromosomes in all investigated taxonomic groups. The high correspondence of heterogeneity scores obtained on three genome fractions, coding, repetitive, and the remaining part of the noncoding DNA (the genome dark matter--GDM) allows the assumption that CS-heterogeneity may have functional relevance to genome regulation. Of special interest for such interpretation is the fact that natural GDM sequences display the highest deviation from the corresponding reshuffled sequences.

European Chlamydia abortus livestock isolate genomes reveal unusual stability and limited diversity, reflected in geographical signatures.

PubMed

Seth-Smith, H M B; Busó, Leonor Sánchez; Livingstone, M; Sait, M; Harris, S R; Aitchison, K D; Vretou, Evangelia; Siarkou, V I; Laroucau, K; Sachse, K; Longbottom, D; Thomson, N R

2017-05-04

Chlamydia abortus (formerly Chlamydophila abortus) is an economically important livestock pathogen, causing ovine enzootic abortion (OEA), and can also cause zoonotic infections in humans affecting pregnancy outcome. Large-scale genomic studies on other chlamydial species are giving insights into the biology of these organisms but have not yet been performed on C. abortus. Our aim was to investigate a broad collection of European isolates of C. abortus, using next generation sequencing methods, looking at diversity, geographic distribution and genome dynamics. Whole genome sequencing was performed on our collection of 57 C. abortus isolates originating primarily from the UK, Germany, France and Greece, but also from Tunisia, Namibia and the USA. Phylogenetic analysis of a total of 64 genomes shows a deep structural division within the C. abortus species with a major clade displaying limited diversity, in addition to a branch carrying two more distantly related Greek isolates, LLG and POS. Within the major clade, seven further phylogenetic groups can be identified, demonstrating geographical associations. The number of variable nucleotide positions across the sampled isolates is significantly lower than those published for C. trachomatis and C. psittaci. No recombination was identified within C. abortus, and no plasmid was found. Analysis of pseudogenes showed lineage specific loss of some functions, notably with several Pmp and TMH/Inc proteins predicted to be inactivated in many of the isolates studied. The diversity within C. abortus appears to be much lower compared to other species within the genus. There are strong geographical signatures within the phylogeny, indicating clonal expansion within areas of limited livestock transport. No recombination has been identified within this species, showing that different species of Chlamydia may demonstrate different evolutionary dynamics, and that the genome of C. abortus is highly stable.

Genome-wide network analysis of Wnt signaling in three pediatric cancers

NASA Astrophysics Data System (ADS)

Bao, Ju; Lee, Ho-Jin; Zheng, Jie J.

2013-10-01

Genomic structural alteration is common in pediatric cancers, and analysis of data generated by the Pediatric Cancer Genome Project reveals such tumor-related alterations in many Wnt signaling-associated genes. Most pediatric cancers are thought to arise within developing tissues that undergo substantial expansion during early organ formation, growth and maturation, and Wnt signaling plays an important role in this development. We examined three pediatric tumors--medullobastoma, early T-cell precursor acute lymphoblastic leukemia, and retinoblastoma--that show multiple genomic structural variations within Wnt signaling pathways. We mathematically modeled this pathway to investigate the effects of cancer-related structural variations on Wnt signaling. Surprisingly, we found that an outcome measure of canonical Wnt signaling was consistently similar in matched cancer cells and normal cells, even in the context of different cancers, different mutations, and different Wnt-related genes. Our results suggest that the cancer cells maintain a normal level of Wnt signaling by developing multiple mutations.

MultiMetEval: Comparative and Multi-Objective Analysis of Genome-Scale Metabolic Models

PubMed Central

Gevorgyan, Albert; Kierzek, Andrzej M.; Breitling, Rainer; Takano, Eriko

2012-01-01

Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEval/downloads. PMID:23272111

Anaplasma marginale superinfection attributable to pathogen strains with distinct genomic backgrounds.

USDA-ARS?s Scientific Manuscript database

Microbial strain structure is dynamic over space and time; shifts in pathogen strain structure result in changing patterns of disease. The scale of change in space and time differs markedly among pathogens depending on multiple factors including pathogen-specific mechanisms of genetic change and the...

Rainbow: a tool for large-scale whole-genome sequencing data analysis using cloud computing.

PubMed

Zhao, Shanrong; Prenger, Kurt; Smith, Lance; Messina, Thomas; Fan, Hongtao; Jaeger, Edward; Stephens, Susan

2013-06-27

Technical improvements have decreased sequencing costs and, as a result, the size and number of genomic datasets have increased rapidly. Because of the lower cost, large amounts of sequence data are now being produced by small to midsize research groups. Crossbow is a software tool that can detect single nucleotide polymorphisms (SNPs) in whole-genome sequencing (WGS) data from a single subject; however, Crossbow has a number of limitations when applied to multiple subjects from large-scale WGS projects. The data storage and CPU resources that are required for large-scale whole genome sequencing data analyses are too large for many core facilities and individual laboratories to provide. To help meet these challenges, we have developed Rainbow, a cloud-based software package that can assist in the automation of large-scale WGS data analyses. Here, we evaluated the performance of Rainbow by analyzing 44 different whole-genome-sequenced subjects. Rainbow has the capacity to process genomic data from more than 500 subjects in two weeks using cloud computing provided by the Amazon Web Service. The time includes the import and export of the data using Amazon Import/Export service. The average cost of processing a single sample in the cloud was less than 120 US dollars. Compared with Crossbow, the main improvements incorporated into Rainbow include the ability: (1) to handle BAM as well as FASTQ input files; (2) to split large sequence files for better load balance downstream; (3) to log the running metrics in data processing and monitoring multiple Amazon Elastic Compute Cloud (EC2) instances; and (4) to merge SOAPsnp outputs for multiple individuals into a single file to facilitate downstream genome-wide association studies. Rainbow is a scalable, cost-effective, and open-source tool for large-scale WGS data analysis. For human WGS data sequenced by either the Illumina HiSeq 2000 or HiSeq 2500 platforms, Rainbow can be used straight out of the box. Rainbow is available for third-party implementation and use, and can be downloaded from http://s3.amazonaws.com/jnj_rainbow/index.html.

Rainbow: a tool for large-scale whole-genome sequencing data analysis using cloud computing

PubMed Central

2013-01-01

Background Technical improvements have decreased sequencing costs and, as a result, the size and number of genomic datasets have increased rapidly. Because of the lower cost, large amounts of sequence data are now being produced by small to midsize research groups. Crossbow is a software tool that can detect single nucleotide polymorphisms (SNPs) in whole-genome sequencing (WGS) data from a single subject; however, Crossbow has a number of limitations when applied to multiple subjects from large-scale WGS projects. The data storage and CPU resources that are required for large-scale whole genome sequencing data analyses are too large for many core facilities and individual laboratories to provide. To help meet these challenges, we have developed Rainbow, a cloud-based software package that can assist in the automation of large-scale WGS data analyses. Results Here, we evaluated the performance of Rainbow by analyzing 44 different whole-genome-sequenced subjects. Rainbow has the capacity to process genomic data from more than 500 subjects in two weeks using cloud computing provided by the Amazon Web Service. The time includes the import and export of the data using Amazon Import/Export service. The average cost of processing a single sample in the cloud was less than 120 US dollars. Compared with Crossbow, the main improvements incorporated into Rainbow include the ability: (1) to handle BAM as well as FASTQ input files; (2) to split large sequence files for better load balance downstream; (3) to log the running metrics in data processing and monitoring multiple Amazon Elastic Compute Cloud (EC2) instances; and (4) to merge SOAPsnp outputs for multiple individuals into a single file to facilitate downstream genome-wide association studies. Conclusions Rainbow is a scalable, cost-effective, and open-source tool for large-scale WGS data analysis. For human WGS data sequenced by either the Illumina HiSeq 2000 or HiSeq 2500 platforms, Rainbow can be used straight out of the box. Rainbow is available for third-party implementation and use, and can be downloaded from http://s3.amazonaws.com/jnj_rainbow/index.html. PMID:23802613

The complete chloroplast genome sequence of the medicinal plant Salvia miltiorrhiza.

PubMed

Qian, Jun; Song, Jingyuan; Gao, Huanhuan; Zhu, Yingjie; Xu, Jiang; Pang, Xiaohui; Yao, Hui; Sun, Chao; Li, Xian'en; Li, Chuyuan; Liu, Juyan; Xu, Haibin; Chen, Shilin

2013-01-01

Salvia miltiorrhiza is an important medicinal plant with great economic and medicinal value. The complete chloroplast (cp) genome sequence of Salvia miltiorrhiza, the first sequenced member of the Lamiaceae family, is reported here. The genome is 151,328 bp in length and exhibits a typical quadripartite structure of the large (LSC, 82,695 bp) and small (SSC, 17,555 bp) single-copy regions, separated by a pair of inverted repeats (IRs, 25,539 bp). It contains 114 unique genes, including 80 protein-coding genes, 30 tRNAs and four rRNAs. The genome structure, gene order, GC content and codon usage are similar to the typical angiosperm cp genomes. Four forward, three inverted and seven tandem repeats were detected in the Salvia miltiorrhiza cp genome. Simple sequence repeat (SSR) analysis among the 30 asterid cp genomes revealed that most SSRs are AT-rich, which contribute to the overall AT richness of these cp genomes. Additionally, fewer SSRs are distributed in the protein-coding sequences compared to the non-coding regions, indicating an uneven distribution of SSRs within the cp genomes. Entire cp genome comparison of Salvia miltiorrhiza and three other Lamiales cp genomes showed a high degree of sequence similarity and a relatively high divergence of intergenic spacers. Sequence divergence analysis discovered the ten most divergent and ten most conserved genes as well as their length variation, which will be helpful for phylogenetic studies in asterids. Our analysis also supports that both regional and functional constraints affect gene sequence evolution. Further, phylogenetic analysis demonstrated a sister relationship between Salvia miltiorrhiza and Sesamum indicum. The complete cp genome sequence of Salvia miltiorrhiza reported in this paper will facilitate population, phylogenetic and cp genetic engineering studies of this medicinal plant.

Predicting protein-protein interactions on a proteome scale by matching evolutionary and structural similarities at interfaces using PRISM.

PubMed

Tuncbag, Nurcan; Gursoy, Attila; Nussinov, Ruth; Keskin, Ozlem

2011-08-11

Prediction of protein-protein interactions at the structural level on the proteome scale is important because it allows prediction of protein function, helps drug discovery and takes steps toward genome-wide structural systems biology. We provide a protocol (termed PRISM, protein interactions by structural matching) for large-scale prediction of protein-protein interactions and assembly of protein complex structures. The method consists of two components: rigid-body structural comparisons of target proteins to known template protein-protein interfaces and flexible refinement using a docking energy function. The PRISM rationale follows our observation that globally different protein structures can interact via similar architectural motifs. PRISM predicts binding residues by using structural similarity and evolutionary conservation of putative binding residue 'hot spots'. Ultimately, PRISM could help to construct cellular pathways and functional, proteome-scale annotation. PRISM is implemented in Python and runs in a UNIX environment. The program accepts Protein Data Bank-formatted protein structures and is available at http://prism.ccbb.ku.edu.tr/prism_protocol/.

A statistical approach for inferring the 3D structure of the genome.

PubMed

Varoquaux, Nelle; Ay, Ferhat; Noble, William Stafford; Vert, Jean-Philippe

2014-06-15

Recent technological advances allow the measurement, in a single Hi-C experiment, of the frequencies of physical contacts among pairs of genomic loci at a genome-wide scale. The next challenge is to infer, from the resulting DNA-DNA contact maps, accurate 3D models of how chromosomes fold and fit into the nucleus. Many existing inference methods rely on multidimensional scaling (MDS), in which the pairwise distances of the inferred model are optimized to resemble pairwise distances derived directly from the contact counts. These approaches, however, often optimize a heuristic objective function and require strong assumptions about the biophysics of DNA to transform interaction frequencies to spatial distance, and thereby may lead to incorrect structure reconstruction. We propose a novel approach to infer a consensus 3D structure of a genome from Hi-C data. The method incorporates a statistical model of the contact counts, assuming that the counts between two loci follow a Poisson distribution whose intensity decreases with the physical distances between the loci. The method can automatically adjust the transfer function relating the spatial distance to the Poisson intensity and infer a genome structure that best explains the observed data. We compare two variants of our Poisson method, with or without optimization of the transfer function, to four different MDS-based algorithms-two metric MDS methods using different stress functions, a non-metric version of MDS and ChromSDE, a recently described, advanced MDS method-on a wide range of simulated datasets. We demonstrate that the Poisson models reconstruct better structures than all MDS-based methods, particularly at low coverage and high resolution, and we highlight the importance of optimizing the transfer function. On publicly available Hi-C data from mouse embryonic stem cells, we show that the Poisson methods lead to more reproducible structures than MDS-based methods when we use data generated using different restriction enzymes, and when we reconstruct structures at different resolutions. A Python implementation of the proposed method is available at http://cbio.ensmp.fr/pastis. © The Author 2014. Published by Oxford University Press.

An Integrative Breakage Model of genome architecture, reshuffling and evolution: The Integrative Breakage Model of genome evolution, a novel multidisciplinary hypothesis for the study of genome plasticity.

PubMed

Farré, Marta; Robinson, Terence J; Ruiz-Herrera, Aurora

2015-05-01

Our understanding of genomic reorganization, the mechanics of genomic transmission to offspring during germ line formation, and how these structural changes contribute to the speciation process, and genetic disease is far from complete. Earlier attempts to understand the mechanism(s) and constraints that govern genome remodeling suffered from being too narrowly focused, and failed to provide a unified and encompassing view of how genomes are organized and regulated inside cells. Here, we propose a new multidisciplinary Integrative Breakage Model for the study of genome evolution. The analysis of the high-level structural organization of genomes (nucleome), together with the functional constrains that accompany genome reshuffling, provide insights into the origin and plasticity of genome organization that may assist with the detection and isolation of therapeutic targets for the treatment of complex human disorders. © 2015 WILEY Periodicals, Inc.

Construction of a plant-transformation-competent BIBAC library and genome sequence analysis of polyploid Upland cotton (Gossypium hirsutum L.)

PubMed Central

2013-01-01

Background Cotton, one of the world’s leading crops, is important to the world’s textile and energy industries, and is a model species for studies of plant polyploidization, cellulose biosynthesis and cell wall biogenesis. Here, we report the construction of a plant-transformation-competent binary bacterial artificial chromosome (BIBAC) library and comparative genome sequence analysis of polyploid Upland cotton (Gossypium hirsutum L.) with one of its diploid putative progenitor species, G. raimondii Ulbr. Results We constructed the cotton BIBAC library in a vector competent for high-molecular-weight DNA transformation in different plant species through either Agrobacterium or particle bombardment. The library contains 76,800 clones with an average insert size of 135 kb, providing an approximate 99% probability of obtaining at least one positive clone from the library using a single-copy probe. The quality and utility of the library were verified by identifying BIBACs containing genes important for fiber development, fiber cellulose biosynthesis, seed fatty acid metabolism, cotton-nematode interaction, and bacterial blight resistance. In order to gain an insight into the Upland cotton genome and its relationship with G. raimondii, we sequenced nearly 10,000 BIBAC ends (BESs) randomly selected from the library, generating approximately one BES for every 250 kb along the Upland cotton genome. The retroelement Gypsy/DIRS1 family predominates in the Upland cotton genome, accounting for over 77% of all transposable elements. From the BESs, we identified 1,269 simple sequence repeats (SSRs), of which 1,006 were new, thus providing additional markers for cotton genome research. Surprisingly, comparative sequence analysis showed that Upland cotton is much more diverged from G. raimondii at the genomic sequence level than expected. There seems to be no significant difference between the relationships of the Upland cotton D- and A-subgenomes with the G. raimondii genome, even though G. raimondii contains a D genome (D5). Conclusions The library represents the first BIBAC library in cotton and related species, thus providing tools useful for integrative physical mapping, large-scale genome sequencing and large-scale functional analysis of the Upland cotton genome. Comparative sequence analysis provides insights into the Upland cotton genome, and a possible mechanism underlying the divergence and evolution of polyploid Upland cotton from its diploid putative progenitor species, G. raimondii. PMID:23537070

Genetic diversity and population structure of Musa accessions in ex situ conservation

PubMed Central

2013-01-01

Background Banana cultivars are mostly derived from hybridization between wild diploid subspecies of Musa acuminata (A genome) and M. balbisiana (B genome), and they exhibit various levels of ploidy and genomic constitution. The Embrapa ex situ Musa collection contains over 220 accessions, of which only a few have been genetically characterized. Knowledge regarding the genetic relationships and diversity between modern cultivars and wild relatives would assist in conservation and breeding strategies. Our objectives were to determine the genomic constitution based on Internal Transcribed Spacer (ITS) regions polymorphism and the ploidy of all accessions by flow cytometry and to investigate the population structure of the collection using Simple Sequence Repeat (SSR) loci as co-dominant markers based on Structure software, not previously performed in Musa. Results From the 221 accessions analyzed by flow cytometry, the correct ploidy was confirmed or established for 212 (95.9%), whereas digestion of the ITS region confirmed the genomic constitution of 209 (94.6%). Neighbor-joining clustering analysis derived from SSR binary data allowed the detection of two major groups, essentially distinguished by the presence or absence of the B genome, while subgroups were formed according to the genomic composition and commercial classification. The co-dominant nature of SSR was explored to analyze the structure of the population based on a Bayesian approach, detecting 21 subpopulations. Most of the subpopulations were in agreement with the clustering analysis. Conclusions The data generated by flow cytometry, ITS and SSR supported the hypothesis about the occurrence of homeologue recombination between A and B genomes, leading to discrepancies in the number of sets or portions from each parental genome. These phenomenons have been largely disregarded in the evolution of banana, as the “single-step domestication” hypothesis had long predominated. These findings will have an impact in future breeding approaches. Structure analysis enabled the efficient detection of ancestry of recently developed tetraploid hybrids by breeding programs, and for some triploids. However, for the main commercial subgroups, Structure appeared to be less efficient to detect the ancestry in diploid groups, possibly due to sampling restrictions. The possibility of inferring the membership among accessions to correct the effects of genetic structure opens possibilities for its use in marker-assisted selection by association mapping. PMID:23497122

Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh

Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. Tomore » alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs.« less

The genome- and transcriptome-wide analysis of innate immunity in the brown planthopper, Nilaparvata lugens

PubMed Central

2013-01-01

Background The brown planthopper (Nilaparvata lugens) is one of the most serious rice plant pests in Asia. N. lugens causes extensive rice damage by sucking rice phloem sap, which results in stunted plant growth and the transmission of plant viruses. Despite the importance of this insect pest, little is known about the immunological mechanisms occurring in this hemimetabolous insect species. Results In this study, we performed a genome- and transcriptome-wide analysis aiming at the immune-related genes. The transcriptome datasets include the N. lugens intestine, the developmental stage, wing formation, and sex-specific expression information that provided useful gene expression sequence data for the genome-wide analysis. As a result, we identified a large number of genes encoding N. lugens pattern recognition proteins, modulation proteins in the prophenoloxidase (proPO) activating cascade, immune effectors, and the signal transduction molecules involved in the immune pathways, including the Toll, Immune deficiency (Imd) and Janus kinase signal transducers and activators of transcription (JAK-STAT) pathways. The genome scale analysis revealed detailed information of the gene structure, distribution and transcription orientations in scaffolds. A comparison of the genome-available hemimetabolous and metabolous insect species indicate the differences in the immune-related gene constitution. We investigated the gene expression profiles with regards to how they responded to bacterial infections and tissue, as well as development and sex expression specificity. Conclusions The genome- and transcriptome-wide analysis of immune-related genes including pattern recognition and modulation molecules, immune effectors, and the signal transduction molecules involved in the immune pathways is an important step in determining the overall architecture and functional network of the immune components in N. lugens. Our findings provide the comprehensive gene sequence resource and expression profiles of the immune-related genes of N. lugens, which could facilitate the understanding of the innate immune mechanisms in the hemimetabolous insect species. These data give insight into clarifying the potential functional roles of the immune-related genes involved in the biological processes of development, reproduction, and virus transmission in N. lugens. PMID:23497397

Using large-scale genome variation cohorts to decipher the molecular mechanism of cancer.

