BAYESIAN LARGE-SCALE MULTIPLE REGRESSION WITH SUMMARY STATISTICS FROM GENOME-WIDE ASSOCIATION STUDIES1

PubMed Central

Zhu, Xiang; Stephens, Matthew

2017-01-01

Bayesian methods for large-scale multiple regression provide attractive approaches to the analysis of genome-wide association studies (GWAS). For example, they can estimate heritability of complex traits, allowing for both polygenic and sparse models; and by incorporating external genomic data into the priors, they can increase power and yield new biological insights. However, these methods require access to individual genotypes and phenotypes, which are often not easily available. Here we provide a framework for performing these analyses without individual-level data. Specifically, we introduce a “Regression with Summary Statistics” (RSS) likelihood, which relates the multiple regression coefficients to univariate regression results that are often easily available. The RSS likelihood requires estimates of correlations among covariates (SNPs), which also can be obtained from public databases. We perform Bayesian multiple regression analysis by combining the RSS likelihood with previously proposed prior distributions, sampling posteriors by Markov chain Monte Carlo. In a wide range of simulations RSS performs similarly to analyses using the individual data, both for estimating heritability and detecting associations. We apply RSS to a GWAS of human height that contains 253,288 individuals typed at 1.06 million SNPs, for which analyses of individual-level data are practically impossible. Estimates of heritability (52%) are consistent with, but more precise, than previous results using subsets of these data. We also identify many previously unreported loci that show evidence for association with height in our analyses. Software is available at https://github.com/stephenslab/rss. PMID:29399241

Novel genomic findings in multiple myeloma identified through routine diagnostic sequencing.

PubMed

Ryland, Georgina L; Jones, Kate; Chin, Melody; Markham, John; Aydogan, Elle; Kankanige, Yamuna; Caruso, Marisa; Guinto, Jerick; Dickinson, Michael; Prince, H Miles; Yong, Kwee; Blombery, Piers

2018-05-14

Multiple myeloma is a genomically complex haematological malignancy with many genomic alterations recognised as important in diagnosis, prognosis and therapeutic decision making. Here, we provide a summary of genomic findings identified through routine diagnostic next-generation sequencing at our centre. A cohort of 86 patients with multiple myeloma underwent diagnostic sequencing using a custom hybridisation-based panel targeting 104 genes. Sequence variants, genome-wide copy number changes and structural rearrangements were detected using an inhouse-developed bioinformatics pipeline. At least one mutation was found in 69 (80%) patients. Frequently mutated genes included TP53 (36%), KRAS (22.1%), NRAS (15.1%), FAM46C/DIS3 (8.1%) and TET2/FGFR3 (5.8%), including multiple mutations not previously described in myeloma. Importantly we observed TP53 mutations in the absence of a 17 p deletion in 8% of the cohort, highlighting the need for sequencing-based assessment in addition to cytogenetics to identify these high-risk patients. Multiple novel copy number changes and immunoglobulin heavy chain translocations are also discussed. Our results demonstrate that many clinically relevant genomic findings remain in multiple myeloma which have not yet been identified through large-scale sequencing efforts, and provide important mechanistic insights into plasma cell pathobiology. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Radiation-induced genomic instability: radiation quality and dose response

NASA Technical Reports Server (NTRS)

Smith, Leslie E.; Nagar, Shruti; Kim, Grace J.; Morgan, William F.

2003-01-01

Genomic instability is a term used to describe a phenomenon that results in the accumulation of multiple changes required to convert a stable genome of a normal cell to an unstable genome characteristic of a tumor. There has been considerable recent debate concerning the importance of genomic instability in human cancer and its temporal occurrence in the carcinogenic process. Radiation is capable of inducing genomic instability in mammalian cells and instability is thought to be the driving force responsible for radiation carcinogenesis. Genomic instability is characterized by a large collection of diverse endpoints that include large-scale chromosomal rearrangements and aberrations, amplification of genetic material, aneuploidy, micronucleus formation, microsatellite instability, and gene mutation. The capacity of radiation to induce genomic instability depends to a large extent on radiation quality or linear energy transfer (LET) and dose. There appears to be a low dose threshold effect with low LET, beyond which no additional genomic instability is induced. Low doses of both high and low LET radiation are capable of inducing this phenomenon. This report reviews data concerning dose rate effects of high and low LET radiation and their capacity to induce genomic instability assayed by chromosomal aberrations, delayed lethal mutations, micronuclei and apoptosis.

Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci

USDA-ARS?s Scientific Manuscript database

Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholest...

Minimal-assumption inference from population-genomic data

NASA Astrophysics Data System (ADS)

Weissman, Daniel; Hallatschek, Oskar

Samples of multiple complete genome sequences contain vast amounts of information about the evolutionary history of populations, much of it in the associations among polymorphisms at different loci. Current methods that take advantage of this linkage information rely on models of recombination and coalescence, limiting the sample sizes and populations that they can analyze. We introduce a method, Minimal-Assumption Genomic Inference of Coalescence (MAGIC), that reconstructs key features of the evolutionary history, including the distribution of coalescence times, by integrating information across genomic length scales without using an explicit model of recombination, demography or selection. Using simulated data, we show that MAGIC's performance is comparable to PSMC' on single diploid samples generated with standard coalescent and recombination models. More importantly, MAGIC can also analyze arbitrarily large samples and is robust to changes in the coalescent and recombination processes. Using MAGIC, we show that the inferred coalescence time histories of samples of multiple human genomes exhibit inconsistencies with a description in terms of an effective population size based on single-genome data.

InSilico DB genomic datasets hub: an efficient starting point for analyzing genome-wide studies in GenePattern, Integrative Genomics Viewer, and R/Bioconductor.

PubMed

Coletta, Alain; Molter, Colin; Duqué, Robin; Steenhoff, David; Taminau, Jonatan; de Schaetzen, Virginie; Meganck, Stijn; Lazar, Cosmin; Venet, David; Detours, Vincent; Nowé, Ann; Bersini, Hugues; Weiss Solís, David Y

2012-11-18

Genomics datasets are increasingly useful for gaining biomedical insights, with adoption in the clinic underway. However, multiple hurdles related to data management stand in the way of their efficient large-scale utilization. The solution proposed is a web-based data storage hub. Having clear focus, flexibility and adaptability, InSilico DB seamlessly connects genomics dataset repositories to state-of-the-art and free GUI and command-line data analysis tools. The InSilico DB platform is a powerful collaborative environment, with advanced capabilities for biocuration, dataset sharing, and dataset subsetting and combination. InSilico DB is available from https://insilicodb.org.

Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.

PubMed

Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen

2017-02-01

Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too. Our solution (PSOMCS) is to use particle swarm optimization (PSO) along with the direct calculation of cMCSs from the stoichiometric matrix to obtain optimal designs satisfying multiple objectives. To illustrate the working of PSOMCS, we apply it to a toy network. Next we show its superiority by comparing its performance against other comparable methods on a medium sized E. coli core metabolic network. PSOMCS not only finds solutions comparable to previously published results but also it is orders of magnitude faster. Finally, we use PSOMCS to predict knockouts satisfying multiple objectives in a genome-scale metabolic model of E. coli and compare it with OptKnock and RobustKnock. PSOMCS finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. It can be used in identifying knockouts which will force optimal desired behaviors in large and genome scale metabolic networks. It will be even more useful as larger metabolic models of industrially relevant organisms become available.

Natural Selection and Recombination Rate Variation Shape Nucleotide Polymorphism Across the Genomes of Three Related Populus Species

PubMed Central

Wang, Jing; Street, Nathaniel R.; Scofield, Douglas G.; Ingvarsson, Pär K.

2016-01-01

A central aim of evolutionary genomics is to identify the relative roles that various evolutionary forces have played in generating and shaping genetic variation within and among species. Here we use whole-genome resequencing data to characterize and compare genome-wide patterns of nucleotide polymorphism, site frequency spectrum, and population-scaled recombination rates in three species of Populus: Populus tremula, P. tremuloides, and P. trichocarpa. We find that P. tremuloides has the highest level of genome-wide variation, skewed allele frequencies, and population-scaled recombination rates, whereas P. trichocarpa harbors the lowest. Our findings highlight multiple lines of evidence suggesting that natural selection, due to both purifying and positive selection, has widely shaped patterns of nucleotide polymorphism at linked neutral sites in all three species. Differences in effective population sizes and rates of recombination largely explain the disparate magnitudes and signatures of linked selection that we observe among species. The present work provides the first phylogenetic comparative study on a genome-wide scale in forest trees. This information will also improve our ability to understand how various evolutionary forces have interacted to influence genome evolution among related species. PMID:26721855

Natural Selection and Recombination Rate Variation Shape Nucleotide Polymorphism Across the Genomes of Three Related Populus Species.

PubMed

Wang, Jing; Street, Nathaniel R; Scofield, Douglas G; Ingvarsson, Pär K

2016-03-01

A central aim of evolutionary genomics is to identify the relative roles that various evolutionary forces have played in generating and shaping genetic variation within and among species. Here we use whole-genome resequencing data to characterize and compare genome-wide patterns of nucleotide polymorphism, site frequency spectrum, and population-scaled recombination rates in three species of Populus: Populus tremula, P. tremuloides, and P. trichocarpa. We find that P. tremuloides has the highest level of genome-wide variation, skewed allele frequencies, and population-scaled recombination rates, whereas P. trichocarpa harbors the lowest. Our findings highlight multiple lines of evidence suggesting that natural selection, due to both purifying and positive selection, has widely shaped patterns of nucleotide polymorphism at linked neutral sites in all three species. Differences in effective population sizes and rates of recombination largely explain the disparate magnitudes and signatures of linked selection that we observe among species. The present work provides the first phylogenetic comparative study on a genome-wide scale in forest trees. This information will also improve our ability to understand how various evolutionary forces have interacted to influence genome evolution among related species. Copyright © 2016 by the Genetics Society of America.

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.

Legume genome evolution viewed through the Medicago truncatula and Lotus japonicus genomes

PubMed Central

Cannon, Steven B.; Sterck, Lieven; Rombauts, Stephane; Sato, Shusei; Cheung, Foo; Gouzy, Jérôme; Wang, Xiaohong; Mudge, Joann; Vasdewani, Jayprakash; Schiex, Thomas; Spannagl, Manuel; Monaghan, Erin; Nicholson, Christine; Humphray, Sean J.; Schoof, Heiko; Mayer, Klaus F. X.; Rogers, Jane; Quétier, Francis; Oldroyd, Giles E.; Debellé, Frédéric; Cook, Douglas R.; Retzel, Ernest F.; Roe, Bruce A.; Town, Christopher D.; Tabata, Satoshi; Van de Peer, Yves; Young, Nevin D.

2006-01-01

Genome sequencing of the model legumes, Medicago truncatula and Lotus japonicus, provides an opportunity for large-scale sequence-based comparison of two genomes in the same plant family. Here we report synteny comparisons between these species, including details about chromosome relationships, large-scale synteny blocks, microsynteny within blocks, and genome regions lacking clear correspondence. The Lotus and Medicago genomes share a minimum of 10 large-scale synteny blocks, each with substantial collinearity and frequently extending the length of whole chromosome arms. The proportion of genes syntenic and collinear within each synteny block is relatively homogeneous. Medicago–Lotus comparisons also indicate similar and largely homogeneous gene densities, although gene-containing regions in Mt occupy 20–30% more space than Lj counterparts, primarily because of larger numbers of Mt retrotransposons. Because the interpretation of genome comparisons is complicated by large-scale genome duplications, we describe synteny, synonymous substitutions and phylogenetic analyses to identify and date a probable whole-genome duplication event. There is no direct evidence for any recent large-scale genome duplication in either Medicago or Lotus but instead a duplication predating speciation. Phylogenetic comparisons place this duplication within the Rosid I clade, clearly after the split between legumes and Salicaceae (poplar). PMID:17003129

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.

Large-scale analysis of antisense transcription in wheat using the Affymetrix GeneChip Wheat Genome Array

USDA-ARS?s Scientific Manuscript database

Natural antisense transcripts (NATs) are transcripts of the opposite DNA strand to the sense-strand either at the same locus (cis-encoded) or a different locus (trans-encoded). They can affect gene expression at multiple stages including transcription, RNA processing and transport, and translation....

Large-scale gene function analysis with the PANTHER classification system.

PubMed

Mi, Huaiyu; Muruganujan, Anushya; Casagrande, John T; Thomas, Paul D

2013-08-01

The PANTHER (protein annotation through evolutionary relationship) classification system (http://www.pantherdb.org/) is a comprehensive system that combines gene function, ontology, pathways and statistical analysis tools that enable biologists to analyze large-scale, genome-wide data from sequencing, proteomics or gene expression experiments. The system is built with 82 complete genomes organized into gene families and subfamilies, and their evolutionary relationships are captured in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models or HMMs). Genes are classified according to their function in several different ways: families and subfamilies are annotated with ontology terms (Gene Ontology (GO) and PANTHER protein class), and sequences are assigned to PANTHER pathways. The PANTHER website includes a suite of tools that enable users to browse and query gene functions, and to analyze large-scale experimental data with a number of statistical tests. It is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists. In the 2013 release of PANTHER (v.8.0), in addition to an update of the data content, we redesigned the website interface to improve both user experience and the system's analytical capability. This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system.

Functional genomic Landscape of Human Breast Cancer drivers, vulnerabilities, and resistance

PubMed Central

Marcotte, Richard; Sayad, Azin; Brown, Kevin R.; Sanchez-Garcia, Felix; Reimand, Jüri; Haider, Maliha; Virtanen, Carl; Bradner, James E.; Bader, Gary D.; Mills, Gordon B.; Pe’er, Dana; Moffat, Jason; Neel, Benjamin G.

2016-01-01

Summary Large-scale genomic studies have identified multiple somatic aberrations in breast cancer, including copy number alterations, and point mutations. Still, identifying causal variants and emergent vulnerabilities that arise as a consequence of genetic alterations remain major challenges. We performed whole genome shRNA “dropout screens” on 77 breast cancer cell lines. Using a hierarchical linear regression algorithm to score our screen results and integrate them with accompanying detailed genetic and proteomic information, we identify vulnerabilities in breast cancer, including candidate “drivers,” and reveal general functional genomic properties of cancer cells. Comparisons of gene essentiality with drug sensitivity data suggest potential resistance mechanisms, effects of existing anti-cancer drugs, and opportunities for combination therapy. Finally, we demonstrate the utility of this large dataset by identifying BRD4 as a potential target in luminal breast cancer, and PIK3CA mutations as a resistance determinant for BET-inhibitors. PMID:26771497

DIALIGN P: fast pair-wise and multiple sequence alignment using parallel processors.

PubMed

Schmollinger, Martin; Nieselt, Kay; Kaufmann, Michael; Morgenstern, Burkhard

2004-09-09

Parallel computing is frequently used to speed up computationally expensive tasks in Bioinformatics. Herein, a parallel version of the multi-alignment program DIALIGN is introduced. We propose two ways of dividing the program into independent sub-routines that can be run on different processors: (a) pair-wise sequence alignments that are used as a first step to multiple alignment account for most of the CPU time in DIALIGN. Since alignments of different sequence pairs are completely independent of each other, they can be distributed to multiple processors without any effect on the resulting output alignments. (b) For alignments of large genomic sequences, we use a heuristics by splitting up sequences into sub-sequences based on a previously introduced anchored alignment procedure. For our test sequences, this combined approach reduces the program running time of DIALIGN by up to 97%. By distributing sub-routines to multiple processors, the running time of DIALIGN can be crucially improved. With these improvements, it is possible to apply the program in large-scale genomics and proteomics projects that were previously beyond its scope.

The Sequenced Angiosperm Genomes and Genome Databases.

PubMed

Chen, Fei; Dong, Wei; Zhang, Jiawei; Guo, Xinyue; Chen, Junhao; Wang, Zhengjia; Lin, Zhenguo; Tang, Haibao; Zhang, Liangsheng

2018-01-01

Angiosperms, the flowering plants, provide the essential resources for human life, such as food, energy, oxygen, and materials. They also promoted the evolution of human, animals, and the planet earth. Despite the numerous advances in genome reports or sequencing technologies, no review covers all the released angiosperm genomes and the genome databases for data sharing. Based on the rapid advances and innovations in the database reconstruction in the last few years, here we provide a comprehensive review for three major types of angiosperm genome databases, including databases for a single species, for a specific angiosperm clade, and for multiple angiosperm species. The scope, tools, and data of each type of databases and their features are concisely discussed. The genome databases for a single species or a clade of species are especially popular for specific group of researchers, while a timely-updated comprehensive database is more powerful for address of major scientific mysteries at the genome scale. Considering the low coverage of flowering plants in any available database, we propose construction of a comprehensive database to facilitate large-scale comparative studies of angiosperm genomes and to promote the collaborative studies of important questions in plant biology.

The Sequenced Angiosperm Genomes and Genome Databases

PubMed Central

Chen, Fei; Dong, Wei; Zhang, Jiawei; Guo, Xinyue; Chen, Junhao; Wang, Zhengjia; Lin, Zhenguo; Tang, Haibao; Zhang, Liangsheng

2018-01-01

Angiosperms, the flowering plants, provide the essential resources for human life, such as food, energy, oxygen, and materials. They also promoted the evolution of human, animals, and the planet earth. Despite the numerous advances in genome reports or sequencing technologies, no review covers all the released angiosperm genomes and the genome databases for data sharing. Based on the rapid advances and innovations in the database reconstruction in the last few years, here we provide a comprehensive review for three major types of angiosperm genome databases, including databases for a single species, for a specific angiosperm clade, and for multiple angiosperm species. The scope, tools, and data of each type of databases and their features are concisely discussed. The genome databases for a single species or a clade of species are especially popular for specific group of researchers, while a timely-updated comprehensive database is more powerful for address of major scientific mysteries at the genome scale. Considering the low coverage of flowering plants in any available database, we propose construction of a comprehensive database to facilitate large-scale comparative studies of angiosperm genomes and to promote the collaborative studies of important questions in plant biology. PMID:29706973

Integrating genome-wide association studies and gene expression data highlights dysregulated multiple sclerosis risk pathways.

PubMed

Liu, Guiyou; Zhang, Fang; Jiang, Yongshuai; Hu, Yang; Gong, Zhongying; Liu, Shoufeng; Chen, Xiuju; Jiang, Qinghua; Hao, Junwei

2017-02-01

Much effort has been expended on identifying the genetic determinants of multiple sclerosis (MS). Existing large-scale genome-wide association study (GWAS) datasets provide strong support for using pathway and network-based analysis methods to investigate the mechanisms underlying MS. However, no shared genetic pathways have been identified to date. We hypothesize that shared genetic pathways may indeed exist in different MS-GWAS datasets. Here, we report results from a three-stage analysis of GWAS and expression datasets. In stage 1, we conducted multiple pathway analyses of two MS-GWAS datasets. In stage 2, we performed a candidate pathway analysis of the large-scale MS-GWAS dataset. In stage 3, we performed a pathway analysis using the dysregulated MS gene list from seven human MS case-control expression datasets. In stage 1, we identified 15 shared pathways. In stage 2, we successfully replicated 14 of these 15 significant pathways. In stage 3, we found that dysregulated MS genes were significantly enriched in 10 of 15 MS risk pathways identified in stages 1 and 2. We report shared genetic pathways in different MS-GWAS datasets and highlight some new MS risk pathways. Our findings provide new insights on the genetic determinants of MS.

Understanding the Origin of Species with Genome-Scale Data: the Role of Gene Flow

PubMed Central

Sousa, Vitor; Hey, Jody

2017-01-01

As it becomes easier to sequence multiple genomes from closely related species, evolutionary biologists working on speciation are struggling to get the most out of very large population-genomic data sets. Such data hold the potential to resolve evolutionary biology’s long-standing questions about the role of gene exchange in species formation. In principle the new population genomic data can be used to disentangle the conflicting roles of natural selection and gene flow during the divergence process. However there are great challenges in taking full advantage of such data, especially with regard to including recombination in genetic models of the divergence process. Current data, models, methods and the potential pitfalls in using them will be considered here. PMID:23657479

Multiple Phenotype Association Tests Using Summary Statistics in Genome-Wide Association Studies

PubMed Central

Liu, Zhonghua; Lin, Xihong

2017-01-01

Summary We study in this paper jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. PMID:28653391

Multiple phenotype association tests using summary statistics in genome-wide association studies.

PubMed

Liu, Zhonghua; Lin, Xihong

2018-03-01

We study in this article jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. © 2017, The International Biometric Society.

Multiplex engineering of industrial yeast genomes using CRISPRm.

PubMed

Ryan, Owen W; Cate, Jamie H D

2014-01-01

Global demand has driven the use of industrial strains of the yeast Saccharomyces cerevisiae for large-scale production of biofuels and renewable chemicals. However, the genetic basis of desired domestication traits is poorly understood because robust genetic tools do not exist for industrial hosts. We present an efficient, marker-free, high-throughput, and multiplexed genome editing platform for industrial strains of S. cerevisiae that uses plasmid-based expression of the CRISPR/Cas9 endonuclease and multiple ribozyme-protected single guide RNAs. With this multiplex CRISPR (CRISPRm) system, it is possible to integrate DNA libraries into the chromosome for evolution experiments, and to engineer multiple loci simultaneously. The CRISPRm tools should therefore find use in many higher-order synthetic biology applications to accelerate improvements in industrial microorganisms.

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

Whole organism lineage tracing by combinatorial and cumulative genome editing

PubMed Central

McKenna, Aaron; Findlay, Gregory M.; Gagnon, James A.; Horwitz, Marshall S.; Schier, Alexander F.; Shendure, Jay

2016-01-01

Multicellular systems develop from single cells through distinct lineages. However, current lineage tracing approaches scale poorly to whole, complex organisms. Here we use genome editing to progressively introduce and accumulate diverse mutations in a DNA barcode over multiple rounds of cell division. The barcode, an array of CRISPR/Cas9 target sites, marks cells and enables the elucidation of lineage relationships via the patterns of mutations shared between cells. In cell culture and zebrafish, we show that rates and patterns of editing are tunable, and that thousands of lineage-informative barcode alleles can be generated. By sampling hundreds of thousands of cells from individual zebrafish, we find that most cells in adult organs derive from relatively few embryonic progenitors. In future analyses, genome editing of synthetic target arrays for lineage tracing (GESTALT) can be used to generate large-scale maps of cell lineage in multicellular systems for normal development and disease. PMID:27229144

Sockeye: A 3D Environment for Comparative Genomics

PubMed Central

Montgomery, Stephen B.; Astakhova, Tamara; Bilenky, Mikhail; Birney, Ewan; Fu, Tony; Hassel, Maik; Melsopp, Craig; Rak, Marcin; Robertson, A. Gordon; Sleumer, Monica; Siddiqui, Asim S.; Jones, Steven J.M.

2004-01-01

Comparative genomics techniques are used in bioinformatics analyses to identify the structural and functional properties of DNA sequences. As the amount of available sequence data steadily increases, the ability to perform large-scale comparative analyses has become increasingly relevant. In addition, the growing complexity of genomic feature annotation means that new approaches to genomic visualization need to be explored. We have developed a Java-based application called Sockeye that uses three-dimensional (3D) graphics technology to facilitate the visualization of annotation and conservation across multiple sequences. This software uses the Ensembl database project to import sequence and annotation information from several eukaryotic species. A user can additionally import their own custom sequence and annotation data. Individual annotation objects are displayed in Sockeye by using custom 3D models. Ensembl-derived and imported sequences can be analyzed by using a suite of multiple and pair-wise alignment algorithms. The results of these comparative analyses are also displayed in the 3D environment of Sockeye. By using the Java3D API to visualize genomic data in a 3D environment, we are able to compactly display cross-sequence comparisons. This provides the user with a novel platform for visualizing and comparing genomic feature organization. PMID:15123592

Chromatin Landscapes of Retroviral and Transposon Integration Profiles

PubMed Central

Badhai, Jitendra; Rust, Alistair G.; Rad, Roland; Hilkens, John; Berns, Anton; van Lohuizen, Maarten; Wessels, Lodewyk F. A.; de Ridder, Jeroen

2014-01-01

The ability of retroviruses and transposons to insert their genetic material into host DNA makes them widely used tools in molecular biology, cancer research and gene therapy. However, these systems have biases that may strongly affect research outcomes. To address this issue, we generated very large datasets consisting of to unselected integrations in the mouse genome for the Sleeping Beauty (SB) and piggyBac (PB) transposons, and the Mouse Mammary Tumor Virus (MMTV). We analyzed (epi)genomic features to generate bias maps at both local and genome-wide scales. MMTV showed a remarkably uniform distribution of integrations across the genome. More distinct preferences were observed for the two transposons, with PB showing remarkable resemblance to bias profiles of the Murine Leukemia Virus. Furthermore, we present a model where target site selection is directed at multiple scales. At a large scale, target site selection is similar across systems, and defined by domain-oriented features, namely expression of proximal genes, proximity to CpG islands and to genic features, chromatin compaction and replication timing. Notable differences between the systems are mainly observed at smaller scales, and are directed by a diverse range of features. To study the effect of these biases on integration sites occupied under selective pressure, we turned to insertional mutagenesis (IM) screens. In IM screens, putative cancer genes are identified by finding frequently targeted genomic regions, or Common Integration Sites (CISs). Within three recently completed IM screens, we identified 7%–33% putative false positive CISs, which are likely not the result of the oncogenic selection process. Moreover, results indicate that PB, compared to SB, is more suited to tag oncogenes. PMID:24721906

Functional Genomic Landscape of Human Breast Cancer Drivers, Vulnerabilities, and Resistance.

PubMed

Marcotte, Richard; Sayad, Azin; Brown, Kevin R; Sanchez-Garcia, Felix; Reimand, Jüri; Haider, Maliha; Virtanen, Carl; Bradner, James E; Bader, Gary D; Mills, Gordon B; Pe'er, Dana; Moffat, Jason; Neel, Benjamin G

2016-01-14

Large-scale genomic studies have identified multiple somatic aberrations in breast cancer, including copy number alterations and point mutations. Still, identifying causal variants and emergent vulnerabilities that arise as a consequence of genetic alterations remain major challenges. We performed whole-genome small hairpin RNA (shRNA) "dropout screens" on 77 breast cancer cell lines. Using a hierarchical linear regression algorithm to score our screen results and integrate them with accompanying detailed genetic and proteomic information, we identify vulnerabilities in breast cancer, including candidate "drivers," and reveal general functional genomic properties of cancer cells. Comparisons of gene essentiality with drug sensitivity data suggest potential resistance mechanisms, effects of existing anti-cancer drugs, and opportunities for combination therapy. Finally, we demonstrate the utility of this large dataset by identifying BRD4 as a potential target in luminal breast cancer and PIK3CA mutations as a resistance determinant for BET-inhibitors. Copyright © 2016 Elsevier Inc. All rights reserved.

Whole-Genome Comparison Reveals Novel Genetic Elements That Characterize the Genome of Industrial Strains of Saccharomyces cerevisiae

PubMed Central

Borneman, Anthony R.; Desany, Brian A.; Riches, David; Affourtit, Jason P.; Forgan, Angus H.; Pretorius, Isak S.; Egholm, Michael; Chambers, Paul J.