PubMed

Habermann, Nina; Mardin, Balca R; Yakneen, Sergei; Korbel, Jan O

2016-01-01

Characterizing genomic structural variations (SVs) in the human genome remains challenging, and there is a growing interest to understand somatic SVs occurring in cancer, a disease of the genome. A havoc-causing SV process known as chromothripsis scars the genome when localized chromosome shattering and repair occur in a one-off catastrophe. Recent efforts led to the development of a set of conceptual criteria for the inference of chromothripsis events in cancer genomes and to the development of experimental model systems for studying this striking DNA alteration process in vitro. We discuss these approaches, and additionally touch upon current "Big Data" efforts that employ hybrid cloud computing to enable studies of numerous cancer genomes in an effort to search for commonalities and differences in molecular DNA alteration processes in cancer. Copyright © 2016. Published by Elsevier SAS.

redGEM: Systematic reduction and analysis of genome-scale metabolic reconstructions for development of consistent core metabolic models

PubMed Central

Ataman, Meric

2017-01-01

Genome-scale metabolic reconstructions have proven to be valuable resources in enhancing our understanding of metabolic networks as they encapsulate all known metabolic capabilities of the organisms from genes to proteins to their functions. However the complexity of these large metabolic networks often hinders their utility in various practical applications. Although reduced models are commonly used for modeling and in integrating experimental data, they are often inconsistent across different studies and laboratories due to different criteria and detail, which can compromise transferability of the findings and also integration of experimental data from different groups. In this study, we have developed a systematic semi-automatic approach to reduce genome-scale models into core models in a consistent and logical manner focusing on the central metabolism or subsystems of interest. The method minimizes the loss of information using an approach that combines graph-based search and optimization methods. The resulting core models are shown to be able to capture key properties of the genome-scale models and preserve consistency in terms of biomass and by-product yields, flux and concentration variability and gene essentiality. The development of these “consistently-reduced” models will help to clarify and facilitate integration of different experimental data to draw new understanding that can be directly extendable to genome-scale models. PMID:28727725

MIPSPlantsDB—plant database resource for integrative and comparative plant genome research

PubMed Central

Spannagl, Manuel; Noubibou, Octave; Haase, Dirk; Yang, Li; Gundlach, Heidrun; Hindemitt, Tobias; Klee, Kathrin; Haberer, Georg; Schoof, Heiko; Mayer, Klaus F. X.

2007-01-01

Genome-oriented plant research delivers rapidly increasing amount of plant genome data. Comprehensive and structured information resources are required to structure and communicate genome and associated analytical data for model organisms as well as for crops. The increase in available plant genomic data enables powerful comparative analysis and integrative approaches. PlantsDB aims to provide data and information resources for individual plant species and in addition to build a platform for integrative and comparative plant genome research. PlantsDB is constituted from genome databases for Arabidopsis, Medicago, Lotus, rice, maize and tomato. Complementary data resources for cis elements, repetive elements and extensive cross-species comparisons are implemented. The PlantsDB portal can be reached at . PMID:17202173

Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma.

PubMed

Jusakul, Apinya; Cutcutache, Ioana; Yong, Chern Han; Lim, Jing Quan; Huang, Mi Ni; Padmanabhan, Nisha; Nellore, Vishwa; Kongpetch, Sarinya; Ng, Alvin Wei Tian; Ng, Ley Moy; Choo, Su Pin; Myint, Swe Swe; Thanan, Raynoo; Nagarajan, Sanjanaa; Lim, Weng Khong; Ng, Cedric Chuan Young; Boot, Arnoud; Liu, Mo; Ong, Choon Kiat; Rajasegaran, Vikneswari; Lie, Stefanus; Lim, Alvin Soon Tiong; Lim, Tse Hui; Tan, Jing; Loh, Jia Liang; McPherson, John R; Khuntikeo, Narong; Bhudhisawasdi, Vajaraphongsa; Yongvanit, Puangrat; Wongkham, Sopit; Totoki, Yasushi; Nakamura, Hiromi; Arai, Yasuhito; Yamasaki, Satoshi; Chow, Pierce Kah-Hoe; Chung, Alexander Yaw Fui; Ooi, London Lucien Peng Jin; Lim, Kiat Hon; Dima, Simona; Duda, Dan G; Popescu, Irinel; Broet, Philippe; Hsieh, Sen-Yung; Yu, Ming-Chin; Scarpa, Aldo; Lai, Jiaming; Luo, Di-Xian; Carvalho, André Lopes; Vettore, André Luiz; Rhee, Hyungjin; Park, Young Nyun; Alexandrov, Ludmil B; Gordân, Raluca; Rozen, Steven G; Shibata, Tatsuhiro; Pairojkul, Chawalit; Teh, Bin Tean; Tan, Patrick

2017-10-01

Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analyzed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined 4 CCA clusters-fluke-positive CCAs (clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations; conversely, fluke-negative CCAs (clusters 3/4) exhibit high copy-number alterations and PD-1 / PD-L2 expression, or epigenetic mutations ( IDH1/2, BAP1 ) and FGFR / PRKA -related gene rearrangements. Whole-genome analysis highlighted FGFR2 3' untranslated region deletion as a mechanism of FGFR2 upregulation. Integration of noncoding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation of H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores-mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Our results exemplify how genetics, epigenetics, and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer. Significance: Integrated whole-genome and epigenomic analysis of CCA on an international scale identifies new CCA driver genes, noncoding promoter mutations, and structural variants. CCA molecular landscapes differ radically by etiology, underscoring how distinct cancer subtypes in the same organ may arise through different extrinsic and intrinsic carcinogenic processes. Cancer Discov; 7(10); 1116-35. ©2017 AACR. This article is highlighted in the In This Issue feature, p. 1047 . ©2017 American Association for Cancer Research.

APPLICATION OF DNA MICROARRAYS TO REPRODUCTIVE TOXICOLOGY AND THE DEVELOPMENT OF A TESTIS ARRAY

EPA Science Inventory

With the advent of sequence information for entire mammalian genomes, it is now possible to analyze gene expression and gene polymorphisms on a genomic scale. The primary tool for analysis of gene expression is the DNA microarray. We have used commercially available cDNA micro...

A genome-wide association study platform built on iPlant cyber-infrastructure

USDA-ARS?s Scientific Manuscript database

We demonstrated a flexible Genome-Wide Association (GWA) Study (GWAS) platform built upon the iPlant Collaborative Cyber-infrastructure. The platform supports big data management, sharing, and large scale study of both genotype and phenotype data on clusters. End users can add their own analysis too...

Genomic analysis of organismal complexity in the multicellular green alga Volvox carteri

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prochnik, Simon E.; Umen, James; Nedelcu, Aurora

2010-07-01

Analysis of the Volvox carteri genome reveals that this green alga's increased organismal complexity and multicellularity are associated with modifications in protein families shared with its unicellular ancestor, and not with large-scale innovations in protein coding capacity. The multicellular green alga Volvox carteri and its morphologically diverse close relatives (the volvocine algae) are uniquely suited for investigating the evolution of multicellularity and development. We sequenced the 138 Mb genome of V. carteri and compared its {approx}14,500 predicted proteins to those of its unicellular relative, Chlamydomonas reinhardtii. Despite fundamental differences in organismal complexity and life history, the two species have similarmore » protein-coding potentials, and few species-specific protein-coding gene predictions. Interestingly, volvocine algal-specific proteins are enriched in Volvox, including those associated with an expanded and highly compartmentalized extracellular matrix. Our analysis shows that increases in organismal complexity can be associated with modifications of lineage-specific proteins rather than large-scale invention of protein-coding capacity.« less

The Large Mitochondrial Genome of Symbiodinium minutum Reveals Conserved Noncoding Sequences between Dinoflagellates and Apicomplexans.

PubMed

Shoguchi, Eiichi; Shinzato, Chuya; Hisata, Kanako; Satoh, Nori; Mungpakdee, Sutada

2015-07-20

Even though mitochondrial genomes, which characterize eukaryotic cells, were first discovered more than 50 years ago, mitochondrial genomics remains an important topic in molecular biology and genome sciences. The Phylum Alveolata comprises three major groups (ciliates, apicomplexans, and dinoflagellates), the mitochondrial genomes of which have diverged widely. Even though the gene content of dinoflagellate mitochondrial genomes is reportedly comparable to that of apicomplexans, the highly fragmented and rearranged genome structures of dinoflagellates have frustrated whole genomic analysis. Consequently, noncoding sequences and gene arrangements of dinoflagellate mitochondrial genomes have not been well characterized. Here we report that the continuous assembled genome (∼326 kb) of the dinoflagellate, Symbiodinium minutum, is AT-rich (∼64.3%) and that it contains three protein-coding genes. Based upon in silico analysis, the remaining 99% of the genome comprises transcriptomic noncoding sequences. RNA edited sites and unique, possible start and stop codons clarify conserved regions among dinoflagellates. Our massive transcriptome analysis shows that almost all regions of the genome are transcribed, including 27 possible fragmented ribosomal RNA genes and 12 uncharacterized small RNAs that are similar to mitochondrial RNA genes of the malarial parasite, Plasmodium falciparum. Gene map comparisons show that gene order is only slightly conserved between S. minutum and P. falciparum. However, small RNAs and intergenic sequences share sequence similarities with P. falciparum, suggesting that the function of noncoding sequences has been preserved despite development of very different genome structures. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Functional precision medicine identifies novel druggable targets and therapeutic options in head and neck cancer. | Office of Cancer Genomics

Cancer.gov

Purpose: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide with high mortality and a lack of targeted therapies. To identify and prioritize druggable targets, we performed genome analysis together with genome-scale siRNA and oncology drug profiling using low passage tumor cells derived from a patient with a treatmentresistant HPV-negative HNSCC.

Apophysomyces variabilis: draft genome sequence and comparison of predictive virulence determinants with other medically important Mucorales.

PubMed

Prakash, Hariprasath; Rudramurthy, Shivaprakash Mandya; Gandham, Prasad S; Ghosh, Anup Kumar; Kumar, Milner M; Badapanda, Chandan; Chakrabarti, Arunaloke

2017-09-18

Apophysomyces species are prevalent in tropical countries and A. variabilis is the second most frequent agent causing mucormycosis in India. Among Apophysomyces species, A. elegans, A. trapeziformis and A. variabilis are commonly incriminated in human infections. The genome sequences of A. elegans and A. trapeziformis are available in public database, but not A. variabilis. We, therefore, performed the whole genome sequence of A. variabilis to explore its genomic structure and possible genes determining the virulence of the organism. The whole genome of A. variabilis NCCPF 102052 was sequenced and the genomic structure of A. variabilis was compared with already available genome structures of A. elegans, A. trapeziformis and other medically important Mucorales. The total size of genome assembly of A. variabilis was 39.38 Mb with 12,764 protein-coding genes. The transposable elements (TEs) were low in Apophysomyces genome and the retrotransposon Ty3-gypsy was the common TE. Phylogenetically, Apophysomyces species were grouped closely with Phycomyces blakesleeanus. OrthoMCL analysis revealed 3025 orthologues proteins, which were common in those three pathogenic Apophysomyces species. Expansion of multiple gene families/duplication was observed in Apophysomyces genomes. Approximately 6% of Apophysomyces genes were predicted to be associated with virulence on PHIbase analysis. The virulence determinants included the protein families of CotH proteins (invasins), proteases, iron utilisation pathways, siderophores and signal transduction pathways. Serine proteases were the major group of proteases found in all Apophysomyces genomes. The carbohydrate active enzymes (CAZymes) constitute the majority of the secretory proteins. The present study is the maiden attempt to sequence and analyze the genomic structure of A. variabilis. Together with available genome sequence of A. elegans and A. trapeziformis, the study helped to indicate the possible virulence determinants of pathogenic Apophysomyces species. The presence of unique CAZymes in cell wall might be exploited in future for antifungal drug development.

Inference of Ancestral Recombination Graphs through Topological Data Analysis

PubMed Central

Cámara, Pablo G.; Levine, Arnold J.; Rabadán, Raúl

2016-01-01

The recent explosion of genomic data has underscored the need for interpretable and comprehensive analyses that can capture complex phylogenetic relationships within and across species. Recombination, reassortment and horizontal gene transfer constitute examples of pervasive biological phenomena that cannot be captured by tree-like representations. Starting from hundreds of genomes, we are interested in the reconstruction of potential evolutionary histories leading to the observed data. Ancestral recombination graphs represent potential histories that explicitly accommodate recombination and mutation events across orthologous genomes. However, they are computationally costly to reconstruct, usually being infeasible for more than few tens of genomes. Recently, Topological Data Analysis (TDA) methods have been proposed as robust and scalable methods that can capture the genetic scale and frequency of recombination. We build upon previous TDA developments for detecting and quantifying recombination, and present a novel framework that can be applied to hundreds of genomes and can be interpreted in terms of minimal histories of mutation and recombination events, quantifying the scales and identifying the genomic locations of recombinations. We implement this framework in a software package, called TARGet, and apply it to several examples, including small migration between different populations, human recombination, and horizontal evolution in finches inhabiting the Galápagos Islands. PMID:27532298

Emerging Genomic Tools for Legume Breeding: Current Status and Future Prospects

PubMed Central

Pandey, Manish K.; Roorkiwal, Manish; Singh, Vikas K.; Ramalingam, Abirami; Kudapa, Himabindu; Thudi, Mahendar; Chitikineni, Anu; Rathore, Abhishek; Varshney, Rajeev K.

2016-01-01

Legumes play a vital role in ensuring global nutritional food security and improving soil quality through nitrogen fixation. Accelerated higher genetic gains is required to meet the demand of ever increasing global population. In recent years, speedy developments have been witnessed in legume genomics due to advancements in next-generation sequencing (NGS) and high-throughput genotyping technologies. Reference genome sequences for many legume crops have been reported in the last 5 years. The availability of the draft genome sequences and re-sequencing of elite genotypes for several important legume crops have made it possible to identify structural variations at large scale. Availability of large-scale genomic resources and low-cost and high-throughput genotyping technologies are enhancing the efficiency and resolution of genetic mapping and marker-trait association studies. Most importantly, deployment of molecular breeding approaches has resulted in development of improved lines in some legume crops such as chickpea and groundnut. In order to support genomics-driven crop improvement at a fast pace, the deployment of breeder-friendly genomics and decision support tools seems appear to be critical in breeding programs in developing countries. This review provides an overview of emerging genomics and informatics tools/approaches that will be the key driving force for accelerating genomics-assisted breeding and ultimately ensuring nutritional and food security in developing countries. PMID:27199998

LOLAweb: a containerized web server for interactive genomic locus overlap enrichment analysis.

PubMed

Nagraj, V P; Magee, Neal E; Sheffield, Nathan C

2018-06-06

The past few years have seen an explosion of interest in understanding the role of regulatory DNA. This interest has driven large-scale production of functional genomics data and analytical methods. One popular analysis is to test for enrichment of overlaps between a query set of genomic regions and a database of region sets. In this way, new genomic data can be easily connected to annotations from external data sources. Here, we present an interactive interface for enrichment analysis of genomic locus overlaps using a web server called LOLAweb. LOLAweb accepts a set of genomic ranges from the user and tests it for enrichment against a database of region sets. LOLAweb renders results in an R Shiny application to provide interactive visualization features, enabling users to filter, sort, and explore enrichment results dynamically. LOLAweb is built and deployed in a Linux container, making it scalable to many concurrent users on our servers and also enabling users to download and run LOLAweb locally.

Genetic Diversity and Demographic History of Cajanus spp. Illustrated from Genome-Wide SNPs

PubMed Central

Saxena, Rachit K.; von Wettberg, Eric; Upadhyaya, Hari D.; Sanchez, Vanessa; Songok, Serah; Saxena, Kulbhushan; Kimurto, Paul; Varshney, Rajeev K.

2014-01-01

Understanding genetic structure of Cajanus spp. is essential for achieving genetic improvement by quantitative trait loci (QTL) mapping or association studies and use of selected markers through genomic assisted breeding and genomic selection. After developing a comprehensive set of 1,616 single nucleotide polymorphism (SNPs) and their conversion into cost effective KASPar assays for pigeonpea (Cajanus cajan), we studied levels of genetic variability both within and between diverse set of Cajanus lines including 56 breeding lines, 21 landraces and 107 accessions from 18 wild species. These results revealed a high frequency of polymorphic SNPs and relatively high level of cross-species transferability. Indeed, 75.8% of successful SNP assays revealed polymorphism, and more than 95% of these assays could be successfully transferred to related wild species. To show regional patterns of variation, we used STRUCTURE and Analysis of Molecular Variance (AMOVA) to partition variance among hierarchical sets of landraces and wild species at either the continental scale or within India. STRUCTURE separated most of the domesticated germplasm from wild ecotypes, and separates Australian and Asian wild species as has been found previously. Among Indian regions and states within regions, we found 36% of the variation between regions, and 64% within landraces or wilds within states. The highest level of polymorphism in wild relatives and landraces was found in Madhya Pradesh and Andhra Pradesh provinces of India representing the centre of origin and domestication of pigeonpea respectively. PMID:24533111

Improvisation in evolution of genes and genomes: whose structure is it anyway?

PubMed

Shakhnovich, Boris E; Shakhnovich, Eugene I

2008-06-01

Significant progress has been made in recent years in a variety of seemingly unrelated fields such as sequencing, protein structure prediction, and high-throughput transcriptomics and metabolomics. At the same time, new microscopic models have been developed that made it possible to analyze the evolution of genes and genomes from first principles. The results from these efforts enable, for the first time, a comprehensive insight into the evolution of complex systems and organisms on all scales--from sequences to organisms and populations. Every newly sequenced genome uncovers new genes, families, and folds. Where do these new genes come from? How do gene duplication and subsequent divergence of sequence and structure affect the fitness of the organism? What role does regulation play in the evolution of proteins and folds? Emerging synergism between data and modeling provides first robust answers to these questions.

Comparative genome-scale modelling of Staphylococcus aureus strains identifies strain-specific metabolic capabilities linked to pathogenicity

PubMed Central

Bosi, Emanuele; Monk, Jonathan M.; Aziz, Ramy K.; Fondi, Marco; Nizet, Victor; Palsson, Bernhard Ø.

2016-01-01

Staphylococcus aureus is a preeminent bacterial pathogen capable of colonizing diverse ecological niches within its human host. We describe here the pangenome of S. aureus based on analysis of genome sequences from 64 strains of S. aureus spanning a range of ecological niches, host types, and antibiotic resistance profiles. Based on this set, S. aureus is expected to have an open pangenome composed of 7,411 genes and a core genome composed of 1,441 genes. Metabolism was highly conserved in this core genome; however, differences were identified in amino acid and nucleotide biosynthesis pathways between the strains. Genome-scale models (GEMs) of metabolism were constructed for the 64 strains of S. aureus. These GEMs enabled a systems approach to characterizing the core metabolic and panmetabolic capabilities of the S. aureus species. All models were predicted to be auxotrophic for the vitamins niacin (vitamin B3) and thiamin (vitamin B1), whereas strain-specific auxotrophies were predicted for riboflavin (vitamin B2), guanosine, leucine, methionine, and cysteine, among others. GEMs were used to systematically analyze growth capabilities in more than 300 different growth-supporting environments. The results identified metabolic capabilities linked to pathogenic traits and virulence acquisitions. Such traits can be used to differentiate strains responsible for mild vs. severe infections and preference for hosts (e.g., animals vs. humans). Genome-scale analysis of multiple strains of a species can thus be used to identify metabolic determinants of virulence and increase our understanding of why certain strains of this deadly pathogen have spread rapidly throughout the world. PMID:27286824

Collinearity between potato (Solanum tuberosum L.) and wild relatives assessed by comparative cytogenetic mapping.

PubMed

Gaiero, Paola; van de Belt, José; Vilaró, Francisco; Schranz, M Eric; Speranza, Pablo; de Jong, Hans

2017-03-01

A major bottleneck to introgressive hybridization is the lack of genome collinearity between the donor (alien) genome and the recipient crop genome. Structural differences between the homeologs may create unbalanced segregation of chromosomes or cause linkage drag. To assess large-scale collinearity between potato and two of its wild relatives (Solanum commersonii and Solanum chacoense), we used BAC-FISH mapping of sequences with known positions on the RH potato map. BAC probes could successfully be hybridized to the S. commersonii and S. chachoense pachytene chromosomes, confirming their correspondence with linkage groups in RH potato. Our study shows that the order of BAC signals is conserved. Distances between BAC signals were quantified and compared; some differences found suggest either small-scale rearrangements or reduction/amplification of repeats. We conclude that S. commersonii and S. chacoense are collinear with cultivated Solanum tuberosum on the whole chromosome scale, making these amenable species for efficient introgressive hybridization breeding.

Savant Genome Browser 2: visualization and analysis for population-scale genomics.

PubMed

Fiume, Marc; Smith, Eric J M; Brook, Andrew; Strbenac, Dario; Turner, Brian; Mezlini, Aziz M; Robinson, Mark D; Wodak, Shoshana J; Brudno, Michael

2012-07-01

High-throughput sequencing (HTS) technologies are providing an unprecedented capacity for data generation, and there is a corresponding need for efficient data exploration and analysis capabilities. Although most existing tools for HTS data analysis are developed for either automated (e.g. genotyping) or visualization (e.g. genome browsing) purposes, such tools are most powerful when combined. For example, integration of visualization and computation allows users to iteratively refine their analyses by updating computational parameters within the visual framework in real-time. Here we introduce the second version of the Savant Genome Browser, a standalone program for visual and computational analysis of HTS data. Savant substantially improves upon its predecessor and existing tools by introducing innovative visualization modes and navigation interfaces for several genomic datatypes, and synergizing visual and automated analyses in a way that is powerful yet easy even for non-expert users. We also present a number of plugins that were developed by the Savant Community, which demonstrate the power of integrating visual and automated analyses using Savant. The Savant Genome Browser is freely available (open source) at www.savantbrowser.com.

Savant Genome Browser 2: visualization and analysis for population-scale genomics

PubMed Central

Smith, Eric J. M.; Brook, Andrew; Strbenac, Dario; Turner, Brian; Mezlini, Aziz M.; Robinson, Mark D.; Wodak, Shoshana J.; Brudno, Michael

2012-01-01

High-throughput sequencing (HTS) technologies are providing an unprecedented capacity for data generation, and there is a corresponding need for efficient data exploration and analysis capabilities. Although most existing tools for HTS data analysis are developed for either automated (e.g. genotyping) or visualization (e.g. genome browsing) purposes, such tools are most powerful when combined. For example, integration of visualization and computation allows users to iteratively refine their analyses by updating computational parameters within the visual framework in real-time. Here we introduce the second version of the Savant Genome Browser, a standalone program for visual and computational analysis of HTS data. Savant substantially improves upon its predecessor and existing tools by introducing innovative visualization modes and navigation interfaces for several genomic datatypes, and synergizing visual and automated analyses in a way that is powerful yet easy even for non-expert users. We also present a number of plugins that were developed by the Savant Community, which demonstrate the power of integrating visual and automated analyses using Savant. The Savant Genome Browser is freely available (open source) at www.savantbrowser.com. PMID:22638571

PGen: large-scale genomic variations analysis workflow and browser in SoyKB.

PubMed

Liu, Yang; Khan, Saad M; Wang, Juexin; Rynge, Mats; Zhang, Yuanxun; Zeng, Shuai; Chen, Shiyuan; Maldonado Dos Santos, Joao V; Valliyodan, Babu; Calyam, Prasad P; Merchant, Nirav; Nguyen, Henry T; Xu, Dong; Joshi, Trupti

2016-10-06

With the advances in next-generation sequencing (NGS) technology and significant reductions in sequencing costs, it is now possible to sequence large collections of germplasm in crops for detecting genome-scale genetic variations and to apply the knowledge towards improvements in traits. To efficiently facilitate large-scale NGS resequencing data analysis of genomic variations, we have developed "PGen", an integrated and optimized workflow using the Extreme Science and Engineering Discovery Environment (XSEDE) high-performance computing (HPC) virtual system, iPlant cloud data storage resources and Pegasus workflow management system (Pegasus-WMS). The workflow allows users to identify single nucleotide polymorphisms (SNPs) and insertion-deletions (indels), perform SNP annotations and conduct copy number variation analyses on multiple resequencing datasets in a user-friendly and seamless way. We have developed both a Linux version in GitHub ( https://github.com/pegasus-isi/PGen-GenomicVariations-Workflow ) and a web-based implementation of the PGen workflow integrated within the Soybean Knowledge Base (SoyKB), ( http://soykb.org/Pegasus/index.php ). Using PGen, we identified 10,218,140 single-nucleotide polymorphisms (SNPs) and 1,398,982 indels from analysis of 106 soybean lines sequenced at 15X coverage. 297,245 non-synonymous SNPs and 3330 copy number variation (CNV) regions were identified from this analysis. SNPs identified using PGen from additional soybean resequencing projects adding to 500+ soybean germplasm lines in total have been integrated. These SNPs are being utilized for trait improvement using genotype to phenotype prediction approaches developed in-house. In order to browse and access NGS data easily, we have also developed an NGS resequencing data browser ( http://soykb.org/NGS_Resequence/NGS_index.php ) within SoyKB to provide easy access to SNP and downstream analysis results for soybean researchers. PGen workflow has been optimized for the most efficient analysis of soybean data using thorough testing and validation. This research serves as an example of best practices for development of genomics data analysis workflows by integrating remote HPC resources and efficient data management with ease of use for biological users. PGen workflow can also be easily customized for analysis of data in other species.

CGAT: a model for immersive personalized training in computational genomics

PubMed Central

Sims, David; Ponting, Chris P.

2016-01-01

How should the next generation of genomics scientists be trained while simultaneously pursuing high quality and diverse research? CGAT, the Computational Genomics Analysis and Training programme, was set up in 2010 by the UK Medical Research Council to complement its investment in next-generation sequencing capacity. CGAT was conceived around the twin goals of training future leaders in genome biology and medicine, and providing much needed capacity to UK science for analysing genome scale data sets. Here we outline the training programme employed by CGAT and describe how it dovetails with collaborative research projects to launch scientists on the road towards independent research careers in genomics. PMID:25981124

Scanning the human genome at kilobase resolution.

PubMed

Chen, Jun; Kim, Yeong C; Jung, Yong-Chul; Xuan, Zhenyu; Dworkin, Geoff; Zhang, Yanming; Zhang, Michael Q; Wang, San Ming

2008-05-01

Normal genome variation and pathogenic genome alteration frequently affect small regions in the genome. Identifying those genomic changes remains a technical challenge. We report here the development of the DGS (Ditag Genome Scanning) technique for high-resolution analysis of genome structure. The basic features of DGS include (1) use of high-frequent restriction enzymes to fractionate the genome into small fragments; (2) collection of two tags from two ends of a given DNA fragment to form a ditag to represent the fragment; (3) application of the 454 sequencing system to reach a comprehensive ditag sequence collection; (4) determination of the genome origin of ditags by mapping to reference ditags from known genome sequences; (5) use of ditag sequences directly as the sense and antisense PCR primers to amplify the original DNA fragment. To study the relationship between ditags and genome structure, we performed a computational study by using the human genome reference sequences as a model, and analyzed the ditags experimentally collected from the well-characterized normal human DNA GM15510 and the leukemic human DNA of Kasumi-1 cells. Our studies show that DGS provides a kilobase resolution for studying genome structure with high specificity and high genome coverage. DGS can be applied to validate genome assembly, to compare genome similarity and variation in normal populations, and to identify genomic abnormality including insertion, inversion, deletion, translocation, and amplification in pathological genomes such as cancer genomes.

Nanoscale Bio-engineering Solutions for Space Exploration: The Nanopore Sequencer

NASA Technical Reports Server (NTRS)

Stolc, Viktor; Cozmuta, Ioana

2004-01-01

Characterization of biological systems at the molecular level and extraction of essential information for nano-engineering design to guide the nano-fabrication of solid-state sensors and molecular identification devices is a computational challenge. The alpha hemolysin protein ion channel is used as a model system for structural analysis of nucleic acids like DNA. Applied voltage draws a DNA strand and surrounding ionic solution through the biological nanopore. The subunits in the DNA strand block ion flow by differing amounts. Atomistic scale simulations are employed using NASA supercomputers to study DNA translocation, with the aim to enhance single DNA subunit identification. Compared to protein channels, solid-state nanopores offer a better temporal control of the translocation of DNA and the possibility to easily tune its chemistry to increase the signal resolution. Potential applications for NASA missions, besides real-time genome sequencing include astronaut health, life detection and decoding of various genomes.

Nanoscale Bioengineering Solutions for Space Exploration the Nanopore Sequencer

NASA Technical Reports Server (NTRS)

Ioana, Cozmuta; Viktor, Stoic

2005-01-01

Characterization of biological systems at the molecular level and extraction of essential information for nano-engineering design to guide the nano-fabrication of solid-state sensors and molecular identification devices is a computational challenge. The alpha hemolysin protein ion channel is used as a model system for structural analysis of nucleic acids like DNA. Applied voltage draws a DNA strand and surrounding ionic solution through the biological nanopore. The subunits in the DNA strand block ion flow by differing amounts. Atomistic scale simulations are employed using NASA supercomputers to study DNA translocation. with the aim to enhance single DNA subunit identification. Compared to protein channels, solid-state nanopores offer a better temporal control of the translocation of DNA and the possibility to easily tune its chemistry to increase the signal resolution. Potential applications for NASA missions, besides real-time genome sequencing include astronaut health, life detection and decoding of various genomes. http://phenomrph.arc.nasa.gov/index.php

Comparative Population Genomics Analysis of the Mammalian Fungal Pathogen Pneumocystis

PubMed Central

Ma, Liang; Wei Huang, Da; Khil, Pavel P.; Dekker, John P.; Kutty, Geetha; Bishop, Lisa; Liu, Yueqin; Deng, Xilong; Pagni, Marco; Hirsch, Vanessa; Lempicki, Richard A.

2018-01-01

ABSTRACT Pneumocystis species are opportunistic mammalian pathogens that cause severe pneumonia in immunocompromised individuals. These fungi are highly host specific and uncultivable in vitro. Human Pneumocystis infections present major challenges because of a limited therapeutic arsenal and the rise of drug resistance. To investigate the diversity and demographic history of natural populations of Pneumocystis infecting humans, rats, and mice, we performed whole-genome and large-scale multilocus sequencing of infected tissues collected in various geographic locations. Here, we detected reduced levels of recombination and variations in historical demography, which shape the global population structures. We report estimates of evolutionary rates, levels of genetic diversity, and population sizes. Molecular clock estimates indicate that Pneumocystis species diverged before their hosts, while the asynchronous timing of population declines suggests host shifts. Our results have uncovered complex patterns of genetic variation influenced by multiple factors that shaped the adaptation of Pneumocystis populations during their spread across mammals. PMID:29739910

What is bioinformatics? A proposed definition and overview of the field.

PubMed

Luscombe, N M; Greenbaum, D; Gerstein, M

2001-01-01

The recent flood of data from genome sequences and functional genomics has given rise to new field, bioinformatics, which combines elements of biology and computer science. Here we propose a definition for this new field and review some of the research that is being pursued, particularly in relation to transcriptional regulatory systems. Our definition is as follows: Bioinformatics is conceptualizing biology in terms of macromolecules (in the sense of physical-chemistry) and then applying "informatics" techniques (derived from disciplines such as applied maths, computer science, and statistics) to understand and organize the information associated with these molecules, on a large-scale. Analyses in bioinformatics predominantly focus on three types of large datasets available in molecular biology: macromolecular structures, genome sequences, and the results of functional genomics experiments (e.g. expression data). Additional information includes the text of scientific papers and "relationship data" from metabolic pathways, taxonomy trees, and protein-protein interaction networks. Bioinformatics employs a wide range of computational techniques including sequence and structural alignment, database design and data mining, macromolecular geometry, phylogenetic tree construction, prediction of protein structure and function, gene finding, and expression data clustering. The emphasis is on approaches integrating a variety of computational methods and heterogeneous data sources. Finally, bioinformatics is a practical discipline. We survey some representative applications, such as finding homologues, designing drugs, and performing large-scale censuses. Additional information pertinent to the review is available over the web at http://bioinfo.mbb.yale.edu/what-is-it.

NordicDB: a Nordic pool and portal for genome-wide control data.

PubMed

Leu, Monica; Humphreys, Keith; Surakka, Ida; Rehnberg, Emil; Muilu, Juha; Rosenström, Päivi; Almgren, Peter; Jääskeläinen, Juha; Lifton, Richard P; Kyvik, Kirsten Ohm; Kaprio, Jaakko; Pedersen, Nancy L; Palotie, Aarno; Hall, Per; Grönberg, Henrik; Groop, Leif; Peltonen, Leena; Palmgren, Juni; Ripatti, Samuli

2010-12-01

A cost-efficient way to increase power in a genetic association study is to pool controls from different sources. The genotyping effort can then be directed to large case series. The Nordic Control database, NordicDB, has been set up as a unique resource in the Nordic area and the data are available for authorized users through the web portal (http://www.nordicdb.org). The current version of NordicDB pools together high-density genome-wide SNP information from ∼5000 controls originating from Finnish, Swedish and Danish studies and shows country-specific allele frequencies for SNP markers. The genetic homogeneity of the samples was investigated using multidimensional scaling (MDS) analysis and pairwise allele frequency differences between the studies. The plot of the first two MDS components showed excellent resemblance to the geographical placement of the samples, with a clear NW-SE gradient. We advise researchers to assess the impact of population structure when incorporating NordicDB controls in association studies. This harmonized Nordic database presents a unique genome-wide resource for future genetic association studies in the Nordic countries.

NordicDB: a Nordic pool and portal for genome-wide control data

PubMed Central

Leu, Monica; Humphreys, Keith; Surakka, Ida; Rehnberg, Emil; Muilu, Juha; Rosenström, Päivi; Almgren, Peter; Jääskeläinen, Juha; Lifton, Richard P; Kyvik, Kirsten Ohm; Kaprio, Jaakko; Pedersen, Nancy L; Palotie, Aarno; Hall, Per; Grönberg, Henrik; Groop, Leif; Peltonen, Leena; Palmgren, Juni; Ripatti, Samuli

2010-01-01

A cost-efficient way to increase power in a genetic association study is to pool controls from different sources. The genotyping effort can then be directed to large case series. The Nordic Control database, NordicDB, has been set up as a unique resource in the Nordic area and the data are available for authorized users through the web portal (http://www.nordicdb.org). The current version of NordicDB pools together high-density genome-wide SNP information from ∼5000 controls originating from Finnish, Swedish and Danish studies and shows country-specific allele frequencies for SNP markers. The genetic homogeneity of the samples was investigated using multidimensional scaling (MDS) analysis and pairwise allele frequency differences between the studies. The plot of the first two MDS components showed excellent resemblance to the geographical placement of the samples, with a clear NW–SE gradient. We advise researchers to assess the impact of population structure when incorporating NordicDB controls in association studies. This harmonized Nordic database presents a unique genome-wide resource for future genetic association studies in the Nordic countries. PMID:20664631

Comparative and Evolutionary Analysis of Grass Pollen Allergens Using Brachypodium distachyon as a Model System.

PubMed

Sharma, Akanksha; Sharma, Niharika; Bhalla, Prem; Singh, Mohan

2017-01-01

Comparative genomics have facilitated the mining of biological information from a genome sequence, through the detection of similarities and differences with genomes of closely or more distantly related species. By using such comparative approaches, knowledge can be transferred from the model to non-model organisms and insights can be gained in the structural and evolutionary patterns of specific genes. In the absence of sequenced genomes for allergenic grasses, this study was aimed at understanding the structure, organisation and expression profiles of grass pollen allergens using the genomic data from Brachypodium distachyon as it is phylogenetically related to the allergenic grasses. Combining genomic data with the anther RNA-Seq dataset revealed 24 pollen allergen genes belonging to eight allergen groups mapping on the five chromosomes in B. distachyon. High levels of anther-specific expression profiles were observed for the 24 identified putative allergen-encoding genes in Brachypodium. The genomic evidence suggests that gene encoding the group 5 allergen, the most potent trigger of hay fever and allergic asthma originated as a pollen specific orphan gene in a common grass ancestor of Brachypodium and Triticiae clades. Gene structure analysis showed that the putative allergen-encoding genes in Brachypodium either lack or contain reduced number of introns. Promoter analysis of the identified Brachypodium genes revealed the presence of specific cis-regulatory sequences likely responsible for high anther/pollen-specific expression. With the identification of putative allergen-encoding genes in Brachypodium, this study has also described some important plant gene families (e.g. expansin superfamily, EF-Hand family, profilins etc) for the first time in the model plant Brachypodium. Altogether, the present study provides new insights into structural characterization and evolution of pollen allergens and will further serve as a base for their functional characterization in related grass species.

Whole Genome Amplification and Reduced-Representation Genome Sequencing of Schistosoma japonicum Miracidia

PubMed Central

Shortt, Jonathan A.; Card, Daren C.; Schield, Drew R.; Liu, Yang; Zhong, Bo; Castoe, Todd A.

2017-01-01

Background In areas where schistosomiasis control programs have been implemented, morbidity and prevalence have been greatly reduced. However, to sustain these reductions and move towards interruption of transmission, new tools for disease surveillance are needed. Genomic methods have the potential to help trace the sources of new infections, and allow us to monitor drug resistance. Large-scale genotyping efforts for schistosome species have been hindered by cost, limited numbers of established target loci, and the small amount of DNA obtained from miracidia, the life stage most readily acquired from humans. Here, we present a method using next generation sequencing to provide high-resolution genomic data from S. japonicum for population-based studies. Methodology/Principal Findings We applied whole genome amplification followed by double digest restriction site associated DNA sequencing (ddRADseq) to individual S. japonicum miracidia preserved on Whatman FTA cards. We found that we could effectively and consistently survey hundreds of thousands of variants from 10,000 to 30,000 loci from archived miracidia as old as six years. An analysis of variation from eight miracidia obtained from three hosts in two villages in Sichuan showed clear population structuring by village and host even within this limited sample. Conclusions/Significance This high-resolution sequencing approach yields three orders of magnitude more information than microsatellite genotyping methods that have been employed over the last decade, creating the potential to answer detailed questions about the sources of human infections and to monitor drug resistance. Costs per sample range from $50-$200, depending on the amount of sequence information desired, and we expect these costs can be reduced further given continued reductions in sequencing costs, improvement of protocols, and parallelization. This approach provides new promise for using modern genome-scale sampling to S. japonicum surveillance, and could be applied to other schistosome species and other parasitic helminthes. PMID:28107347

Microbial genome analysis: the COG approach.