2011-01-01

Human intervention has subjected the yeast Saccharomyces cerevisiae to multiple rounds of independent domestication and thousands of generations of artificial selection. As a result, this species comprises a genetically diverse collection of natural isolates as well as domesticated strains that are used in specific industrial applications. However the scope of genetic diversity that was captured during the domesticated evolution of the industrial representatives of this important organism remains to be determined. To begin to address this, we have produced whole-genome assemblies of six commercial strains of S. cerevisiae (four wine and two brewing strains). These represent the first genome assemblies produced from S. cerevisiae strains in their industrially-used forms and the first high-quality assemblies for S. cerevisiae strains used in brewing. By comparing these sequences to six existing high-coverage S. cerevisiae genome assemblies, clear signatures were found that defined each industrial class of yeast. This genetic variation was comprised of both single nucleotide polymorphisms and large-scale insertions and deletions, with the latter often being associated with ORF heterogeneity between strains. This included the discovery of more than twenty probable genes that had not been identified previously in the S. cerevisiae genome. Comparison of this large number of S. cerevisiae strains also enabled the characterization of a cluster of five ORFs that have integrated into the genomes of the wine and bioethanol strains on multiple occasions and at diverse genomic locations via what appears to involve the resolution of a circular DNA intermediate. This work suggests that, despite the scrutiny that has been directed at the yeast genome, there remains a significant reservoir of ORFs and novel modes of genetic transmission that may have significant phenotypic impact in this important model and industrial species. PMID:21304888

Analyses of transcriptome sequences reveal multiple ancient large-scale duplication events in the ancestor of Sphagnopsida (Bryophyta)

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

Devos, Nicolas; Szövényi, Péter; Weston, David J.

In this study, the goal of this research was to investigate whether there has been a whole-genome duplication (WGD) in the ancestry of Sphagnum (peatmoss) or the class Sphagnopsida, and to determine if the timing of any such duplication(s) and patterns of paralog retention could help explain the rapid radiation and current ecological dominance of peatmosses.

Analyses of transcriptome sequences reveal multiple ancient large-scale duplication events in the ancestor of Sphagnopsida (Bryophyta)

DOE PAGES

Devos, Nicolas; Szövényi, Péter; Weston, David J.; ...

2016-02-22

In this study, the goal of this research was to investigate whether there has been a whole-genome duplication (WGD) in the ancestry of Sphagnum (peatmoss) or the class Sphagnopsida, and to determine if the timing of any such duplication(s) and patterns of paralog retention could help explain the rapid radiation and current ecological dominance of peatmosses.

CyanoGEBA: A Better Understanding of Cynobacterial Diversity through Large-Scale Genomics (JGI Seventh Annual User Meeting 2012: Genomics of Energy and Environment)

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

Shih, Patrick

2012-03-22

Patrick Shih, representing both the University of California, Berkeley and JGI, gives a talk titled "CyanoGEBA: A Better Understanding of Cynobacterial Diversity through Large-scale Genomics" at the JGI 7th Annual Users Meeting: Genomics of Energy & Environment Meeting on March 22, 2012 in Walnut Creek, California.

CyanoGEBA: A Better Understanding of Cynobacterial Diversity through Large-Scale Genomics (JGI Seventh Annual User Meeting 2012: Genomics of Energy and Environment)

ScienceCinema

Shih, Patrick

2018-01-10

Patrick Shih, representing both the University of California, Berkeley and JGI, gives a talk titled "CyanoGEBA: A Better Understanding of Cynobacterial Diversity through Large-scale Genomics" at the JGI 7th Annual Users Meeting: Genomics of Energy & Environment Meeting on March 22, 2012 in Walnut Creek, California.

SNPassoc: an R package to perform whole genome association studies.

PubMed

González, Juan R; Armengol, Lluís; Solé, Xavier; Guinó, Elisabet; Mercader, Josep M; Estivill, Xavier; Moreno, Víctor

2007-03-01

The popularization of large-scale genotyping projects has led to the widespread adoption of genetic association studies as the tool of choice in the search for single nucleotide polymorphisms (SNPs) underlying susceptibility to complex diseases. Although the analysis of individual SNPs is a relatively trivial task, when the number is large and multiple genetic models need to be explored it becomes necessary a tool to automate the analyses. In order to address this issue, we developed SNPassoc, an R package to carry out most common analyses in whole genome association studies. These analyses include descriptive statistics and exploratory analysis of missing values, calculation of Hardy-Weinberg equilibrium, analysis of association based on generalized linear models (either for quantitative or binary traits), and analysis of multiple SNPs (haplotype and epistasis analysis). Package SNPassoc is available at CRAN from http://cran.r-project.org. A tutorial is available on Bioinformatics online and in http://davinci.crg.es/estivill_lab/snpassoc.

Segmental Duplications and Copy-Number Variation in the Human Genome

PubMed Central

Sharp, Andrew J. ; Locke, Devin P. ; McGrath, Sean D. ; Cheng, Ze ; Bailey, Jeffrey A. ; Vallente, Rhea U. ; Pertz, Lisa M. ; Clark, Royden A. ; Schwartz, Stuart ; Segraves, Rick ; Oseroff, Vanessa V. ; Albertson, Donna G. ; Pinkel, Daniel ; Eichler, Evan E. 

2005-01-01

The human genome contains numerous blocks of highly homologous duplicated sequence. This higher-order architecture provides a substrate for recombination and recurrent chromosomal rearrangement associated with genomic disease. However, an assessment of the role of segmental duplications in normal variation has not yet been made. On the basis of the duplication architecture of the human genome, we defined a set of 130 potential rearrangement hotspots and constructed a targeted bacterial artificial chromosome (BAC) microarray (with 2,194 BACs) to assess copy-number variation in these regions by array comparative genomic hybridization. Using our segmental duplication BAC microarray, we screened a panel of 47 normal individuals, who represented populations from four continents, and we identified 119 regions of copy-number polymorphism (CNP), 73 of which were previously unreported. We observed an equal frequency of duplications and deletions, as well as a 4-fold enrichment of CNPs within hotspot regions, compared with control BACs (P < .000001), which suggests that segmental duplications are a major catalyst of large-scale variation in the human genome. Importantly, segmental duplications themselves were also significantly enriched >4-fold within regions of CNP. Almost without exception, CNPs were not confined to a single population, suggesting that these either are recurrent events, having occurred independently in multiple founders, or were present in early human populations. Our study demonstrates that segmental duplications define hotspots of chromosomal rearrangement, likely acting as mediators of normal variation as well as genomic disease, and it suggests that the consideration of genomic architecture can significantly improve the ascertainment of large-scale rearrangements. Our specialized segmental duplication BAC microarray and associated database of structural polymorphisms will provide an important resource for the future characterization of human genomic disorders. PMID:15918152

Whole genome sequence analysis of Geitlerinema sp. FC II unveils competitive edge of the strain in marine cultivation system for biofuel production.

PubMed

Batchu, Navish Kumar; Khater, Shradha; Patil, Sonal; Nagle, Vinod; Das, Gautam; Bhadra, Bhaskar; Sapre, Ajit; Dasgupta, Santanu

2018-03-05

A filamentous cyanobacteria, Geitlerinema sp. FC II, was isolated from marine algae culture pond at Reliance Industries Limited (RIL), India. The 6.7 Mb draft genome of FC II encodes for 6697 protein coding genes. Analysis of the whole genome sequence revealed presence of nif gene cluster, supporting its capability to fix atmospheric nitrogen. FC II genome contains two variants of sulfide:quinone oxidoreductases (SQR), which is a crucial elector donor in cyanobacterial metabolic processes. FC II is characterized by the presence of multiple CRISPR- Cas (Clustered Regularly Interspaced Short Palindrome Repeats - CRISPR associated proteins) clusters, multiple variants of genes encoding photosystem reaction centres, biosynthetic gene clusters of alkane, polyketides and non-ribosomal peptides. Presence of these pathways will help FC II in gaining an ecological advantage over other strains for biomass production in large scale cultivation system. Hence, FC II may be used for production of biofuel and other industrially important metabolites. Copyright © 2018 Elsevier Inc. All rights reserved.

Genomic signatures of fine-scale local selection in Atlantic salmon suggest involvement of sexual maturation, energy homeostasis and immune defence-related genes.

PubMed

Pritchard, Victoria L; Mäkinen, Hannu; Vähä, Juha-Pekka; Erkinaro, Jaakko; Orell, Panu; Primmer, Craig R

2018-06-01

Elucidating the genetic basis of adaptation to the local environment can improve our understanding of how the diversity of life has evolved. In this study, we used a dense SNP array to identify candidate loci potentially underlying fine-scale local adaptation within a large Atlantic salmon (Salmo salar) population. By combining outlier, gene-environment association and haplotype homozygosity analyses, we identified multiple regions of the genome with strong evidence for diversifying selection. Several of these candidate regions had previously been identified in other studies, demonstrating that the same loci could be adaptively important in Atlantic salmon at subdrainage, regional and continental scales. Notably, we identified signals consistent with local selection around genes associated with variation in sexual maturation, energy homeostasis and immune defence. These included the large-effect age-at-maturity gene vgll3, the known obesity gene mc4r, and major histocompatibility complex II. Most strikingly, we confirmed a genomic region on Ssa09 that was extremely differentiated among subpopulations and that is also a candidate for local selection over the global range of Atlantic salmon. This region colocalized with a haplotype strongly associated with spawning ecotype in sockeye salmon (Oncorhynchus nerka), with circumstantial evidence that the same gene (six6) may be the selective target in both cases. The phenotypic effect of this region in Atlantic salmon remains cryptic, although allelic variation is related to upstream catchment area and covaries with timing of the return spawning migration. Our results further inform management of Atlantic salmon and open multiple avenues for future research. © 2018 John Wiley & Sons Ltd.

pico-PLAZA, a genome database of microbial photosynthetic eukaryotes.

PubMed

Vandepoele, Klaas; Van Bel, Michiel; Richard, Guilhem; Van Landeghem, Sofie; Verhelst, Bram; Moreau, Hervé; Van de Peer, Yves; Grimsley, Nigel; Piganeau, Gwenael

2013-08-01

With the advent of next generation genome sequencing, the number of sequenced algal genomes and transcriptomes is rapidly growing. Although a few genome portals exist to browse individual genome sequences, exploring complete genome information from multiple species for the analysis of user-defined sequences or gene lists remains a major challenge. pico-PLAZA is a web-based resource (http://bioinformatics.psb.ugent.be/pico-plaza/) for algal genomics that combines different data types with intuitive tools to explore genomic diversity, perform integrative evolutionary sequence analysis and study gene functions. Apart from homologous gene families, multiple sequence alignments, phylogenetic trees, Gene Ontology, InterPro and text-mining functional annotations, different interactive viewers are available to study genome organization using gene collinearity and synteny information. Different search functions, documentation pages, export functions and an extensive glossary are available to guide non-expert scientists. To illustrate the versatility of the platform, different case studies are presented demonstrating how pico-PLAZA can be used to functionally characterize large-scale EST/RNA-Seq data sets and to perform environmental genomics. Functional enrichments analysis of 16 Phaeodactylum tricornutum transcriptome libraries offers a molecular view on diatom adaptation to different environments of ecological relevance. Furthermore, we show how complementary genomic data sources can easily be combined to identify marker genes to study the diversity and distribution of algal species, for example in metagenomes, or to quantify intraspecific diversity from environmental strains. © 2013 John Wiley & Sons Ltd and Society for Applied Microbiology.

Random codon re-encoding induces stable reduction of replicative fitness of Chikungunya virus in primate and mosquito cells.

PubMed

Nougairede, Antoine; De Fabritus, Lauriane; Aubry, Fabien; Gould, Ernest A; Holmes, Edward C; de Lamballerie, Xavier

2013-02-01

Large-scale codon re-encoding represents a powerful method of attenuating viruses to generate safe and cost-effective vaccines. In contrast to specific approaches of codon re-encoding which modify genome-scale properties, we evaluated the effects of random codon re-encoding on the re-emerging human pathogen Chikungunya virus (CHIKV), and assessed the stability of the resultant viruses during serial in cellulo passage. Using different combinations of three 1.4 kb randomly re-encoded regions located throughout the CHIKV genome six codon re-encoded viruses were obtained. Introducing a large number of slightly deleterious synonymous mutations reduced the replicative fitness of CHIKV in both primate and arthropod cells, demonstrating the impact of synonymous mutations on fitness. Decrease of replicative fitness correlated with the extent of re-encoding, an observation that may assist in the modulation of viral attenuation. The wild-type and two re-encoded viruses were passaged 50 times either in primate or insect cells, or in each cell line alternately. These viruses were analyzed using detailed fitness assays, complete genome sequences and the analysis of intra-population genetic diversity. The response to codon re-encoding and adaptation to culture conditions occurred simultaneously, resulting in significant replicative fitness increases for both re-encoded and wild type viruses. Importantly, however, the most re-encoded virus failed to recover its replicative fitness. Evolution of these viruses in response to codon re-encoding was largely characterized by the emergence of both synonymous and non-synonymous mutations, sometimes located in genomic regions other than those involving re-encoding, and multiple convergent and compensatory mutations. However, there was a striking absence of codon reversion (<0.4%). Finally, multiple mutations were rapidly fixed in primate cells, whereas mosquito cells acted as a brake on evolution. In conclusion, random codon re-encoding provides important information on the evolution and genetic stability of CHIKV viruses and could be exploited to develop a safe, live attenuated CHIKV vaccine.

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.

Analyses of transcriptome sequences reveal multiple ancient large-scale duplication events in the ancestor of Sphagnopsida (Bryophyta).

PubMed

Devos, Nicolas; Szövényi, Péter; Weston, David J; Rothfels, Carl J; Johnson, Matthew G; Shaw, A Jonathan

2016-07-01

The goal of this research was to investigate whether there has been a whole-genome duplication (WGD) in the ancestry of Sphagnum (peatmoss) or the class Sphagnopsida, and to determine if the timing of any such duplication(s) and patterns of paralog retention could help explain the rapid radiation and current ecological dominance of peatmosses. RNA sequencing (RNA-seq) data were generated for nine taxa in Sphagnopsida (Bryophyta). Analyses of frequency plots for synonymous substitutions per synonymous site (Ks ) between paralogous gene pairs and reconciliation of 578 gene trees were conducted to assess evidence of large-scale or genome-wide duplication events in each transcriptome. Both Ks frequency plots and gene tree-based analyses indicate multiple duplication events in the history of the Sphagnopsida. The most recent WGD event predates divergence of Sphagnum from the two other genera of Sphagnopsida. Duplicate retention is highly variable across species, which might be best explained by local adaptation. Our analyses indicate that the last WGD could have been an important factor underlying the diversification of peatmosses and facilitated their rise to ecological dominance in peatlands. The timing of the duplication events and their significance in the evolutionary history of peat mosses are discussed. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Convergence between biological, behavioural and genetic determinants of obesity.

PubMed

Ghosh, Sujoy; Bouchard, Claude

2017-12-01

Multiple biological, behavioural and genetic determinants or correlates of obesity have been identified to date. Genome-wide association studies (GWAS) have contributed to the identification of more than 100 obesity-associated genetic variants, but their roles in causal processes leading to obesity remain largely unknown. Most variants are likely to have tissue-specific regulatory roles through joint contributions to biological pathways and networks, through changes in gene expression that influence quantitative traits, or through the regulation of the epigenome. The recent availability of large-scale functional genomics resources provides an opportunity to re-examine obesity GWAS data to begin elucidating the function of genetic variants. Interrogation of knockout mouse phenotype resources provides a further avenue to test for evidence of convergence between genetic variation and biological or behavioural determinants of obesity.

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.

Whole Genome Analysis of 132 Clinical Saccharomyces cerevisiae Strains Reveals Extensive Ploidy Variation

PubMed Central

Zhu, Yuan O.; Sherlock, Gavin; Petrov, Dmitri A.

2016-01-01

Budding yeast has undergone several independent transitions from commercial to clinical lifestyles. The frequency of such transitions suggests that clinical yeast strains are derived from environmentally available yeast populations, including commercial sources. However, despite their important role in adaptive evolution, the prevalence of polyploidy and aneuploidy has not been extensively analyzed in clinical strains. In this study, we have looked for patterns governing the transition to clinical invasion in the largest screen of clinical yeast isolates to date. In particular, we have focused on the hypothesis that ploidy changes have influenced adaptive processes. We sequenced 144 yeast strains, 132 of which are clinical isolates. We found pervasive large-scale genomic variation in both overall ploidy (34% of strains identified as 3n/4n) and individual chromosomal copy numbers (36% of strains identified as aneuploid). We also found evidence for the highly dynamic nature of yeast genomes, with 35 strains showing partial chromosomal copy number changes and eight strains showing multiple independent chromosomal events. Intriguingly, a lineage identified to be baker’s/commercial derived with a unique damaging mutation in NDC80 was particularly prone to polyploidy, with 83% of its members being triploid or tetraploid. Polyploidy was in turn associated with a >2× increase in aneuploidy rates as compared to other lineages. This dataset provides a rich source of information on the genomics of clinical yeast strains and highlights the potential importance of large-scale genomic copy variation in yeast adaptation. PMID:27317778

Prokaryotic Gene Clusters: A Rich Toolbox for Synthetic Biology

PubMed Central

Fischbach, Michael; Voigt, Christopher A.

2014-01-01

Bacteria construct elaborate nanostructures, obtain nutrients and energy from diverse sources, synthesize complex molecules, and implement signal processing to react to their environment. These complex phenotypes require the coordinated action of multiple genes, which are often encoded in a contiguous region of the genome, referred to as a gene cluster. Gene clusters sometimes contain all of the genes necessary and sufficient for a particular function. As an evolutionary mechanism, gene clusters facilitate the horizontal transfer of the complete function between species. Here, we review recent work on a number of clusters whose functions are relevant to biotechnology. Engineering these clusters has been hindered by their regulatory complexity, the need to balance the expression of many genes, and a lack of tools to design and manipulate DNA at this scale. Advances in synthetic biology will enable the large-scale bottom-up engineering of the clusters to optimize their functions, wake up cryptic clusters, or to transfer them between organisms. Understanding and manipulating gene clusters will move towards an era of genome engineering, where multiple functions can be “mixed-and-matched” to create a designer organism. PMID:21154668

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

CNVcaller: highly efficient and widely applicable software for detecting copy number variations in large populations.

PubMed

Wang, Xihong; Zheng, Zhuqing; Cai, Yudong; Chen, Ting; Li, Chao; Fu, Weiwei; Jiang, Yu

2017-12-01

The increasing amount of sequencing data available for a wide variety of species can be theoretically used for detecting copy number variations (CNVs) at the population level. However, the growing sample sizes and the divergent complexity of nonhuman genomes challenge the efficiency and robustness of current human-oriented CNV detection methods. Here, we present CNVcaller, a read-depth method for discovering CNVs in population sequencing data. The computational speed of CNVcaller was 1-2 orders of magnitude faster than CNVnator and Genome STRiP for complex genomes with thousands of unmapped scaffolds. CNV detection of 232 goats required only 1.4 days on a single compute node. Additionally, the Mendelian consistency of sheep trios indicated that CNVcaller mitigated the influence of high proportions of gaps and misassembled duplications in the nonhuman reference genome assembly. Furthermore, multiple evaluations using real sheep and human data indicated that CNVcaller achieved the best accuracy and sensitivity for detecting duplications. The fast generalized detection algorithms included in CNVcaller overcome prior computational barriers for detecting CNVs in large-scale sequencing data with complex genomic structures. Therefore, CNVcaller promotes population genetic analyses of functional CNVs in more species. © The Authors 2017. Published by Oxford University Press.

CNVcaller: highly efficient and widely applicable software for detecting copy number variations in large populations

PubMed Central

Wang, Xihong; Zheng, Zhuqing; Cai, Yudong; Chen, Ting; Li, Chao; Fu, Weiwei

2017-01-01

Abstract Background The increasing amount of sequencing data available for a wide variety of species can be theoretically used for detecting copy number variations (CNVs) at the population level. However, the growing sample sizes and the divergent complexity of nonhuman genomes challenge the efficiency and robustness of current human-oriented CNV detection methods. Results Here, we present CNVcaller, a read-depth method for discovering CNVs in population sequencing data. The computational speed of CNVcaller was 1–2 orders of magnitude faster than CNVnator and Genome STRiP for complex genomes with thousands of unmapped scaffolds. CNV detection of 232 goats required only 1.4 days on a single compute node. Additionally, the Mendelian consistency of sheep trios indicated that CNVcaller mitigated the influence of high proportions of gaps and misassembled duplications in the nonhuman reference genome assembly. Furthermore, multiple evaluations using real sheep and human data indicated that CNVcaller achieved the best accuracy and sensitivity for detecting duplications. Conclusions The fast generalized detection algorithms included in CNVcaller overcome prior computational barriers for detecting CNVs in large-scale sequencing data with complex genomic structures. Therefore, CNVcaller promotes population genetic analyses of functional CNVs in more species. PMID:29220491

Merlin: Computer-Aided Oligonucleotide Design for Large Scale Genome Engineering with MAGE.

PubMed

Quintin, Michael; Ma, Natalie J; Ahmed, Samir; Bhatia, Swapnil; Lewis, Aaron; Isaacs, Farren J; Densmore, Douglas

2016-06-17

Genome engineering technologies now enable precise manipulation of organism genotype, but can be limited in scalability by their design requirements. Here we describe Merlin ( http://merlincad.org ), an open-source web-based tool to assist biologists in designing experiments using multiplex automated genome engineering (MAGE). Merlin provides methods to generate pools of single-stranded DNA oligonucleotides (oligos) for MAGE experiments by performing free energy calculation and BLAST scoring on a sliding window spanning the targeted site. These oligos are designed not only to improve recombination efficiency, but also to minimize off-target interactions. The application further assists experiment planning by reporting predicted allelic replacement rates after multiple MAGE cycles, and enables rapid result validation by generating primer sequences for multiplexed allele-specific colony PCR. Here we describe the Merlin oligo and primer design procedures and validate their functionality compared to OptMAGE by eliminating seven AvrII restriction sites from the Escherichia coli genome.

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.

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.

Understanding the direction of evolution in Burkholderia glumae through comparative genomics.

PubMed

Lee, Hyun-Hee; Park, Jungwook; Kim, Jinnyun; Park, Inmyoung; Seo, Young-Su

2016-02-01

Members of the genus Burkholderia occupy remarkably diverse niches, with genome sizes ranging from ~3.75 to 11.29 Mbp. The genome of Burkholderia glumae ranges in size from ~5.81 to 7.89 Mbp. Unlike other plant pathogenic bacteria, B. glumae can infect a wide range of monocot and dicot plants. Comparative genome analysis of B. glumae strains can provide insight into genome variation as well as differential features of whole metabolism or pathways between multiple strains of B. glumae infecting the same host. Comparative analysis of complete genomes among B. glumae BGR1, B. glumae LMG 2196, and B. glumae PG1 revealed the largest departmentalization of genes onto separate replicons in B. glumae BGR1 and considerable downsizing of the genome in B. glumae LMG 2196. In addition, the presence of large-scale evolutionary events such as rearrangement and inversion and the development of highly specialized systems were found to be related to virulence-associated features in the three B. glumae strains. This connection may explain why this bacterium broadens its host range and reinforces its interaction with hosts.

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

Fast and Accurate Approximation to Significance Tests in Genome-Wide Association Studies

PubMed Central

Zhang, Yu; Liu, Jun S.

2011-01-01

Genome-wide association studies commonly involve simultaneous tests of millions of single nucleotide polymorphisms (SNP) for disease association. The SNPs in nearby genomic regions, however, are often highly correlated due to linkage disequilibrium (LD, a genetic term for correlation). Simple Bonferonni correction for multiple comparisons is therefore too conservative. Permutation tests, which are often employed in practice, are both computationally expensive for genome-wide studies and limited in their scopes. We present an accurate and computationally efficient method, based on Poisson de-clumping heuristics, for approximating genome-wide significance of SNP associations. Compared with permutation tests and other multiple comparison adjustment approaches, our method computes the most accurate and robust p-value adjustments for millions of correlated comparisons within seconds. We demonstrate analytically that the accuracy and the efficiency of our method are nearly independent of the sample size, the number of SNPs, and the scale of p-values to be adjusted. In addition, our method can be easily adopted to estimate false discovery rate. When applied to genome-wide SNP datasets, we observed highly variable p-value adjustment results evaluated from different genomic regions. The variation in adjustments along the genome, however, are well conserved between the European and the African populations. The p-value adjustments are significantly correlated with LD among SNPs, recombination rates, and SNP densities. Given the large variability of sequence features in the genome, we further discuss a novel approach of using SNP-specific (local) thresholds to detect genome-wide significant associations. This article has supplementary material online. PMID:22140288

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.

PATIKA: an integrated visual environment for collaborative construction and analysis of cellular pathways.

PubMed

Demir, E; Babur, O; Dogrusoz, U; Gursoy, A; Nisanci, G; Cetin-Atalay, R; Ozturk, M

2002-07-01

Availability of the sequences of entire genomes shifts the scientific curiosity towards the identification of function of the genomes in large scale as in genome studies. In the near future, data produced about cellular processes at molecular level will accumulate with an accelerating rate as a result of proteomics studies. In this regard, it is essential to develop tools for storing, integrating, accessing, and analyzing this data effectively. We define an ontology for a comprehensive representation of cellular events. The ontology presented here enables integration of fragmented or incomplete pathway information and supports manipulation and incorporation of the stored data, as well as multiple levels of abstraction. Based on this ontology, we present the architecture of an integrated environment named Patika (Pathway Analysis Tool for Integration and Knowledge Acquisition). Patika is composed of a server-side, scalable, object-oriented database and client-side editors to provide an integrated, multi-user environment for visualizing and manipulating network of cellular events. This tool features automated pathway layout, functional computation support, advanced querying and a user-friendly graphical interface. We expect that Patika will be a valuable tool for rapid knowledge acquisition, microarray generated large-scale data interpretation, disease gene identification, and drug development. A prototype of Patika is available upon request from the authors.

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

A hybrid computational strategy to address WGS variant analysis in >5000 samples.

PubMed

Huang, Zhuoyi; Rustagi, Navin; Veeraraghavan, Narayanan; Carroll, Andrew; Gibbs, Richard; Boerwinkle, Eric; Venkata, Manjunath Gorentla; Yu, Fuli

2016-09-10

The decreasing costs of sequencing are driving the need for cost effective and real time variant calling of whole genome sequencing data. The scale of these projects are far beyond the capacity of typical computing resources available with most research labs. Other infrastructures like the cloud AWS environment and supercomputers also have limitations due to which large scale joint variant calling becomes infeasible, and infrastructure specific variant calling strategies either fail to scale up to large datasets or abandon joint calling strategies. We present a high throughput framework including multiple variant callers for single nucleotide variant (SNV) calling, which leverages hybrid computing infrastructure consisting of cloud AWS, supercomputers and local high performance computing infrastructures. We present a novel binning approach for large scale joint variant calling and imputation which can scale up to over 10,000 samples while producing SNV callsets with high sensitivity and specificity. As a proof of principle, we present results of analysis on Cohorts for Heart And Aging Research in Genomic Epidemiology (CHARGE) WGS freeze 3 dataset in which joint calling, imputation and phasing of over 5300 whole genome samples was produced in under 6 weeks using four state-of-the-art callers. The callers used were SNPTools, GATK-HaplotypeCaller, GATK-UnifiedGenotyper and GotCloud. We used Amazon AWS, a 4000-core in-house cluster at Baylor College of Medicine, IBM power PC Blue BioU at Rice and Rhea at Oak Ridge National Laboratory (ORNL) for the computation. AWS was used for joint calling of 180 TB of BAM files, and ORNL and Rice supercomputers were used for the imputation and phasing step. All other steps were carried out on the local compute cluster. The entire operation used 5.2 million core hours and only transferred a total of 6 TB of data across the platforms. Even with increasing sizes of whole genome datasets, ensemble joint calling of SNVs for low coverage data can be accomplished in a scalable, cost effective and fast manner by using heterogeneous computing platforms without compromising on the quality of variants.