PubMed

Galperin, Michael Y; Kristensen, David M; Makarova, Kira S; Wolf, Yuri I; Koonin, Eugene V

2017-09-14

For the past 20 years, the Clusters of Orthologous Genes (COG) database had been a popular tool for microbial genome annotation and comparative genomics. Initially created for the purpose of evolutionary classification of protein families, the COG have been used, apart from straightforward functional annotation of sequenced genomes, for such tasks as (i) unification of genome annotation in groups of related organisms; (ii) identification of missing and/or undetected genes in complete microbial genomes; (iii) analysis of genomic neighborhoods, in many cases allowing prediction of novel functional systems; (iv) analysis of metabolic pathways and prediction of alternative forms of enzymes; (v) comparison of organisms by COG functional categories; and (vi) prioritization of targets for structural and functional characterization. Here we review the principles of the COG approach and discuss its key advantages and drawbacks in microbial genome analysis. Published by Oxford University Press 2017. This work is written by US Government employees and is in the public domain in the US.

The FLEXGene repository: exploiting the fruits of the genome projects by creating a needed resource to face the challenges of the post-genomic era.

PubMed

Brizuela, Leonardo; Richardson, Aaron; Marsischky, Gerald; Labaer, Joshua

2002-01-01

Thanks to the results of the multiple completed and ongoing genome sequencing projects and to the newly available recombination-based cloning techniques, it is now possible to build gene repositories with no precedent in their composition, formatting, and potential. This new type of gene repository is necessary to address the challenges imposed by the post-genomic era, i.e., experimentation on a genome-wide scale. We are building the FLEXGene (Full Length EXpression-ready) repository. This unique resource will contain clones representing the complete ORFeome of different organisms, including Homo sapiens as well as several pathogens and model organisms. It will consist of a comprehensive, characterized (sequence-verified), and arrayed gene repository. This resource will allow full exploitation of the genomic information by enabling genome-wide scale experimentation at the level of functional/phenotypic assays as well as at the level of protein expression, purification, and analysis. Here we describe the rationale and construction of this resource and focus on the data obtained from the Saccharomyces cerevisiae project.

2012 U.S. Department of Energy: Joint Genome Institute: Progress Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gilbert, David

2013-01-01

The mission of the U.S. Department of Energy Joint Genome Institute (DOE JGI) is to serve the diverse scientific community as a user facility, enabling the application of large-scale genomics and analysis of plants, microbes, and communities of microbes to address the DOE mission goals in bioenergy and the environment. The DOE JGI's sequencing efforts fall under the Eukaryote Super Program, which includes the Plant and Fungal Genomics Programs; and the Prokaryote Super Program, which includes the Microbial Genomics and Metagenomics Programs. In 2012, several projects made news for their contributions to energy and environment research.

Population-Sequencing as a Biomarker of Burkholderia mallei and Burkholderia pseudomallei Evolution through Microbial Forensic Analysis.

PubMed

Jakupciak, John P; Wells, Jeffrey M; Karalus, Richard J; Pawlowski, David R; Lin, Jeffrey S; Feldman, Andrew B

2013-01-01

Large-scale genomics projects are identifying biomarkers to detect human disease. B. pseudomallei and B. mallei are two closely related select agents that cause melioidosis and glanders. Accurate characterization of metagenomic samples is dependent on accurate measurements of genetic variation between isolates with resolution down to strain level. Often single biomarker sensitivity is augmented by use of multiple or panels of biomarkers. In parallel with single biomarker validation, advances in DNA sequencing enable analysis of entire genomes in a single run: population-sequencing. Potentially, direct sequencing could be used to analyze an entire genome to serve as the biomarker for genome identification. However, genome variation and population diversity complicate use of direct sequencing, as well as differences caused by sample preparation protocols including sequencing artifacts and mistakes. As part of a Department of Homeland Security program in bacterial forensics, we examined how to implement whole genome sequencing (WGS) analysis as a judicially defensible forensic method for attributing microbial sample relatedness; and also to determine the strengths and limitations of whole genome sequence analysis in a forensics context. Herein, we demonstrate use of sequencing to provide genetic characterization of populations: direct sequencing of populations.

Population-Sequencing as a Biomarker of Burkholderia mallei and Burkholderia pseudomallei Evolution through Microbial Forensic Analysis

PubMed Central

Jakupciak, John P.; Wells, Jeffrey M.; Karalus, Richard J.; Pawlowski, David R.; Lin, Jeffrey S.; Feldman, Andrew B.

2013-01-01

Large-scale genomics projects are identifying biomarkers to detect human disease. B. pseudomallei and B. mallei are two closely related select agents that cause melioidosis and glanders. Accurate characterization of metagenomic samples is dependent on accurate measurements of genetic variation between isolates with resolution down to strain level. Often single biomarker sensitivity is augmented by use of multiple or panels of biomarkers. In parallel with single biomarker validation, advances in DNA sequencing enable analysis of entire genomes in a single run: population-sequencing. Potentially, direct sequencing could be used to analyze an entire genome to serve as the biomarker for genome identification. However, genome variation and population diversity complicate use of direct sequencing, as well as differences caused by sample preparation protocols including sequencing artifacts and mistakes. As part of a Department of Homeland Security program in bacterial forensics, we examined how to implement whole genome sequencing (WGS) analysis as a judicially defensible forensic method for attributing microbial sample relatedness; and also to determine the strengths and limitations of whole genome sequence analysis in a forensics context. Herein, we demonstrate use of sequencing to provide genetic characterization of populations: direct sequencing of populations. PMID:24455204

Search for 5'-leader regulatory RNA structures based on gene annotation aided by the RiboGap database.

PubMed

Naghdi, Mohammad Reza; Smail, Katia; Wang, Joy X; Wade, Fallou; Breaker, Ronald R; Perreault, Jonathan

2017-03-15

The discovery of noncoding RNAs (ncRNAs) and their importance for gene regulation led us to develop bioinformatics tools to pursue the discovery of novel ncRNAs. Finding ncRNAs de novo is challenging, first due to the difficulty of retrieving large numbers of sequences for given gene activities, and second due to exponential demands on calculation needed for comparative genomics on a large scale. Recently, several tools for the prediction of conserved RNA secondary structure were developed, but many of them are not designed to uncover new ncRNAs, or are too slow for conducting analyses on a large scale. Here we present various approaches using the database RiboGap as a primary tool for finding known ncRNAs and for uncovering simple sequence motifs with regulatory roles. This database also can be used to easily extract intergenic sequences of eubacteria and archaea to find conserved RNA structures upstream of given genes. We also show how to extend analysis further to choose the best candidate ncRNAs for experimental validation. Copyright © 2017 Elsevier Inc. All rights reserved.

Cloning, production, and purification of proteins for a medium-scale structural genomics project.

PubMed

Quevillon-Cheruel, Sophie; Collinet, Bruno; Trésaugues, Lionel; Minard, Philippe; Henckes, Gilles; Aufrère, Robert; Blondeau, Karine; Zhou, Cong-Zhao; Liger, Dominique; Bettache, Nabila; Poupon, Anne; Aboulfath, Ilham; Leulliot, Nicolas; Janin, Joël; van Tilbeurgh, Herman

2007-01-01

The South-Paris Yeast Structural Genomics Pilot Project (http://www.genomics.eu.org) aims at systematically expressing, purifying, and determining the three-dimensional structures of Saccharomyces cerevisiae proteins. We have already cloned 240 yeast open reading frames in the Escherichia coli pET system. Eighty-two percent of the targets can be expressed in E. coli, and 61% yield soluble protein. We have currently purified 58 proteins. Twelve X-ray structures have been solved, six are in progress, and six other proteins gave crystals. In this chapter, we present the general experimental flowchart applied for this project. One of the main difficulties encountered in this pilot project was the low solubility of a great number of target proteins. We have developed parallel strategies to recover these proteins from inclusion bodies, including refolding, coexpression with chaperones, and an in vitro expression system. A limited proteolysis protocol, developed to localize flexible regions in proteins that could hinder crystallization, is also described.

ATLAS (Automatic Tool for Local Assembly Structures) - A Comprehensive Infrastructure for Assembly, Annotation, and Genomic Binning of Metagenomic and Metaranscripomic Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, Richard A.; Brown, Joseph M.; Colby, Sean M.

ATLAS (Automatic Tool for Local Assembly Structures) is a comprehensive multiomics data analysis pipeline that is massively parallel and scalable. ATLAS contains a modular analysis pipeline for assembly, annotation, quantification and genome binning of metagenomics and metatranscriptomics data and a framework for reference metaproteomic database construction. ATLAS transforms raw sequence data into functional and taxonomic data at the microbial population level and provides genome-centric resolution through genome binning. ATLAS provides robust taxonomy based on majority voting of protein coding open reading frames rolled-up at the contig level using modified lowest common ancestor (LCA) analysis. ATLAS provides robust taxonomy based onmore » majority voting of protein coding open reading frames rolled-up at the contig level using modified lowest common ancestor (LCA) analysis. ATLAS is user-friendly, easy install through bioconda maintained as open-source on GitHub, and is implemented in Snakemake for modular customizable workflows.« less

Genome Editing of Structural Variations: Modeling and Gene Correction.

PubMed

Park, Chul-Yong; Sung, Jin Jea; Kim, Dong-Wook

2016-07-01

The analysis of chromosomal structural variations (SVs), such as inversions and translocations, was made possible by the completion of the human genome project and the development of genome-wide sequencing technologies. SVs contribute to genetic diversity and evolution, although some SVs can cause diseases such as hemophilia A in humans. Genome engineering technology using programmable nucleases (e.g., ZFNs, TALENs, and CRISPR/Cas9) has been rapidly developed, enabling precise and efficient genome editing for SV research. Here, we review advances in modeling and gene correction of SVs, focusing on inversion, translocation, and nucleotide repeat expansion. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparative analysis of syntenic genes in grass genomes reveals accelerated rates of gene structure and coding sequence evolution in polyploid wheat

USDA-ARS?s Scientific Manuscript database

Cycles of whole genome duplication (WGD) and diploidization are hallmarks of eukaryotic genome evolution and speciation. Polyploid wheat (Triticum aestivum) has had a massive increase in genome size largely due to recent WGDs. How these processes may impact the dynamics of gene evolution was studied...

Small Traditional Human Communities Sustain Genomic Diversity over Microgeographic Scales despite Linguistic Isolation

PubMed Central

Cox, Murray P.; Hudjashov, Georgi; Sim, Andre; Savina, Olga; Karafet, Tatiana M.; Sudoyo, Herawati; Lansing, J. Stephen

2016-01-01

At least since the Neolithic, humans have largely lived in networks of small, traditional communities. Often socially isolated, these groups evolved distinct languages and cultures over microgeographic scales of just tens of kilometers. Population genetic theory tells us that genetic drift should act quickly in such isolated groups, thus raising the question: do networks of small human communities maintain levels of genetic diversity over microgeographic scales? This question can no longer be asked in most parts of the world, which have been heavily impacted by historical events that make traditional society structures the exception. However, such studies remain possible in parts of Island Southeast Asia and Oceania, where traditional ways of life are still practiced. We captured genome-wide genetic data, together with linguistic records, for a case–study system—eight villages distributed across Sumba, a small, remote island in eastern Indonesia. More than 4,000 years after these communities were established during the Neolithic period, most speak different languages and can be distinguished genetically. Yet their nuclear diversity is not reduced, instead being comparable to other, even much larger, regional groups. Modeling reveals a separation of time scales: while languages and culture can evolve quickly, creating social barriers, sporadic migration averaged over many generations is sufficient to keep villages linked genetically. This loosely-connected network structure, once the global norm and still extant on Sumba today, provides a living proxy to explore fine-scale genome dynamics in the sort of small traditional communities within which the most recent episodes of human evolution occurred. PMID:27274003

Detecting the Population Structure and Scanning for Signatures of Selection in Horses (Equus caballus) From Whole-Genome Sequencing Data

PubMed Central

Zhang, Cheng; Ni, Pan; Ahmad, Hafiz Ishfaq; Gemingguli, M; Baizilaitibei, A; Gulibaheti, D; Fang, Yaping; Wang, Haiyang; Asif, Akhtar Rasool; Xiao, Changyi; Chen, Jianhai; Ma, Yunlong; Liu, Xiangdong; Du, Xiaoyong; Zhao, Shuhong

2018-01-01

Animal domestication gives rise to gradual changes at the genomic level through selection in populations. Selective sweeps have been traced in the genomes of many animal species, including humans, cattle, and dogs. However, little is known regarding positional candidate genes and genomic regions that exhibit signatures of selection in domestic horses. In addition, an understanding of the genetic processes underlying horse domestication, especially the origin of Chinese native populations, is still lacking. In our study, we generated whole genome sequences from 4 Chinese native horses and combined them with 48 publicly available full genome sequences, from which 15 341 213 high-quality unique single-nucleotide polymorphism variants were identified. Kazakh and Lichuan horses are 2 typical Asian native breeds that were formed in Kazakh or Northwest China and South China, respectively. We detected 1390 loss-of-function (LoF) variants in protein-coding genes, and gene ontology (GO) enrichment analysis revealed that some LoF-affected genes were overrepresented in GO terms related to the immune response. Bayesian clustering, distance analysis, and principal component analysis demonstrated that the population structure of these breeds largely reflected weak geographic patterns. Kazakh and Lichuan horses were assigned to the same lineage with other Asian native breeds, in agreement with previous studies on the genetic origin of Chinese domestic horses. We applied the composite likelihood ratio method to scan for genomic regions showing signals of recent selection in the horse genome. A total of 1052 genomic windows of 10 kB, corresponding to 933 distinct core regions, significantly exceeded neutral simulations. The GO enrichment analysis revealed that the genes under selective sweeps were overrepresented with GO terms, including “negative regulation of canonical Wnt signaling pathway,” “muscle contraction,” and “axon guidance.” Frequent exercise training in domestic horses may have resulted in changes in the expression of genes related to metabolism, muscle structure, and the nervous system.

The RAVEN Toolbox and Its Use for Generating a Genome-scale Metabolic Model for Penicillium chrysogenum

PubMed Central

Agren, Rasmus; Liu, Liming; Shoaie, Saeed; Vongsangnak, Wanwipa; Nookaew, Intawat; Nielsen, Jens

2013-01-01

We present the RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox: a software suite that allows for semi-automated reconstruction of genome-scale models. It makes use of published models and/or the KEGG database, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology. The RAVEN Toolbox workflow was applied in order to reconstruct a genome-scale metabolic model for the important microbial cell factory Penicillium chrysogenum Wisconsin54-1255. The model was validated in a bibliomic study of in total 440 references, and it comprises 1471 unique biochemical reactions and 1006 ORFs. It was then used to study the roles of ATP and NADPH in the biosynthesis of penicillin, and to identify potential metabolic engineering targets for maximization of penicillin production. PMID:23555215

Using SQL Databases for Sequence Similarity Searching and Analysis.

PubMed

Pearson, William R; Mackey, Aaron J

2017-09-13

Relational databases can integrate diverse types of information and manage large sets of similarity search results, greatly simplifying genome-scale analyses. By focusing on taxonomic subsets of sequences, relational databases can reduce the size and redundancy of sequence libraries and improve the statistical significance of homologs. In addition, by loading similarity search results into a relational database, it becomes possible to explore and summarize the relationships between all of the proteins in an organism and those in other biological kingdoms. This unit describes how to use relational databases to improve the efficiency of sequence similarity searching and demonstrates various large-scale genomic analyses of homology-related data. It also describes the installation and use of a simple protein sequence database, seqdb_demo, which is used as a basis for the other protocols. The unit also introduces search_demo, a database that stores sequence similarity search results. The search_demo database is then used to explore the evolutionary relationships between E. coli proteins and proteins in other organisms in a large-scale comparative genomic analysis. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

An efficient and scalable analysis framework for variant extraction and refinement from population-scale DNA sequence data.

PubMed

Jun, Goo; Wing, Mary Kate; Abecasis, Gonçalo R; Kang, Hyun Min

2015-06-01

The analysis of next-generation sequencing data is computationally and statistically challenging because of the massive volume of data and imperfect data quality. We present GotCloud, a pipeline for efficiently detecting and genotyping high-quality variants from large-scale sequencing data. GotCloud automates sequence alignment, sample-level quality control, variant calling, filtering of likely artifacts using machine-learning techniques, and genotype refinement using haplotype information. The pipeline can process thousands of samples in parallel and requires less computational resources than current alternatives. Experiments with whole-genome and exome-targeted sequence data generated by the 1000 Genomes Project show that the pipeline provides effective filtering against false positive variants and high power to detect true variants. Our pipeline has already contributed to variant detection and genotyping in several large-scale sequencing projects, including the 1000 Genomes Project and the NHLBI Exome Sequencing Project. We hope it will now prove useful to many medical sequencing studies. © 2015 Jun et al.; Published by Cold Spring Harbor Laboratory Press.

Genomic analysis of regulatory network dynamics reveals large topological changes

NASA Astrophysics Data System (ADS)

Luscombe, Nicholas M.; Madan Babu, M.; Yu, Haiyuan; Snyder, Michael; Teichmann, Sarah A.; Gerstein, Mark

2004-09-01

Network analysis has been applied widely, providing a unifying language to describe disparate systems ranging from social interactions to power grids. It has recently been used in molecular biology, but so far the resulting networks have only been analysed statically. Here we present the dynamics of a biological network on a genomic scale, by integrating transcriptional regulatory information and gene-expression data for multiple conditions in Saccharomyces cerevisiae. We develop an approach for the statistical analysis of network dynamics, called SANDY, combining well-known global topological measures, local motifs and newly derived statistics. We uncover large changes in underlying network architecture that are unexpected given current viewpoints and random simulations. In response to diverse stimuli, transcription factors alter their interactions to varying degrees, thereby rewiring the network. A few transcription factors serve as permanent hubs, but most act transiently only during certain conditions. By studying sub-network structures, we show that environmental responses facilitate fast signal propagation (for example, with short regulatory cascades), whereas the cell cycle and sporulation direct temporal progression through multiple stages (for example, with highly inter-connected transcription factors). Indeed, to drive the latter processes forward, phase-specific transcription factors inter-regulate serially, and ubiquitously active transcription factors layer above them in a two-tiered hierarchy. We anticipate that many of the concepts presented here-particularly the large-scale topological changes and hub transience-will apply to other biological networks, including complex sub-systems in higher eukaryotes.

Flux coupling and transcriptional regulation within the metabolic network of the photosynthetic bacterium Synechocystis sp. PCC6803.

PubMed

Montagud, Arnau; Zelezniak, Aleksej; Navarro, Emilio; de Córdoba, Pedro Fernández; Urchueguía, Javier F; Patil, Kiran Raosaheb

2011-03-01

Synechocystis sp. PCC6803 is a model cyanobacterium capable of producing biofuels with CO(2) as carbon source and with its metabolism fueled by light, for which it stands as a potential production platform of socio-economic importance. Compilation and characterization of Synechocystis genome-scale metabolic model is a pre-requisite toward achieving a proficient photosynthetic cell factory. To this end, we report iSyn811, an upgraded genome-scale metabolic model of Synechocystis sp. PCC6803 consisting of 956 reactions and accounting for 811 genes. To gain insights into the interplay between flux activities and metabolic physiology, flux coupling analysis was performed for iSyn811 under four different growth conditions, viz., autotrophy, mixotrophy, heterotrophy, and light-activated heterotrophy (LH). Initial steps of carbon acquisition and catabolism formed the versatile center of the flux coupling networks, surrounded by a stable core of pathways leading to biomass building blocks. This analysis identified potential bottlenecks for hydrogen and ethanol production. Integration of transcriptomic data with the Synechocystis flux coupling networks lead to identification of reporter flux coupling pairs and reporter flux coupling groups - regulatory hot spots during metabolic shifts triggered by the availability of light. Overall, flux coupling analysis provided insight into the structural organization of Synechocystis sp. PCC6803 metabolic network toward designing of a photosynthesis-based production platform. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ancient DNA analysis identifies marine mollusc shells as new metagenomic archives of the past.

PubMed

Der Sarkissian, Clio; Pichereau, Vianney; Dupont, Catherine; Ilsøe, Peter C; Perrigault, Mickael; Butler, Paul; Chauvaud, Laurent; Eiríksson, Jón; Scourse, James; Paillard, Christine; Orlando, Ludovic

2017-09-01

Marine mollusc shells enclose a wealth of information on coastal organisms and their environment. Their life history traits as well as (palaeo-) environmental conditions, including temperature, food availability, salinity and pollution, can be traced through the analysis of their shell (micro-) structure and biogeochemical composition. Adding to this list, the DNA entrapped in shell carbonate biominerals potentially offers a novel and complementary proxy both for reconstructing palaeoenvironments and tracking mollusc evolutionary trajectories. Here, we assess this potential by applying DNA extraction, high-throughput shotgun DNA sequencing and metagenomic analyses to marine mollusc shells spanning the last ~7,000 years. We report successful DNA extraction from shells, including a variety of ancient specimens, and find that DNA recovery is highly dependent on their biomineral structure, carbonate layer preservation and disease state. We demonstrate positive taxonomic identification of mollusc species using a combination of mitochondrial DNA genomes, barcodes, genome-scale data and metagenomic approaches. We also find shell biominerals to contain a diversity of microbial DNA from the marine environment. Finally, we reconstruct genomic sequences of organisms closely related to the Vibrio tapetis bacteria from Manila clam shells previously diagnosed with Brown Ring Disease. Our results reveal marine mollusc shells as novel genetic archives of the past, which opens new perspectives in ancient DNA research, with the potential to reconstruct the evolutionary history of molluscs, microbial communities and pathogens in the face of environmental changes. Other future applications include conservation of endangered mollusc species and aquaculture management. © 2017 John Wiley & Sons Ltd.

Large-Scale Phylogenomics of the Lactobacillus casei Group Highlights Taxonomic Inconsistencies and Reveals Novel Clade-Associated Features

PubMed Central

Wuyts, Sander; Wittouck, Stijn; De Boeck, Ilke; Allonsius, Camille N.; Pasolli, Edoardo

2017-01-01

ABSTRACT Although the genotypic and phenotypic properties of the Lactobacillus casei group have been studied extensively, the taxonomic structure has been the subject of debate for a long time. Here, we performed a large-scale comparative analysis by using 183 publicly available genomes supplemented with a Lactobacillus strain isolated from the human upper respiratory tract. On the basis of this analysis, we identified inconsistencies in the taxonomy and reclassified all of the genomes according to their most closely related type strains. This led to the identification of a catalase-encoding gene in all 10 L. casei sensu stricto strains, making it the first described catalase-positive species in the Lactobacillus genus. Moreover, we found that 6 of 10 L. casei genomes contained a SecA2/SecY2 gene cluster with two putative glycosylated surface adhesin proteins. Altogether, our results highlight current inconsistencies in the taxonomy of the L. casei group and reveal new clade-associated functional features. IMPORTANCE The closely related species of the Lactobacillus casei group are extensively studied because of their applications in food fermentations and as probiotics. Our results show that many strains in this group are incorrectly classified and that reclassifying them to their most closely related species type strain improves the functional predictive power of their taxonomy. In addition, our findings may spark increased interest in the L. casei species. We find that after reclassification, only 10 genomes remain classified as L. casei. These strains show some interesting properties. First, they all appear to be catalase positive. This suggests that they have increased oxidative stress resistance. Second, we isolated an L. casei strain from the human upper respiratory tract and discovered that it and multiple other L. casei strains harbor one or even two large, glycosylated putative surface adhesins. This might inspire further exploration of this species as a potential probiotic organism. PMID:28845461

The Proteome Folding Project: Proteome-scale prediction of structure and function

PubMed Central

Drew, Kevin; Winters, Patrick; Butterfoss, Glenn L.; Berstis, Viktors; Uplinger, Keith; Armstrong, Jonathan; Riffle, Michael; Schweighofer, Erik; Bovermann, Bill; Goodlett, David R.; Davis, Trisha N.; Shasha, Dennis; Malmström, Lars; Bonneau, Richard

2011-01-01

The incompleteness of proteome structure and function annotation is a critical problem for biologists and, in particular, severely limits interpretation of high-throughput and next-generation experiments. We have developed a proteome annotation pipeline based on structure prediction, where function and structure annotations are generated using an integration of sequence comparison, fold recognition, and grid-computing-enabled de novo structure prediction. We predict protein domain boundaries and three-dimensional (3D) structures for protein domains from 94 genomes (including human, Arabidopsis, rice, mouse, fly, yeast, Escherichia coli, and worm). De novo structure predictions were distributed on a grid of more than 1.5 million CPUs worldwide (World Community Grid). We generated significant numbers of new confident fold annotations (9% of domains that are otherwise unannotated in these genomes). We demonstrate that predicted structures can be combined with annotations from the Gene Ontology database to predict new and more specific molecular functions. PMID:21824995

Applications of the 1000 Genomes Project resources

PubMed Central

Zheng-Bradley, Xiangqun

2017-01-01

Abstract The 1000 Genomes Project created a valuable, worldwide reference for human genetic variation. Common uses of the 1000 Genomes dataset include genotype imputation supporting Genome-wide Association Studies, mapping expression Quantitative Trait Loci, filtering non-pathogenic variants from exome, whole genome and cancer genome sequencing projects, and genetic analysis of population structure and molecular evolution. In this article, we will highlight some of the multiple ways that the 1000 Genomes data can be and has been utilized for genetic studies. PMID:27436001

Genomic characterization and phylogenetic analysis of Zika virus circulating in the Americas.

PubMed

Ye, Qing; Liu, Zhong-Yu; Han, Jian-Feng; Jiang, Tao; Li, Xiao-Feng; Qin, Cheng-Feng

2016-09-01

The rapid spread and potential link with birth defects have made Zika virus (ZIKV) a global public health problem. The virus was discovered 70years ago, yet the knowledge about its genomic structure and the genetic variations associated with current ZIKV explosive epidemics remains not fully understood. In this review, the genome organization, especially conserved terminal structures of ZIKV genome were characterized and compared with other mosquito-borne flaviviruses. It is suggested that major viral proteins of ZIKV share high structural and functional similarity with other known flaviviruses as shown by sequence comparison and prediction of functional motifs in viral proteins. Phylogenetic analysis demonstrated that all ZIKV strains circulating in the America form a unique clade within the Asian lineage. Furthermore, we identified a series of conserved amino acid residues that differentiate the Asian strains including the current circulating American strains from the ancient African strains. Overall, our findings provide an overview of ZIKV genome characterization and evolutionary dynamics in the Americas and point out critical clues for future virological and epidemiological studies. Copyright © 2016 Elsevier B.V. All rights reserved.

Selected Insights from Application of Whole Genome Sequencing for Outbreak Investigations

PubMed Central

Le, Vien Thi Minh; Diep, Binh An

2014-01-01

Purpose of review The advent of high-throughput whole genome sequencing has the potential to revolutionize the conduct of outbreak investigation. Because of its ultimate pathogen strain resolution, whole genome sequencing could augment traditional epidemiologic investigations of infectious disease outbreaks. Recent findings The combination of whole genome sequencing and intensive epidemiologic analysis provided new insights on the sources and transmission dynamics of large-scale epidemics caused by Escherichia coli and Vibrio cholerae, nosocomial outbreaks caused by methicillin-resistant Staphylococcus aureus, Klebsiella pneumonia, and Mycobacterium abscessus, community-centered outbreaks caused by Mycobacterium tuberculosis, and natural disaster-associated outbreak caused by environmentally acquired molds. Summary When combined with traditional epidemiologic investigation, whole genome sequencing has proven useful for elucidating sources and transmission dynamics of disease outbreaks. Development of a fully automated bioinformatics pipeline for analysis of whole genome sequence data is much needed to make this powerful tool more widely accessible. PMID:23856896

Self-similarity analysis of eubacteria genome based on weighted graph.

PubMed

Qi, Zhao-Hui; Li, Ling; Zhang, Zhi-Meng; Qi, Xiao-Qin

2011-07-07

We introduce a weighted graph model to investigate the self-similarity characteristics of eubacteria genomes. The regular treating in similarity comparison about genome is to discover the evolution distance among different genomes. Few people focus their attention on the overall statistical characteristics of each gene compared with other genes in the same genome. In our model, each genome is attributed to a weighted graph, whose topology describes the similarity relationship among genes in the same genome. Based on the related weighted graph theory, we extract some quantified statistical variables from the topology, and give the distribution of some variables derived from the largest social structure in the topology. The 23 eubacteria recently studied by Sorimachi and Okayasu are markedly classified into two different groups by their double logarithmic point-plots describing the similarity relationship among genes of the largest social structure in genome. The results show that the proposed model may provide us with some new sights to understand the structures and evolution patterns determined from the complete genomes. Copyright © 2011 Elsevier Ltd. All rights reserved.

Polygamy and an absence of fine-scale structure in Dendroctonus ponderosae (Hopk.) (Coleoptera: Curcilionidae) confirmed using molecular markers

PubMed Central

Janes, J K; Roe, A D; Rice, A V; Gorrell, J C; Coltman, D W; Langor, D W; Sperling, F A H

2016-01-01

An understanding of mating systems and fine-scale spatial genetic structure is required to effectively manage forest pest species such as Dendroctonus ponderosae (mountain pine beetle). Here we used genome-wide single-nucleotide polymorphisms to assess the fine-scale genetic structure and mating system of D. ponderosae collected from a single stand in Alberta, Canada. Fine-scale spatial genetic structure was absent within the stand and the majority of genetic variation was best explained at the individual level. Relatedness estimates support previous reports of pre-emergence mating. Parentage assignment tests indicate that a polygamous mating system better explains the relationships among individuals within a gallery than the previously reported female monogamous/male polygynous system. Furthermore, there is some evidence to suggest that females may exploit the galleries of other females, at least under epidemic conditions. Our results suggest that current management models are likely to be effective across large geographic areas based on the absence of fine-scale genetic structure. PMID:26286666

Population Structure and Antimicrobial Resistance Profiles of Streptococcus suis Serotype 2 Sequence Type 25 Strains.

PubMed

Athey, Taryn B T; Teatero, Sarah; Takamatsu, Daisuke; Wasserscheid, Jessica; Dewar, Ken; Gottschalk, Marcelo; Fittipaldi, Nahuel

2016-01-01

Strains of serotype 2 Streptococcus suis are responsible for swine and human infections. Different serotype 2 genetic backgrounds have been defined using multilocus sequence typing (MLST). However, little is known about the genetic diversity within each MLST sequence type (ST). Here, we used whole-genome sequencing to test the hypothesis that S. suis serotype 2 strains of the ST25 lineage are genetically heterogeneous. We evaluated 51 serotype 2 ST25 S. suis strains isolated from diseased pigs and humans in Canada, the United States of America, and Thailand. Whole-genome sequencing revealed numerous large-scale rearrangements in the ST25 genome, compared to the genomes of ST1 and ST28 S. suis strains, which result, among other changes, in disruption of a pilus island locus. We report that recombination and lateral gene transfer contribute to ST25 genetic diversity. Phylogenetic analysis identified two main and distinct Thai and North American clades grouping most strains investigated. These clades also possessed distinct patterns of antimicrobial resistance genes, which correlated with acquisition of different integrative and conjugative elements (ICEs). Some of these ICEs were found to be integrated at a recombination hot spot, previously identified as the site of integration of the 89K pathogenicity island in serotype 2 ST7 S. suis strains. Our results highlight the limitations of MLST for phylogenetic analysis of S. suis, and the importance of lateral gene transfer and recombination as drivers of diversity in this swine pathogen and zoonotic agent.

Population Structure and Antimicrobial Resistance Profiles of Streptococcus suis Serotype 2 Sequence Type 25 Strains

PubMed Central

Athey, Taryn B. T.; Teatero, Sarah; Takamatsu, Daisuke; Wasserscheid, Jessica; Dewar, Ken; Gottschalk, Marcelo; Fittipaldi, Nahuel

2016-01-01

Strains of serotype 2 Streptococcus suis are responsible for swine and human infections. Different serotype 2 genetic backgrounds have been defined using multilocus sequence typing (MLST). However, little is known about the genetic diversity within each MLST sequence type (ST). Here, we used whole-genome sequencing to test the hypothesis that S. suis serotype 2 strains of the ST25 lineage are genetically heterogeneous. We evaluated 51 serotype 2 ST25 S. suis strains isolated from diseased pigs and humans in Canada, the United States of America, and Thailand. Whole-genome sequencing revealed numerous large-scale rearrangements in the ST25 genome, compared to the genomes of ST1 and ST28 S. suis strains, which result, among other changes, in disruption of a pilus island locus. We report that recombination and lateral gene transfer contribute to ST25 genetic diversity. Phylogenetic analysis identified two main and distinct Thai and North American clades grouping most strains investigated. These clades also possessed distinct patterns of antimicrobial resistance genes, which correlated with acquisition of different integrative and conjugative elements (ICEs). Some of these ICEs were found to be integrated at a recombination hot spot, previously identified as the site of integration of the 89K pathogenicity island in serotype 2 ST7 S. suis strains. Our results highlight the limitations of MLST for phylogenetic analysis of S. suis, and the importance of lateral gene transfer and recombination as drivers of diversity in this swine pathogen and zoonotic agent. PMID:26954687

DNA Data Visualization (DDV): Software for Generating Web-Based Interfaces Supporting Navigation and Analysis of DNA Sequence Data of Entire Genomes.

PubMed

Neugebauer, Tomasz; Bordeleau, Eric; Burrus, Vincent; Brzezinski, Ryszard

2015-01-01

Data visualization methods are necessary during the exploration and analysis activities of an increasingly data-intensive scientific process. There are few existing visualization methods for raw nucleotide sequences of a whole genome or chromosome. Software for data visualization should allow the researchers to create accessible data visualization interfaces that can be exported and shared with others on the web. Herein, novel software developed for generating DNA data visualization interfaces is described. The software converts DNA data sets into images that are further processed as multi-scale images to be accessed through a web-based interface that supports zooming, panning and sequence fragment selection. Nucleotide composition frequencies and GC skew of a selected sequence segment can be obtained through the interface. The software was used to generate DNA data visualization of human and bacterial chromosomes. Examples of visually detectable features such as short and long direct repeats, long terminal repeats, mobile genetic elements, heterochromatic segments in microbial and human chromosomes, are presented. The software and its source code are available for download and further development. The visualization interfaces generated with the software allow for the immediate identification and observation of several types of sequence patterns in genomes of various sizes and origins. The visualization interfaces generated with the software are readily accessible through a web browser. This software is a useful research and teaching tool for genetics and structural genomics.

StructRNAfinder: an automated pipeline and web server for RNA families prediction.

PubMed

Arias-Carrasco, Raúl; Vásquez-Morán, Yessenia; Nakaya, Helder I; Maracaja-Coutinho, Vinicius

2018-02-17

The function of many noncoding RNAs (ncRNAs) depend upon their secondary structures. Over the last decades, several methodologies have been developed to predict such structures or to use them to functionally annotate RNAs into RNA families. However, to fully perform this analysis, researchers should utilize multiple tools, which require the constant parsing and processing of several intermediate files. This makes the large-scale prediction and annotation of RNAs a daunting task even to researchers with good computational or bioinformatics skills. We present an automated pipeline named StructRNAfinder that predicts and annotates RNA families in transcript or genome sequences. This single tool not only displays the sequence/structural consensus alignments for each RNA family, according to Rfam database but also provides a taxonomic overview for each assigned functional RNA. Moreover, we implemented a user-friendly web service that allows researchers to upload their own nucleotide sequences in order to perform the whole analysis. Finally, we provided a stand-alone version of StructRNAfinder to be used in large-scale projects. The tool was developed under GNU General Public License (GPLv3) and is freely available at http://structrnafinder.integrativebioinformatics.me . The main advantage of StructRNAfinder relies on the large-scale processing and integrating the data obtained by each tool and database employed along the workflow, of which several files are generated and displayed in user-friendly reports, useful for downstream analyses and data exploration.

Informational laws of genome structures

PubMed Central

Bonnici, Vincenzo; Manca, Vincenzo

2016-01-01

In recent years, the analysis of genomes by means of strings of length k occurring in the genomes, called k-mers, has provided important insights into the basic mechanisms and design principles of genome structures. In the present study, we focus on the proper choice of the value of k for applying information theoretic concepts that express intrinsic aspects of genomes. The value k = lg2(n), where n is the genome length, is determined to be the best choice in the definition of some genomic informational indexes that are studied and computed for seventy genomes. These indexes, which are based on information entropies and on suitable comparisons with random genomes, suggest five informational laws, to which all of the considered genomes obey. Moreover, an informational genome complexity measure is proposed, which is a generalized logistic map that balances entropic and anti-entropic components of genomes and is related to their evolutionary dynamics. Finally, applications to computational synthetic biology are briefly outlined. PMID:27354155

Informational laws of genome structures

NASA Astrophysics Data System (ADS)

Bonnici, Vincenzo; Manca, Vincenzo

2016-06-01

In recent years, the analysis of genomes by means of strings of length k occurring in the genomes, called k-mers, has provided important insights into the basic mechanisms and design principles of genome structures. In the present study, we focus on the proper choice of the value of k for applying information theoretic concepts that express intrinsic aspects of genomes. The value k = lg2(n), where n is the genome length, is determined to be the best choice in the definition of some genomic informational indexes that are studied and computed for seventy genomes. These indexes, which are based on information entropies and on suitable comparisons with random genomes, suggest five informational laws, to which all of the considered genomes obey. Moreover, an informational genome complexity measure is proposed, which is a generalized logistic map that balances entropic and anti-entropic components of genomes and is related to their evolutionary dynamics. Finally, applications to computational synthetic biology are briefly outlined.

A genome-scale metabolic reconstruction of Pseudomonas putida KT2440: iJN746 as a cell factory.