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

RGAugury: a pipeline for genome-wide prediction of resistance gene analogs (RGAs) in plants.

PubMed

Li, Pingchuan; Quan, Xiande; Jia, Gaofeng; Xiao, Jin; Cloutier, Sylvie; You, Frank M

2016-11-02

Resistance gene analogs (RGAs), such as NBS-encoding proteins, receptor-like protein kinases (RLKs) and receptor-like proteins (RLPs), are potential R-genes that contain specific conserved domains and motifs. Thus, RGAs can be predicted based on their conserved structural features using bioinformatics tools. Computer programs have been developed for the identification of individual domains and motifs from the protein sequences of RGAs but none offer a systematic assessment of the different types of RGAs. A user-friendly and efficient pipeline is needed for large-scale genome-wide RGA predictions of the growing number of sequenced plant genomes. An integrative pipeline, named RGAugury, was developed to automate RGA prediction. The pipeline first identifies RGA-related protein domains and motifs, namely nucleotide binding site (NB-ARC), leucine rich repeat (LRR), transmembrane (TM), serine/threonine and tyrosine kinase (STTK), lysin motif (LysM), coiled-coil (CC) and Toll/Interleukin-1 receptor (TIR). RGA candidates are identified and classified into four major families based on the presence of combinations of these RGA domains and motifs: NBS-encoding, TM-CC, and membrane associated RLP and RLK. All time-consuming analyses of the pipeline are paralleled to improve performance. The pipeline was evaluated using the well-annotated Arabidopsis genome. A total of 98.5, 85.2, and 100 % of the reported NBS-encoding genes, membrane associated RLPs and RLKs were validated, respectively. The pipeline was also successfully applied to predict RGAs for 50 sequenced plant genomes. A user-friendly web interface was implemented to ease command line operations, facilitate visualization and simplify result management for multiple datasets. RGAugury is an efficiently integrative bioinformatics tool for large scale genome-wide identification of RGAs. It is freely available at Bitbucket: https://bitbucket.org/yaanlpc/rgaugury .

Genome-Wide Motif Statistics are Shaped by DNA Binding Proteins over Evolutionary Time Scales

NASA Astrophysics Data System (ADS)

Qian, Long; Kussell, Edo

2016-10-01

The composition of a genome with respect to all possible short DNA motifs impacts the ability of DNA binding proteins to locate and bind their target sites. Since nonfunctional DNA binding can be detrimental to cellular functions and ultimately to organismal fitness, organisms could benefit from reducing the number of nonfunctional DNA binding sites genome wide. Using in vitro measurements of binding affinities for a large collection of DNA binding proteins, in multiple species, we detect a significant global avoidance of weak binding sites in genomes. We demonstrate that the underlying evolutionary process leaves a distinct genomic hallmark in that similar words have correlated frequencies, a signal that we detect in all species across domains of life. We consider the possibility that natural selection against weak binding sites contributes to this process, and using an evolutionary model we show that the strength of selection needed to maintain global word compositions is on the order of point mutation rates. Likewise, we show that evolutionary mechanisms based on interference of protein-DNA binding with replication and mutational repair processes could yield similar results and operate with similar rates. On the basis of these modeling and bioinformatic results, we conclude that genome-wide word compositions have been molded by DNA binding proteins acting through tiny evolutionary steps over time scales spanning millions of generations.

Shared regulatory sites are abundant in the human genome and shed light on genome evolution and disease pleiotropy.

PubMed

Tong, Pin; Monahan, Jack; Prendergast, James G D

2017-03-01

Large-scale gene expression datasets are providing an increasing understanding of the location of cis-eQTLs in the human genome and their role in disease. However, little is currently known regarding the extent of regulatory site-sharing between genes. This is despite it having potentially wide-ranging implications, from the determination of the way in which genetic variants may shape multiple phenotypes to the understanding of the evolution of human gene order. By first identifying the location of non-redundant cis-eQTLs, we show that regulatory site-sharing is a relatively common phenomenon in the human genome, with over 10% of non-redundant regulatory variants linked to the expression of multiple nearby genes. We show that these shared, local regulatory sites are linked to high levels of chromatin looping between the regulatory sites and their associated genes. In addition, these co-regulated gene modules are found to be strongly conserved across mammalian species, suggesting that shared regulatory sites have played an important role in shaping human gene order. The association of these shared cis-eQTLs with multiple genes means they also appear to be unusually important in understanding the genetics of human phenotypes and pleiotropy, with shared regulatory sites more often linked to multiple human phenotypes than other regulatory variants. This study shows that regulatory site-sharing is likely an underappreciated aspect of gene regulation and has important implications for the understanding of various biological phenomena, including how the two and three dimensional structures of the genome have been shaped and the potential causes of disease pleiotropy outside coding regions.

A universal genomic coordinate translator for comparative genomics

PubMed Central

2014-01-01

Background Genomic duplications constitute major events in the evolution of species, allowing paralogous copies of genes to take on fine-tuned biological roles. Unambiguously identifying the orthology relationship between copies across multiple genomes can be resolved by synteny, i.e. the conserved order of genomic sequences. However, a comprehensive analysis of duplication events and their contributions to evolution would require all-to-all genome alignments, which increases at N2 with the number of available genomes, N. Results Here, we introduce Kraken, software that omits the all-to-all requirement by recursively traversing a graph of pairwise alignments and dynamically re-computing orthology. Kraken scales linearly with the number of targeted genomes, N, which allows for including large numbers of genomes in analyses. We first evaluated the method on the set of 12 Drosophila genomes, finding that orthologous correspondence computed indirectly through a graph of multiple synteny maps comes at minimal cost in terms of sensitivity, but reduces overall computational runtime by an order of magnitude. We then used the method on three well-annotated mammalian genomes, human, mouse, and rat, and show that up to 93% of protein coding transcripts have unambiguous pairwise orthologous relationships across the genomes. On a nucleotide level, 70 to 83% of exons match exactly at both splice junctions, and up to 97% on at least one junction. We last applied Kraken to an RNA-sequencing dataset from multiple vertebrates and diverse tissues, where we confirmed that brain-specific gene family members, i.e. one-to-many or many-to-many homologs, are more highly correlated across species than single-copy (i.e. one-to-one homologous) genes. Not limited to protein coding genes, Kraken also identifies thousands of newly identified transcribed loci, likely non-coding RNAs that are consistently transcribed in human, chimpanzee and gorilla, and maintain significant correlation of expression levels across species. Conclusions Kraken is a computational genome coordinate translator that facilitates cross-species comparisons, distinguishes orthologs from paralogs, and does not require costly all-to-all whole genome mappings. Kraken is freely available under LPGL from http://github.com/nedaz/kraken. PMID:24976580

A universal genomic coordinate translator for comparative genomics.

PubMed

Zamani, Neda; Sundström, Görel; Meadows, Jennifer R S; Höppner, Marc P; Dainat, Jacques; Lantz, Henrik; Haas, Brian J; Grabherr, Manfred G

2014-06-30

Genomic duplications constitute major events in the evolution of species, allowing paralogous copies of genes to take on fine-tuned biological roles. Unambiguously identifying the orthology relationship between copies across multiple genomes can be resolved by synteny, i.e. the conserved order of genomic sequences. However, a comprehensive analysis of duplication events and their contributions to evolution would require all-to-all genome alignments, which increases at N2 with the number of available genomes, N. Here, we introduce Kraken, software that omits the all-to-all requirement by recursively traversing a graph of pairwise alignments and dynamically re-computing orthology. Kraken scales linearly with the number of targeted genomes, N, which allows for including large numbers of genomes in analyses. We first evaluated the method on the set of 12 Drosophila genomes, finding that orthologous correspondence computed indirectly through a graph of multiple synteny maps comes at minimal cost in terms of sensitivity, but reduces overall computational runtime by an order of magnitude. We then used the method on three well-annotated mammalian genomes, human, mouse, and rat, and show that up to 93% of protein coding transcripts have unambiguous pairwise orthologous relationships across the genomes. On a nucleotide level, 70 to 83% of exons match exactly at both splice junctions, and up to 97% on at least one junction. We last applied Kraken to an RNA-sequencing dataset from multiple vertebrates and diverse tissues, where we confirmed that brain-specific gene family members, i.e. one-to-many or many-to-many homologs, are more highly correlated across species than single-copy (i.e. one-to-one homologous) genes. Not limited to protein coding genes, Kraken also identifies thousands of newly identified transcribed loci, likely non-coding RNAs that are consistently transcribed in human, chimpanzee and gorilla, and maintain significant correlation of expression levels across species. Kraken is a computational genome coordinate translator that facilitates cross-species comparisons, distinguishes orthologs from paralogs, and does not require costly all-to-all whole genome mappings. Kraken is freely available under LPGL from http://github.com/nedaz/kraken.

Genome resequencing in Populus: Revealing large-scale genome variation and implications on specialized-trait genomics

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

Muchero, Wellington; Labbe, Jessy L; Priya, Ranjan

2014-01-01

To date, Populus ranks among a few plant species with a complete genome sequence and other highly developed genomic resources. With the first genome sequence among all tree species, Populus has been adopted as a suitable model organism for genomic studies in trees. However, far from being just a model species, Populus is a key renewable economic resource that plays a significant role in providing raw materials for the biofuel and pulp and paper industries. Therefore, aside from leading frontiers of basic tree molecular biology and ecological research, Populus leads frontiers in addressing global economic challenges related to fuel andmore » fiber production. The latter fact suggests that research aimed at improving quality and quantity of Populus as a raw material will likely drive the pursuit of more targeted and deeper research in order to unlock the economic potential tied in molecular biology processes that drive this tree species. Advances in genome sequence-driven technologies, such as resequencing individual genotypes, which in turn facilitates large scale SNP discovery and identification of large scale polymorphisms are key determinants of future success in these initiatives. In this treatise we discuss implications of genome sequence-enable technologies on Populus genomic and genetic studies of complex and specialized-traits.« less

Academic-industrial partnerships in drug discovery in the age of genomics.

PubMed

Harris, Tim; Papadopoulos, Stelios; Goldstein, David B

2015-06-01

Many US FDA-approved drugs have been developed through productive interactions between the biotechnology industry and academia. Technological breakthroughs in genomics, in particular large-scale sequencing of human genomes, is creating new opportunities to understand the biology of disease and to identify high-value targets relevant to a broad range of disorders. However, the scale of the work required to appropriately analyze large genomic and clinical data sets is challenging industry to develop a broader view of what areas of work constitute precompetitive research. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Rates and Genomic Consequences of Spontaneous Mutational Events in Drosophila melanogaster

PubMed Central

Schrider, Daniel R.; Houle, David; Lynch, Michael; Hahn, Matthew W.

2013-01-01

Because spontaneous mutation is the source of all genetic diversity, measuring mutation rates can reveal how natural selection drives patterns of variation within and between species. We sequenced eight genomes produced by a mutation-accumulation experiment in Drosophila melanogaster. Our analysis reveals that point mutation and small indel rates vary significantly between the two different genetic backgrounds examined. We also find evidence that ∼2% of mutational events affect multiple closely spaced nucleotides. Unlike previous similar experiments, we were able to estimate genome-wide rates of large deletions and tandem duplications. These results suggest that, at least in inbred lines like those examined here, mutational pressures may result in net growth rather than contraction of the Drosophila genome. By comparing our mutation rate estimates to polymorphism data, we are able to estimate the fraction of new mutations that are eliminated by purifying selection. These results suggest that ∼99% of duplications and deletions are deleterious—making them 10 times more likely to be removed by selection than nonsynonymous mutations. Our results illuminate not only the rates of new small- and large-scale mutations, but also the selective forces that they encounter once they arise. PMID:23733788

Extreme-Scale De Novo Genome Assembly

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

Georganas, Evangelos; Hofmeyr, Steven; Egan, Rob

De novo whole genome assembly reconstructs genomic sequence from short, overlapping, and potentially erroneous DNA segments and is one of the most important computations in modern genomics. This work presents HipMER, a high-quality end-to-end de novo assembler designed for extreme scale analysis, via efficient parallelization of the Meraculous code. Genome assembly software has many components, each of which stresses different components of a computer system. This chapter explains the computational challenges involved in each step of the HipMer pipeline, the key distributed data structures, and communication costs in detail. We present performance results of assembling the human genome and themore » large hexaploid wheat genome on large supercomputers up to tens of thousands of cores.« less

GenomeVista

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

Poliakov, Alexander; Couronne, Olivier

2002-11-04

Aligning large vertebrate genomes that are structurally complex poses a variety of problems not encountered on smaller scales. Such genomes are rich in repetitive elements and contain multiple segmental duplications, which increases the difficulty of identifying true orthologous SNA segments in alignments. The sizes of the sequences make many alignment algorithms designed for comparing single proteins extremely inefficient when processing large genomic intervals. We integrated both local and global alignment tools and developed a suite of programs for automatically aligning large vertebrate genomes and identifying conserved non-coding regions in the alignments. Our method uses the BLAT local alignment program tomore » find anchors on the base genome to identify regions of possible homology for a query sequence. These regions are postprocessed to find the best candidates which are then globally aligned using the AVID global alignment program. In the last step conserved non-coding segments are identified using VISTA. Our methods are fast and the resulting alignments exhibit a high degree of sensitivity, covering more than 90% of known coding exons in the human genome. The GenomeVISTA software is a suite of Perl programs that is built on a MySQL database platform. The scheduler gets control data from the database, builds a queve of jobs, and dispatches them to a PC cluster for execution. The main program, running on each node of the cluster, processes individual sequences. A Perl library acts as an interface between the database and the above programs. The use of a separate library allows the programs to function independently of the database schema. The library also improves on the standard Perl MySQL database interfere package by providing auto-reconnect functionality and improved error handling.« less

Sequencing of the large dsDNA genome of Oryctes rhinoceros nudivirus using multiple displacement amplification of nanogram amounts of virus DNA.

PubMed

Wang, Yongjie; Kleespies, Regina G; Ramle, Moslim B; Jehle, Johannes A

2008-09-01

The genomic sequence analysis of many large dsDNA viruses is hampered by the lack of enough sample materials. Here, we report a whole genome amplification of the Oryctes rhinoceros nudivirus (OrNV) isolate Ma07 starting from as few as about 10 ng of purified viral DNA by application of phi29 DNA polymerase- and exonuclease-resistant random hexamer-based multiple displacement amplification (MDA) method. About 60 microg of high molecular weight DNA with fragment sizes of up to 25 kbp was amplified. A genomic DNA clone library was generated using the product DNA. After 8-fold sequencing coverage, the 127,615 bp of OrNV whole genome was sequenced successfully. The results demonstrate that the MDA-based whole genome amplification enables rapid access to genomic information from exiguous virus samples.

Genomic Sequence around Butterfly Wing Development Genes: Annotation and Comparative Analysis

PubMed Central

Conceição, Inês C.; Long, Anthony D.; Gruber, Jonathan D.; Beldade, Patrícia

2011-01-01

Background Analysis of genomic sequence allows characterization of genome content and organization, and access beyond gene-coding regions for identification of functional elements. BAC libraries, where relatively large genomic regions are made readily available, are especially useful for species without a fully sequenced genome and can increase genomic coverage of phylogenetic and biological diversity. For example, no butterfly genome is yet available despite the unique genetic and biological properties of this group, such as diversified wing color patterns. The evolution and development of these patterns is being studied in a few target species, including Bicyclus anynana, where a whole-genome BAC library allows targeted access to large genomic regions. Methodology/Principal Findings We characterize ∼1.3 Mb of genomic sequence around 11 selected genes expressed in B. anynana developing wings. Extensive manual curation of in silico predictions, also making use of a large dataset of expressed genes for this species, identified repetitive elements and protein coding sequence, and highlighted an expansion of Alcohol dehydrogenase genes. Comparative analysis with orthologous regions of the lepidopteran reference genome allowed assessment of conservation of fine-scale synteny (with detection of new inversions and translocations) and of DNA sequence (with detection of high levels of conservation of non-coding regions around some, but not all, developmental genes). Conclusions The general properties and organization of the available B. anynana genomic sequence are similar to the lepidopteran reference, despite the more than 140 MY divergence. Our results lay the groundwork for further studies of new interesting findings in relation to both coding and non-coding sequence: 1) the Alcohol dehydrogenase expansion with higher similarity between the five tandemly-repeated B. anynana paralogs than with the corresponding B. mori orthologs, and 2) the high conservation of non-coding sequence around the genes wingless and Ecdysone receptor, both involved in multiple developmental processes including wing pattern formation. PMID:21909358

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

Comparative Microbial Modules Resource: Generation and Visualization of Multi-species Biclusters

PubMed Central

Bate, Ashley; Eichenberger, Patrick; Bonneau, Richard

2011-01-01

The increasing abundance of large-scale, high-throughput datasets for many closely related organisms provides opportunities for comparative analysis via the simultaneous biclustering of datasets from multiple species. These analyses require a reformulation of how to organize multi-species datasets and visualize comparative genomics data analyses results. Recently, we developed a method, multi-species cMonkey, which integrates heterogeneous high-throughput datatypes from multiple species to identify conserved regulatory modules. Here we present an integrated data visualization system, built upon the Gaggle, enabling exploration of our method's results (available at http://meatwad.bio.nyu.edu/cmmr.html). The system can also be used to explore other comparative genomics datasets and outputs from other data analysis procedures – results from other multiple-species clustering programs or from independent clustering of different single-species datasets. We provide an example use of our system for two bacteria, Escherichia coli and Salmonella Typhimurium. We illustrate the use of our system by exploring conserved biclusters involved in nitrogen metabolism, uncovering a putative function for yjjI, a currently uncharacterized gene that we predict to be involved in nitrogen assimilation. PMID:22144874

Comparative microbial modules resource: generation and visualization of multi-species biclusters.

PubMed

Kacmarczyk, Thadeous; Waltman, Peter; Bate, Ashley; Eichenberger, Patrick; Bonneau, Richard

2011-12-01

The increasing abundance of large-scale, high-throughput datasets for many closely related organisms provides opportunities for comparative analysis via the simultaneous biclustering of datasets from multiple species. These analyses require a reformulation of how to organize multi-species datasets and visualize comparative genomics data analyses results. Recently, we developed a method, multi-species cMonkey, which integrates heterogeneous high-throughput datatypes from multiple species to identify conserved regulatory modules. Here we present an integrated data visualization system, built upon the Gaggle, enabling exploration of our method's results (available at http://meatwad.bio.nyu.edu/cmmr.html). The system can also be used to explore other comparative genomics datasets and outputs from other data analysis procedures - results from other multiple-species clustering programs or from independent clustering of different single-species datasets. We provide an example use of our system for two bacteria, Escherichia coli and Salmonella Typhimurium. We illustrate the use of our system by exploring conserved biclusters involved in nitrogen metabolism, uncovering a putative function for yjjI, a currently uncharacterized gene that we predict to be involved in nitrogen assimilation. © 2011 Kacmarczyk et al.

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.

Design of DNA pooling to allow incorporation of covariates in rare variants analysis.

PubMed

Guan, Weihua; Li, Chun

2014-01-01

Rapid advances in next-generation sequencing technologies facilitate genetic association studies of an increasingly wide array of rare variants. To capture the rare or less common variants, a large number of individuals will be needed. However, the cost of a large scale study using whole genome or exome sequencing is still high. DNA pooling can serve as a cost-effective approach, but with a potential limitation that the identity of individual genomes would be lost and therefore individual characteristics and environmental factors could not be adjusted in association analysis, which may result in power loss and a biased estimate of genetic effect. For case-control studies, we propose a design strategy for pool creation and an analysis strategy that allows covariate adjustment, using multiple imputation technique. Simulations show that our approach can obtain reasonable estimate for genotypic effect with only slight loss of power compared to the much more expensive approach of sequencing individual genomes. Our design and analysis strategies enable more powerful and cost-effective sequencing studies of complex diseases, while allowing incorporation of covariate adjustment.

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...

A De-Novo Genome Analysis Pipeline (DeNoGAP) for large-scale comparative prokaryotic genomics studies.

PubMed

Thakur, Shalabh; Guttman, David S

2016-06-30

Comparative analysis of whole genome sequence data from closely related prokaryotic species or strains is becoming an increasingly important and accessible approach for addressing both fundamental and applied biological questions. While there are number of excellent tools developed for performing this task, most scale poorly when faced with hundreds of genome sequences, and many require extensive manual curation. We have developed a de-novo genome analysis pipeline (DeNoGAP) for the automated, iterative and high-throughput analysis of data from comparative genomics projects involving hundreds of whole genome sequences. The pipeline is designed to perform reference-assisted and de novo gene prediction, homolog protein family assignment, ortholog prediction, functional annotation, and pan-genome analysis using a range of proven tools and databases. While most existing methods scale quadratically with the number of genomes since they rely on pairwise comparisons among predicted protein sequences, DeNoGAP scales linearly since the homology assignment is based on iteratively refined hidden Markov models. This iterative clustering strategy enables DeNoGAP to handle a very large number of genomes using minimal computational resources. Moreover, the modular structure of the pipeline permits easy updates as new analysis programs become available. DeNoGAP integrates bioinformatics tools and databases for comparative analysis of a large number of genomes. The pipeline offers tools and algorithms for annotation and analysis of completed and draft genome sequences. The pipeline is developed using Perl, BioPerl and SQLite on Ubuntu Linux version 12.04 LTS. Currently, the software package accompanies script for automated installation of necessary external programs on Ubuntu Linux; however, the pipeline should be also compatible with other Linux and Unix systems after necessary external programs are installed. DeNoGAP is freely available at https://sourceforge.net/projects/denogap/ .

Systematic Identification of Combinatorial Drivers and Targets in Cancer Cell Lines

PubMed Central

Tabchy, Adel; Eltonsy, Nevine; Housman, David E.; Mills, Gordon B.

2013-01-01

There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance. PMID:23577104

Systematic identification of combinatorial drivers and targets in cancer cell lines.

PubMed

Tabchy, Adel; Eltonsy, Nevine; Housman, David E; Mills, Gordon B

2013-01-01

There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance.

Hal: an automated pipeline for phylogenetic analyses of genomic data.

PubMed

Robbertse, Barbara; Yoder, Ryan J; Boyd, Alex; Reeves, John; Spatafora, Joseph W

2011-02-07

The rapid increase in genomic and genome-scale data is resulting in unprecedented levels of discrete sequence data available for phylogenetic analyses. Major analytical impasses exist, however, prior to analyzing these data with existing phylogenetic software. Obstacles include the management of large data sets without standardized naming conventions, identification and filtering of orthologous clusters of proteins or genes, and the assembly of alignments of orthologous sequence data into individual and concatenated super alignments. Here we report the production of an automated pipeline, Hal that produces multiple alignments and trees from genomic data. These alignments can be produced by a choice of four alignment programs and analyzed by a variety of phylogenetic programs. In short, the Hal pipeline connects the programs BLASTP, MCL, user specified alignment programs, GBlocks, ProtTest and user specified phylogenetic programs to produce species trees. The script is available at sourceforge (http://sourceforge.net/projects/bio-hal/). The results from an example analysis of Kingdom Fungi are briefly discussed.

Genome-Level Longitudinal Expression of Signaling Pathways and Gene Networks in Pediatric Septic Shock

PubMed Central

Shanley, Thomas P; Cvijanovich, Natalie; Lin, Richard; Allen, Geoffrey L; Thomas, Neal J; Doctor, Allan; Kalyanaraman, Meena; Tofil, Nancy M; Penfil, Scott; Monaco, Marie; Odoms, Kelli; Barnes, Michael; Sakthivel, Bhuvaneswari; Aronow, Bruce J; Wong, Hector R

2007-01-01

We have conducted longitudinal studies focused on the expression profiles of signaling pathways and gene networks in children with septic shock. Genome-level expression profiles were generated from whole blood-derived RNA of children with septic shock (n = 30) corresponding to day one and day three of septic shock, respectively. Based on sequential statistical and expression filters, day one and day three of septic shock were characterized by differential regulation of 2,142 and 2,504 gene probes, respectively, relative to controls (n = 15). Venn analysis demonstrated 239 unique genes in the day one dataset, 598 unique genes in the day three dataset, and 1,906 genes common to both datasets. Functional analyses demonstrated time-dependent, differential regulation of genes involved in multiple signaling pathways and gene networks primarily related to immunity and inflammation. Notably, multiple and distinct gene networks involving T cell- and MHC antigen-related biology were persistently downregulated on both day one and day three. Further analyses demonstrated large scale, persistent downregulation of genes corresponding to functional annotations related to zinc homeostasis. These data represent the largest reported cohort of patients with septic shock subjected to longitudinal genome-level expression profiling. The data further advance our genome-level understanding of pediatric septic shock and support novel hypotheses. PMID:17932561

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

Harnessing the genome for characterization of GPCRs in cancer pathogenesis

PubMed Central

Feigin, Michael E.

2014-01-01

G-protein coupled receptors (GPCRs) mediate numerous physiological processes and represent the targets for a vast array of therapeutics for diseases ranging from depression to hypertension to reflux. Despite the recognition that GPCRs can act as oncogenes and tumor suppressors by regulating oncogenic signaling networks, few drugs targeting GPCRs are utilized in cancer therapy. Recent large-scale genome-wide analyses of multiple human tumors have uncovered novel GPCRs altered in cancer. However, the work of determining which GPCRs from these lists are drivers of tumorigenesis, and hence valid therapeutic targets, remains a formidable challenge. In this review I will highlight recent studies providing evidence that GPCRs are relevant targets for cancer therapy through their effects on known cancer signaling pathways, tumor progression, invasion and metastasis, and the microenvironment. Furthermore, I will explore how genomic analysis is beginning to shine a light on GPCRs as therapeutic targets in the age of personalized medicine. PMID:23927072

GenomeDiagram: a python package for the visualization of large-scale genomic data.

PubMed

Pritchard, Leighton; White, Jennifer A; Birch, Paul R J; Toth, Ian K

2006-03-01

We present GenomeDiagram, a flexible, open-source Python module for the visualization of large-scale genomic, comparative genomic and other data with reference to a single chromosome or other biological sequence. GenomeDiagram may be used to generate publication-quality vector graphics, rastered images and in-line streamed graphics for webpages. The package integrates with datatypes from the BioPython project, and is available for Windows, Linux and Mac OS X systems. GenomeDiagram is freely available as source code (under GNU Public License) at http://bioinf.scri.ac.uk/lp/programs.html, and requires Python 2.3 or higher, and recent versions of the ReportLab and BioPython packages. A user manual, example code and images are available at http://bioinf.scri.ac.uk/lp/programs.html.

Exploring the feasibility of using copy number variants as genetic markers through large-scale whole genome sequencing experiments

USDA-ARS?s Scientific Manuscript database

Copy number variants (CNV) are large scale duplications or deletions of genomic sequence that are caused by a diverse set of molecular phenomena that are distinct from single nucleotide polymorphism (SNP) formation. Due to their different mechanisms of formation, CNVs are often difficult to track us...

Asymmetric author-topic model for knowledge discovering of big data in toxicogenomics.