PubMed

Nogales, Juan; Palsson, Bernhard Ø; Thiele, Ines

2008-09-16

Pseudomonas putida is the best studied pollutant degradative bacteria and is harnessed by industrial biotechnology to synthesize fine chemicals. Since the publication of P. putida KT2440's genome, some in silico analyses of its metabolic and biotechnology capacities have been published. However, global understanding of the capabilities of P. putida KT2440 requires the construction of a metabolic model that enables the integration of classical experimental data along with genomic and high-throughput data. The constraint-based reconstruction and analysis (COBRA) approach has been successfully used to build and analyze in silico genome-scale metabolic reconstructions. We present a genome-scale reconstruction of P. putida KT2440's metabolism, iJN746, which was constructed based on genomic, biochemical, and physiological information. This manually-curated reconstruction accounts for 746 genes, 950 reactions, and 911 metabolites. iJN746 captures biotechnologically relevant pathways, including polyhydroxyalkanoate synthesis and catabolic pathways of aromatic compounds (e.g., toluene, benzoate, phenylacetate, nicotinate), not described in other metabolic reconstructions or biochemical databases. The predictive potential of iJN746 was validated using experimental data including growth performance and gene deletion studies. Furthermore, in silico growth on toluene was found to be oxygen-limited, suggesting the existence of oxygen-efficient pathways not yet annotated in P. putida's genome. Moreover, we evaluated the production efficiency of polyhydroxyalkanoates from various carbon sources and found fatty acids as the most prominent candidates, as expected. Here we presented the first genome-scale reconstruction of P. putida, a biotechnologically interesting all-surrounder. Taken together, this work illustrates the utility of iJN746 as i) a knowledge-base, ii) a discovery tool, and iii) an engineering platform to explore P. putida's potential in bioremediation and bioplastic production.

Delta: a new web-based 3D genome visualization and analysis platform.

PubMed

Tang, Bixia; Li, Feifei; Li, Jing; Zhao, Wenming; Zhang, Zhihua

2018-04-15

Delta is an integrative visualization and analysis platform to facilitate visually annotating and exploring the 3D physical architecture of genomes. Delta takes Hi-C or ChIA-PET contact matrix as input and predicts the topologically associating domains and chromatin loops in the genome. It then generates a physical 3D model which represents the plausible consensus 3D structure of the genome. Delta features a highly interactive visualization tool which enhances the integration of genome topology/physical structure with extensive genome annotation by juxtaposing the 3D model with diverse genomic assay outputs. Finally, by visually comparing the 3D model of the β-globin gene locus and its annotation, we speculated a plausible transitory interaction pattern in the locus. Experimental evidence was found to support this speculation by literature survey. This served as an example of intuitive hypothesis testing with the help of Delta. Delta is freely accessible from http://delta.big.ac.cn, and the source code is available at https://github.com/zhangzhwlab/delta. zhangzhihua@big.ac.cn. Supplementary data are available at Bioinformatics online.

Ancestry estimation and control of population stratification for sequence-based association studies.

PubMed

Wang, Chaolong; Zhan, Xiaowei; Bragg-Gresham, Jennifer; Kang, Hyun Min; Stambolian, Dwight; Chew, Emily Y; Branham, Kari E; Heckenlively, John; Fulton, Robert; Wilson, Richard K; Mardis, Elaine R; Lin, Xihong; Swaroop, Anand; Zöllner, Sebastian; Abecasis, Gonçalo R

2014-04-01

Estimating individual ancestry is important in genetic association studies where population structure leads to false positive signals, although assigning ancestry remains challenging with targeted sequence data. We propose a new method for the accurate estimation of individual genetic ancestry, based on direct analysis of off-target sequence reads, and implement our method in the publicly available LASER software. We validate the method using simulated and empirical data and show that the method can accurately infer worldwide continental ancestry when used with sequencing data sets with whole-genome shotgun coverage as low as 0.001×. For estimates of fine-scale ancestry within Europe, the method performs well with coverage of 0.1×. On an even finer scale, the method improves discrimination between exome-sequenced study participants originating from different provinces within Finland. Finally, we show that our method can be used to improve case-control matching in genetic association studies and to reduce the risk of spurious findings due to population structure.

A multi-scale analysis of bull sperm methylome revealed both species peculiarities and conserved tissue-specific features.

PubMed

Perrier, Jean-Philippe; Sellem, Eli; Prézelin, Audrey; Gasselin, Maxime; Jouneau, Luc; Piumi, François; Al Adhami, Hala; Weber, Michaël; Fritz, Sébastien; Boichard, Didier; Le Danvic, Chrystelle; Schibler, Laurent; Jammes, Hélène; Kiefer, Hélène

2018-05-29

Spermatozoa have a remarkable epigenome in line with their degree of specialization, their unique nature and different requirements for successful fertilization. Accordingly, perturbations in the establishment of DNA methylation patterns during male germ cell differentiation have been associated with infertility in several species. While bull semen is widely used in artificial insemination, the literature describing DNA methylation in bull spermatozoa is still scarce. The purpose of this study was therefore to characterize the bull sperm methylome relative to both bovine somatic cells and the sperm of other mammals through a multiscale analysis. The quantification of DNA methylation at CCGG sites using luminometric methylation assay (LUMA) highlighted the undermethylation of bull sperm compared to the sperm of rams, stallions, mice, goats and men. Total blood cells displayed a similarly high level of methylation in bulls and rams, suggesting that undermethylation of the bovine genome was specific to sperm. Annotation of CCGG sites in different species revealed no striking bias in the distribution of genome features targeted by LUMA that could explain undermethylation of bull sperm. To map DNA methylation at a genome-wide scale, bull sperm was compared with bovine liver, fibroblasts and monocytes using reduced representation bisulfite sequencing (RRBS) and immunoprecipitation of methylated DNA followed by microarray hybridization (MeDIP-chip). These two methods exhibited differences in terms of genome coverage, and consistently, two independent sets of sequences differentially methylated in sperm and somatic cells were identified for RRBS and MeDIP-chip. Remarkably, in the two sets most of the differentially methylated sequences were hypomethylated in sperm. In agreement with previous studies in other species, the sequences that were specifically hypomethylated in bull sperm targeted processes relevant to the germline differentiation program (piRNA metabolism, meiosis, spermatogenesis) and sperm functions (cell adhesion, fertilization), as well as satellites and rDNA repeats. These results highlight the undermethylation of bull spermatozoa when compared with both bovine somatic cells and the sperm of other mammals, and raise questions regarding the dynamics of DNA methylation in bovine male germline. Whether sperm undermethylation has potential interactions with structural variation in the cattle genome may deserve further attention.

Fundamental differences in diversity and genomic population structure between Atlantic and Pacific Prochlorococcus.

PubMed

Kashtan, Nadav; Roggensack, Sara E; Berta-Thompson, Jessie W; Grinberg, Maor; Stepanauskas, Ramunas; Chisholm, Sallie W

2017-09-01

The Atlantic and Pacific Oceans represent different biogeochemical regimes in which the abundant marine cyanobacterium Prochlorococcus thrives. We have shown that Prochlorococcus populations in the Atlantic are composed of hundreds of genomically, and likely ecologically, distinct coexisting subpopulations with distinct genomic backbones. Here we ask if differences in the ecology and selection pressures between the Atlantic and Pacific are reflected in the diversity and genomic composition of their indigenous Prochlorococcus populations. We applied large-scale single-cell genomics and compared the cell-by-cell genomic composition of wild populations of co-occurring cells from samples from Station ALOHA off Hawaii, and from Bermuda Atlantic Time Series Station off Bermuda. We reveal fundamental differences in diversity and genomic structure of populations between the sites. The Pacific populations are more diverse than those in the Atlantic, composed of significantly more coexisting subpopulations and lacking dominant subpopulations. Prochlorococcus from the two sites seem to be composed of mostly non-overlapping distinct sets of subpopulations with different genomic backbones-likely reflecting different sets of ocean-specific micro-niches. Furthermore, phylogenetically closely related strains carry ocean-associated nutrient acquisition genes likely reflecting differences in major selection pressures between the oceans. This differential selection, along with geographic separation, clearly has a significant role in shaping these populations.

A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress

USDA-ARS?s Scientific Manuscript database

Functional annotations of large plant genome projects mostly provide information on gene function and gene families based on the presence of protein domains and gene homology, but not necessarily in association with gene expression or metabolic and regulatory networks. These additional annotations a...

Construction of a large collection of small genome variations in French dairy and beef breeds using whole-genome sequences.

PubMed

Boussaha, Mekki; Michot, Pauline; Letaief, Rabia; Hozé, Chris; Fritz, Sébastien; Grohs, Cécile; Esquerré, Diane; Duchesne, Amandine; Philippe, Romain; Blanquet, Véronique; Phocas, Florence; Floriot, Sandrine; Rocha, Dominique; Klopp, Christophe; Capitan, Aurélien; Boichard, Didier

2016-11-15

In recent years, several bovine genome sequencing projects were carried out with the aim of developing genomic tools to improve dairy and beef production efficiency and sustainability. In this study, we describe the first French cattle genome variation dataset obtained by sequencing 274 whole genomes representing several major dairy and beef breeds. This dataset contains over 28 million single nucleotide polymorphisms (SNPs) and small insertions and deletions. Comparisons between sequencing results and SNP array genotypes revealed a very high genotype concordance rate, which indicates the good quality of our data. To our knowledge, this is the first large-scale catalog of small genomic variations in French dairy and beef cattle. This resource will contribute to the study of gene functions and population structure and also help to improve traits through genotype-guided selection.

GIANT 2.0: genome-scale integrated analysis of gene networks in tissues.

PubMed

Wong, Aaron K; Krishnan, Arjun; Troyanskaya, Olga G

2018-05-25

GIANT2 (Genome-wide Integrated Analysis of gene Networks in Tissues) is an interactive web server that enables biomedical researchers to analyze their proteins and pathways of interest and generate hypotheses in the context of genome-scale functional maps of human tissues. The precise actions of genes are frequently dependent on their tissue context, yet direct assay of tissue-specific protein function and interactions remains infeasible in many normal human tissues and cell-types. With GIANT2, researchers can explore predicted tissue-specific functional roles of genes and reveal changes in those roles across tissues, all through interactive multi-network visualizations and analyses. Additionally, the NetWAS approach available through the server uses tissue-specific/cell-type networks predicted by GIANT2 to re-prioritize statistical associations from GWAS studies and identify disease-associated genes. GIANT2 predicts tissue-specific interactions by integrating diverse functional genomics data from now over 61 400 experiments for 283 diverse tissues and cell-types. GIANT2 does not require any registration or installation and is freely available for use at http://giant-v2.princeton.edu.

Chloroplast genomes of Arabidopsis halleri ssp. gemmifera and Arabidopsis lyrata ssp. petraea: Structures and comparative analysis.

PubMed

Asaf, Sajjad; Khan, Abdul Latif; Khan, Muhammad Aaqil; Waqas, Muhammad; Kang, Sang-Mo; Yun, Byung-Wook; Lee, In-Jung

2017-08-08

We investigated the complete chloroplast (cp) genomes of non-model Arabidopsis halleri ssp. gemmifera and Arabidopsis lyrata ssp. petraea using Illumina paired-end sequencing to understand their genetic organization and structure. Detailed bioinformatics analysis revealed genome sizes of both subspecies ranging between 154.4~154.5 kbp, with a large single-copy region (84,197~84,158 bp), a small single-copy region (17,738~17,813 bp) and pair of inverted repeats (IRa/IRb; 26,264~26,259 bp). Both cp genomes encode 130 genes, including 85 protein-coding genes, eight ribosomal RNA genes and 37 transfer RNA genes. Whole cp genome comparison of A. halleri ssp. gemmifera and A. lyrata ssp. petraea, along with ten other Arabidopsis species, showed an overall high degree of sequence similarity, with divergence among some intergenic spacers. The location and distribution of repeat sequences were determined, and sequence divergences of shared genes were calculated among related species. Comparative phylogenetic analysis of the entire genomic data set and 70 shared genes between both cp genomes confirmed the previous phylogeny and generated phylogenetic trees with the same topologies. The sister species of A. halleri ssp. gemmifera is A. umezawana, whereas the closest relative of A. lyrata spp. petraea is A. arenicola.

Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network

PubMed Central

2011-01-01

Background Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. Results We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism’s metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. Conclusions After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis. PMID:22784571

Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network.

PubMed

Kim, Hyun Uk; Kim, Tae Yong; Lee, Sang Yup

2011-01-01

Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism's metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

How gene order is influenced by the biophysics of transcription regulation

PubMed Central

Kolesov, Grigory; Wunderlich, Zeba; Laikova, Olga N.; Gelfand, Mikhail S.; Mirny, Leonid A.

2007-01-01

What are the forces that shape the structure of prokaryotic genomes: the order of genes, their proximity, and their orientation? Coregulation and coordinated horizontal gene transfer are believed to promote the proximity of functionally related genes and the formation of operons. However, forces that influence the structure of the genome beyond the level of a single operon remain unknown. Here, we show that the biophysical mechanism by which regulatory proteins search for their sites on DNA can impose constraints on genome structure. Using simulations, we demonstrate that rapid and reliable gene regulation requires that the transcription factor (TF) gene be close to the site on DNA the TF has to bind, thus promoting the colocalization of TF genes and their targets on the genome. We use parameters that have been measured in recent experiments to estimate the relevant length and times scales of this process and demonstrate that the search for a cognate site may be prohibitively slow if a TF has a low copy number and is not colocalized. We also analyze TFs and their sites in a number of bacterial genomes, confirm that they are colocalized significantly more often than expected, and show that this observation cannot be attributed to the pressure for coregulation or formation of selfish gene clusters, thus supporting the role of the biophysical constraint in shaping the structure of prokaryotic genomes. Our results demonstrate how spatial organization can influence timing and noise in gene expression. PMID:17709750

Genomic paradigms for food-borne enteric pathogen analysis at the USFDA: case studies highlighting method utility, integration and resolution.

PubMed

Elkins, C A; Kotewicz, M L; Jackson, S A; Lacher, D W; Abu-Ali, G S; Patel, I R

2013-01-01

Modern risk control and food safety practices involving food-borne bacterial pathogens are benefiting from new genomic technologies for rapid, yet highly specific, strain characterisations. Within the United States Food and Drug Administration (USFDA) Center for Food Safety and Applied Nutrition (CFSAN), optical genome mapping and DNA microarray genotyping have been used for several years to quickly assess genomic architecture and gene content, respectively, for outbreak strain subtyping and to enhance retrospective trace-back analyses. The application and relative utility of each method varies with outbreak scenario and the suspect pathogen, with comparative analytical power enhanced by database scale and depth. Integration of these two technologies allows high-resolution scrutiny of the genomic landscapes of enteric food-borne pathogens with notable examples including Shiga toxin-producing Escherichia coli (STEC) and Salmonella enterica serovars from a variety of food commodities. Moreover, the recent application of whole genome sequencing technologies to food-borne pathogen outbreaks and surveillance has enhanced resolution to the single nucleotide scale. This new wealth of sequence data will support more refined next-generation custom microarray designs, targeted re-sequencing and "genomic signature recognition" approaches involving a combination of genes and single nucleotide polymorphism detection to distil strain-specific fingerprinting to a minimised scale. This paper examines the utility of microarrays and optical mapping in analysing outbreaks, reviews best practices and the limits of these technologies for pathogen differentiation, and it considers future integration with whole genome sequencing efforts.

Damming the genomic data flood using a comprehensive analysis and storage data structure

PubMed Central

Bouffard, Marc; Phillips, Michael S.; Brown, Andrew M.K.; Marsh, Sharon; Tardif, Jean-Claude; van Rooij, Tibor

2010-01-01

Data generation, driven by rapid advances in genomic technologies, is fast outpacing our analysis capabilities. Faced with this flood of data, more hardware and software resources are added to accommodate data sets whose structure has not specifically been designed for analysis. This leads to unnecessarily lengthy processing times and excessive data handling and storage costs. Current efforts to address this have centered on developing new indexing schemas and analysis algorithms, whereas the root of the problem lies in the format of the data itself. We have developed a new data structure for storing and analyzing genotype and phenotype data. By leveraging data normalization techniques, database management system capabilities and the use of a novel multi-table, multidimensional database structure we have eliminated the following: (i) unnecessarily large data set size due to high levels of redundancy, (ii) sequential access to these data sets and (iii) common bottlenecks in analysis times. The resulting novel data structure horizontally divides the data to circumvent traditional problems associated with the use of databases for very large genomic data sets. The resulting data set required 86% less disk space and performed analytical calculations 6248 times faster compared to a standard approach without any loss of information. Database URL: http://castor.pharmacogenomics.ca PMID:21159730

The Arab genome: Health and wealth.

PubMed

Zayed, Hatem

2016-11-05

The 22 Arab nations have a unique genetic structure, which reflects both conserved and diverse gene pools due to the prevalent endogamous and consanguineous marriage culture and the long history of admixture among different ethnic subcultures descended from the Asian, European, and African continents. Human genome sequencing has enabled large-scale genomic studies of different populations and has become a powerful tool for studying disease predictions and diagnosis. Despite the importance of the Arab genome for better understanding the dynamics of the human genome, discovering rare genetic variations, and studying early human migration out of Africa, it is poorly represented in human genome databases, such as HapMap and the 1000 Genomes Project. In this review, I demonstrate the significance of sequencing the Arab genome and setting an Arab genome reference(s) for better understanding the molecular pathogenesis of genetic diseases, discovering novel/rare variants, and identifying a meaningful genotype-phenotype correlation for complex diseases. Copyright © 2016. Published by Elsevier B.V.

First genome sequences of Achromobacter phages reveal new members of the N4 family.

PubMed

Wittmann, Johannes; Dreiseikelmann, Brigitte; Rohde, Manfred; Meier-Kolthoff, Jan P; Bunk, Boyke; Rohde, Christine

2014-01-27

Multi-resistant Achromobacter xylosoxidans has been recognized as an emerging pathogen causing nosocomially acquired infections during the last years. Phages as natural opponents could be an alternative to fight such infections. Bacteriophages against this opportunistic pathogen were isolated in a recent study. This study shows a molecular analysis of two podoviruses and reveals first insights into the genomic structure of Achromobacter phages so far. Growth curve experiments and adsorption kinetics were performed for both phages. Adsorption and propagation in cells were visualized by electron microscopy. Both phage genomes were sequenced with the PacBio RS II system based on single molecule, real-time (SMRT) technology and annotated with several bioinformatic tools. To further elucidate the evolutionary relationships between the phage genomes, a phylogenomic analysis was conducted using the genome Blast Distance Phylogeny approach (GBDP). In this study, we present the first detailed analysis of genome sequences of two Achromobacter phages so far. Phages JWAlpha and JWDelta were isolated from two different waste water treatment plants in Germany. Both phages belong to the Podoviridae and contain linear, double-stranded DNA with a length of 72329 bp and 73659 bp, respectively. 92 and 89 putative open reading frames were identified for JWAlpha and JWDelta, respectively, by bioinformatic analysis with several tools. The genomes have nearly the same organization and could be divided into different clusters for transcription, replication, host interaction, head and tail structure and lysis. Detailed annotation via protein comparisons with BLASTP revealed strong similarities to N4-like phages. Analysis of the genomes of Achromobacter phages JWAlpha and JWDelta and comparisons of different gene clusters with other phages revealed that they might be strongly related to other N4-like phages, especially of the Escherichia group. Although all these phages show a highly conserved genomic structure and partially strong similarities at the amino acid level, some differences could be identified. Those differences, e.g. the existence of specific genes for replication or host interaction in some N4-like phages, seem to be interesting targets for further examination of function and specific mechanisms, which might enlighten the mechanism of phage establishment in the host cell after infection.

The complete mitochondrial genome of the armored catfish, Hypostomus plecostomus (Siluriformes: Loricariidae).

PubMed

Liu, Shikai; Zhang, Jiaren; Yao, Jun; Liu, Zhanjiang

2016-05-01

The complete mitochondrial genome of the armored catfish, Hypostomus plecostomus, was determined by next generation sequencing of genomic DNA without prior sample processing or primer design. Bioinformatics analysis resulted in the entire mitochondrial genome sequence with length of 16,523 bp. The H. plecostomus mitochondrial genome is consisted of 13 protein-coding genes, 22 tRNA genes, 2 rRNA genes, and 1 control region, showing typical circular molecule structure of mitochondrial genome as in other vertebrates. The whole genome base composition was estimated to be 31.8% A, 27.0% T, 14.6% G, and 26.6% C, with A/T bias of 58.8%. This work provided the H. plecostomus mitochondrial genome sequence which should be valuable for species identification, phylogenetic analysis and conservation genetics studies in catfishes.