PubMed

Chung, Ming-Hua; Wang, Yuping; Tang, Hailin; Zou, Wen; Basinger, John; Xu, Xiaowei; Tong, Weida

2015-01-01

The advancement of high-throughput screening technologies facilitates the generation of massive amount of biological data, a big data phenomena in biomedical science. Yet, researchers still heavily rely on keyword search and/or literature review to navigate the databases and analyses are often done in rather small-scale. As a result, the rich information of a database has not been fully utilized, particularly for the information embedded in the interactive nature between data points that are largely ignored and buried. For the past 10 years, probabilistic topic modeling has been recognized as an effective machine learning algorithm to annotate the hidden thematic structure of massive collection of documents. The analogy between text corpus and large-scale genomic data enables the application of text mining tools, like probabilistic topic models, to explore hidden patterns of genomic data and to the extension of altered biological functions. In this paper, we developed a generalized probabilistic topic model to analyze a toxicogenomics dataset that consists of a large number of gene expression data from the rat livers treated with drugs in multiple dose and time-points. We discovered the hidden patterns in gene expression associated with the effect of doses and time-points of treatment. Finally, we illustrated the ability of our model to identify the evidence of potential reduction of animal use.

Development of Bioinformatics Infrastructure for Genomics Research.

PubMed

Mulder, Nicola J; Adebiyi, Ezekiel; Adebiyi, Marion; Adeyemi, Seun; Ahmed, Azza; Ahmed, Rehab; Akanle, Bola; Alibi, Mohamed; Armstrong, Don L; Aron, Shaun; Ashano, Efejiro; Baichoo, Shakuntala; Benkahla, Alia; Brown, David K; Chimusa, Emile R; Fadlelmola, Faisal M; Falola, Dare; Fatumo, Segun; Ghedira, Kais; Ghouila, Amel; Hazelhurst, Scott; Isewon, Itunuoluwa; Jung, Segun; Kassim, Samar Kamal; Kayondo, Jonathan K; Mbiyavanga, Mamana; Meintjes, Ayton; Mohammed, Somia; Mosaku, Abayomi; Moussa, Ahmed; Muhammd, Mustafa; Mungloo-Dilmohamud, Zahra; Nashiru, Oyekanmi; Odia, Trust; Okafor, Adaobi; Oladipo, Olaleye; Osamor, Victor; Oyelade, Jellili; Sadki, Khalid; Salifu, Samson Pandam; Soyemi, Jumoke; Panji, Sumir; Radouani, Fouzia; Souiai, Oussama; Tastan Bishop, Özlem

2017-06-01

Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet's role has evolved in response to changing needs from the consortium and the African bioinformatics community. H3ABioNet set out to develop core bioinformatics infrastructure and capacity for genomics research in various aspects of data collection, transfer, storage, and analysis. Various resources have been developed to address genomic data management and analysis needs of H3Africa researchers and other scientific communities on the continent. NetMap was developed and used to build an accurate picture of network performance within Africa and between Africa and the rest of the world, and Globus Online has been rolled out to facilitate data transfer. A participant recruitment database was developed to monitor participant enrollment, and data is being harmonized through the use of ontologies and controlled vocabularies. The standardized metadata will be integrated to provide a search facility for H3Africa data and biospecimens. Because H3Africa projects are generating large-scale genomic data, facilities for analysis and interpretation are critical. H3ABioNet is implementing several data analysis platforms that provide a large range of bioinformatics tools or workflows, such as Galaxy, the Job Management System, and eBiokits. A set of reproducible, portable, and cloud-scalable pipelines to support the multiple H3Africa data types are also being developed and dockerized to enable execution on multiple computing infrastructures. In addition, new tools have been developed for analysis of the uniquely divergent African data and for downstream interpretation of prioritized variants. To provide support for these and other bioinformatics queries, an online bioinformatics helpdesk backed by broad consortium expertise has been established. Further support is provided by means of various modes of bioinformatics training. For the past 4 years, the development of infrastructure support and human capacity through H3ABioNet, have significantly contributed to the establishment of African scientific networks, data analysis facilities, and training programs. Here, we describe the infrastructure and how it has affected genomics and bioinformatics research in Africa. Copyright © 2017 World Heart Federation (Geneva). Published by Elsevier B.V. All rights reserved.

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

Insertion Sequence-Caused Large Scale-Rearrangements in the Genome of Escherichia coli

DTIC Science & Technology

2016-07-18

rearrangements in the genome of Escherichia coli Heewook Lee1,2, Thomas G. Doak3,4, Ellen Popodi3, Patricia L. Foster3 and Haixu Tang1,* 1School of...and excisions of IS elements and recombi- nation between homologous IS elements identified in a large collection of Escherichia coli mutation accu...scale rear- rangements arose in the Escherichia coli genome during a long-term evolution experiment in a recent study (8). Com- bining WGSS with

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

A Novel Genome-Information Content-Based Statistic for Genome-Wide Association Analysis Designed for Next-Generation Sequencing Data

PubMed Central

Luo, Li; Zhu, Yun

2012-01-01

Abstract The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T2, collapsing method, multivariate and collapsing (CMC) method, individual χ2 test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets. PMID:22651812

A novel genome-information content-based statistic for genome-wide association analysis designed for next-generation sequencing data.

PubMed

Luo, Li; Zhu, Yun; Xiong, Momiao

2012-06-01

The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T(2), collapsing method, multivariate and collapsing (CMC) method, individual χ(2) test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets.

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.

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...

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.

Evolution via recombination: Cell-to-cell contact facilitates larger recombination events in Streptococcus pneumoniae.

PubMed

Cowley, Lauren A; Petersen, Fernanda C; Junges, Roger; Jimson D Jimenez, Med; Morrison, Donald A; Hanage, William P

2018-06-01

Homologous recombination in the genetic transformation model organism Streptococcus pneumoniae is thought to be important in the adaptation and evolution of this pathogen. While competent pneumococci are able to scavenge DNA added to laboratory cultures, large-scale transfers of multiple kb are rare under these conditions. We used whole genome sequencing (WGS) to map transfers in recombinants arising from contact of competent cells with non-competent 'target' cells, using strains with known genomes, distinguished by a total of ~16,000 SNPs. Experiments designed to explore the effect of environment on large scale recombination events used saturating purified donor DNA, short-term cell assemblages on Millipore filters, and mature biofilm mixed cultures. WGS of 22 recombinants for each environment mapped all SNPs that were identical between the recombinant and the donor but not the recipient. The mean recombination event size was found to be significantly larger in cell-to-cell contact cultures (4051 bp in filter assemblage and 3938 bp in biofilm co-culture versus 1815 bp with saturating DNA). Up to 5.8% of the genome was transferred, through 20 recombination events, to a single recipient, with the largest single event incorporating 29,971 bp. We also found that some recombination events are clustered, that these clusters are more likely to occur in cell-to-cell contact environments, and that they cause significantly increased linkage of genes as far apart as 60,000 bp. We conclude that pneumococcal evolution through homologous recombination is more likely to occur on a larger scale in environments that permit cell-to-cell contact.

Cloning, Assembly, and Modification of the Primary Human Cytomegalovirus Isolate Toledo by Yeast-Based Transformation-Associated Recombination.

PubMed

Vashee, Sanjay; Stockwell, Timothy B; Alperovich, Nina; Denisova, Evgeniya A; Gibson, Daniel G; Cady, Kyle C; Miller, Kristofer; Kannan, Krishna; Malouli, Daniel; Crawford, Lindsey B; Voorhies, Alexander A; Bruening, Eric; Caposio, Patrizia; Früh, Klaus

2017-01-01

Genetic engineering of cytomegalovirus (CMV) currently relies on generating a bacterial artificial chromosome (BAC) by introducing a bacterial origin of replication into the viral genome using in vivo recombination in virally infected tissue culture cells. However, this process is inefficient, results in adaptive mutations, and involves deletion of viral genes to avoid oversized genomes when inserting the BAC cassette. Moreover, BAC technology does not permit the simultaneous manipulation of multiple genome loci and cannot be used to construct synthetic genomes. To overcome these limitations, we adapted synthetic biology tools to clone CMV genomes in Saccharomyces cerevisiae . Using an early passage of the human CMV isolate Toledo, we first applied transformation-associated recombination (TAR) to clone 16 overlapping fragments covering the entire Toledo genome in Saccharomyces cerevisiae . Then, we assembled these fragments by TAR in a stepwise process until the entire genome was reconstituted in yeast. Since next-generation sequence analysis revealed that the low-passage-number isolate represented a mixture of parental and fibroblast-adapted genomes, we selectively modified individual DNA fragments of fibroblast-adapted Toledo (Toledo-F) and again used TAR assembly to recreate parental Toledo (Toledo-P). Linear, full-length HCMV genomes were transfected into human fibroblasts to recover virus. Unlike Toledo-F, Toledo-P displayed characteristics of primary isolates, including broad cellular tropism in vitro and the ability to establish latency and reactivation in humanized mice. Our novel strategy thus enables de novo cloning of CMV genomes, more-efficient genome-wide engineering, and the generation of viral genomes that are partially or completely derived from synthetic DNA. IMPORTANCE The genomes of large DNA viruses, such as human cytomegalovirus (HCMV), are difficult to manipulate using current genetic tools, and at this time, it is not possible to obtain, molecular clones of CMV without extensive tissue culture. To overcome these limitations, we used synthetic biology tools to capture genomic fragments from viral DNA and assemble full-length genomes in yeast. Using an early passage of the HCMV isolate Toledo containing a mixture of wild-type and tissue culture-adapted virus. we directly cloned the majority sequence and recreated the minority sequence by simultaneous modification of multiple genomic regions. Thus, our novel approach provides a paradigm to not only efficiently engineer HCMV and other large DNA viruses on a genome-wide scale but also facilitates the cloning and genetic manipulation of primary isolates and provides a pathway to generating entirely synthetic genomes.

Cloning, Assembly, and Modification of the Primary Human Cytomegalovirus Isolate Toledo by Yeast-Based Transformation-Associated Recombination

PubMed Central

Vashee, Sanjay; Stockwell, Timothy B.; Alperovich, Nina; Denisova, Evgeniya A.; Gibson, Daniel G.; Cady, Kyle C.; Miller, Kristofer; Kannan, Krishna; Malouli, Daniel; Crawford, Lindsey B.; Voorhies, Alexander A.; Bruening, Eric; Caposio, Patrizia

2017-01-01

ABSTRACT Genetic engineering of cytomegalovirus (CMV) currently relies on generating a bacterial artificial chromosome (BAC) by introducing a bacterial origin of replication into the viral genome using in vivo recombination in virally infected tissue culture cells. However, this process is inefficient, results in adaptive mutations, and involves deletion of viral genes to avoid oversized genomes when inserting the BAC cassette. Moreover, BAC technology does not permit the simultaneous manipulation of multiple genome loci and cannot be used to construct synthetic genomes. To overcome these limitations, we adapted synthetic biology tools to clone CMV genomes in Saccharomyces cerevisiae. Using an early passage of the human CMV isolate Toledo, we first applied transformation-associated recombination (TAR) to clone 16 overlapping fragments covering the entire Toledo genome in Saccharomyces cerevisiae. Then, we assembled these fragments by TAR in a stepwise process until the entire genome was reconstituted in yeast. Since next-generation sequence analysis revealed that the low-passage-number isolate represented a mixture of parental and fibroblast-adapted genomes, we selectively modified individual DNA fragments of fibroblast-adapted Toledo (Toledo-F) and again used TAR assembly to recreate parental Toledo (Toledo-P). Linear, full-length HCMV genomes were transfected into human fibroblasts to recover virus. Unlike Toledo-F, Toledo-P displayed characteristics of primary isolates, including broad cellular tropism in vitro and the ability to establish latency and reactivation in humanized mice. Our novel strategy thus enables de novo cloning of CMV genomes, more-efficient genome-wide engineering, and the generation of viral genomes that are partially or completely derived from synthetic DNA. IMPORTANCE The genomes of large DNA viruses, such as human cytomegalovirus (HCMV), are difficult to manipulate using current genetic tools, and at this time, it is not possible to obtain, molecular clones of CMV without extensive tissue culture. To overcome these limitations, we used synthetic biology tools to capture genomic fragments from viral DNA and assemble full-length genomes in yeast. Using an early passage of the HCMV isolate Toledo containing a mixture of wild-type and tissue culture-adapted virus. we directly cloned the majority sequence and recreated the minority sequence by simultaneous modification of multiple genomic regions. Thus, our novel approach provides a paradigm to not only efficiently engineer HCMV and other large DNA viruses on a genome-wide scale but also facilitates the cloning and genetic manipulation of primary isolates and provides a pathway to generating entirely synthetic genomes. PMID:28989973

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.

The UCSC genome browser and associated tools

PubMed Central

Haussler, David; Kent, W. James

2013-01-01

The UCSC Genome Browser (http://genome.ucsc.edu) is a graphical viewer for genomic data now in its 13th year. Since the early days of the Human Genome Project, it has presented an integrated view of genomic data of many kinds. Now home to assemblies for 58 organisms, the Browser presents visualization of annotations mapped to genomic coordinates. The ability to juxtapose annotations of many types facilitates inquiry-driven data mining. Gene predictions, mRNA alignments, epigenomic data from the ENCODE project, conservation scores from vertebrate whole-genome alignments and variation data may be viewed at any scale from a single base to an entire chromosome. The Browser also includes many other widely used tools, including BLAT, which is useful for alignments from high-throughput sequencing experiments. Private data uploaded as Custom Tracks and Data Hubs in many formats may be displayed alongside the rich compendium of precomputed data in the UCSC database. The Table Browser is a full-featured graphical interface, which allows querying, filtering and intersection of data tables. The Saved Session feature allows users to store and share customized views, enhancing the utility of the system for organizing multiple trains of thought. Binary Alignment/Map (BAM), Variant Call Format and the Personal Genome Single Nucleotide Polymorphisms (SNPs) data formats are useful for visualizing a large sequencing experiment (whole-genome or whole-exome), where the differences between the data set and the reference assembly may be displayed graphically. Support for high-throughput sequencing extends to compact, indexed data formats, such as BAM, bigBed and bigWig, allowing rapid visualization of large datasets from RNA-seq and ChIP-seq experiments via local hosting. PMID:22908213

The UCSC genome browser and associated tools.

PubMed

Kuhn, Robert M; Haussler, David; Kent, W James

2013-03-01

The UCSC Genome Browser (http://genome.ucsc.edu) is a graphical viewer for genomic data now in its 13th year. Since the early days of the Human Genome Project, it has presented an integrated view of genomic data of many kinds. Now home to assemblies for 58 organisms, the Browser presents visualization of annotations mapped to genomic coordinates. The ability to juxtapose annotations of many types facilitates inquiry-driven data mining. Gene predictions, mRNA alignments, epigenomic data from the ENCODE project, conservation scores from vertebrate whole-genome alignments and variation data may be viewed at any scale from a single base to an entire chromosome. The Browser also includes many other widely used tools, including BLAT, which is useful for alignments from high-throughput sequencing experiments. Private data uploaded as Custom Tracks and Data Hubs in many formats may be displayed alongside the rich compendium of precomputed data in the UCSC database. The Table Browser is a full-featured graphical interface, which allows querying, filtering and intersection of data tables. The Saved Session feature allows users to store and share customized views, enhancing the utility of the system for organizing multiple trains of thought. Binary Alignment/Map (BAM), Variant Call Format and the Personal Genome Single Nucleotide Polymorphisms (SNPs) data formats are useful for visualizing a large sequencing experiment (whole-genome or whole-exome), where the differences between the data set and the reference assembly may be displayed graphically. Support for high-throughput sequencing extends to compact, indexed data formats, such as BAM, bigBed and bigWig, allowing rapid visualization of large datasets from RNA-seq and ChIP-seq experiments via local hosting.

High-Throughput resequencing of maize landraces at genomic regions associated with flowering time

USDA-ARS?s Scientific Manuscript database

Despite the reduction in the price of sequencing, it remains expensive to sequence and assemble whole, complex genomes of multiple samples for population studies, particularly for large genomes like those of many crop species. Enrichment of target genome regions coupled with next generation sequenci...

The Use of Weighted Graphs for Large-Scale Genome Analysis

PubMed Central

Zhou, Fang; Toivonen, Hannu; King, Ross D.

2014-01-01

There is an acute need for better tools to extract knowledge from the growing flood of sequence data. For example, thousands of complete genomes have been sequenced, and their metabolic networks inferred. Such data should enable a better understanding of evolution. However, most existing network analysis methods are based on pair-wise comparisons, and these do not scale to thousands of genomes. Here we propose the use of weighted graphs as a data structure to enable large-scale phylogenetic analysis of networks. We have developed three types of weighted graph for enzymes: taxonomic (these summarize phylogenetic importance), isoenzymatic (these summarize enzymatic variety/redundancy), and sequence-similarity (these summarize sequence conservation); and we applied these types of weighted graph to survey prokaryotic metabolism. To demonstrate the utility of this approach we have compared and contrasted the large-scale evolution of metabolism in Archaea and Eubacteria. Our results provide evidence for limits to the contingency of evolution. PMID:24619061

[Genome editing of industrial microorganism].

PubMed

Zhu, Linjiang; Li, Qi

2015-03-01

Genome editing is defined as highly-effective and precise modification of cellular genome in a large scale. In recent years, such genome-editing methods have been rapidly developed in the field of industrial strain improvement. The quickly-updating methods thoroughly change the old mode of inefficient genetic modification, which is "one modification, one selection marker, and one target site". Highly-effective modification mode in genome editing have been developed including simultaneous modification of multiplex genes, highly-effective insertion, replacement, and deletion of target genes in the genome scale, cut-paste of a large DNA fragment. These new tools for microbial genome editing will certainly be applied widely, and increase the efficiency of industrial strain improvement, and promote the revolution of traditional fermentation industry and rapid development of novel industrial biotechnology like production of biofuel and biomaterial. The technological principle of these genome-editing methods and their applications were summarized in this review, which can benefit engineering and construction of industrial microorganism.

Cancer Genomics: Integrative and Scalable Solutions in R / Bioconductor | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

This proposal develops scalable R / Bioconductor software infrastructure and data resources to integrate complex, heterogeneous, and large cancer genomic experiments. The falling cost of genomic assays facilitates collection of multiple data types (e.g., gene and transcript expression, structural variation, copy number, methylation, and microRNA data) from a set of clinical specimens. Furthermore, substantial resources are now available from large consortium activities like The Cancer Genome Atlas (TCGA).

Advances in Setaria genomics for genetic improvement of cereals and bioenergy grasses.

PubMed

Muthamilarasan, Mehanathan; Prasad, Manoj

2015-01-01

Recent advances in Setaria genomics appear promising for genetic improvement of cereals and biofuel crops towards providing multiple securities to the steadily increasing global population. The prominent attributes of foxtail millet (Setaria italica, cultivated) and green foxtail (S. viridis, wild) including small genome size, short life-cycle, in-breeding nature, genetic close-relatedness to several cereals, millets and bioenergy grasses, and potential abiotic stress tolerance have accentuated these two Setaria species as novel model system for studying C4 photosynthesis, stress biology and biofuel traits. Considering this, studies have been performed on structural and functional genomics of these plants to develop genetic and genomic resources, and to delineate the physiology and molecular biology of stress tolerance, for the improvement of millets, cereals and bioenergy grasses. The release of foxtail millet genome sequence has provided a new dimension to Setaria genomics, resulting in large-scale development of genetic and genomic tools, construction of informative databases, and genome-wide association and functional genomic studies. In this context, this review discusses the advancements made in Setaria genomics, which have generated a considerable knowledge that could be used for the improvement of millets, cereals and biofuel crops. Further, this review also shows the nutritional potential of foxtail millet in providing health benefits to global population and provides a preliminary information on introgressing the nutritional properties in graminaceous species through molecular breeding and transgene-based approaches.

Linear score tests for variance components in linear mixed models and applications to genetic association studies.

PubMed

Qu, Long; Guennel, Tobias; Marshall, Scott L

2013-12-01

Following the rapid development of genome-scale genotyping technologies, genetic association mapping has become a popular tool to detect genomic regions responsible for certain (disease) phenotypes, especially in early-phase pharmacogenomic studies with limited sample size. In response to such applications, a good association test needs to be (1) applicable to a wide range of possible genetic models, including, but not limited to, the presence of gene-by-environment or gene-by-gene interactions and non-linearity of a group of marker effects, (2) accurate in small samples, fast to compute on the genomic scale, and amenable to large scale multiple testing corrections, and (3) reasonably powerful to locate causal genomic regions. The kernel machine method represented in linear mixed models provides a viable solution by transforming the problem into testing the nullity of variance components. In this study, we consider score-based tests by choosing a statistic linear in the score function. When the model under the null hypothesis has only one error variance parameter, our test is exact in finite samples. When the null model has more than one variance parameter, we develop a new moment-based approximation that performs well in simulations. Through simulations and analysis of real data, we demonstrate that the new test possesses most of the aforementioned characteristics, especially when compared to existing quadratic score tests or restricted likelihood ratio tests. © 2013, The International Biometric Society.

Genome-wide inference of regulatory networks in Streptomyces coelicolor.

PubMed

Castro-Melchor, Marlene; Charaniya, Salim; Karypis, George; Takano, Eriko; Hu, Wei-Shou

2010-10-18

The onset of antibiotics production in Streptomyces species is co-ordinated with differentiation events. An understanding of the genetic circuits that regulate these coupled biological phenomena is essential to discover and engineer the pharmacologically important natural products made by these species. The availability of genomic tools and access to a large warehouse of transcriptome data for the model organism, Streptomyces coelicolor, provides incentive to decipher the intricacies of the regulatory cascades and develop biologically meaningful hypotheses. In this study, more than 500 samples of genome-wide temporal transcriptome data, comprising wild-type and more than 25 regulatory gene mutants of Streptomyces coelicolor probed across multiple stress and medium conditions, were investigated. Information based on transcript and functional similarity was used to update a previously-predicted whole-genome operon map and further applied to predict transcriptional networks constituting modules enriched in diverse functions such as secondary metabolism, and sigma factor. The predicted network displays a scale-free architecture with a small-world property observed in many biological networks. The networks were further investigated to identify functionally-relevant modules that exhibit functional coherence and a consensus motif in the promoter elements indicative of DNA-binding elements. Despite the enormous experimental as well as computational challenges, a systems approach for integrating diverse genome-scale datasets to elucidate complex regulatory networks is beginning to emerge. We present an integrated analysis of transcriptome data and genomic features to refine a whole-genome operon map and to construct regulatory networks at the cistron level in Streptomyces coelicolor. The functionally-relevant modules identified in this study pose as potential targets for further studies and verification.

Genome-Wide Motif Statistics are Shaped by DNA Binding Proteins over Evolutionary Time Scales

NASA Astrophysics Data System (ADS)

Qian, Long; Kussell, Edo

The composition of genomes with respect to short DNA motifs impacts the ability of DNA binding proteins to locate and bind their target sites. Since nonfunctional DNA binding can be detrimental to cellular functions and ultimately to organismal fitness, organisms could benefit from reducing the number of nonfunctional binding sites genome wide. Using in vitro measurements of binding affinities for a large collection of DNA binding proteins, in multiple species, we detect a significant global avoidance of weak binding sites in genomes. The underlying evolutionary process leaves a distinct genomic hallmark in that similar words have correlated frequencies, which we detect in all species across domains of life. We hypothesize that natural selection against weak binding sites contributes to this process, and using an evolutionary model we show that the strength of selection needed to maintain global word compositions is on the order of point mutation rates. Alternative contributions may come from interference of protein-DNA binding with replication and mutational repair processes, which operates with similar rates. We conclude that genome-wide word compositions have been molded by DNA binding proteins through tiny evolutionary steps over timescales spanning millions of generations.

Perilobar nephrogenic rests are non-obligate molecular genetic precursor lesions of IGF2-associated Wilms tumours

PubMed Central

Vuononvirta, Raisa; Sebire, Neil J.; Dallosso, Anthony R.; Reis-Filho, Jorge S.; Williams, Richard D.; Mackay, Alan; Fenwick, Kerry; Grigoriadis, Anita; Ashworth, Alan; Pritchard-Jones, Kathy; Brown, Keith W.; Vujanic, Gordan M.; Jones, Chris

2009-01-01

Purpose: Perilobar nephrogenic rests (PLNRs) are abnormally persistent foci of embryonal immature blastema that have been associated with dysregulation at the 11p15 locus by genetic/epigenetic means, and are thought to be precursor lesions of Wilms tumour. The precise genomic events are, however, largely unknown. Experimental Design: We used arrayCGH to analyse a series of 50 PLNRs and 25 corresponding Wilms tumours characterised for 11p15 genetic/epigenetic alterations and IGF2 expression. Results: The genomic profiles of PLNRs could be subdivided into three categories: those with no copy number changes (22/50, 44%), those with single, whole chromosome alterations (8/50, 16%), and those with multiple gains/losses (20/50, 40%). The most frequent aberrations included 1p- (7/50, 14%) +18 (6/50, 12%), +13 (5/50, 10%) and +12 (3/50, 6%). For the majority (19/25, 76%) of cases, the rest harboured a subset of the copy number changes in the associated Wilms tumour. We identified a temporal order of genomic changes which occur during the IGF2/PLNR pathway of Wilms tumorigenesis, with large scale chromosomal alterations such as 1p-, +12, +13 and +18 regarded as ‘early’ events. In some of the cases (24%), the PLNRs harboured large-scale copy number changes not observed in the concurrent Wilms tumour, including +10p, +14q and +18. Conclusions: These data suggest that although the evidence for PLNRs as precursors is compelling, not all lesions must necessarily undergo malignant transformation. PMID:19047088

Large-Scale Gene Relocations following an Ancient Genome Triplication Associated with the Diversification of Core Eudicots.

PubMed

Wang, Yupeng; Ficklin, Stephen P; Wang, Xiyin; Feltus, F Alex; Paterson, Andrew H

2016-01-01

Different modes of gene duplication including whole-genome duplication (WGD), and tandem, proximal and dispersed duplications are widespread in angiosperm genomes. Small-scale, stochastic gene relocations and transposed gene duplications are widely accepted to be the primary mechanisms for the creation of dispersed duplicates. However, here we show that most surviving ancient dispersed duplicates in core eudicots originated from large-scale gene relocations within a narrow window of time following a genome triplication (γ) event that occurred in the stem lineage of core eudicots. We name these surviving ancient dispersed duplicates as relocated γ duplicates. In Arabidopsis thaliana, relocated γ, WGD and single-gene duplicates have distinct features with regard to gene functions, essentiality, and protein interactions. Relative to γ duplicates, relocated γ duplicates have higher non-synonymous substitution rates, but comparable levels of expression and regulation divergence. Thus, relocated γ duplicates should be distinguished from WGD and single-gene duplicates for evolutionary investigations. Our results suggest large-scale gene relocations following the γ event were associated with the diversification of core eudicots.

Large-Scale Gene Relocations following an Ancient Genome Triplication Associated with the Diversification of Core Eudicots

PubMed Central

Wang, Yupeng; Ficklin, Stephen P.; Wang, Xiyin; Feltus, F. Alex; Paterson, Andrew H.

2016-01-01

Different modes of gene duplication including whole-genome duplication (WGD), and tandem, proximal and dispersed duplications are widespread in angiosperm genomes. Small-scale, stochastic gene relocations and transposed gene duplications are widely accepted to be the primary mechanisms for the creation of dispersed duplicates. However, here we show that most surviving ancient dispersed duplicates in core eudicots originated from large-scale gene relocations within a narrow window of time following a genome triplication (γ) event that occurred in the stem lineage of core eudicots. We name these surviving ancient dispersed duplicates as relocated γ duplicates. In Arabidopsis thaliana, relocated γ, WGD and single-gene duplicates have distinct features with regard to gene functions, essentiality, and protein interactions. Relative to γ duplicates, relocated γ duplicates have higher non-synonymous substitution rates, but comparable levels of expression and regulation divergence. Thus, relocated γ duplicates should be distinguished from WGD and single-gene duplicates for evolutionary investigations. Our results suggest large-scale gene relocations following the γ event were associated with the diversification of core eudicots. PMID:27195960

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.

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

New Markers for Predicting Fertility of the Male Gametes in the Post Genomic Age.

PubMed

Dipresa, Savina; De Toni, Luca; Foresta, Carlo; Garolla, Andrea

2018-04-18

A number of test have been proposed to assess male fertility potential, ranging from routine testing by light microscopic method for evaluating semen samples, to screening test for DNA integrity aimed to look at sperm chromatin abnormalities. Spermatozoa are an extremely differentiated cell, they have critical functions for embryo development and heredity, in addiction to delivering a haploid paternal genome to the oocyte. Towards this goal certain requirements must always be met. The ability of spermatozoa to perform its reproductive function taking place in the spermatogenesis, a highly specialized process depending on multiple factors with effect on male fertility. In the past 30 years, large-scale analyses of transcriptomic and genome expression in mammals have generated a large amount of informations on numberless biomolecules involved in spermatogenesis and male germ cell reproductive function. Sperm proteome represents the protein content that spermatozoa needs to survive and work correctly and modifications of sperm proteome play a role in determining functional changes leading to a decrease of reproductive competence into affected spermatozoa. The post-genomic approach consists of different methodologies for concurrently testicular transcriptome studies, protein compositional analysis and metabolomics findings of the spermatozoa in humans. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

VirSorter: mining viral signal from microbial genomic data.

PubMed

Roux, Simon; Enault, Francois; Hurwitz, Bonnie L; Sullivan, Matthew B

2015-01-01

Viruses of microbes impact all ecosystems where microbes drive key energy and substrate transformations including the oceans, humans and industrial fermenters. However, despite this recognized importance, our understanding of viral diversity and impacts remains limited by too few model systems and reference genomes. One way to fill these gaps in our knowledge of viral diversity is through the detection of viral signal in microbial genomic data. While multiple approaches have been developed and applied for the detection of prophages (viral genomes integrated in a microbial genome), new types of microbial genomic data are emerging that are more fragmented and larger scale, such as Single-cell Amplified Genomes (SAGs) of uncultivated organisms or genomic fragments assembled from metagenomic sequencing. Here, we present VirSorter, a tool designed to detect viral signal in these different types of microbial sequence data in both a reference-dependent and reference-independent manner, leveraging probabilistic models and extensive virome data to maximize detection of novel viruses. Performance testing shows that VirSorter's prophage prediction capability compares to that of available prophage predictors for complete genomes, but is superior in predicting viral sequences outside of a host genome (i.e., from extrachromosomal prophages, lytic infections, or partially assembled prophages). Furthermore, VirSorter outperforms existing tools for fragmented genomic and metagenomic datasets, and can identify viral signal in assembled sequence (contigs) as short as 3kb, while providing near-perfect identification (>95% Recall and 100% Precision) on contigs of at least 10kb. Because VirSorter scales to large datasets, it can also be used in "reverse" to more confidently identify viral sequence in viral metagenomes by sorting away cellular DNA whether derived from gene transfer agents, generalized transduction or contamination. Finally, VirSorter is made available through the iPlant Cyberinfrastructure that provides a web-based user interface interconnected with the required computing resources. VirSorter thus complements existing prophage prediction softwares to better leverage fragmented, SAG and metagenomic datasets in a way that will scale to modern sequencing. Given these features, VirSorter should enable the discovery of new viruses in microbial datasets, and further our understanding of uncultivated viral communities across diverse ecosystems.

VirSorter: mining viral signal from microbial genomic data

PubMed Central

Roux, Simon; Enault, Francois; Hurwitz, Bonnie L.

2015-01-01

Viruses of microbes impact all ecosystems where microbes drive key energy and substrate transformations including the oceans, humans and industrial fermenters. However, despite this recognized importance, our understanding of viral diversity and impacts remains limited by too few model systems and reference genomes. One way to fill these gaps in our knowledge of viral diversity is through the detection of viral signal in microbial genomic data. While multiple approaches have been developed and applied for the detection of prophages (viral genomes integrated in a microbial genome), new types of microbial genomic data are emerging that are more fragmented and larger scale, such as Single-cell Amplified Genomes (SAGs) of uncultivated organisms or genomic fragments assembled from metagenomic sequencing. Here, we present VirSorter, a tool designed to detect viral signal in these different types of microbial sequence data in both a reference-dependent and reference-independent manner, leveraging probabilistic models and extensive virome data to maximize detection of novel viruses. Performance testing shows that VirSorter’s prophage prediction capability compares to that of available prophage predictors for complete genomes, but is superior in predicting viral sequences outside of a host genome (i.e., from extrachromosomal prophages, lytic infections, or partially assembled prophages). Furthermore, VirSorter outperforms existing tools for fragmented genomic and metagenomic datasets, and can identify viral signal in assembled sequence (contigs) as short as 3kb, while providing near-perfect identification (>95% Recall and 100% Precision) on contigs of at least 10kb. Because VirSorter scales to large datasets, it can also be used in “reverse” to more confidently identify viral sequence in viral metagenomes by sorting away cellular DNA whether derived from gene transfer agents, generalized transduction or contamination. Finally, VirSorter is made available through the iPlant Cyberinfrastructure that provides a web-based user interface interconnected with the required computing resources. VirSorter thus complements existing prophage prediction softwares to better leverage fragmented, SAG and metagenomic datasets in a way that will scale to modern sequencing. Given these features, VirSorter should enable the discovery of new viruses in microbial datasets, and further our understanding of uncultivated viral communities across diverse ecosystems. PMID:26038737

LS-SNP: large-scale annotation of coding non-synonymous SNPs based on multiple information sources.

PubMed

Karchin, Rachel; Diekhans, Mark; Kelly, Libusha; Thomas, Daryl J; Pieper, Ursula; Eswar, Narayanan; Haussler, David; Sali, Andrej

2005-06-15

The NCBI dbSNP database lists over 9 million single nucleotide polymorphisms (SNPs) in the human genome, but currently contains limited annotation information. SNPs that result in amino acid residue changes (nsSNPs) are of critical importance in variation between individuals, including disease and drug sensitivity. We have developed LS-SNP, a genomic scale software pipeline to annotate nsSNPs. LS-SNP comprehensively maps nsSNPs onto protein sequences, functional pathways and comparative protein structure models, and predicts positions where nsSNPs destabilize proteins, interfere with the formation of domain-domain interfaces, have an effect on protein-ligand binding or severely impact human health. It currently annotates 28,043 validated SNPs that produce amino acid residue substitutions in human proteins from the SwissProt/TrEMBL database. Annotations can be viewed via a web interface either in the context of a genomic region or by selecting sets of SNPs, genes, proteins or pathways. These results are useful for identifying candidate functional SNPs within a gene, haplotype or pathway and in probing molecular mechanisms responsible for functional impacts of nsSNPs. http://www.salilab.org/LS-SNP CONTACT: rachelk@salilab.org http://salilab.org/LS-SNP/supp-info.pdf.

Panoptes: web-based exploration of large scale genome variation data.

PubMed

Vauterin, Paul; Jeffery, Ben; Miles, Alistair; Amato, Roberto; Hart, Lee; Wright, Ian; Kwiatkowski, Dominic

2017-10-15

The size and complexity of modern large-scale genome variation studies demand novel approaches for exploring and sharing the data. In order to unlock the potential of these data for a broad audience of scientists with various areas of expertise, a unified exploration framework is required that is accessible, coherent and user-friendly. Panoptes is an open-source software framework for collaborative visual exploration of large-scale genome variation data and associated metadata in a web browser. It relies on technology choices that allow it to operate in near real-time on very large datasets. It can be used to browse rich, hybrid content in a coherent way, and offers interactive visual analytics approaches to assist the exploration. We illustrate its application using genome variation data of Anopheles gambiae, Plasmodium falciparum and Plasmodium vivax. Freely available at https://github.com/cggh/panoptes, under the GNU Affero General Public License. paul.vauterin@gmail.com. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Optimized distributed systems achieve significant performance improvement on sorted merging of massive VCF files.

PubMed

Sun, Xiaobo; Gao, Jingjing; Jin, Peng; Eng, Celeste; Burchard, Esteban G; Beaty, Terri H; Ruczinski, Ingo; Mathias, Rasika A; Barnes, Kathleen; Wang, Fusheng; Qin, Zhaohui S

2018-06-01

Sorted merging of genomic data is a common data operation necessary in many sequencing-based studies. It involves sorting and merging genomic data from different subjects by their genomic locations. In particular, merging a large number of variant call format (VCF) files is frequently required in large-scale whole-genome sequencing or whole-exome sequencing projects. Traditional single-machine based methods become increasingly inefficient when processing large numbers of files due to the excessive computation time and Input/Output bottleneck. Distributed systems and more recent cloud-based systems offer an attractive solution. However, carefully designed and optimized workflow patterns and execution plans (schemas) are required to take full advantage of the increased computing power while overcoming bottlenecks to achieve high performance. In this study, we custom-design optimized schemas for three Apache big data platforms, Hadoop (MapReduce), HBase, and Spark, to perform sorted merging of a large number of VCF files. These schemas all adopt the divide-and-conquer strategy to split the merging job into sequential phases/stages consisting of subtasks that are conquered in an ordered, parallel, and bottleneck-free way. In two illustrating examples, we test the performance of our schemas on merging multiple VCF files into either a single TPED or a single VCF file, which are benchmarked with the traditional single/parallel multiway-merge methods, message passing interface (MPI)-based high-performance computing (HPC) implementation, and the popular VCFTools. Our experiments suggest all three schemas either deliver a significant improvement in efficiency or render much better strong and weak scalabilities over traditional methods. Our findings provide generalized scalable schemas for performing sorted merging on genetics and genomics data using these Apache distributed systems.

Optimized distributed systems achieve significant performance improvement on sorted merging of massive VCF files

PubMed Central

Gao, Jingjing; Jin, Peng; Eng, Celeste; Burchard, Esteban G; Beaty, Terri H; Ruczinski, Ingo; Mathias, Rasika A; Barnes, Kathleen; Wang, Fusheng

2018-01-01

Abstract Background Sorted merging of genomic data is a common data operation necessary in many sequencing-based studies. It involves sorting and merging genomic data from different subjects by their genomic locations. In particular, merging a large number of variant call format (VCF) files is frequently required in large-scale whole-genome sequencing or whole-exome sequencing projects. Traditional single-machine based methods become increasingly inefficient when processing large numbers of files due to the excessive computation time and Input/Output bottleneck. Distributed systems and more recent cloud-based systems offer an attractive solution. However, carefully designed and optimized workflow patterns and execution plans (schemas) are required to take full advantage of the increased computing power while overcoming bottlenecks to achieve high performance. Findings In this study, we custom-design optimized schemas for three Apache big data platforms, Hadoop (MapReduce), HBase, and Spark, to perform sorted merging of a large number of VCF files. These schemas all adopt the divide-and-conquer strategy to split the merging job into sequential phases/stages consisting of subtasks that are conquered in an ordered, parallel, and bottleneck-free way. In two illustrating examples, we test the performance of our schemas on merging multiple VCF files into either a single TPED or a single VCF file, which are benchmarked with the traditional single/parallel multiway-merge methods, message passing interface (MPI)–based high-performance computing (HPC) implementation, and the popular VCFTools. Conclusions Our experiments suggest all three schemas either deliver a significant improvement in efficiency or render much better strong and weak scalabilities over traditional methods. Our findings provide generalized scalable schemas for performing sorted merging on genetics and genomics data using these Apache distributed systems. PMID:29762754

Molecular biology of bladder cancer.

PubMed

Martin-Doyle, William; Kwiatkowski, David J

2015-04-01

Classic as well as more recent large-scale genomic analyses have uncovered multiple genes and pathways important for bladder cancer development. Genes involved in cell-cycle control, chromatin regulation, and receptor tyrosine and PI3 kinase-mammalian target of rapamycin signaling pathways are commonly mutated in muscle-invasive bladder cancer. Expression-based analyses have identified distinct types of bladder cancer that are similar to subsets of breast cancer, and have prognostic and therapeutic significance. These observations are leading to novel therapeutic approaches in bladder cancer, providing optimism for therapeutic progress. Copyright © 2015 Elsevier Inc. All rights reserved.

Software engineering the mixed model for genome-wide association studies on large samples

USDA-ARS?s Scientific Manuscript database

Mixed models improve the ability to detect phenotype-genotype associations in the presence of population stratification and multiple levels of relatedness in genome-wide association studies (GWAS), but for large data sets the resource consumption becomes impractical. At the same time, the sample siz...

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.

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.

Big Data Analytics for Genomic Medicine

PubMed Central

He, Karen Y.; Ge, Dongliang; He, Max M.

2017-01-01

Genomic medicine attempts to build individualized strategies for diagnostic or therapeutic decision-making by utilizing patients’ genomic information. Big Data analytics uncovers hidden patterns, unknown correlations, and other insights through examining large-scale various data sets. While integration and manipulation of diverse genomic data and comprehensive electronic health records (EHRs) on a Big Data infrastructure exhibit challenges, they also provide a feasible opportunity to develop an efficient and effective approach to identify clinically actionable genetic variants for individualized diagnosis and therapy. In this paper, we review the challenges of manipulating large-scale next-generation sequencing (NGS) data and diverse clinical data derived from the EHRs for genomic medicine. We introduce possible solutions for different challenges in manipulating, managing, and analyzing genomic and clinical data to implement genomic medicine. Additionally, we also present a practical Big Data toolset for identifying clinically actionable genetic variants using high-throughput NGS data and EHRs. PMID:28212287

Big Data Analytics for Genomic Medicine.

PubMed

He, Karen Y; Ge, Dongliang; He, Max M

2017-02-15

Genomic medicine attempts to build individualized strategies for diagnostic or therapeutic decision-making by utilizing patients' genomic information. Big Data analytics uncovers hidden patterns, unknown correlations, and other insights through examining large-scale various data sets. While integration and manipulation of diverse genomic data and comprehensive electronic health records (EHRs) on a Big Data infrastructure exhibit challenges, they also provide a feasible opportunity to develop an efficient and effective approach to identify clinically actionable genetic variants for individualized diagnosis and therapy. In this paper, we review the challenges of manipulating large-scale next-generation sequencing (NGS) data and diverse clinical data derived from the EHRs for genomic medicine. We introduce possible solutions for different challenges in manipulating, managing, and analyzing genomic and clinical data to implement genomic medicine. Additionally, we also present a practical Big Data toolset for identifying clinically actionable genetic variants using high-throughput NGS data and EHRs.

Massive dispersal of Coxiella burnetii among cattle across the United States

PubMed Central

Olivas, Sonora; Hornstra, Heidie; Priestley, Rachael A.; Kaufman, Emily; Hepp, Crystal; Sonderegger, Derek L.; Handady, Karthik; Massung, Robert F.; Keim, Paul; Kersh, Gilbert J.

2016-01-01

Q-fever is an underreported disease caused by the bacterium Coxiella burnetii, which is highly infectious and has the ability to disperse great distances. It is a completely clonal pathogen with low genetic diversity and requires whole-genome analysis to identify discriminating features among closely related isolates. C. burnetii, and in particular one genotype (ST20), is commonly found in cow’s milk across the entire dairy industry of the USA. This single genotype dominance is suggestive of host-specific adaptation, rapid dispersal and persistence within cattle. We used a comparative genomic approach to identify SNPs for high-resolution and high-throughput genotyping assays to better describe the dispersal of ST20 across the USA. We genotyped 507 ST20 cow milk samples and discovered three subgenotypes, all of which were present across the entire country and over the complete time period studied. Only one of these sub-genotypes was observed in a single dairy herd. The temporal and geographic distribution of these sub-genotypes is consistent with a model of large-scale, rapid, frequent and continuous dissemination on a continental scale. The distribution of subgenotypes is not consistent with wind-based dispersal alone, and it is likely that animal husbandry and transportation practices, including pooling of milk from multiple herds, have also shaped the patterns. On the scale of an entire country, there appear to be few barriers to rapid, frequent and large-scale dissemination of the ST20 subgenotypes. PMID:28348863

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

Ontology-based meta-analysis of global collections of high-throughput public data.

PubMed

Kupershmidt, Ilya; Su, Qiaojuan Jane; Grewal, Anoop; Sundaresh, Suman; Halperin, Inbal; Flynn, James; Shekar, Mamatha; Wang, Helen; Park, Jenny; Cui, Wenwu; Wall, Gregory D; Wisotzkey, Robert; Alag, Satnam; Akhtari, Saeid; Ronaghi, Mostafa

2010-09-29

The investigation of the interconnections between the molecular and genetic events that govern biological systems is essential if we are to understand the development of disease and design effective novel treatments. Microarray and next-generation sequencing technologies have the potential to provide this information. However, taking full advantage of these approaches requires that biological connections be made across large quantities of highly heterogeneous genomic datasets. Leveraging the increasingly huge quantities of genomic data in the public domain is fast becoming one of the key challenges in the research community today. We have developed a novel data mining framework that enables researchers to use this growing collection of public high-throughput data to investigate any set of genes or proteins. The connectivity between molecular states across thousands of heterogeneous datasets from microarrays and other genomic platforms is determined through a combination of rank-based enrichment statistics, meta-analyses, and biomedical ontologies. We address data quality concerns through dataset replication and meta-analysis and ensure that the majority of the findings are derived using multiple lines of evidence. As an example of our strategy and the utility of this framework, we apply our data mining approach to explore the biology of brown fat within the context of the thousands of publicly available gene expression datasets. Our work presents a practical strategy for organizing, mining, and correlating global collections of large-scale genomic data to explore normal and disease biology. Using a hypothesis-free approach, we demonstrate how a data-driven analysis across very large collections of genomic data can reveal novel discoveries and evidence to support existing hypothesis.

Whole-Genome Duplication and the Functional Diversification of Teleost Fish Hemoglobins

PubMed Central

Opazo, Juan C.; Butts, G. Tyler; Nery, Mariana F.; Storz, Jay F.; Hoffmann, Federico G.

2013-01-01

Subsequent to the two rounds of whole-genome duplication that occurred in the common ancestor of vertebrates, a third genome duplication occurred in the stem lineage of teleost fishes. This teleost-specific genome duplication (TGD) is thought to have provided genetic raw materials for the physiological, morphological, and behavioral diversification of this highly speciose group. The extreme physiological versatility of teleost fish is manifest in their diversity of blood–gas transport traits, which reflects the myriad solutions that have evolved to maintain tissue O2 delivery in the face of changing metabolic demands and environmental O2 availability during different ontogenetic stages. During the course of development, regulatory changes in blood–O2 transport are mediated by the expression of multiple, functionally distinct hemoglobin (Hb) isoforms that meet the particular O2-transport challenges encountered by the developing embryo or fetus (in viviparous or oviparous species) and in free-swimming larvae and adults. The main objective of the present study was to assess the relative contributions of whole-genome duplication, large-scale segmental duplication, and small-scale gene duplication in producing the extraordinary functional diversity of teleost Hbs. To accomplish this, we integrated phylogenetic reconstructions with analyses of conserved synteny to characterize the genomic organization and evolutionary history of the globin gene clusters of teleosts. These results were then integrated with available experimental data on functional properties and developmental patterns of stage-specific gene expression. Our results indicate that multiple α- and β-globin genes were present in the common ancestor of gars (order Lepisoteiformes) and teleosts. The comparative genomic analysis revealed that teleosts possess a dual set of TGD-derived globin gene clusters, each of which has undergone lineage-specific changes in gene content via repeated duplication and deletion events. Phylogenetic reconstructions revealed that paralogous genes convergently evolved similar functional properties in different teleost lineages. Consistent with other recent studies of globin gene family evolution in vertebrates, our results revealed evidence for repeated evolutionary transitions in the developmental regulation of Hb synthesis. PMID:22949522

A genome-scale Escherichia coli kinetic metabolic model k-ecoli457 satisfying flux data for multiple mutant strains

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

Khodayari, Ali; Maranas, Costas D.

Kinetic models of metabolism at a genome scale that faithfully recapitulate the effect of multiple genetic interventions would be transformative in our ability to reliably design novel overproducing microbial strains. Here, we introduce k-ecoli457, a genome-scale kinetic model of Escherichia coli metabolism that satisfies fluxomic data for wild-type and 25 mutant strains under different substrates and growth conditions. The k-ecoli457 model contains 457 model reactions, 337 metabolites and 295 substrate-level regulatory interactions. Parameterization is carried out using a genetic algorithm by simultaneously imposing all available fluxomic data (about 30 measured fluxes per mutant). Furthermore, the Pearson correlation coefficient between experimentalmore » data and predicted product yields for 320 engineered strains spanning 24 product metabolites is 0.84. This is substantially higher than that using flux balance analysis, minimization of metabolic adjustment or maximization of product yield exhibiting systematic errors with correlation coefficients of, respectively, 0.18, 0.37 and 0.47.« less

A genome-scale Escherichia coli kinetic metabolic model k-ecoli457 satisfying flux data for multiple mutant strains

DOE PAGES

Khodayari, Ali; Maranas, Costas D.

2016-12-20

Kinetic models of metabolism at a genome scale that faithfully recapitulate the effect of multiple genetic interventions would be transformative in our ability to reliably design novel overproducing microbial strains. Here, we introduce k-ecoli457, a genome-scale kinetic model of Escherichia coli metabolism that satisfies fluxomic data for wild-type and 25 mutant strains under different substrates and growth conditions. The k-ecoli457 model contains 457 model reactions, 337 metabolites and 295 substrate-level regulatory interactions. Parameterization is carried out using a genetic algorithm by simultaneously imposing all available fluxomic data (about 30 measured fluxes per mutant). Furthermore, the Pearson correlation coefficient between experimentalmore » data and predicted product yields for 320 engineered strains spanning 24 product metabolites is 0.84. This is substantially higher than that using flux balance analysis, minimization of metabolic adjustment or maximization of product yield exhibiting systematic errors with correlation coefficients of, respectively, 0.18, 0.37 and 0.47.« less

Principles of gene microarray data analysis.

PubMed

Mocellin, Simone; Rossi, Carlo Riccardo

2007-01-01

The development of several gene expression profiling methods, such as comparative genomic hybridization (CGH), differential display, serial analysis of gene expression (SAGE), and gene microarray, together with the sequencing of the human genome, has provided an opportunity to monitor and investigate the complex cascade of molecular events leading to tumor development and progression. The availability of such large amounts of information has shifted the attention of scientists towards a nonreductionist approach to biological phenomena. High throughput technologies can be used to follow changing patterns of gene expression over time. Among them, gene microarray has become prominent because it is easier to use, does not require large-scale DNA sequencing, and allows for the parallel quantification of thousands of genes from multiple samples. Gene microarray technology is rapidly spreading worldwide and has the potential to drastically change the therapeutic approach to patients affected with tumor. Therefore, it is of paramount importance for both researchers and clinicians to know the principles underlying the analysis of the huge amount of data generated with microarray technology.

Genome amplification of single sperm using multiple displacement amplification.

PubMed

Jiang, Zhengwen; Zhang, Xingqi; Deka, Ranjan; Jin, Li

2005-06-07

Sperm typing is an effective way to study recombination rate on a fine scale in regions of interest. There are two strategies for the amplification of single meiotic recombinants: repulsion-phase allele-specific PCR and whole genome amplification (WGA). The former can selectively amplify single recombinant molecules from a batch of sperm but is not scalable for high-throughput operation. Currently, primer extension pre-amplification is the only method used in WGA of single sperm, whereas it has limited capacity to produce high-coverage products enough for the analysis of local recombination rate in multiple large regions. Here, we applied for the first time a recently developed WGA method, multiple displacement amplification (MDA), to amplify single sperm DNA, and demonstrated its great potential for producing high-yield and high-coverage products. In a 50 mul reaction, 76 or 93% of loci can be amplified at least 2500- or 250-fold, respectively, from single sperm DNA, and second-round MDA can further offer >200-fold amplification. The MDA products are usable for a variety of genetic applications, including sequencing and microsatellite marker and single nucleotide polymorphism (SNP) analysis. The use of MDA in single sperm amplification may open a new era for studies on local recombination rates.

Blueprints for green biotech: development and application of standards for plant synthetic biology.

PubMed

Patron, Nicola J

2016-06-15

Synthetic biology aims to apply engineering principles to the design and modification of biological systems and to the construction of biological parts and devices. The ability to programme cells by providing new instructions written in DNA is a foundational technology of the field. Large-scale de novo DNA synthesis has accelerated synthetic biology by offering custom-made molecules at ever decreasing costs. However, for large fragments and for experiments in which libraries of DNA sequences are assembled in different combinations, assembly in the laboratory is still desirable. Biological assembly standards allow DNA parts, even those from multiple laboratories and experiments, to be assembled together using the same reagents and protocols. The adoption of such standards for plant synthetic biology has been cohesive for the plant science community, facilitating the application of genome editing technologies to plant systems and streamlining progress in large-scale, multi-laboratory bioengineering projects. © 2016 The Author(s). published by Portland Press Limited on behalf of the Biochemical Society.

The Cancer Genome Atlas (TCGA): The next stage - TCGA

Cancer.gov

The Cancer Genome Atlas (TCGA), the NIH research program that has helped set the standards for characterizing the genomic underpinnings of dozens of cancers on a large scale, is moving to its next phase.

Frequently Asked Questions about Genetic and Genomic Science

MedlinePlus

... of the new genetic and genomic techniques and technologies? Proteomics The suffix "-ome" comes from the Greek ... pharmacogenomics is one of the large-scale "omic" technologies, it can examine the entirety of the genome, ...

Dynamic Quantitative Trait Locus Analysis of Plant Phenomic Data.

PubMed

Li, Zitong; Sillanpää, Mikko J

2015-12-01

Advanced platforms have recently become available for automatic and systematic quantification of plant growth and development. These new techniques can efficiently produce multiple measurements of phenotypes over time, and introduce time as an extra dimension to quantitative trait locus (QTL) studies. Functional mapping utilizes a class of statistical models for identifying QTLs associated with the growth characteristics of interest. A major benefit of functional mapping is that it integrates information over multiple timepoints, and therefore could increase the statistical power for QTL detection. We review the current development of computationally efficient functional mapping methods which provide invaluable tools for analyzing large-scale timecourse data that are readily available in our post-genome era. Copyright © 2015 Elsevier Ltd. All rights reserved.

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/.

“SNP Snappy”: A Strategy for Fast Genome-Wide Association Studies Fitting a Full Mixed Model

PubMed Central

Meyer, Karin; Tier, Bruce

2012-01-01

A strategy to reduce computational demands of genome-wide association studies fitting a mixed model is presented. Improvements are achieved by utilizing a large proportion of calculations that remain constant across the multiple analyses for individual markers involved, with estimates obtained without inverting large matrices. PMID:22021386

Hi-Corrector: a fast, scalable and memory-efficient package for normalizing large-scale Hi-C data.