Analysis of whole genome sequences of 16 strains of rubella virus from the United States, 1961-2009.

PubMed

Abernathy, Emily; Chen, Min-hsin; Bera, Jayati; Shrivastava, Susmita; Kirkness, Ewen; Zheng, Qi; Bellini, William; Icenogle, Joseph

2013-01-25

Rubella virus is the causative agent of rubella, a mild rash illness, and a potent teratogenic agent when contracted by a pregnant woman. Global rubella control programs target the reduction and elimination of congenital rubella syndrome. Phylogenetic analysis of partial sequences of rubella viruses has contributed to virus surveillance efforts and played an important role in demonstrating that indigenous rubella viruses have been eliminated in the United States. Sixteen wild-type rubella viruses were chosen for whole genome sequencing. All 16 viruses were collected in the United States from 1961 to 2009 and are from 8 of the 13 known rubella genotypes. Phylogenetic analysis of 30 whole genome sequences produced a maximum likelihood tree giving high bootstrap values for all genotypes except provisional genotype 1a. Comparison of the 16 new complete sequences and 14 previously sequenced wild-type viruses found regions with clusters of variable amino acids. The 5' 250 nucleotides of the genome are more conserved than any other part of the genome. Genotype specific deletions in the untranslated region between the non-structural and structural open reading frames were observed for genotypes 2B and genotype 1G. No evidence was seen for recombination events among the 30 viruses. The analysis presented here is consistent with previous reports on the genetic characterization of rubella virus genomes. Conserved and variable regions were identified and additional evidence for genotype specific nucleotide deletions in the intergenic region was found. Phylogenetic analysis confirmed genotype groupings originally based on structural protein coding region sequences, which provides support for the WHO nomenclature for genetic characterization of wild-type rubella viruses.

A fast boosting-based screening method for large-scale association study in complex traits with genetic heterogeneity.

PubMed

Wang, Lu-Yong; Fasulo, D

2006-01-01

Genome-wide association study for complex diseases will generate massive amount of single nucleotide polymorphisms (SNPs) data. Univariate statistical test (i.e. Fisher exact test) was used to single out non-associated SNPs. However, the disease-susceptible SNPs may have little marginal effects in population and are unlikely to retain after the univariate tests. Also, model-based methods are impractical for large-scale dataset. Moreover, genetic heterogeneity makes the traditional methods harder to identify the genetic causes of diseases. A more recent random forest method provides a more robust method for screening the SNPs in thousands scale. However, for more large-scale data, i.e., Affymetrix Human Mapping 100K GeneChip data, a faster screening method is required to screening SNPs in whole-genome large scale association analysis with genetic heterogeneity. We propose a boosting-based method for rapid screening in large-scale analysis of complex traits in the presence of genetic heterogeneity. It provides a relatively fast and fairly good tool for screening and limiting the candidate SNPs for further more complex computational modeling task.

Moving image analysis to the cloud: A case study with a genome-scale tomographic study

NASA Astrophysics Data System (ADS)

Mader, Kevin; Stampanoni, Marco

2016-01-01

Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures.

A dictionary based informational genome analysis

PubMed Central

2012-01-01

Background In the post-genomic era several methods of computational genomics are emerging to understand how the whole information is structured within genomes. Literature of last five years accounts for several alignment-free methods, arisen as alternative metrics for dissimilarity of biological sequences. Among the others, recent approaches are based on empirical frequencies of DNA k-mers in whole genomes. Results Any set of words (factors) occurring in a genome provides a genomic dictionary. About sixty genomes were analyzed by means of informational indexes based on genomic dictionaries, where a systemic view replaces a local sequence analysis. A software prototype applying a methodology here outlined carried out some computations on genomic data. We computed informational indexes, built the genomic dictionaries with different sizes, along with frequency distributions. The software performed three main tasks: computation of informational indexes, storage of these in a database, index analysis and visualization. The validation was done by investigating genomes of various organisms. A systematic analysis of genomic repeats of several lengths, which is of vivid interest in biology (for example to compute excessively represented functional sequences, such as promoters), was discussed, and suggested a method to define synthetic genetic networks. Conclusions We introduced a methodology based on dictionaries, and an efficient motif-finding software application for comparative genomics. This approach could be extended along many investigation lines, namely exported in other contexts of computational genomics, as a basis for discrimination of genomic pathologies. PMID:22985068

De Novo Protein Structure Prediction

NASA Astrophysics Data System (ADS)

Hung, Ling-Hong; Ngan, Shing-Chung; Samudrala, Ram

An unparalleled amount of sequence data is being made available from large-scale genome sequencing efforts. The data provide a shortcut to the determination of the function of a gene of interest, as long as there is an existing sequenced gene with similar sequence and of known function. This has spurred structural genomic initiatives with the goal of determining as many protein folds as possible (Brenner and Levitt, 2000; Burley, 2000; Brenner, 2001; Heinemann et al., 2001). The purpose of this is twofold: First, the structure of a gene product can often lead to direct inference of its function. Second, since the function of a protein is dependent on its structure, direct comparison of the structures of gene products can be more sensitive than the comparison of sequences of genes for detecting homology. Presently, structural determination by crystallography and NMR techniques is still slow and expensive in terms of manpower and resources, despite attempts to automate the processes. Computer structure prediction algorithms, while not providing the accuracy of the traditional techniques, are extremely quick and inexpensive and can provide useful low-resolution data for structure comparisons (Bonneau and Baker, 2001). Given the immense number of structures which the structural genomic projects are attempting to solve, there would be a considerable gain even if the computer structure prediction approach were applicable to a subset of proteins.

Genome structure of bacillus cereus tsu1 and genes involved in cellulose degradation and poly-3-hydroxybutyrate synthesis

USDA-ARS?s Scientific Manuscript database

In previous work, we reported on the isolation and genome sequence analysis of Bacillus cereus strain tsu1 NCBI accession number JPYN00000000. The 36 scaffolds in the assembled tsu1 genome were all aligned with B. cereus B4264 genome with variations. Genes encoding for xylanase and cellulase and the...

Population genomic analysis suggests strong influence of river network on spatial distribution of genetic variation in invasive saltcedar across the southwestern United States

USGS Publications Warehouse

Lee, Soo-Rang; Jo, Yeong-Seok; Park, Chan-Ho; Friedman, Jonathan M.; Olson, Matthew S.

2018-01-01

Understanding the complex influences of landscape and anthropogenic elements that shape the population genetic structure of invasive species provides insight into patterns of colonization and spread. The application of landscape genomics techniques to these questions may offer detailed, previously undocumented insights into factors influencing species invasions. We investigated the spatial pattern of genetic variation and the influences of landscape factors on population similarity in an invasive riparian shrub, saltcedar (Tamarix L.) by analysing 1,997 genomewide SNP markers for 259 individuals from 25 populations collected throughout the southwestern United States. Our results revealed a broad-scale spatial genetic differentiation of saltcedar populations between the Colorado and Rio Grande river basins and identified potential barriers to population similarity along both river systems. River pathways most strongly contributed to population similarity. In contrast, low temperature and dams likely served as barriers to population similarity. We hypothesize that large-scale geographic patterns in genetic diversity resulted from a combination of early introductions from distinct populations, the subsequent influence of natural selection, dispersal barriers and founder effects during range expansion.

Refined genetic maps reveal sexual dimorphism in human meiotic recombination at multiple scales

NASA Astrophysics Data System (ADS)

Bhérer, Claude; Campbell, Christopher L.; Auton, Adam

2017-04-01

In humans, males have lower recombination rates than females over the majority of the genome, but the opposite is usually true near the telomeres. These broad-scale differences have been known for decades, yet little is known about differences at the fine scale. By combining data sets, we have collected recombination events from over 100,000 meioses and have constructed sex-specific genetic maps at a previously unachievable resolution. Here we show that, although a substantial fraction of the genome shows some degree of sexually dimorphic recombination, the vast majority of hotspots are shared between the sexes, with only a small number of putative sex-specific hotspots. Wavelet analysis indicates that most of the differences can be attributed to the fine scale, and that variation in rate between the sexes can mostly be explained by differences in hotspot magnitude, rather than location. Nonetheless, known recombination-associated genomic features, such as THE1B repeat elements, show systematic differences between the sexes.

Transcription forms and remodels supercoiling domains unfolding large-scale chromatin structures

PubMed Central

Naughton, Catherine; Avlonitis, Nicolaos; Corless, Samuel; Prendergast, James G.; Mati, Ioulia K.; Eijk, Paul P.; Cockroft, Scott L.; Bradley, Mark; Ylstra, Bauke; Gilbert, Nick

2013-01-01

DNA supercoiling is an inherent consequence of twisting DNA and is critical for regulating gene expression and DNA replication. However, DNA supercoiling at a genomic scale in human cells is uncharacterized. To map supercoiling we used biotinylated-trimethylpsoralen as a DNA structure probe to show the genome is organized into supercoiling domains. Domains are formed and remodeled by RNA polymerase and topoisomerase activities and are flanked by GC-AT boundaries and CTCF binding sites. Under-wound domains are transcriptionally active, enriched in topoisomerase I, “open” chromatin fibers and DNaseI sites, but are depleted of topoisomerase II. Furthermore DNA supercoiling impacts on additional levels of chromatin compaction as under-wound domains are cytologically decondensed, topologically constrained, and decompacted by transcription of short RNAs. We suggest that supercoiling domains create a topological environment that facilitates gene activation providing an evolutionary purpose for clustering genes along chromosomes. PMID:23416946

Entropic Profiler – detection of conservation in genomes using information theory

PubMed Central

Fernandes, Francisco; Freitas, Ana T; Almeida, Jonas S; Vinga, Susana

2009-01-01

Background In the last decades, with the successive availability of whole genome sequences, many research efforts have been made to mathematically model DNA. Entropic Profiles (EP) were proposed recently as a new measure of continuous entropy of genome sequences. EP represent local information plots related to DNA randomness and are based on information theory and statistical concepts. They express the weighed relative abundance of motifs for each position in genomes. Their study is very relevant because under or over-representation segments are often associated with significant biological meaning. Findings The Entropic Profiler application here presented is a new tool designed to detect and extract under and over-represented DNA segments in genomes by using EP. It allows its computation in a very efficient way by recurring to improved algorithms and data structures, which include modified suffix trees. Available through a web interface and as downloadable source code, it allows to study positions and to search for motifs inside the whole sequence or within a specified range. DNA sequences can be entered from different sources, including FASTA files, pre-loaded examples or resuming a previously saved work. Besides the EP value plots, p-values and z-scores for each motif are also computed, along with the Chaos Game Representation of the sequence. Conclusion EP are directly related with the statistical significance of motifs and can be considered as a new method to extract and classify significant regions in genomes and estimate local scales in DNA. The present implementation establishes an efficient and useful tool for whole genome analysis. PMID:19416538

The standard operating procedure of the DOE-JGI Microbial Genome Annotation Pipeline (MGAP v.4).

PubMed

Huntemann, Marcel; Ivanova, Natalia N; Mavromatis, Konstantinos; Tripp, H James; Paez-Espino, David; Palaniappan, Krishnaveni; Szeto, Ernest; Pillay, Manoj; Chen, I-Min A; Pati, Amrita; Nielsen, Torben; Markowitz, Victor M; Kyrpides, Nikos C

2015-01-01

The DOE-JGI Microbial Genome Annotation Pipeline performs structural and functional annotation of microbial genomes that are further included into the Integrated Microbial Genome comparative analysis system. MGAP is applied to assembled nucleotide sequence datasets that are provided via the IMG submission site. Dataset submission for annotation first requires project and associated metadata description in GOLD. The MGAP sequence data processing consists of feature prediction including identification of protein-coding genes, non-coding RNAs and regulatory RNA features, as well as CRISPR elements. Structural annotation is followed by assignment of protein product names and functions.

CGAT: a model for immersive personalized training in computational genomics.

PubMed

Sims, David; Ponting, Chris P; Heger, Andreas

2016-01-01

How should the next generation of genomics scientists be trained while simultaneously pursuing high quality and diverse research? CGAT, the Computational Genomics Analysis and Training programme, was set up in 2010 by the UK Medical Research Council to complement its investment in next-generation sequencing capacity. CGAT was conceived around the twin goals of training future leaders in genome biology and medicine, and providing much needed capacity to UK science for analysing genome scale data sets. Here we outline the training programme employed by CGAT and describe how it dovetails with collaborative research projects to launch scientists on the road towards independent research careers in genomics. © The Author 2015. Published by Oxford University Press.

The layout of a bacterial genome.

PubMed

Képès, François; Jester, Brian C; Lepage, Thibaut; Rafiei, Nafiseh; Rosu, Bianca; Junier, Ivan

2012-07-16

Recently the mismatch between our newly acquired capacity to synthetize DNA at genome scale, and our low capacity to design ab initio a functional genome has become conspicuous. This essay gathers a variety of constraints that globally shape natural genomes, with a focus on eubacteria. These constraints originate from chromosome replication (leading/lagging strand asymmetry; gene dosage gradient from origin to terminus; collisions with the transcription complexes), from biased codon usage, from noise control in gene expression, and from genome layout for co-functional genes. On the basis of this analysis, lessons are drawn for full genome design. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Genome-environment association study suggests local adaptation to climate at the regional scale in Fagus sylvatica.

PubMed

Pluess, Andrea R; Frank, Aline; Heiri, Caroline; Lalagüe, Hadrien; Vendramin, Giovanni G; Oddou-Muratorio, Sylvie

2016-04-01

The evolutionary potential of long-lived species, such as forest trees, is fundamental for their local persistence under climate change (CC). Genome-environment association (GEA) analyses reveal if species in heterogeneous environments at the regional scale are under differential selection resulting in populations with potential preadaptation to CC within this area. In 79 natural Fagus sylvatica populations, neutral genetic patterns were characterized using 12 simple sequence repeat (SSR) markers, and genomic variation (144 single nucleotide polymorphisms (SNPs) out of 52 candidate genes) was related to 87 environmental predictors in the latent factor mixed model, logistic regressions and isolation by distance/environmental (IBD/IBE) tests. SSR diversity revealed relatedness at up to 150 m intertree distance but an absence of large-scale spatial genetic structure and IBE. In the GEA analyses, 16 SNPs in 10 genes responded to one or several environmental predictors and IBE, corrected for IBD, was confirmed. The GEA often reflected the proposed gene functions, including indications for adaptation to water availability and temperature. Genomic divergence and the lack of large-scale neutral genetic patterns suggest that gene flow allows the spread of advantageous alleles in adaptive genes. Thereby, adaptation processes are likely to take place in species occurring in heterogeneous environments, which might reduce their regional extinction risk under CC. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

New Era of Studying RNA Secondary Structure and Its Influence on Gene Regulation in Plants.

PubMed

Yang, Xiaofei; Yang, Minglei; Deng, Hongjing; Ding, Yiliang

2018-01-01

The dynamic structure of RNA plays a central role in post-transcriptional regulation of gene expression such as RNA maturation, degradation, and translation. With the rise of next-generation sequencing, the study of RNA structure has been transformed from in vitro low-throughput RNA structure probing methods to in vivo high-throughput RNA structure profiling. The development of these methods enables incremental studies on the function of RNA structure to be performed, revealing new insights of novel regulatory mechanisms of RNA structure in plants. Genome-wide scale RNA structure profiling allows us to investigate general RNA structural features over 10s of 1000s of mRNAs and to compare RNA structuromes between plant species. Here, we provide a comprehensive and up-to-date overview of: (i) RNA structure probing methods; (ii) the biological functions of RNA structure; (iii) genome-wide RNA structural features corresponding to their regulatory mechanisms; and (iv) RNA structurome evolution in plants.

[Short interspersed repetitive sequences (SINEs) and their use as a phylogenetic tool].

PubMed

Kramerov, D A; Vasetskiĭ, N S

2009-01-01

The data on one of the most common repetitive elements of eukaryotic genomes, short interspersed elements (SINEs), are reviewed. Their structure, origin, and functioning in the genome are discussed. The variation and abundance of these neutral genomic markers makes them a convenient and reliable tool for phylogenetic analysis. The main methods of such analysis are presented, and the potential and limitations of this approach are discussed using specific examples.

A New Method for Rapid Screening of End-Point PCR Products: Application to Single Genome Amplified HIV and SIV Envelope Amplicons

PubMed Central

Houzet, Laurent; Deleage, Claire; Satie, Anne-Pascale; Merlande, Laetitia; Mahe, Dominique; Dejucq-Rainsford, Nathalie

2015-01-01

PCR is the most widely applied technique for large scale screening of bacterial clones, mouse genotypes, virus genomes etc. A drawback of large PCR screening is that amplicon analysis is usually performed using gel electrophoresis, a step that is very labor intensive, tedious and chemical waste generating. Single genome amplification (SGA) is used to characterize the diversity and evolutionary dynamics of virus populations within infected hosts. SGA is based on the isolation of single template molecule using limiting dilution followed by nested PCR amplification and requires the analysis of hundreds of reactions per sample, making large scale SGA studies very challenging. Here we present a novel approach entitled Long Amplicon Melt Profiling (LAMP) based on the analysis of the melting profile of the PCR reactions using SYBR Green and/or EvaGreen fluorescent dyes. The LAMP method represents an attractive alternative to gel electrophoresis and enables the quick discrimination of positive reactions. We validate LAMP for SIV and HIV env-SGA, in 96- and 384-well plate formats. Because the melt profiling allows the screening of several thousands of PCR reactions in a cost-effective, rapid and robust way, we believe it will greatly facilitate any large scale PCR screening. PMID:26053379

Computing patient data in the cloud: practical and legal considerations for genetics and genomics research in Europe and internationally.

PubMed

Molnár-Gábor, Fruzsina; Lueck, Rupert; Yakneen, Sergei; Korbel, Jan O

2017-06-20

Biomedical research is becoming increasingly large-scale and international. Cloud computing enables the comprehensive integration of genomic and clinical data, and the global sharing and collaborative processing of these data within a flexibly scalable infrastructure. Clouds offer novel research opportunities in genomics, as they facilitate cohort studies to be carried out at unprecedented scale, and they enable computer processing with superior pace and throughput, allowing researchers to address questions that could not be addressed by studies using limited cohorts. A well-developed example of such research is the Pan-Cancer Analysis of Whole Genomes project, which involves the analysis of petabyte-scale genomic datasets from research centers in different locations or countries and different jurisdictions. Aside from the tremendous opportunities, there are also concerns regarding the utilization of clouds; these concerns pertain to perceived limitations in data security and protection, and the need for due consideration of the rights of patient donors and research participants. Furthermore, the increased outsourcing of information technology impedes the ability of researchers to act within the realm of existing local regulations owing to fundamental differences in the understanding of the right to data protection in various legal systems. In this Opinion article, we address the current opportunities and limitations of cloud computing and highlight the responsible use of federated and hybrid clouds that are set up between public and private partners as an adequate solution for genetics and genomics research in Europe, and under certain conditions between Europe and international partners. This approach could represent a sensible middle ground between fragmented individual solutions and a "one-size-fits-all" approach.

New families of human regulatory RNA structures identified by comparative analysis of vertebrate genomes.

PubMed

Parker, Brian J; Moltke, Ida; Roth, Adam; Washietl, Stefan; Wen, Jiayu; Kellis, Manolis; Breaker, Ronald; Pedersen, Jakob Skou

2011-11-01

Regulatory RNA structures are often members of families with multiple paralogous instances across the genome. Family members share functional and structural properties, which allow them to be studied as a whole, facilitating both bioinformatic and experimental characterization. We have developed a comparative method, EvoFam, for genome-wide identification of families of regulatory RNA structures, based on primary sequence and secondary structure similarity. We apply EvoFam to a 41-way genomic vertebrate alignment. Genome-wide, we identify 220 human, high-confidence families outside protein-coding regions comprising 725 individual structures, including 48 families with known structural RNA elements. Known families identified include both noncoding RNAs, e.g., miRNAs and the recently identified MALAT1/MEN β lincRNA family; and cis-regulatory structures, e.g., iron-responsive elements. We also identify tens of new families supported by strong evolutionary evidence and other statistical evidence, such as GO term enrichments. For some of these, detailed analysis has led to the formulation of specific functional hypotheses. Examples include two hypothesized auto-regulatory feedback mechanisms: one involving six long hairpins in the 3'-UTR of MAT2A, a key metabolic gene that produces the primary human methyl donor S-adenosylmethionine; the other involving a tRNA-like structure in the intron of the tRNA maturation gene POP1. We experimentally validate the predicted MAT2A structures. Finally, we identify potential new regulatory networks, including large families of short hairpins enriched in immunity-related genes, e.g., TNF, FOS, and CTLA4, which include known transcript destabilizing elements. Our findings exemplify the diversity of post-transcriptional regulation and provide a resource for further characterization of new regulatory mechanisms and families of noncoding RNAs.

13C metabolic flux analysis at a genome-scale.

PubMed

Gopalakrishnan, Saratram; Maranas, Costas D

2015-11-01

Metabolic models used in 13C metabolic flux analysis generally include a limited number of reactions primarily from central metabolism. They typically omit degradation pathways, complete cofactor balances, and atom transition contributions for reactions outside central metabolism. This study addresses the impact on prediction fidelity of scaling-up mapping models to a genome-scale. The core mapping model employed in this study accounts for (75 reactions and 65 metabolites) primarily from central metabolism. The genome-scale metabolic mapping model (GSMM) (697 reaction and 595 metabolites) is constructed using as a basis the iAF1260 model upon eliminating reactions guaranteed not to carry flux based on growth and fermentation data for a minimal glucose growth medium. Labeling data for 17 amino acid fragments obtained from cells fed with glucose labeled at the second carbon was used to obtain fluxes and ranges. Metabolic fluxes and confidence intervals are estimated, for both core and genome-scale mapping models, by minimizing the sum of square of differences between predicted and experimentally measured labeling patterns using the EMU decomposition algorithm. Overall, we find that both topology and estimated values of the metabolic fluxes remain largely consistent between core and GSM model. Stepping up to a genome-scale mapping model leads to wider flux inference ranges for 20 key reactions present in the core model. The glycolysis flux range doubles due to the possibility of active gluconeogenesis, the TCA flux range expanded by 80% due to the availability of a bypass through arginine consistent with labeling data, and the transhydrogenase reaction flux was essentially unresolved due to the presence of as many as five routes for the inter-conversion of NADPH to NADH afforded by the genome-scale model. By globally accounting for ATP demands in the GSMM model the unused ATP decreased drastically with the lower bound matching the maintenance ATP requirement. A non-zero flux for the arginine degradation pathway was identified to meet biomass precursor demands as detailed in the iAF1260 model. Inferred ranges for 81% of the reactions in the genome-scale metabolic (GSM) model varied less than one-tenth of the basis glucose uptake rate (95% confidence test). This is because as many as 411 reactions in the GSM are growth coupled meaning that the single measurement of biomass formation rate locks the reaction flux values. This implies that accurate biomass formation rate and composition are critical for resolving metabolic fluxes away from central metabolism and suggests the importance of biomass composition (re)assessment under different genetic and environmental backgrounds. In addition, the loss of information associated with mapping fluxes from MFA on a core model to a GSM model is quantified. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

New Implications on Genomic Adaptation Derived from the Helicobacter pylori Genome Comparison

PubMed Central

Lara-Ramírez, Edgar Eduardo; Segura-Cabrera, Aldo; Guo, Xianwu; Yu, Gongxin; García-Pérez, Carlos Armando; Rodríguez-Pérez, Mario A.

2011-01-01

Background Helicobacter pylori has a reduced genome and lives in a tough environment for long-term persistence. It evolved with its particular characteristics for biological adaptation. Because several H. pylori genome sequences are available, comparative analysis could help to better understand genomic adaptation of this particular bacterium. Principal Findings We analyzed nine H. pylori genomes with emphasis on microevolution from a different perspective. Inversion was an important factor to shape the genome structure. Illegitimate recombination not only led to genomic inversion but also inverted fragment duplication, both of which contributed to the creation of new genes and gene family, and further, homological recombination contributed to events of inversion. Based on the information of genomic rearrangement, the first genome scaffold structure of H. pylori last common ancestor was produced. The core genome consists of 1186 genes, of which 22 genes could particularly adapt to human stomach niche. H. pylori contains high proportion of pseudogenes whose genesis was principally caused by homopolynucleotide (HPN) mutations. Such mutations are reversible and facilitate the control of gene expression through the change of DNA structure. The reversible mutations and a quasi-panmictic feature could allow such genes or gene fragments frequently transferred within or between populations. Hence, pseudogenes could be a reservoir of adaptation materials and the HPN mutations could be favorable to H. pylori adaptation, leading to HPN accumulation on the genomes, which corresponds to a special feature of Helicobacter species: extremely high HPN composition of genome. Conclusion Our research demonstrated that both genome content and structure of H. pylori have been highly adapted to its particular life style. PMID:21387011

Novel probabilistic models of spatial genetic ancestry with applications to stratification correction in genome-wide association studies.

PubMed

Bhaskar, Anand; Javanmard, Adel; Courtade, Thomas A; Tse, David

2017-03-15

Genetic variation in human populations is influenced by geographic ancestry due to spatial locality in historical mating and migration patterns. Spatial population structure in genetic datasets has been traditionally analyzed using either model-free algorithms, such as principal components analysis (PCA) and multidimensional scaling, or using explicit spatial probabilistic models of allele frequency evolution. We develop a general probabilistic model and an associated inference algorithm that unify the model-based and data-driven approaches to visualizing and inferring population structure. Our spatial inference algorithm can also be effectively applied to the problem of population stratification in genome-wide association studies (GWAS), where hidden population structure can create fictitious associations when population ancestry is correlated with both the genotype and the trait. Our algorithm Geographic Ancestry Positioning (GAP) relates local genetic distances between samples to their spatial distances, and can be used for visually discerning population structure as well as accurately inferring the spatial origin of individuals on a two-dimensional continuum. On both simulated and several real datasets from diverse human populations, GAP exhibits substantially lower error in reconstructing spatial ancestry coordinates compared to PCA. We also develop an association test that uses the ancestry coordinates inferred by GAP to accurately account for ancestry-induced correlations in GWAS. Based on simulations and analysis of a dataset of 10 metabolic traits measured in a Northern Finland cohort, which is known to exhibit significant population structure, we find that our method has superior power to current approaches. Our software is available at https://github.com/anand-bhaskar/gap . abhaskar@stanford.edu or ajavanma@usc.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

RNAslider: a faster engine for consecutive windows folding and its application to the analysis of genomic folding asymmetry.

PubMed

Horesh, Yair; Wexler, Ydo; Lebenthal, Ilana; Ziv-Ukelson, Michal; Unger, Ron

2009-03-04

Scanning large genomes with a sliding window in search of locally stable RNA structures is a well motivated problem in bioinformatics. Given a predefined window size L and an RNA sequence S of size N (L < N), the consecutive windows folding problem is to compute the minimal free energy (MFE) for the folding of each of the L-sized substrings of S. The consecutive windows folding problem can be naively solved in O(NL3) by applying any of the classical cubic-time RNA folding algorithms to each of the N-L windows of size L. Recently an O(NL2) solution for this problem has been described. Here, we describe and implement an O(NLpsi(L)) engine for the consecutive windows folding problem, where psi(L) is shown to converge to O(1) under the assumption of a standard probabilistic polymer folding model, yielding an O(L) speedup which is experimentally confirmed. Using this tool, we note an intriguing directionality (5'-3' vs. 3'-5') folding bias, i.e. that the minimal free energy (MFE) of folding is higher in the native direction of the DNA than in the reverse direction of various genomic regions in several organisms including regions of the genomes that do not encode proteins or ncRNA. This bias largely emerges from the genomic dinucleotide bias which affects the MFE, however we see some variations in the folding bias in the different genomic regions when normalized to the dinucleotide bias. We also present results from calculating the MFE landscape of a mouse chromosome 1, characterizing the MFE of the long ncRNA molecules that reside in this chromosome. The efficient consecutive windows folding engine described in this paper allows for genome wide scans for ncRNA molecules as well as large-scale statistics. This is implemented here as a software tool, called RNAslider, and applied to the scanning of long chromosomes, leading to the observation of features that are visible only on a large scale.

Next generation haplotyping to decipher nuclear genomic interspecific admixture in Citrus species: analysis of chromosome 2.

PubMed

Curk, Franck; Ancillo, Gema; Garcia-Lor, Andres; Luro, François; Perrier, Xavier; Jacquemoud-Collet, Jean-Pierre; Navarro, Luis; Ollitrault, Patrick

2014-12-29

The most economically important Citrus species originated by natural interspecific hybridization between four ancestral taxa (Citrus reticulata, Citrus maxima, Citrus medica, and Citrus micrantha) and from limited subsequent interspecific recombination as a result of apomixis and vegetative propagation. Such reticulate evolution coupled with vegetative propagation results in mosaic genomes with large chromosome fragments from the basic taxa in frequent interspecific heterozygosity. Modern breeding of these species is hampered by their complex heterozygous genomic structures that determine species phenotype and are broken by sexual hybridisation. Nevertheless, a large amount of diversity is present in the citrus gene pool, and breeding to allow inclusion of desirable traits is of paramount importance. However, the efficient mobilization of citrus biodiversity in innovative breeding schemes requires previous understanding of Citrus origins and genomic structures. Haplotyping of multiple gene fragments along the whole genome is a powerful approach to reveal the admixture genomic structure of current species and to resolve the evolutionary history of the gene pools. In this study, the efficiency of parallel sequencing with 454 methodology to decipher the hybrid structure of modern citrus species was assessed by analysis of 16 gene fragments on chromosome 2. 454 amplicon libraries were established using the Fluidigm array system for 48 genotypes and 16 gene fragments from chromosome 2. Haplotypes were established from the reads of each accession and phylogenetic analyses were performed using the haplotypic data for each gene fragment. The length of 454 reads and the level of differentiation between the ancestral taxa of modern citrus allowed efficient haplotype phylogenetic assignations for 12 of the 16 gene fragments. The analysis of the mixed genomic structure of modern species and cultivars (i) revealed C. maxima introgressions in modern mandarins, (ii) was consistent with previous hypotheses regarding the origin of secondary species, and (iii) provided a new picture of the evolution of chromosome 2. 454 sequencing was an efficient strategy to establish haplotypes with significant phylogenetic assignations in Citrus, providing a new picture of the mixed structure on chromosome 2 in 48 citrus genotypes.

Segmental duplications: evolution and impact among the current Lepidoptera genomes.

PubMed

Zhao, Qian; Ma, Dongna; Vasseur, Liette; You, Minsheng

2017-07-06

Structural variation among genomes is now viewed to be as important as single nucleoid polymorphisms in influencing the phenotype and evolution of a species. Segmental duplication (SD) is defined as segments of DNA with homologous sequence. Here, we performed a systematic analysis of segmental duplications (SDs) among five lepidopteran reference genomes (Plutella xylostella, Danaus plexippus, Bombyx mori, Manduca sexta and Heliconius melpomene) to understand their potential impact on the evolution of these species. We find that the SDs content differed substantially among species, ranging from 1.2% of the genome in B. mori to 15.2% in H. melpomene. Most SDs formed very high identity (similarity higher than 90%) blocks but had very few large blocks. Comparative analysis showed that most of the SDs arose after the divergence of each linage and we found that P. xylostella and H. melpomene showed more duplications than other species, suggesting they might be able to tolerate extensive levels of variation in their genomes. Conserved ancestral and species specific SD events were assessed, revealing multiple examples of the gain, loss or maintenance of SDs over time. SDs content analysis showed that most of the genes embedded in SDs regions belonged to species-specific SDs ("Unique" SDs). Functional analysis of these genes suggested their potential roles in the lineage-specific evolution. SDs and flanking regions often contained transposable elements (TEs) and this association suggested some involvement in SDs formation. Further studies on comparison of gene expression level between SDs and non-SDs showed that the expression level of genes embedded in SDs was significantly lower, suggesting that structure changes in the genomes are involved in gene expression differences in species. The results showed that most of the SDs were "unique SDs", which originated after species formation. Functional analysis suggested that SDs might play different roles in different species. Our results provide a valuable resource beyond the genetic mutation to explore the genome structure for future Lepidoptera research.

Comparative Chloroplast Genomics of Gossypium Species: Insights Into Repeat Sequence Variations and Phylogeny

PubMed Central

Wu, Ying; Liu, Fang; Yang, Dai-Gang; Li, Wei; Zhou, Xiao-Jian; Pei, Xiao-Yu; Liu, Yan-Gai; He, Kun-Lun; Zhang, Wen-Sheng; Ren, Zhong-Ying; Zhou, Ke-Hai; Ma, Xiong-Feng; Li, Zhong-Hu

2018-01-01

Cotton is one of the most economically important fiber crop plants worldwide. The genus Gossypium contains a single allotetraploid group (AD) and eight diploid genome groups (A–G and K). However, the evolution of repeat sequences in the chloroplast genomes and the phylogenetic relationships of Gossypium species are unclear. Thus, we determined the variations in the repeat sequences and the evolutionary relationships of 40 cotton chloroplast genomes, which represented the most diverse in the genus, including five newly sequenced diploid species, i.e., G. nandewarense (C1-n), G. armourianum (D2-1), G. lobatum (D7), G. trilobum (D8), and G. schwendimanii (D11), and an important semi-wild race of upland cotton, G. hirsutum race latifolium (AD1). The genome structure, gene order, and GC content of cotton species were similar to those of other higher plant plastid genomes. In total, 2860 long sequence repeats (>10 bp in length) were identified, where the F-genome species had the largest number of repeats (G. longicalyx F1: 108) and E-genome species had the lowest (G. stocksii E1: 53). Large-scale repeat sequences possibly enrich the genetic information and maintain genome stability in cotton species. We also identified 10 divergence hotspot regions, i.e., rpl33-rps18, psbZ-trnG (GCC), rps4-trnT (UGU), trnL (UAG)-rpl32, trnE (UUC)-trnT (GGU), atpE, ndhI, rps2, ycf1, and ndhF, which could be useful molecular genetic markers for future population genetics and phylogenetic studies. Site-specific selection analysis showed that some of the coding sites of 10 chloroplast genes (atpB, atpE, rps2, rps3, petB, petD, ccsA, cemA, ycf1, and rbcL) were under protein sequence evolution. Phylogenetic analysis based on the whole plastomes suggested that the Gossypium species grouped into six previously identified genetic clades. Interestingly, all 13 D-genome species clustered into a strong monophyletic clade. Unexpectedly, the cotton species with C, G, and K-genomes were admixed and nested in a large clade, which could have been due to their recent radiation, incomplete lineage sorting, and introgression hybridization among different cotton lineages. In conclusion, the results of this study provide new insights into the evolution of repeat sequences in chloroplast genomes and interspecific relationships in the genus Gossypium. PMID:29619041

A randomized approach to speed up the analysis of large-scale read-count data in the application of CNV detection.

PubMed

Wang, WeiBo; Sun, Wei; Wang, Wei; Szatkiewicz, Jin

2018-03-01

The application of high-throughput sequencing in a broad range of quantitative genomic assays (e.g., DNA-seq, ChIP-seq) has created a high demand for the analysis of large-scale read-count data. Typically, the genome is divided into tiling windows and windowed read-count data is generated for the entire genome from which genomic signals are detected (e.g. copy number changes in DNA-seq, enrichment peaks in ChIP-seq). For accurate analysis of read-count data, many state-of-the-art statistical methods use generalized linear models (GLM) coupled with the negative-binomial (NB) distribution by leveraging its ability for simultaneous bias correction and signal detection. However, although statistically powerful, the GLM+NB method has a quadratic computational complexity and therefore suffers from slow running time when applied to large-scale windowed read-count data. In this study, we aimed to speed up substantially the GLM+NB method by using a randomized algorithm and we demonstrate here the utility of our approach in the application of detecting copy number variants (CNVs) using a real example. We propose an efficient estimator, the randomized GLM+NB coefficients estimator (RGE), for speeding up the GLM+NB method. RGE samples the read-count data and solves the estimation problem on a smaller scale. We first theoretically validated the consistency and the variance properties of RGE. We then applied RGE to GENSENG, a GLM+NB based method for detecting CNVs. We named the resulting method as "R-GENSENG". Based on extensive evaluation using both simulated and empirical data, we concluded that R-GENSENG is ten times faster than the original GENSENG while maintaining GENSENG's accuracy in CNV detection. Our results suggest that RGE strategy developed here could be applied to other GLM+NB based read-count analyses, i.e. ChIP-seq data analysis, to substantially improve their computational efficiency while preserving the analytic power.

Integrated Approach to Reconstruction of Microbial Regulatory Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodionov, Dmitry A; Novichkov, Pavel S

2013-11-04

This project had the goal(s) of development of integrated bioinformatics platform for genome-scale inference and visualization of transcriptional regulatory networks (TRNs) in bacterial genomes. The work was done in Sanford-Burnham Medical Research Institute (SBMRI, P.I. D.A. Rodionov) and Lawrence Berkeley National Laboratory (LBNL, co-P.I. P.S. Novichkov). The developed computational resources include: (1) RegPredict web-platform for TRN inference and regulon reconstruction in microbial genomes, and (2) RegPrecise database for collection, visualization and comparative analysis of transcriptional regulons reconstructed by comparative genomics. These analytical resources were selected as key components in the DOE Systems Biology KnowledgeBase (SBKB). The high-quality data accumulated inmore » RegPrecise will provide essential datasets of reference regulons in diverse microbes to enable automatic reconstruction of draft TRNs in newly sequenced genomes. We outline our progress toward the three aims of this grant proposal, which were: Develop integrated platform for genome-scale regulon reconstruction; Infer regulatory annotations in several groups of bacteria and building of reference collections of microbial regulons; and Develop KnowledgeBase on microbial transcriptional regulation.« less

Prokaryote genome fluidity: toward a system approach of the mobilome.

PubMed

Toussaint, Ariane; Chandler, Mick

2012-01-01

The importance of horizontal/lateral gene transfer (LGT) in shaping the genomes of prokaryotic organisms has been recognized in recent years as a result of analysis of the increasing number of available genome sequences. LGT is largely due to the transfer and recombination activities of mobile genetic elements (MGEs). Bacterial and archaeal genomes are mosaics of vertically and horizontally transmitted DNA segments. This generates reticulate relationships between members of the prokaryotic world that are better represented by networks than by "classical" phylogenetic trees. In this review we summarize the nature and activities of MGEs, and the problems that presently limit their analysis on a large scale. We propose routes to improve their annotation in the flow of genomic and metagenomic sequences that currently exist and those that become available. We describe network analysis of evolutionary relationships among some MGE categories and sketch out possible developments of this type of approach to get more insight into the role of the mobilome in bacterial adaptation and evolution.