PubMed

Li, Wenyuan; Gong, Ke; Li, Qingjiao; Alber, Frank; Zhou, Xianghong Jasmine

2015-03-15

Genome-wide proximity ligation assays, e.g. Hi-C and its variant TCC, have recently become important tools to study spatial genome organization. Removing biases from chromatin contact matrices generated by such techniques is a critical preprocessing step of subsequent analyses. The continuing decline of sequencing costs has led to an ever-improving resolution of the Hi-C data, resulting in very large matrices of chromatin contacts. Such large-size matrices, however, pose a great challenge on the memory usage and speed of its normalization. Therefore, there is an urgent need for fast and memory-efficient methods for normalization of Hi-C data. We developed Hi-Corrector, an easy-to-use, open source implementation of the Hi-C data normalization algorithm. Its salient features are (i) scalability-the software is capable of normalizing Hi-C data of any size in reasonable times; (ii) memory efficiency-the sequential version can run on any single computer with very limited memory, no matter how little; (iii) fast speed-the parallel version can run very fast on multiple computing nodes with limited local memory. The sequential version is implemented in ANSI C and can be easily compiled on any system; the parallel version is implemented in ANSI C with the MPI library (a standardized and portable parallel environment designed for solving large-scale scientific problems). The package is freely available at http://zhoulab.usc.edu/Hi-Corrector/. © The Author 2014. Published by Oxford University Press.

Economic importance, taxonomic representation and scientific priority as drivers of genome sequencing projects.

PubMed

Vallée, Geneviève C; Muñoz, Daniella Santos; Sankoff, David

2016-11-11

Of the approximately two hundred sequenced plant genomes, how many and which ones were sequenced motivated by strictly or largely scientific considerations, and how many by chiefly economic, in a wide sense, incentives? And how large a role does publication opportunity play? In an integration of multiple disparate databases and other sources of information, we collect and analyze data on the size (number of species) in the plant orders and families containing sequenced genomes, on the trade value of these species, and of all the same-family or same-order species, and on the publication priority within the family and order. These data are subjected to multiple regression and other statistical analyses. We find that despite the initial importance of model organisms, it is clearly economic considerations that outweigh others in the choice of genome to be sequenced. This has important implications for generalizations about plant genomes, since human choices of plants to harvest (and cultivate) will have incurred many biases with respect to phenotypic characteristics and hence of genomic properties, and recent genomic evolution will also have been affected by human agricultural practices.

Engineered human skin substitutes undergo large-scale genomic reprogramming and normal skin-like maturation after transplantation to athymic mice.

PubMed

Klingenberg, Jennifer M; McFarland, Kevin L; Friedman, Aaron J; Boyce, Steven T; Aronow, Bruce J; Supp, Dorothy M

2010-02-01

Bioengineered skin substitutes can facilitate wound closure in severely burned patients, but deficiencies limit their outcomes compared with native skin autografts. To identify gene programs associated with their in vivo capabilities and limitations, we extended previous gene expression profile analyses to now compare engineered skin after in vivo grafting with both in vitro maturation and normal human skin. Cultured skin substitutes were grafted on full-thickness wounds in athymic mice, and biopsy samples for microarray analyses were collected at multiple in vitro and in vivo time points. Over 10,000 transcripts exhibited large-scale expression pattern differences during in vitro and in vivo maturation. Using hierarchical clustering, 11 different expression profile clusters were partitioned on the basis of differential sample type and temporal stage-specific activation or repression. Analyses show that the wound environment exerts a massive influence on gene expression in skin substitutes. For example, in vivo-healed skin substitutes gained the expression of many native skin-expressed genes, including those associated with epidermal barrier and multiple categories of cell-cell and cell-basement membrane adhesion. In contrast, immunological, trichogenic, and endothelial gene programs were largely lacking. These analyses suggest important areas for guiding further improvement of engineered skin for both increased homology with native skin and enhanced wound healing.

Continental-level population differentiation and environmental adaptation in the mushroom Suillus brevipes

PubMed Central

Branco, Sara; Bi, Ke; Liao, Hui-Ling; Gladieux, Pierre; Badouin, Hélène; Ellison, Christopher E.; Nguyen, Nhu H.; Vilgalys, Rytas; Peay, Kabir G.; Taylor, John W.; Bruns, Thomas D.

2016-01-01

Recent advancements in sequencing technology allowed researchers to better address the patterns and mechanisms involved in microbial environmental adaptation at large spatial scales. Here we investigated the genomic basis of adaptation to climate at the continental scale in Suillus brevipes, an ectomycorrhizal fungus symbiotically associated with the roots of pine trees. We used genomic data from 55 individuals in seven locations across North America to perform genome scans to detect signatures of positive selection and assess whether temperature and precipitation were associated with genetic differentiation. We found that S. brevipes exhibited overall strong population differentiation, with potential admixture in Canadian populations. This species also displayed genomic signatures of positive selection as well as genomic sites significantly associated with distinct climatic regimes and abiotic environmental parameters. These genomic regions included genes involved in transmembrane transport of substances and helicase activity potentially involved in cold stress response. Our study sheds light on large-scale environmental adaptation in fungi by identifying putative adaptive genes and providing a framework to further investigate the genetic basis of fungal adaptation. PMID:27761941

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.

GenoMetric Query Language: a novel approach to large-scale genomic data management.

PubMed

Masseroli, Marco; Pinoli, Pietro; Venco, Francesco; Kaitoua, Abdulrahman; Jalili, Vahid; Palluzzi, Fernando; Muller, Heiko; Ceri, Stefano

2015-06-15

Improvement of sequencing technologies and data processing pipelines is rapidly providing sequencing data, with associated high-level features, of many individual genomes in multiple biological and clinical conditions. They allow for data-driven genomic, transcriptomic and epigenomic characterizations, but require state-of-the-art 'big data' computing strategies, with abstraction levels beyond available tool capabilities. We propose a high-level, declarative GenoMetric Query Language (GMQL) and a toolkit for its use. GMQL operates downstream of raw data preprocessing pipelines and supports queries over thousands of heterogeneous datasets and samples; as such it is key to genomic 'big data' analysis. GMQL leverages a simple data model that provides both abstractions of genomic region data and associated experimental, biological and clinical metadata and interoperability between many data formats. Based on Hadoop framework and Apache Pig platform, GMQL ensures high scalability, expressivity, flexibility and simplicity of use, as demonstrated by several biological query examples on ENCODE and TCGA datasets. The GMQL toolkit is freely available for non-commercial use at http://www.bioinformatics.deib.polimi.it/GMQL/. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Pharmacogenomic agreement between two cancer cell line data sets.

PubMed

2015-12-03

Large cancer cell line collections broadly capture the genomic diversity of human cancers and provide valuable insight into anti-cancer drug response. Here we show substantial agreement and biological consilience between drug sensitivity measurements and their associated genomic predictors from two publicly available large-scale pharmacogenomics resources: The Cancer Cell Line Encyclopedia and the Genomics of Drug Sensitivity in Cancer databases.

Distinct retroelement classes define evolutionary breakpoints demarcating sites of evolutionary novelty

PubMed Central

Longo, Mark S; Carone, Dawn M; Green, Eric D; O'Neill, Michael J; O'Neill, Rachel J

2009-01-01

Background Large-scale genome rearrangements brought about by chromosome breaks underlie numerous inherited diseases, initiate or promote many cancers and are also associated with karyotype diversification during species evolution. Recent research has shown that these breakpoints are nonrandomly distributed throughout the mammalian genome and many, termed "evolutionary breakpoints" (EB), are specific genomic locations that are "reused" during karyotypic evolution. When the phylogenetic trajectory of orthologous chromosome segments is considered, many of these EB are coincident with ancient centromere activity as well as new centromere formation. While EB have been characterized as repeat-rich regions, it has not been determined whether specific sequences have been retained during evolution that would indicate previous centromere activity or a propensity for new centromere formation. Likewise, the conservation of specific sequence motifs or classes at EBs among divergent mammalian taxa has not been determined. Results To define conserved sequence features of EBs associated with centromere evolution, we performed comparative sequence analysis of more than 4.8 Mb within the tammar wallaby, Macropus eugenii, derived from centromeric regions (CEN), euchromatic regions (EU), and an evolutionary breakpoint (EB) that has undergone convergent breakpoint reuse and past centromere activity in marsupials. We found a dramatic enrichment for long interspersed nucleotide elements (LINE1s) and endogenous retroviruses (ERVs) and a depletion of short interspersed nucleotide elements (SINEs) shared between CEN and EBs. We analyzed the orthologous human EB (14q32.33), known to be associated with translocations in many cancers including multiple myelomas and plasma cell leukemias, and found a conserved distribution of similar repetitive elements. Conclusion Our data indicate that EBs tracked within the class Mammalia harbor sequence features retained since the divergence of marsupials and eutherians that may have predisposed these genomic regions to large-scale chromosomal instability. PMID:19630942

A continuum of admixture in the Western Hemisphere revealed by the African Diaspora genome

PubMed Central

Mathias, Rasika Ann; Taub, Margaret A.; Gignoux, Christopher R.; Fu, Wenqing; Musharoff, Shaila; O'Connor, Timothy D.; Vergara, Candelaria; Torgerson, Dara G.; Pino-Yanes, Maria; Shringarpure, Suyash S.; Huang, Lili; Rafaels, Nicholas; Boorgula, Meher Preethi; Johnston, Henry Richard; Ortega, Victor E.; Levin, Albert M.; Song, Wei; Torres, Raul; Padhukasahasram, Badri; Eng, Celeste; Mejia-Mejia, Delmy-Aracely; Ferguson, Trevor; Qin, Zhaohui S.; Scott, Alan F.; Yazdanbakhsh, Maria; Wilson, James G.; Marrugo, Javier; Lange, Leslie A.; Kumar, Rajesh; Avila, Pedro C.; Williams, L. Keoki; Watson, Harold; Ware, Lorraine B.; Olopade, Christopher; Olopade, Olufunmilayo; Oliveira, Ricardo; Ober, Carole; Nicolae, Dan L.; Meyers, Deborah; Mayorga, Alvaro; Knight-Madden, Jennifer; Hartert, Tina; Hansel, Nadia N.; Foreman, Marilyn G.; Ford, Jean G.; Faruque, Mezbah U.; Dunston, Georgia M.; Caraballo, Luis; Burchard, Esteban G.; Bleecker, Eugene; Araujo, Maria Ilma; Herrera-Paz, Edwin Francisco; Gietzen, Kimberly; Grus, Wendy E.; Bamshad, Michael; Bustamante, Carlos D.; Kenny, Eimear E.; Hernandez, Ryan D.; Beaty, Terri H.; Ruczinski, Ingo; Akey, Joshua; Campbell, Monica; Chavan, Sameer; Foster, Cassandra; Gao, Li; Horowitz, Edward; Ortiz, Romina; Potee, Joseph; Gao, Jingjing; Hu, Yijuan; Hansen, Mark; Deshpande, Aniket; Locke, Devin P.; Grammer, Leslie; Kim, Kwang-YounA; Schleimer, Robert; De La Vega, Francisco M.; Szpiech, Zachary A.; Oluwole, Oluwafemi; Arinola, Ganiyu; Correa, Adolfo; Musani, Solomon; Chong, Jessica; Nickerson, Deborah; Reiner, Alexander; Maul, Pissamai; Maul, Trevor; Martinez, Beatriz; Meza, Catherine; Ayestas, Gerardo; Landaverde-Torres, Pamela; Erazo, Said Omar Leiva; Martinez, Rosella; Mayorga, Luis F.; Ramos, Hector; Saenz, Allan; Varela, Gloria; Vasquez, Olga Marina; Samms-Vaughan, Maureen; Wilks, Rainford J.; Adegnika, Akim; Ateba-Ngoa, Ulysse; Barnes, Kathleen C.

2016-01-01

The African Diaspora in the Western Hemisphere represents one of the largest forced migrations in history and had a profound impact on genetic diversity in modern populations. To date, the fine-scale population structure of descendants of the African Diaspora remains largely uncharacterized. Here we present genetic variation from deeply sequenced genomes of 642 individuals from North and South American, Caribbean and West African populations, substantially increasing the lexicon of human genomic variation and suggesting much variation remains to be discovered in African-admixed populations in the Americas. We summarize genetic variation in these populations, quantifying the postcolonial sex-biased European gene flow across multiple regions. Moreover, we refine estimates on the burden of deleterious variants carried across populations and how this varies with African ancestry. Our data are an important resource for empowering disease mapping studies in African-admixed individuals and will facilitate gene discovery for diseases disproportionately affecting individuals of African ancestry. PMID:27725671

GAMES identifies and annotates mutations in next-generation sequencing projects.

PubMed

Sana, Maria Elena; Iascone, Maria; Marchetti, Daniela; Palatini, Jeff; Galasso, Marco; Volinia, Stefano

2011-01-01

Next-generation sequencing (NGS) methods have the potential for changing the landscape of biomedical science, but at the same time pose several problems in analysis and interpretation. Currently, there are many commercial and public software packages that analyze NGS data. However, the limitations of these applications include output which is insufficiently annotated and of difficult functional comprehension to end users. We developed GAMES (Genomic Analysis of Mutations Extracted by Sequencing), a pipeline aiming to serve as an efficient middleman between data deluge and investigators. GAMES attains multiple levels of filtering and annotation, such as aligning the reads to a reference genome, performing quality control and mutational analysis, integrating results with genome annotations and sorting each mismatch/deletion according to a range of parameters. Variations are matched to known polymorphisms. The prediction of functional mutations is achieved by using different approaches. Overall GAMES enables an effective complexity reduction in large-scale DNA-sequencing projects. GAMES is available free of charge to academic users and may be obtained from http://aqua.unife.it/GAMES.

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...

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

Genome Partitioner: A web tool for multi-level partitioning of large-scale DNA constructs for synthetic biology applications.

PubMed

Christen, Matthias; Del Medico, Luca; Christen, Heinz; Christen, Beat

2017-01-01

Recent advances in lower-cost DNA synthesis techniques have enabled new innovations in the field of synthetic biology. Still, efficient design and higher-order assembly of genome-scale DNA constructs remains a labor-intensive process. Given the complexity, computer assisted design tools that fragment large DNA sequences into fabricable DNA blocks are needed to pave the way towards streamlined assembly of biological systems. Here, we present the Genome Partitioner software implemented as a web-based interface that permits multi-level partitioning of genome-scale DNA designs. Without the need for specialized computing skills, biologists can submit their DNA designs to a fully automated pipeline that generates the optimal retrosynthetic route for higher-order DNA assembly. To test the algorithm, we partitioned a 783 kb Caulobacter crescentus genome design. We validated the partitioning strategy by assembling a 20 kb test segment encompassing a difficult to synthesize DNA sequence. Successful assembly from 1 kb subblocks into the 20 kb segment highlights the effectiveness of the Genome Partitioner for reducing synthesis costs and timelines for higher-order DNA assembly. The Genome Partitioner is broadly applicable to translate DNA designs into ready to order sequences that can be assembled with standardized protocols, thus offering new opportunities to harness the diversity of microbial genomes for synthetic biology applications. The Genome Partitioner web tool can be accessed at https://christenlab.ethz.ch/GenomePartitioner.

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

Weighted mining of massive collections of [Formula: see text]-values by convex optimization.

PubMed

Dobriban, Edgar

2018-06-01

Researchers in data-rich disciplines-think of computational genomics and observational cosmology-often wish to mine large bodies of [Formula: see text]-values looking for significant effects, while controlling the false discovery rate or family-wise error rate. Increasingly, researchers also wish to prioritize certain hypotheses, for example, those thought to have larger effect sizes, by upweighting, and to impose constraints on the underlying mining, such as monotonicity along a certain sequence. We introduce Princessp , a principled method for performing weighted multiple testing by constrained convex optimization. Our method elegantly allows one to prioritize certain hypotheses through upweighting and to discount others through downweighting, while constraining the underlying weights involved in the mining process. When the [Formula: see text]-values derive from monotone likelihood ratio families such as the Gaussian means model, the new method allows exact solution of an important optimal weighting problem previously thought to be non-convex and computationally infeasible. Our method scales to massive data set sizes. We illustrate the applications of Princessp on a series of standard genomics data sets and offer comparisons with several previous 'standard' methods. Princessp offers both ease of operation and the ability to scale to extremely large problem sizes. The method is available as open-source software from github.com/dobriban/pvalue_weighting_matlab (accessed 11 October 2017).

A Powerful Approach to Estimating Annotation-Stratified Genetic Covariance via GWAS Summary Statistics.

PubMed

Lu, Qiongshi; Li, Boyang; Ou, Derek; Erlendsdottir, Margret; Powles, Ryan L; Jiang, Tony; Hu, Yiming; Chang, David; Jin, Chentian; Dai, Wei; He, Qidu; Liu, Zefeng; Mukherjee, Shubhabrata; Crane, Paul K; Zhao, Hongyu

2017-12-07

Despite the success of large-scale genome-wide association studies (GWASs) on complex traits, our understanding of their genetic architecture is far from complete. Jointly modeling multiple traits' genetic profiles has provided insights into the shared genetic basis of many complex traits. However, large-scale inference sets a high bar for both statistical power and biological interpretability. Here we introduce a principled framework to estimate annotation-stratified genetic covariance between traits using GWAS summary statistics. Through theoretical and numerical analyses, we demonstrate that our method provides accurate covariance estimates, thereby enabling researchers to dissect both the shared and distinct genetic architecture across traits to better understand their etiologies. Among 50 complex traits with publicly accessible GWAS summary statistics (N total ≈ 4.5 million), we identified more than 170 pairs with statistically significant genetic covariance. In particular, we found strong genetic covariance between late-onset Alzheimer disease (LOAD) and amyotrophic lateral sclerosis (ALS), two major neurodegenerative diseases, in single-nucleotide polymorphisms (SNPs) with high minor allele frequencies and in SNPs located in the predicted functional genome. Joint analysis of LOAD, ALS, and other traits highlights LOAD's correlation with cognitive traits and hints at an autoimmune component for ALS. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

A CRISPR-Based Toolbox for Studying T Cell Signal Transduction

PubMed Central

Chi, Shen; Weiss, Arthur; Wang, Haopeng

2016-01-01

CRISPR/Cas9 system is a powerful technology to perform genome editing in a variety of cell types. To facilitate the application of Cas9 in mapping T cell signaling pathways, we generated a toolbox for large-scale genetic screens in human Jurkat T cells. The toolbox has three different Jurkat cell lines expressing distinct Cas9 variants, including wild-type Cas9, dCas9-KRAB, and sunCas9. We demonstrated that the toolbox allows us to rapidly disrupt endogenous gene expression at the DNA level and to efficiently repress or activate gene expression at the transcriptional level. The toolbox, in combination with multiple currently existing genome-wide sgRNA libraries, will be useful to systematically investigate T cell signal transduction using both loss-of-function and gain-of-function genetic screens. PMID:27057542

TipMT: Identification of PCR-based taxon-specific markers.

PubMed

Rodrigues-Luiz, Gabriela F; Cardoso, Mariana S; Valdivia, Hugo O; Ayala, Edward V; Gontijo, Célia M F; Rodrigues, Thiago de S; Fujiwara, Ricardo T; Lopes, Robson S; Bartholomeu, Daniella C

2017-02-11

Molecular genetic markers are one of the most informative and widely used genome features in clinical and environmental diagnostic studies. A polymerase chain reaction (PCR)-based molecular marker is very attractive because it is suitable to high throughput automation and confers high specificity. However, the design of taxon-specific primers may be difficult and time consuming due to the need to identify appropriate genomic regions for annealing primers and to evaluate primer specificity. Here, we report the development of a Tool for Identification of Primers for Multiple Taxa (TipMT), which is a web application to search and design primers for genotyping based on genomic data. The tool identifies and targets single sequence repeats (SSR) or orthologous/taxa-specific genes for genotyping using Multiplex PCR. This pipeline was applied to the genomes of four species of Leishmania (L. amazonensis, L. braziliensis, L. infantum and L. major) and validated by PCR using artificial genomic DNA mixtures of the Leishmania species as templates. This experimental validation demonstrates the reliability of TipMT because amplification profiles showed discrimination of genomic DNA samples from Leishmania species. The TipMT web tool allows for large-scale identification and design of taxon-specific primers and is freely available to the scientific community at http://200.131.37.155/tipMT/ .

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

Conifer DBMagic: A database housing multiple de novo transcriptome assemblies for twelve diverse conifer species

Treesearch

W. Walter Lorenz; Savavanaraj Ayyampalayam; John M. Bordeaux; Glenn T. Howe; Kathleen D. Jermstad; David B. Neale; Deborah L. Rogers; Jeffrey F.D. Dean

2012-01-01

Conifers comprise an ancient and widespread plant lineage of enormous commercial and ecological value. However, compared to model woody angiosperms, such as Populus and Eucalyptus, our understanding of conifers remains quite limited at a genomic level. Large genome sizes (10,000-40,000 Mbp) and large amounts of repetitive DNA...

Genome multiplication as adaptation to tissue survival: evidence from gene expression in mammalian heart and liver.

PubMed

Anatskaya, Olga V; Vinogradov, Alexander E

2007-01-01

To elucidate the functional significance of genome multiplication in somatic tissues, we performed a large-scale analysis of ploidy-associated changes in expression of non-tissue-specific (i.e., broadly expressed) genes in the heart and liver of human and mouse (6585 homologous genes were analyzed). These species have inverse patterns of polyploidization in cardiomyocytes and hepatocytes. The between-species comparison of two pairs of homologous tissues with crisscross contrast in ploidy levels allows the removal of the effects of species and tissue specificity on the profile of gene activity. The different tests performed from the standpoint of modular biology revealed a consistent picture of ploidy-associated alteration in a wide range of functional gene groups. The major effects consisted of hypoxia-inducible factor-triggered changes in main cellular processes and signaling pathways, activation of defense against DNA lesions, acceleration of protein turnover and transcription, and the impairment of apoptosis, the immune response, and cytoskeleton maintenance. We also found a severe decline in aerobic respiration and stimulation of sugar and fatty acid metabolism. These metabolic rearrangements create a special type of metabolism that can be considered intermediate between aerobic and anaerobic. The metabolic and physiological changes revealed (reflected in the alteration of gene expression) help explain the unique ability of polyploid tissues to combine proliferation and differentiation, which are separated in diploid tissues. We argue that genome multiplication promotes cell survival and tissue regeneration under stressful conditions.

Pediatric Multiple Sclerosis: Genes, Environment, and a Comprehensive Therapeutic Approach.

PubMed

Cappa, Ryan; Theroux, Liana; Brenton, J Nicholas

2017-10-01

Pediatric multiple sclerosis is an increasingly recognized and studied disorder that accounts for 3% to 10% of all patients with multiple sclerosis. The risk for pediatric multiple sclerosis is thought to reflect a complex interplay between environmental and genetic risk factors. Environmental exposures, including sunlight (ultraviolet radiation, vitamin D levels), infections (Epstein-Barr virus), passive smoking, and obesity, have been identified as potential risk factors in youth. Genetic predisposition contributes to the risk of multiple sclerosis, and the major histocompatibility complex on chromosome 6 makes the single largest contribution to susceptibility to multiple sclerosis. With the use of large-scale genome-wide association studies, other non-major histocompatibility complex alleles have been identified as independent risk factors for the disease. The bridge between environment and genes likely lies in the study of epigenetic processes, which are environmentally-influenced mechanisms through which gene expression may be modified. This article will review these topics to provide a framework for discussion of a comprehensive approach to counseling and ultimately treating the pediatric patient with multiple sclerosis. Copyright © 2017 Elsevier Inc. All rights reserved.

Identifying micro-inversions using high-throughput sequencing reads.

PubMed

He, Feifei; Li, Yang; Tang, Yu-Hang; Ma, Jian; Zhu, Huaiqiu

2016-01-11

The identification of inversions of DNA segments shorter than read length (e.g., 100 bp), defined as micro-inversions (MIs), remains challenging for next-generation sequencing reads. It is acknowledged that MIs are important genomic variation and may play roles in causing genetic disease. However, current alignment methods are generally insensitive to detect MIs. Here we develop a novel tool, MID (Micro-Inversion Detector), to identify MIs in human genomes using next-generation sequencing reads. The algorithm of MID is designed based on a dynamic programming path-finding approach. What makes MID different from other variant detection tools is that MID can handle small MIs and multiple breakpoints within an unmapped read. Moreover, MID improves reliability in low coverage data by integrating multiple samples. Our evaluation demonstrated that MID outperforms Gustaf, which can currently detect inversions from 30 bp to 500 bp. To our knowledge, MID is the first method that can efficiently and reliably identify MIs from unmapped short next-generation sequencing reads. MID is reliable on low coverage data, which is suitable for large-scale projects such as the 1000 Genomes Project (1KGP). MID identified previously unknown MIs from the 1KGP that overlap with genes and regulatory elements in the human genome. We also identified MIs in cancer cell lines from Cancer Cell Line Encyclopedia (CCLE). Therefore our tool is expected to be useful to improve the study of MIs as a type of genetic variant in the human genome. The source code can be downloaded from: http://cqb.pku.edu.cn/ZhuLab/MID .

The Psychiatric Genomics Consortium Posttraumatic Stress Disorder Workgroup: Posttraumatic Stress Disorder Enters the Age of Large-Scale Genomic Collaboration

PubMed Central

Logue, Mark W; Amstadter, Ananda B; Baker, Dewleen G; Duncan, Laramie; Koenen, Karestan C; Liberzon, Israel; Miller, Mark W; Morey, Rajendra A; Nievergelt, Caroline M; Ressler, Kerry J; Smith, Alicia K; Smoller, Jordan W; Stein, Murray B; Sumner, Jennifer A; Uddin, Monica

2015-01-01

The development of posttraumatic stress disorder (PTSD) is influenced by genetic factors. Although there have been some replicated candidates, the identification of risk variants for PTSD has lagged behind genetic research of other psychiatric disorders such as schizophrenia, autism, and bipolar disorder. Psychiatric genetics has moved beyond examination of specific candidate genes in favor of the genome-wide association study (GWAS) strategy of very large numbers of samples, which allows for the discovery of previously unsuspected genes and molecular pathways. The successes of genetic studies of schizophrenia and bipolar disorder have been aided by the formation of a large-scale GWAS consortium: the Psychiatric Genomics Consortium (PGC). In contrast, only a handful of GWAS of PTSD have appeared in the literature to date. Here we describe the formation of a group dedicated to large-scale study of PTSD genetics: the PGC-PTSD. The PGC-PTSD faces challenges related to the contingency on trauma exposure and the large degree of ancestral genetic diversity within and across participating studies. Using the PGC analysis pipeline supplemented by analyses tailored to address these challenges, we anticipate that our first large-scale GWAS of PTSD will comprise over 10 000 cases and 30 000 trauma-exposed controls. Following in the footsteps of our PGC forerunners, this collaboration—of a scope that is unprecedented in the field of traumatic stress—will lead the search for replicable genetic associations and new insights into the biological underpinnings of PTSD. PMID:25904361

CGDV: a webtool for circular visualization of genomics and transcriptomics data.

PubMed

Jha, Vineet; Singh, Gulzar; Kumar, Shiva; Sonawane, Amol; Jere, Abhay; Anamika, Krishanpal

2017-10-24

Interpretation of large-scale data is very challenging and currently there is scarcity of web tools which support automated visualization of a variety of high throughput genomics and transcriptomics data and for a wide variety of model organisms along with user defined karyotypes. Circular plot provides holistic visualization of high throughput large scale data but it is very complex and challenging to generate as most of the available tools need informatics expertise to install and run them. We have developed CGDV (Circos for Genomics and Transcriptomics Data Visualization), a webtool based on Circos, for seamless and automated visualization of a variety of large scale genomics and transcriptomics data. CGDV takes output of analyzed genomics or transcriptomics data of different formats, such as vcf, bed, xls, tab limited matrix text file, CNVnator raw output and Gene fusion raw output, to plot circular view of the sample data. CGDV take cares of generating intermediate files required for circos. CGDV is freely available at https://cgdv-upload.persistent.co.in/cgdv/ . The circular plot for each data type is tailored to gain best biological insights into the data. The inter-relationship between data points, homologous sequences, genes involved in fusion events, differential expression pattern, sequencing depth, types and size of variations and enrichment of DNA binding proteins can be seen using CGDV. CGDV thus helps biologists and bioinformaticians to visualize a variety of genomics and transcriptomics data seamlessly.

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.

Serendipitous discovery of Wolbachia genomes in multiple Drosophila species.

PubMed

Salzberg, Steven L; Dunning Hotopp, Julie C; Delcher, Arthur L; Pop, Mihai; Smith, Douglas R; Eisen, Michael B; Nelson, William C

2005-01-01

The Trace Archive is a repository for the raw, unanalyzed data generated by large-scale genome sequencing projects. The existence of this data offers scientists the possibility of discovering additional genomic sequences beyond those originally sequenced. In particular, if the source DNA for a sequencing project came from a species that was colonized by another organism, then the project may yield substantial amounts of genomic DNA, including near-complete genomes, from the symbiotic or parasitic organism. By searching the publicly available repository of DNA sequencing trace data, we discovered three new species of the bacterial endosymbiont Wolbachia pipientis in three different species of fruit fly: Drosophila ananassae, D. simulans, and D. mojavensis. We extracted all sequences with partial matches to a previously sequenced Wolbachia strain and assembled those sequences using customized software. For one of the three new species, the data recovered were sufficient to produce an assembly that covers more than 95% of the genome; for a second species the data produce the equivalent of a 'light shotgun' sampling of the genome, covering an estimated 75-80% of the genome; and for the third species the data cover approximately 6-7% of the genome. The results of this study reveal an unexpected benefit of depositing raw data in a central genome sequence repository: new species can be discovered within this data. The differences between these three new Wolbachia genomes and the previously sequenced strain revealed numerous rearrangements and insertions within each lineage and hundreds of novel genes. The three new genomes, with annotation, have been deposited in GenBank.

SynFind: Compiling Syntenic Regions across Any Set of Genomes on Demand.

PubMed

Tang, Haibao; Bomhoff, Matthew D; Briones, Evan; Zhang, Liangsheng; Schnable, James C; Lyons, Eric

2015-11-11

The identification of conserved syntenic regions enables discovery of predicted locations for orthologous and homeologous genes, even when no such gene is present. This capability means that synteny-based methods are far more effective than sequence similarity-based methods in identifying true-negatives, a necessity for studying gene loss and gene transposition. However, the identification of syntenic regions requires complex analyses which must be repeated for pairwise comparisons between any two species. Therefore, as the number of published genomes increases, there is a growing demand for scalable, simple-to-use applications to perform comparative genomic analyses that cater to both gene family studies and genome-scale studies. We implemented SynFind, a web-based tool that addresses this need. Given one query genome, SynFind is capable of identifying conserved syntenic regions in any set of target genomes. SynFind is capable of reporting per-gene information, useful for researchers studying specific gene families, as well as genome-wide data sets of syntenic gene and predicted gene locations, critical for researchers focused on large-scale genomic analyses. Inference of syntenic homologs provides the basis for correlation of functional changes around genes of interests between related organisms. Deployed on the CoGe online platform, SynFind is connected to the genomic data from over 15,000 organisms from all domains of life as well as supporting multiple releases of the same organism. SynFind makes use of a powerful job execution framework that promises scalability and reproducibility. SynFind can be accessed at http://genomevolution.org/CoGe/SynFind.pl. A video tutorial of SynFind using Phytophthrora as an example is available at http://www.youtube.com/watch?v=2Agczny9Nyc. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Large-scale chromatin remodeling at the immunoglobulin heavy chain locus: a paradigm for multigene regulation.

PubMed

Bolland, Daniel J; Wood, Andrew L; Corcoran, Anne E

2009-01-01

V(D)J recombination in lymphocytes is the cutting and pasting together of antigen receptor genes in cis to generate the enormous variety of coding sequences required to produce diverse antigen receptor proteins. It is the key role of the adaptive immune response, which must potentially combat millions of different foreign antigens. Most antigen receptor loci have evolved to be extremely large and contain multiple individual V, D and J genes. The immunoglobulin heavy chain (Igh) and immunoglobulin kappa light chain (Igk) loci are the largest multigene loci in the mammalian genome and V(D)J recombination is one of the most complicated genetic processes in the nucleus. The challenge for the appropriate lymphocyte is one of macro-management-to make all of the antigen receptor genes in a particular locus available for recombination at the appropriate developmental time-point. Conversely, these large loci must be kept closed in lymphocytes in which they do not normally recombine, to guard against genomic instability generated by the DNA double strand breaks inherent to the V(D)J recombination process. To manage all of these demanding criteria, V(D)J recombination is regulated at numerous levels. It is restricted to lymphocytes since the Rag genes which control the DNA double-strand break step of recombination are only expressed in these cells. Within the lymphocyte lineage, immunoglobulin recombination is restricted to B-lymphocytes and TCR recombination to T-lymphocytes by regulation of locus accessibility, which occurs at multiple levels. Accessibility of recombination signal sequences (RSSs) flanking individual V, D and J genes at the nucleosomal level is the key micro-management mechanism, which is discussed in greater detail in other chapters. This chapter will explore how the antigen receptor loci are regulated as a whole, focussing on the Igh locus as a paradigm for the mechanisms involved. Numerous recent studies have begun to unravel the complex and complementary processes involved in this large-scale locus organisation. We will examine the structure of the Igh locus and the large-scale and higher-order chromatin remodelling processes associated with V(D)J recombination, at the level of the locus itself, its conformational changes and its dynamic localisation within the nucleus.

Extensive Error in the Number of Genes Inferred from Draft Genome Assemblies

PubMed Central

Denton, James F.; Lugo-Martinez, Jose; Tucker, Abraham E.; Schrider, Daniel R.; Warren, Wesley C.; Hahn, Matthew W.

2014-01-01

Current sequencing methods produce large amounts of data, but genome assemblies based on these data are often woefully incomplete. These incomplete and error-filled assemblies result in many annotation errors, especially in the number of genes present in a genome. In this paper we investigate the magnitude of the problem, both in terms of total gene number and the number of copies of genes in specific families. To do this, we compare multiple draft assemblies against higher-quality versions of the same genomes, using several new assemblies of the chicken genome based on both traditional and next-generation sequencing technologies, as well as published draft assemblies of chimpanzee. We find that upwards of 40% of all gene families are inferred to have the wrong number of genes in draft assemblies, and that these incorrect assemblies both add and subtract genes. Using simulated genome assemblies of Drosophila melanogaster, we find that the major cause of increased gene numbers in draft genomes is the fragmentation of genes onto multiple individual contigs. Finally, we demonstrate the usefulness of RNA-Seq in improving the gene annotation of draft assemblies, largely by connecting genes that have been fragmented in the assembly process. PMID:25474019

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

PubMed

Denton, James F; Lugo-Martinez, Jose; Tucker, Abraham E; Schrider, Daniel R; Warren, Wesley C; Hahn, Matthew W

2014-12-01

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

Evaluation of Quality Assessment Protocols for High Throughput Genome Resequencing Data

PubMed Central

Chiara, Matteo; Pavesi, Giulio

2017-01-01

Large-scale initiatives aiming to recover the complete sequence of thousands of human genomes are currently being undertaken worldwide, concurring to the generation of a comprehensive catalog of human genetic variation. The ultimate and most ambitious goal of human population scale genomics is the characterization of the so-called human “variome,” through the identification of causal mutations or haplotypes. Several research institutions worldwide currently use genotyping assays based on Next-Generation Sequencing (NGS) for diagnostics and clinical screenings, and the widespread application of such technologies promises major revolutions in medical science. Bioinformatic analysis of human resequencing data is one of the main factors limiting the effectiveness and general applicability of NGS for clinical studies. The requirement for multiple tools, to be combined in dedicated protocols in order to accommodate different types of data (gene panels, exomes, or whole genomes) and the high variability of the data makes difficult the establishment of a ultimate strategy of general use. While there already exist several studies comparing sensitivity and accuracy of bioinformatic pipelines for the identification of single nucleotide variants from resequencing data, little is known about the impact of quality assessment and reads pre-processing strategies. In this work we discuss major strengths and limitations of the various genome resequencing protocols are currently used in molecular diagnostics and for the discovery of novel disease-causing mutations. By taking advantage of publicly available data we devise and suggest a series of best practices for the pre-processing of the data that consistently improve the outcome of genotyping with minimal impacts on computational costs. PMID:28736571

The Population Reference Sample, POPRES: A Resource for Population, Disease, and Pharmacological Genetics Research

PubMed Central

Nelson, Matthew R.; Bryc, Katarzyna; King, Karen S.; Indap, Amit; Boyko, Adam R.; Novembre, John; Briley, Linda P.; Maruyama, Yuka; Waterworth, Dawn M.; Waeber, Gérard; Vollenweider, Peter; Oksenberg, Jorge R.; Hauser, Stephen L.; Stirnadel, Heide A.; Kooner, Jaspal S.; Chambers, John C.; Jones, Brendan; Mooser, Vincent; Bustamante, Carlos D.; Roses, Allen D.; Burns, Daniel K.; Ehm, Margaret G.; Lai, Eric H.

2008-01-01

Technological and scientific advances, stemming in large part from the Human Genome and HapMap projects, have made large-scale, genome-wide investigations feasible and cost effective. These advances have the potential to dramatically impact drug discovery and development by identifying genetic factors that contribute to variation in disease risk as well as drug pharmacokinetics, treatment efficacy, and adverse drug reactions. In spite of the technological advancements, successful application in biomedical research would be limited without access to suitable sample collections. To facilitate exploratory genetics research, we have assembled a DNA resource from a large number of subjects participating in multiple studies throughout the world. This growing resource was initially genotyped with a commercially available genome-wide 500,000 single-nucleotide polymorphism panel. This project includes nearly 6,000 subjects of African-American, East Asian, South Asian, Mexican, and European origin. Seven informative axes of variation identified via principal-component analysis (PCA) of these data confirm the overall integrity of the data and highlight important features of the genetic structure of diverse populations. The potential value of such extensively genotyped collections is illustrated by selection of genetically matched population controls in a genome-wide analysis of abacavir-associated hypersensitivity reaction. We find that matching based on country of origin, identity-by-state distance, and multidimensional PCA do similarly well to control the type I error rate. The genotype and demographic data from this reference sample are freely available through the NCBI database of Genotypes and Phenotypes (dbGaP). PMID:18760391

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.

Living laboratory: whole-genome sequencing as a learning healthcare enterprise.

PubMed

Angrist, M; Jamal, L

2015-04-01

With the proliferation of affordable large-scale human genomic data come profound and vexing questions about management of such data and their clinical uncertainty. These issues challenge the view that genomic research on human beings can (or should) be fully segregated from clinical genomics, either conceptually or practically. Here, we argue that the sharp distinction between clinical care and research is especially problematic in the context of large-scale genomic sequencing of people with suspected genetic conditions. Core goals of both enterprises (e.g. understanding genotype-phenotype relationships; generating an evidence base for genomic medicine) are more likely to be realized at a population scale if both those ordering and those undergoing sequencing for diagnostic reasons are routinely and longitudinally studied. Rather than relying on expensive and lengthy randomized clinical trials and meta-analyses, we propose leveraging nascent clinical-research hybrid frameworks into a broader, more permanent instantiation of exploratory medical sequencing. Such an investment could enlighten stakeholders about the real-life challenges posed by whole-genome sequencing, such as establishing the clinical actionability of genetic variants, returning 'off-target' results to families, developing effective service delivery models and monitoring long-term outcomes. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The Distant Siblings-A Phylogenomic Roadmap Illuminates the Origins of Extant Diversity in Fungal Aromatic Polyketide Biosynthesis.

PubMed

Koczyk, Grzegorz; Dawidziuk, Adam; Popiel, Delfina

2015-11-03

In recent years, the influx of newly sequenced fungal genomes has enabled sampling of secondary metabolite biosynthesis on an unprecedented scale. However, explanations of extant diversity which take into account both large-scale phylogeny reconstructions and knowledge gained from multiple genome projects are still lacking. We analyzed the evolutionary sources of genetic diversity in aromatic polyketide biosynthesis in over 100 model fungal genomes. By reconciling the history of over 400 nonreducing polyketide synthases (NR-PKSs) with corresponding species history, we demonstrate that extant fungal NR-PKSs are clades of distant siblings, originating from a burst of duplications in early Pezizomycotina and thinned by extensive losses. The capability of higher fungi to biosynthesize the simplest precursor molecule (orsellinic acid) is highlighted as an ancestral trait underlying biosynthesis of aromatic compounds. This base activity was modified during early evolution of filamentous fungi, toward divergent reaction schemes associated with biosynthesis of, for example, aflatoxins and fusarubins (C4-C9 cyclization) or various anthraquinone derivatives (C6-C11 cyclization). The functional plasticity is further shown to have been supplemented by modularization of domain architecture into discrete pieces (conserved splice junctions within product template domain), as well as tight linkage of key accessory enzyme families and divergence in employed transcriptional factors. Although the majority of discord between species and gene history is explained by ancient duplications, this landscape has been altered by more recent duplications, as well as multiple horizontal gene transfers. The 25 detected transfers include previously undescribed events leading to emergence of, for example, fusarubin biosynthesis in Fusarium genus. Both the underlying data and the results of present analysis (including alternative scenarios revealed by sampling multiple reconciliation optima) are maintained as a freely available web-based resource: http://cropnet.pl/metasites/sekmet/nrpks_2014. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Genome Partitioner: A web tool for multi-level partitioning of large-scale DNA constructs for synthetic biology applications

PubMed Central

Del Medico, Luca; Christen, Heinz; Christen, Beat

2017-01-01

Recent advances in lower-cost DNA synthesis techniques have enabled new innovations in the field of synthetic biology. Still, efficient design and higher-order assembly of genome-scale DNA constructs remains a labor-intensive process. Given the complexity, computer assisted design tools that fragment large DNA sequences into fabricable DNA blocks are needed to pave the way towards streamlined assembly of biological systems. Here, we present the Genome Partitioner software implemented as a web-based interface that permits multi-level partitioning of genome-scale DNA designs. Without the need for specialized computing skills, biologists can submit their DNA designs to a fully automated pipeline that generates the optimal retrosynthetic route for higher-order DNA assembly. To test the algorithm, we partitioned a 783 kb Caulobacter crescentus genome design. We validated the partitioning strategy by assembling a 20 kb test segment encompassing a difficult to synthesize DNA sequence. Successful assembly from 1 kb subblocks into the 20 kb segment highlights the effectiveness of the Genome Partitioner for reducing synthesis costs and timelines for higher-order DNA assembly. The Genome Partitioner is broadly applicable to translate DNA designs into ready to order sequences that can be assembled with standardized protocols, thus offering new opportunities to harness the diversity of microbial genomes for synthetic biology applications. The Genome Partitioner web tool can be accessed at https://christenlab.ethz.ch/GenomePartitioner. PMID:28531174

Uniform standards for genome databases in forest and fruit trees

USDA-ARS?s Scientific Manuscript database

TreeGenes and tfGDR serve the international forestry and fruit tree genomics research communities, respectively. These databases hold similar sequence data and provide resources for the submission and recovery of this information in order to enable comparative genomics research. Large-scale genotype...

The Genome of the Anaerobic Fungus Orpinomyces sp. Strain C1A Reveals the Unique Evolutionary History of a Remarkable Plant Biomass Degrader

PubMed Central

Youssef, Noha H.; Couger, M. B.; Struchtemeyer, Christopher G.; Liggenstoffer, Audra S.; Prade, Rolf A.; Najar, Fares Z.; Atiyeh, Hasan K.; Wilkins, Mark R.

2013-01-01

Anaerobic gut fungi represent a distinct early-branching fungal phylum (Neocallimastigomycota) and reside in the rumen, hindgut, and feces of ruminant and nonruminant herbivores. The genome of an anaerobic fungal isolate, Orpinomyces sp. strain C1A, was sequenced using a combination of Illumina and PacBio single-molecule real-time (SMRT) technologies. The large genome (100.95 Mb, 16,347 genes) displayed extremely low G+C content (17.0%), large noncoding intergenic regions (73.1%), proliferation of microsatellite repeats (4.9%), and multiple gene duplications. Comparative genomic analysis identified multiple genes and pathways that are absent in Dikarya genomes but present in early-branching fungal lineages and/or nonfungal Opisthokonta. These included genes for posttranslational fucosylation, the production of specific intramembrane proteases and extracellular protease inhibitors, the formation of a complete axoneme and intraflagellar trafficking machinery, and a near-complete focal adhesion machinery. Analysis of the lignocellulolytic machinery in the C1A genome revealed an extremely rich repertoire, with evidence of horizontal gene acquisition from multiple bacterial lineages. Experimental analysis indicated that strain C1A is a remarkable biomass degrader, capable of simultaneous saccharification and fermentation of the cellulosic and hemicellulosic fractions in multiple untreated grasses and crop residues examined, with the process significantly enhanced by mild pretreatments. This capability, acquired during its separate evolutionary trajectory in the rumen, along with its resilience and invasiveness compared to prokaryotic anaerobes, renders anaerobic fungi promising agents for consolidated bioprocessing schemes in biofuels production. PMID:23709508

The genome of the anaerobic fungus Orpinomyces sp. strain C1A reveals the unique evolutionary history of a remarkable plant biomass degrader.

PubMed

Youssef, Noha H; Couger, M B; Struchtemeyer, Christopher G; Liggenstoffer, Audra S; Prade, Rolf A; Najar, Fares Z; Atiyeh, Hasan K; Wilkins, Mark R; Elshahed, Mostafa S

2013-08-01

Anaerobic gut fungi represent a distinct early-branching fungal phylum (Neocallimastigomycota) and reside in the rumen, hindgut, and feces of ruminant and nonruminant herbivores. The genome of an anaerobic fungal isolate, Orpinomyces sp. strain C1A, was sequenced using a combination of Illumina and PacBio single-molecule real-time (SMRT) technologies. The large genome (100.95 Mb, 16,347 genes) displayed extremely low G+C content (17.0%), large noncoding intergenic regions (73.1%), proliferation of microsatellite repeats (4.9%), and multiple gene duplications. Comparative genomic analysis identified multiple genes and pathways that are absent in Dikarya genomes but present in early-branching fungal lineages and/or nonfungal Opisthokonta. These included genes for posttranslational fucosylation, the production of specific intramembrane proteases and extracellular protease inhibitors, the formation of a complete axoneme and intraflagellar trafficking machinery, and a near-complete focal adhesion machinery. Analysis of the lignocellulolytic machinery in the C1A genome revealed an extremely rich repertoire, with evidence of horizontal gene acquisition from multiple bacterial lineages. Experimental analysis indicated that strain C1A is a remarkable biomass degrader, capable of simultaneous saccharification and fermentation of the cellulosic and hemicellulosic fractions in multiple untreated grasses and crop residues examined, with the process significantly enhanced by mild pretreatments. This capability, acquired during its separate evolutionary trajectory in the rumen, along with its resilience and invasiveness compared to prokaryotic anaerobes, renders anaerobic fungi promising agents for consolidated bioprocessing schemes in biofuels production.

Enhancer Sharing Promotes Neighborhoods of Transcriptional Regulation Across Eukaryotes

PubMed Central

Quintero-Cadena, Porfirio; Sternberg, Paul W.

2016-01-01

Enhancers physically interact with transcriptional promoters, looping over distances that can span multiple regulatory elements. Given that enhancer–promoter (EP) interactions generally occur via common protein complexes, it is unclear whether EP pairing is predominantly deterministic or proximity guided. Here, we present cross-organismic evidence suggesting that most EP pairs are compatible, largely determined by physical proximity rather than specific interactions. By reanalyzing transcriptome datasets, we find that the transcription of gene neighbors is correlated over distances that scale with genome size. We experimentally show that nonspecific EP interactions can explain such correlation, and that EP distance acts as a scaling factor for the transcriptional influence of an enhancer. We propose that enhancer sharing is commonplace among eukaryotes, and that EP distance is an important layer of information in gene regulation. PMID:27799341

Correcting Inconsistencies and Errors in Bacterial Genome Metadata Using an Automated Curation Tool in Excel (AutoCurE).

PubMed

Schmedes, Sarah E; King, Jonathan L; Budowle, Bruce

2015-01-01

Whole-genome data are invaluable for large-scale comparative genomic studies. Current sequencing technologies have made it feasible to sequence entire bacterial genomes with relative ease and time with a substantially reduced cost per nucleotide, hence cost per genome. More than 3,000 bacterial genomes have been sequenced and are available at the finished status. Publically available genomes can be readily downloaded; however, there are challenges to verify the specific supporting data contained within the download and to identify errors and inconsistencies that may be present within the organizational data content and metadata. AutoCurE, an automated tool for bacterial genome database curation in Excel, was developed to facilitate local database curation of supporting data that accompany downloaded genomes from the National Center for Biotechnology Information. AutoCurE provides an automated approach to curate local genomic databases by flagging inconsistencies or errors by comparing the downloaded supporting data to the genome reports to verify genome name, RefSeq accession numbers, the presence of archaea, BioProject/UIDs, and sequence file descriptions. Flags are generated for nine metadata fields if there are inconsistencies between the downloaded genomes and genomes reports and if erroneous or missing data are evident. AutoCurE is an easy-to-use tool for local database curation for large-scale genome data prior to downstream analyses.

Multi-tissue analysis of co-expression networks by higher-order generalized singular value decomposition identifies functionally coherent transcriptional modules.

PubMed

Xiao, Xiaolin; Moreno-Moral, Aida; Rotival, Maxime; Bottolo, Leonardo; Petretto, Enrico

2014-01-01

Recent high-throughput efforts such as ENCODE have generated a large body of genome-scale transcriptional data in multiple conditions (e.g., cell-types and disease states). Leveraging these data is especially important for network-based approaches to human disease, for instance to identify coherent transcriptional modules (subnetworks) that can inform functional disease mechanisms and pathological pathways. Yet, genome-scale network analysis across conditions is significantly hampered by the paucity of robust and computationally-efficient methods. Building on the Higher-Order Generalized Singular Value Decomposition, we introduce a new algorithmic approach for efficient, parameter-free and reproducible identification of network-modules simultaneously across multiple conditions. Our method can accommodate weighted (and unweighted) networks of any size and can similarly use co-expression or raw gene expression input data, without hinging upon the definition and stability of the correlation used to assess gene co-expression. In simulation studies, we demonstrated distinctive advantages of our method over existing methods, which was able to recover accurately both common and condition-specific network-modules without entailing ad-hoc input parameters as required by other approaches. We applied our method to genome-scale and multi-tissue transcriptomic datasets from rats (microarray-based) and humans (mRNA-sequencing-based) and identified several common and tissue-specific subnetworks with functional significance, which were not detected by other methods. In humans we recapitulated the crosstalk between cell-cycle progression and cell-extracellular matrix interactions processes in ventricular zones during neocortex expansion and further, we uncovered pathways related to development of later cognitive functions in the cortical plate of the developing brain which were previously unappreciated. Analyses of seven rat tissues identified a multi-tissue subnetwork of co-expressed heat shock protein (Hsp) and cardiomyopathy genes (Bag3, Cryab, Kras, Emd, Plec), which was significantly replicated using separate failing heart and liver gene expression datasets in humans, thus revealing a conserved functional role for Hsp genes in cardiovascular disease.

methylPipe and compEpiTools: a suite of R packages for the integrative analysis of epigenomics data.

PubMed

Kishore, Kamal; de Pretis, Stefano; Lister, Ryan; Morelli, Marco J; Bianchi, Valerio; Amati, Bruno; Ecker, Joseph R; Pelizzola, Mattia

2015-09-29

Numerous methods are available to profile several epigenetic marks, providing data with different genome coverage and resolution. Large epigenomic datasets are then generated, and often combined with other high-throughput data, including RNA-seq, ChIP-seq for transcription factors (TFs) binding and DNase-seq experiments. Despite the numerous computational tools covering specific steps in the analysis of large-scale epigenomics data, comprehensive software solutions for their integrative analysis are still missing. Multiple tools must be identified and combined to jointly analyze histone marks, TFs binding and other -omics data together with DNA methylation data, complicating the analysis of these data and their integration with publicly available datasets. To overcome the burden of integrating various data types with multiple tools, we developed two companion R/Bioconductor packages. The former, methylPipe, is tailored to the analysis of high- or low-resolution DNA methylomes in several species, accommodating (hydroxy-)methyl-cytosines in both CpG and non-CpG sequence context. The analysis of multiple whole-genome bisulfite sequencing experiments is supported, while maintaining the ability of integrating targeted genomic data. The latter, compEpiTools, seamlessly incorporates the results obtained with methylPipe and supports their integration with other epigenomics data. It provides a number of methods to score these data in regions of interest, leading to the identification of enhancers, lncRNAs, and RNAPII stalling/elongation dynamics. Moreover, it allows a fast and comprehensive annotation of the resulting genomic regions, and the association of the corresponding genes with non-redundant GeneOntology terms. Finally, the package includes a flexible method based on heatmaps for the integration of various data types, combining annotation tracks with continuous or categorical data tracks. methylPipe and compEpiTools provide a comprehensive Bioconductor-compliant solution for the integrative analysis of heterogeneous epigenomics data. These packages are instrumental in providing biologists with minimal R skills a complete toolkit facilitating the analysis of their own data, or in accelerating the analyses performed by more experienced bioinformaticians.

Genome-wide polymorphisms and development of a microarray platform to detect genetic variations in Plasmodium yoelii.

PubMed

Nair, Sethu C; Pattaradilokrat, Sittiporn; Zilversmit, Martine M; Dommer, Jennifer; Nagarajan, Vijayaraj; Stephens, Melissa T; Xiao, Wenming; Tan, John C; Su, Xin-Zhuan

2014-01-01

The rodent malaria parasite Plasmodium yoelii is an important model for studying malaria immunity and pathogenesis. One approach for studying malaria disease phenotypes is genetic mapping, which requires typing a large number of genetic markers from multiple parasite strains and/or progeny from genetic crosses. Hundreds of microsatellite (MS) markers have been developed to genotype the P. yoelii genome; however, typing a large number of MS markers can be labor intensive, time consuming, and expensive. Thus, development of high-throughput genotyping tools such as DNA microarrays that enable rapid and accurate large-scale genotyping of the malaria parasite will be highly desirable. In this study, we sequenced the genomes of two P. yoelii strains (33X and N67) and obtained a large number of single nucleotide polymorphisms (SNPs). Based on the SNPs obtained, we designed sets of oligonucleotide probes to develop a microarray that could interrogate ∼11,000 SNPs across the 14 chromosomes of the parasite in a single hybridization. Results from hybridizations of DNA samples of five P. yoelii strains or cloned lines (17XNL, YM, 33X, N67 and N67C) and two progeny from a genetic cross (N67×17XNL) to the microarray showed that the array had a high call rate (∼97%) and accuracy (99.9%) in calling SNPs, providing a simple and reliable tool for typing the P. yoelii genome. Our data show that the P. yoelii genome is highly polymorphic, although isogenic pairs of parasites were also detected. Additionally, our results indicate that the 33X parasite is a progeny of 17XNL (or YM) and an unknown parasite. The highly accurate and reliable microarray developed in this study will greatly facilitate our ability to study the genetic basis of important traits and the disease it causes. Published by Elsevier B.V.

Transposable element genomic fissuring in Pyrenophora teres is associated with genome expansion and dynamics of host-pathogen genetic interactions

USDA-ARS?s Scientific Manuscript database

Pyrenophora teres, P. teres f. teres (PTT) and P. teres f. maculata (PTM) cause significant diseases in barley, but little is known about the large-scale genomic differences that may distinguish the two forms. Comprehensive genome assemblies were constructed from long DNA reads, optical and genetic ...

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

Targeted enrichment strategies for next-generation plant biology

Treesearch

Richard Cronn; Brian J. Knaus; Aaron Liston; Peter J. Maughan; Matthew Parks; John V. Syring; Joshua Udall

2012-01-01

The dramatic advances offered by modem DNA sequencers continue to redefine the limits of what can be accomplished in comparative plant biology. Even with recent achievements, however, plant genomes present obstacles that can make it difficult to execute large-scale population and phylogenetic studies on next-generation sequencing platforms. Factors like large genome...

WheatGenome.info: an integrated database and portal for wheat genome information.

PubMed

Lai, Kaitao; Berkman, Paul J; Lorenc, Michal Tadeusz; Duran, Chris; Smits, Lars; Manoli, Sahana; Stiller, Jiri; Edwards, David

2012-02-01

Bread wheat (Triticum aestivum) is one of the most important crop plants, globally providing staple food for a large proportion of the human population. However, improvement of this crop has been limited due to its large and complex genome. Advances in genomics are supporting wheat crop improvement. We provide a variety of web-based systems hosting wheat genome and genomic data to support wheat research and crop improvement. WheatGenome.info is an integrated database resource which includes multiple web-based applications. These include a GBrowse2-based wheat genome viewer with BLAST search portal, TAGdb for searching wheat second-generation genome sequence data, wheat autoSNPdb, links to wheat genetic maps using CMap and CMap3D, and a wheat genome Wiki to allow interaction between diverse wheat genome sequencing activities. This system includes links to a variety of wheat genome resources hosted at other research organizations. This integrated database aims to accelerate wheat genome research and is freely accessible via the web interface at http://www.wheatgenome.info/.

Applicability of SCAR markers to food genomics: olive oil traceability.

PubMed

Pafundo, Simona; Agrimonti, Caterina; Maestri, Elena; Marmiroli, Nelson

2007-07-25

DNA analysis with molecular markers has opened a shortcut toward a genomic comprehension of complex organisms. The availability of micro-DNA extraction methods, coupled with selective amplification of the smallest extracted fragments with molecular markers, could equally bring a breakthrough in food genomics: the identification of original components in food. Amplified fragment length polymorphisms (AFLPs) have been instrumental in plant genomics because they may allow rapid and reliable analysis of multiple and potentially polymorphic sites. Nevertheless, their direct application to the analysis of DNA extracted from food matrixes is complicated by the low quality of DNA extracted: its high degradation and the presence of inhibitors of enzymatic reactions. The conversion of an AFLP fragment to a robust and specific single-locus PCR-based marker, therefore, could extend the use of molecular markers to large-scale analysis of complex agro-food matrixes. In the present study is reported the development of sequence characterized amplified regions (SCARs) starting from AFLP profiles of monovarietal olive oils analyzed on agarose gel; one of these was used to identify differences among 56 olive cultivars. All the developed markers were purposefully amplified in olive oils to apply them to olive oil traceability.

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.

Improved Use of Small Reference Panels for Conditional and Joint Analysis with GWAS Summary Statistics.

PubMed

Deng, Yangqing; Pan, Wei

2018-06-01

Due to issues of practicality and confidentiality of genomic data sharing on a large scale, typically only meta- or mega-analyzed genome-wide association study (GWAS) summary data, not individual-level data, are publicly available. Reanalyses of such GWAS summary data for a wide range of applications have become more and more common and useful, which often require the use of an external reference panel with individual-level genotypic data to infer linkage disequilibrium (LD) among genetic variants. However, with a small sample size in only hundreds, as for the most popular 1000 Genomes Project European sample, estimation errors for LD are not negligible, leading to often dramatically increased numbers of false positives in subsequent analyses of GWAS summary data. To alleviate the problem in the context of association testing for a group of SNPs, we propose an alternative estimator of the covariance matrix with an idea similar to multiple imputation. We use numerical examples based on both simulated and real data to demonstrate the severe problem with the use of the 1000 Genomes Project reference panels, and the improved performance of our new approach. Copyright © 2018 by the Genetics Society of America.

Variant-aware saturating mutagenesis using multiple Cas9 nucleases identifies regulatory elements at trait-associated loci.

PubMed

Canver, Matthew C; Lessard, Samuel; Pinello, Luca; Wu, Yuxuan; Ilboudo, Yann; Stern, Emily N; Needleman, Austen J; Galactéros, Frédéric; Brugnara, Carlo; Kutlar, Abdullah; McKenzie, Colin; Reid, Marvin; Chen, Diane D; Das, Partha Pratim; A Cole, Mitchel; Zeng, Jing; Kurita, Ryo; Nakamura, Yukio; Yuan, Guo-Cheng; Lettre, Guillaume; Bauer, Daniel E; Orkin, Stuart H

2017-04-01

Cas9-mediated, high-throughput, saturating in situ mutagenesis permits fine-mapping of function across genomic segments. Disease- and trait-associated variants identified in genome-wide association studies largely cluster at regulatory loci. Here we demonstrate the use of multiple designer nucleases and variant-aware library design to interrogate trait-associated regulatory DNA at high resolution. We developed a computational tool for the creation of saturating-mutagenesis libraries with single or multiple nucleases with incorporation of variants. We applied this methodology to the HBS1L-MYB intergenic region, which is associated with red-blood-cell traits, including fetal hemoglobin levels. This approach identified putative regulatory elements that control MYB expression. Analysis of genomic copy number highlighted potential false-positive regions, thus emphasizing the importance of off-target analysis in the design of saturating-mutagenesis experiments. Together, these data establish a widely applicable high-throughput and high-resolution methodology to identify minimal functional sequences within large disease- and trait-associated regions.

Progress toward a low budget reference grade genome assembly

USDA-ARS?s Scientific Manuscript database

Reference quality de novo genome assemblies were once solely the domain of large, well-funded genome projects. While next-generation short read technology removed some of the cost barriers, accurate chromosome-scale assembly remains a real challenge. Here we present efforts to de novo assemble the...

Performance and Scalability of Discriminative Metrics for Comparative Gene Identification in 12 Drosophila Genomes

PubMed Central

Lin, Michael F.; Deoras, Ameya N.; Rasmussen, Matthew D.; Kellis, Manolis

2008-01-01

Comparative genomics of multiple related species is a powerful methodology for the discovery of functional genomic elements, and its power should increase with the number of species compared. Here, we use 12 Drosophila genomes to study the power of comparative genomics metrics to distinguish between protein-coding and non-coding regions. First, we study the relative power of different comparative metrics and their relationship to single-species metrics. We find that even relatively simple multi-species metrics robustly outperform advanced single-species metrics, especially for shorter exons (≤240 nt), which are common in animal genomes. Moreover, the two capture largely independent features of protein-coding genes, with different sensitivity/specificity trade-offs, such that their combinations lead to even greater discriminatory power. In addition, we study how discovery power scales with the number and phylogenetic distance of the genomes compared. We find that species at a broad range of distances are comparably effective informants for pairwise comparative gene identification, but that these are surpassed by multi-species comparisons at similar evolutionary divergence. In particular, while pairwise discovery power plateaued at larger distances and never outperformed the most advanced single-species metrics, multi-species comparisons continued to benefit even from the most distant species with no apparent saturation. Last, we find that genes in functional categories typically considered fast-evolving can nonetheless be recovered at very high rates using comparative methods. Our results have implications for comparative genomics analyses in any species, including the human. PMID:18421375

Phylogenomics and the Dynamic Genome Evolution of the Genus Streptococcus

PubMed Central

Richards, Vincent P.; Palmer, Sara R.; Pavinski Bitar, Paulina D.; Qin, Xiang; Weinstock, George M.; Highlander, Sarah K.; Town, Christopher D.; Burne, Robert A.; Stanhope, Michael J.

2014-01-01

The genus Streptococcus comprises important pathogens that have a severe impact on human health and are responsible for substantial economic losses to agriculture. Here, we utilize 46 Streptococcus genome sequences (44 species), including eight species sequenced here, to provide the first genomic level insight into the evolutionary history and genetic basis underlying the functional diversity of all major groups of this genus. Gene gain/loss analysis revealed a dynamic pattern of genome evolution characterized by an initial period of gene gain followed by a period of loss, as the major groups within the genus diversified. This was followed by a period of genome expansion associated with the origins of the present extant species. The pattern is concordant with an emerging view that genomes evolve through a dynamic process of expansion and streamlining. A large proportion of the pan-genome has experienced lateral gene transfer (LGT) with causative factors, such as relatedness and shared environment, operating over different evolutionary scales. Multiple gene ontology terms were significantly enriched for each group, and mapping terms onto the phylogeny showed that those corresponding to genes born on branches leading to the major groups represented approximately one-fifth of those enriched. Furthermore, despite the extensive LGT, several biochemical characteristics have been retained since group formation, suggesting genomic cohesiveness through time, and that these characteristics may be fundamental to each group. For example, proteolysis: mitis group; urea metabolism: salivarius group; carbohydrate metabolism: pyogenic group; and transcription regulation: bovis group. PMID:24625962

ExprAlign - the identification of ESTs in non-model species by alignment of cDNA microarray expression profiles

PubMed Central

2009-01-01

Background Sequence identification of ESTs from non-model species offers distinct challenges particularly when these species have duplicated genomes and when they are phylogenetically distant from sequenced model organisms. For the common carp, an environmental model of aquacultural interest, large numbers of ESTs remained unidentified using BLAST sequence alignment. We have used the expression profiles from large-scale microarray experiments to suggest gene identities. Results Expression profiles from ~700 cDNA microarrays describing responses of 7 major tissues to multiple environmental stressors were used to define a co-expression landscape. This was based on the Pearsons correlation coefficient relating each gene with all other genes, from which a network description provided clusters of highly correlated genes as 'mountains'. We show that these contain genes with known identities and genes with unknown identities, and that the correlation constitutes evidence of identity in the latter. This procedure has suggested identities to 522 of 2701 unknown carp ESTs sequences. We also discriminate several common carp genes and gene isoforms that were not discriminated by BLAST sequence alignment alone. Precision in identification was substantially improved by use of data from multiple tissues and treatments. Conclusion The detailed analysis of co-expression landscapes is a sensitive technique for suggesting an identity for the large number of BLAST unidentified cDNAs generated in EST projects. It is capable of detecting even subtle changes in expression profiles, and thereby of distinguishing genes with a common BLAST identity into different identities. It benefits from the use of multiple treatments or contrasts, and from the large-scale microarray data. PMID:19939286

iCN718, an Updated and Improved Genome-Scale Metabolic Network Reconstruction of Acinetobacter baumannii AYE.

PubMed

Norsigian, Charles J; Kavvas, Erol; Seif, Yara; Palsson, Bernhard O; Monk, Jonathan M

2018-01-01

Acinetobacter baumannii has become an urgent clinical threat due to the recent emergence of multi-drug resistant strains. There is thus a significant need to discover new therapeutic targets in this organism. One means for doing so is through the use of high-quality genome-scale reconstructions. Well-curated and accurate genome-scale models (GEMs) of A. baumannii would be useful for improving treatment options. We present an updated and improved genome-scale reconstruction of A. baumannii AYE, named iCN718, that improves and standardizes previous A. baumannii AYE reconstructions. iCN718 has 80% accuracy for predicting gene essentiality data and additionally can predict large-scale phenotypic data with as much as 89% accuracy, a new capability for an A. baumannii reconstruction. We further demonstrate that iCN718 can be used to analyze conserved metabolic functions in the A. baumannii core genome and to build strain-specific GEMs of 74 other A. baumannii strains from genome sequence alone. iCN718 will serve as a resource to integrate and synthesize new experimental data being generated for this urgent threat pathogen.

PSAT: A web tool to compare genomic neighborhoods of multiple prokaryotic genomes

PubMed Central

Fong, Christine; Rohmer, Laurence; Radey, Matthew; Wasnick, Michael; Brittnacher, Mitchell J

2008-01-01

Background The conservation of gene order among prokaryotic genomes can provide valuable insight into gene function, protein interactions, or events by which genomes have evolved. Although some tools are available for visualizing and comparing the order of genes between genomes of study, few support an efficient and organized analysis between large numbers of genomes. The Prokaryotic Sequence homology Analysis Tool (PSAT) is a web tool for comparing gene neighborhoods among multiple prokaryotic genomes. Results PSAT utilizes a database that is preloaded with gene annotation, BLAST hit results, and gene-clustering scores designed to help identify regions of conserved gene order. Researchers use the PSAT web interface to find a gene of interest in a reference genome and efficiently retrieve the sequence homologs found in other bacterial genomes. The tool generates a graphic of the genomic neighborhood surrounding the selected gene and the corresponding regions for its homologs in each comparison genome. Homologs in each region are color coded to assist users with analyzing gene order among various genomes. In contrast to common comparative analysis methods that filter sequence homolog data based on alignment score cutoffs, PSAT leverages gene context information for homologs, including those with weak alignment scores, enabling a more sensitive analysis. Features for constraining or ordering results are designed to help researchers browse results from large numbers of comparison genomes in an organized manner. PSAT has been demonstrated to be useful for helping to identify gene orthologs and potential functional gene clusters, and detecting genome modifications that may result in loss of function. Conclusion PSAT allows researchers to investigate the order of genes within local genomic neighborhoods of multiple genomes. A PSAT web server for public use is available for performing analyses on a growing set of reference genomes through any web browser with no client side software setup or installation required. Source code is freely available to researchers interested in setting up a local version of PSAT for analysis of genomes not available through the public server. Access to the public web server and instructions for obtaining source code can be found at . PMID:18366802

Resources for Functional Genomics Studies in Drosophila melanogaster

PubMed Central

Mohr, Stephanie E.; Hu, Yanhui; Kim, Kevin; Housden, Benjamin E.; Perrimon, Norbert

2014-01-01

Drosophila melanogaster has become a system of choice for functional genomic studies. Many resources, including online databases and software tools, are now available to support design or identification of relevant fly stocks and reagents or analysis and mining of existing functional genomic, transcriptomic, proteomic, etc. datasets. These include large community collections of fly stocks and plasmid clones, “meta” information sites like FlyBase and FlyMine, and an increasing number of more specialized reagents, databases, and online tools. Here, we introduce key resources useful to plan large-scale functional genomics studies in Drosophila and to analyze, integrate, and mine the results of those studies in ways that facilitate identification of highest-confidence results and generation of new hypotheses. We also discuss ways in which existing resources can be used and might be improved and suggest a few areas of future development that would further support large- and small-scale studies in Drosophila and facilitate use of Drosophila information by the research community more generally. PMID:24653003

Ensembl comparative genomics resources.

PubMed

Herrero, Javier; Muffato, Matthieu; Beal, Kathryn; Fitzgerald, Stephen; Gordon, Leo; Pignatelli, Miguel; Vilella, Albert J; Searle, Stephen M J; Amode, Ridwan; Brent, Simon; Spooner, William; Kulesha, Eugene; Yates, Andrew; Flicek, Paul

2016-01-01

Evolution provides the unifying framework with which to understand biology. The coherent investigation of genic and genomic data often requires comparative genomics analyses based on whole-genome alignments, sets of homologous genes and other relevant datasets in order to evaluate and answer evolutionary-related questions. However, the complexity and computational requirements of producing such data are substantial: this has led to only a small number of reference resources that are used for most comparative analyses. The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available. Database URL: http://www.ensembl.org. © The Author(s) 2016. Published by Oxford University Press.

Ensembl comparative genomics resources

PubMed Central

Muffato, Matthieu; Beal, Kathryn; Fitzgerald, Stephen; Gordon, Leo; Pignatelli, Miguel; Vilella, Albert J.; Searle, Stephen M. J.; Amode, Ridwan; Brent, Simon; Spooner, William; Kulesha, Eugene; Yates, Andrew; Flicek, Paul

2016-01-01

Evolution provides the unifying framework with which to understand biology. The coherent investigation of genic and genomic data often requires comparative genomics analyses based on whole-genome alignments, sets of homologous genes and other relevant datasets in order to evaluate and answer evolutionary-related questions. However, the complexity and computational requirements of producing such data are substantial: this has led to only a small number of reference resources that are used for most comparative analyses. The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available. Database URL: http://www.ensembl.org. PMID:26896847

Solving the problem of Trans-Genomic Query with alignment tables.

PubMed

Parker, Douglass Stott; Hsiao, Ruey-Lung; Xing, Yi; Resch, Alissa M; Lee, Christopher J

2008-01-01

The trans-genomic query (TGQ) problem--enabling the free query of biological information, even across genomes--is a central challenge facing bioinformatics. Solutions to this problem can alter the nature of the field, moving it beyond the jungle of data integration and expanding the number and scope of questions that can be answered. An alignment table is a binary relationship on locations (sequence segments). An important special case of alignment tables are hit tables ? tables of pairs of highly similar segments produced by alignment tools like BLAST. However, alignment tables also include general binary relationships, and can represent any useful connection between sequence locations. They can be curated, and provide a high-quality queryable backbone of connections between biological information. Alignment tables thus can be a natural foundation for TGQ, as they permit a central part of the TGQ problem to be reduced to purely technical problems involving tables of locations.Key challenges in implementing alignment tables include efficient representation and indexing of sequence locations. We define a location datatype that can be incorporated naturally into common off-the-shelf database systems. We also describe an implementation of alignment tables in BLASTGRES, an extension of the open-source POSTGRESQL database system that provides indexing and operators on locations required for querying alignment tables. This paper also reviews several successful large-scale applications of alignment tables for Trans-Genomic Query. Tables with millions of alignments have been used in queries about alternative splicing, an area of genomic analysis concerning the way in which a single gene can yield multiple transcripts. Comparative genomics is a large potential application area for TGQ and alignment tables.

GSuite HyperBrowser: integrative analysis of dataset collections across the genome and epigenome.

PubMed

Simovski, Boris; Vodák, Daniel; Gundersen, Sveinung; Domanska, Diana; Azab, Abdulrahman; Holden, Lars; Holden, Marit; Grytten, Ivar; Rand, Knut; Drabløs, Finn; Johansen, Morten; Mora, Antonio; Lund-Andersen, Christin; Fromm, Bastian; Eskeland, Ragnhild; Gabrielsen, Odd Stokke; Ferkingstad, Egil; Nakken, Sigve; Bengtsen, Mads; Nederbragt, Alexander Johan; Thorarensen, Hildur Sif; Akse, Johannes Andreas; Glad, Ingrid; Hovig, Eivind; Sandve, Geir Kjetil

2017-07-01

Recent large-scale undertakings such as ENCODE and Roadmap Epigenomics have generated experimental data mapped to the human reference genome (as genomic tracks) representing a variety of functional elements across a large number of cell types. Despite the high potential value of these publicly available data for a broad variety of investigations, little attention has been given to the analytical methodology necessary for their widespread utilisation. We here present a first principled treatment of the analysis of collections of genomic tracks. We have developed novel computational and statistical methodology to permit comparative and confirmatory analyses across multiple and disparate data sources. We delineate a set of generic questions that are useful across a broad range of investigations and discuss the implications of choosing different statistical measures and null models. Examples include contrasting analyses across different tissues or diseases. The methodology has been implemented in a comprehensive open-source software system, the GSuite HyperBrowser. To make the functionality accessible to biologists, and to facilitate reproducible analysis, we have also developed a web-based interface providing an expertly guided and customizable way of utilizing the methodology. With this system, many novel biological questions can flexibly be posed and rapidly answered. Through a combination of streamlined data acquisition, interoperable representation of dataset collections, and customizable statistical analysis with guided setup and interpretation, the GSuite HyperBrowser represents a first comprehensive solution for integrative analysis of track collections across the genome and epigenome. The software is available at: https://hyperbrowser.uio.no. © The Author 2017. Published by Oxford University Press.

Evolutionary genomics of Staphylococcus aureus: insights into the origin of methicillin-resistant strains and the toxic shock syndrome epidemic.

PubMed

Fitzgerald, J R; Sturdevant, D E; Mackie, S M; Gill, S R; Musser, J M

2001-07-17

An emerging theme in medical microbiology is that extensive variation exists in gene content among strains of many pathogenic bacterial species. However, this topic has not been investigated on a genome scale with strains recovered from patients with well-defined clinical conditions. Staphylococcus aureus is a major human pathogen and also causes economically important infections in cows and sheep. A DNA microarray representing >90% of the S. aureus genome was used to characterize genomic diversity, evolutionary relationships, and virulence gene distribution among 36 strains of divergent clonal lineages, including methicillin-resistant strains and organisms causing toxic shock syndrome. Genetic variation in S. aureus is very extensive, with approximately 22% of the genome comprised of dispensable genetic material. Eighteen large regions of difference were identified, and 10 of these regions have genes that encode putative virulence factors or proteins mediating antibiotic resistance. We find that lateral gene transfer has played a fundamental role in the evolution of S. aureus. The mec gene has been horizontally transferred into distinct S. aureus chromosomal backgrounds at least five times, demonstrating that methicillin-resistant strains have evolved multiple independent times, rather than from a single ancestral strain. This finding resolves a long-standing controversy in S. aureus research. The epidemic of toxic shock syndrome that occurred in the 1970s was caused by a change in the host environment, rather than rapid geographic dissemination of a new hypervirulent strain. DNA microarray analysis of large samples of clinically characterized strains provides broad insights into evolution, pathogenesis, and disease emergence.

The octopus genome and the evolution of cephalopod neural and morphological novelties.

PubMed

Albertin, Caroline B; Simakov, Oleg; Mitros, Therese; Wang, Z Yan; Pungor, Judit R; Edsinger-Gonzales, Eric; Brenner, Sydney; Ragsdale, Clifton W; Rokhsar, Daniel S

2015-08-13

Coleoid cephalopods (octopus, squid and cuttlefish) are active, resourceful predators with a rich behavioural repertoire. They have the largest nervous systems among the invertebrates and present other striking morphological innovations including camera-like eyes, prehensile arms, a highly derived early embryogenesis and a remarkably sophisticated adaptive colouration system. To investigate the molecular bases of cephalopod brain and body innovations, we sequenced the genome and multiple transcriptomes of the California two-spot octopus, Octopus bimaculoides. We found no evidence for hypothesized whole-genome duplications in the octopus lineage. The core developmental and neuronal gene repertoire of the octopus is broadly similar to that found across invertebrate bilaterians, except for massive expansions in two gene families previously thought to be uniquely enlarged in vertebrates: the protocadherins, which regulate neuronal development, and the C2H2 superfamily of zinc-finger transcription factors. Extensive messenger RNA editing generates transcript and protein diversity in genes involved in neural excitability, as previously described, as well as in genes participating in a broad range of other cellular functions. We identified hundreds of cephalopod-specific genes, many of which showed elevated expression levels in such specialized structures as the skin, the suckers and the nervous system. Finally, we found evidence for large-scale genomic rearrangements that are closely associated with transposable element expansions. Our analysis suggests that substantial expansion of a handful of gene families, along with extensive remodelling of genome linkage and repetitive content, played a critical role in the evolution of cephalopod morphological innovations, including their large and complex nervous systems.

Integrated genome browser: visual analytics platform for genomics.

PubMed

Freese, Nowlan H; Norris, David C; Loraine, Ann E

2016-07-15

Genome browsers that support fast navigation through vast datasets and provide interactive visual analytics functions can help scientists achieve deeper insight into biological systems. Toward this end, we developed Integrated Genome Browser (IGB), a highly configurable, interactive and fast open source desktop genome browser. Here we describe multiple updates to IGB, including all-new capabilities to display and interact with data from high-throughput sequencing experiments. To demonstrate, we describe example visualizations and analyses of datasets from RNA-Seq, ChIP-Seq and bisulfite sequencing experiments. Understanding results from genome-scale experiments requires viewing the data in the context of reference genome annotations and other related datasets. To facilitate this, we enhanced IGB's ability to consume data from diverse sources, including Galaxy, Distributed Annotation and IGB-specific Quickload servers. To support future visualization needs as new genome-scale assays enter wide use, we transformed the IGB codebase into a modular, extensible platform for developers to create and deploy all-new visualizations of genomic data. IGB is open source and is freely available from http://bioviz.org/igb aloraine@uncc.edu. © The Author 2016. Published by Oxford University Press.

Integrative approaches for large-scale transcriptome-wide association studies

PubMed Central

Gusev, Alexander; Ko, Arthur; Shi, Huwenbo; Bhatia, Gaurav; Chung, Wonil; Penninx, Brenda W J H; Jansen, Rick; de Geus, Eco JC; Boomsma, Dorret I; Wright, Fred A; Sullivan, Patrick F; Nikkola, Elina; Alvarez, Marcus; Civelek, Mete; Lusis, Aldons J.; Lehtimäki, Terho; Raitoharju, Emma; Kähönen, Mika; Seppälä, Ilkka; Raitakari, Olli T.; Kuusisto, Johanna; Laakso, Markku; Price, Alkes L.; Pajukanta, Päivi; Pasaniuc, Bogdan

2016-01-01

Many genetic variants influence complex traits by modulating gene expression, thus altering the abundance levels of one or multiple proteins. Here, we introduce a powerful strategy that integrates gene expression measurements with summary association statistics from large-scale genome-wide association studies (GWAS) to identify genes whose cis-regulated expression is associated to complex traits. We leverage expression imputation to perform a transcriptome wide association scan (TWAS) to identify significant expression-trait associations. We applied our approaches to expression data from blood and adipose tissue measured in ~3,000 individuals overall. We imputed gene expression into GWAS data from over 900,000 phenotype measurements to identify 69 novel genes significantly associated to obesity-related traits (BMI, lipids, and height). Many of the novel genes are associated with relevant phenotypes in the Hybrid Mouse Diversity Panel. Our results showcase the power of integrating genotype, gene expression and phenotype to gain insights into the genetic basis of complex traits. PMID:26854917

A Tunisian patient with Pearson syndrome harboring the 4.977kb common deletion associated to two novel large-scale mitochondrial deletions.

PubMed

Ayed, Imen Ben; Chamkha, Imen; Mkaouar-Rebai, Emna; Kammoun, Thouraya; Mezghani, Najla; Chabchoub, Imen; Aloulou, Hajer; Hachicha, Mongia; Fakhfakh, Faiza

2011-07-29

Pearson syndrome (PS) is a multisystem disease including refractory anemia, vacuolization of marrow precursors and pancreatic fibrosis. The disease starts during infancy and affects various tissues and organs, and most affected children die before the age of 3years. Pearson syndrome is caused by de novo large-scale deletions or, more rarely, duplications in the mitochondrial genome. In the present report, we described a Pearson syndrome patient harboring multiple mitochondrial deletions which is, in our knowledge, the first case described and studied in Tunisia. In fact, we reported the common 4.977kb deletion and two novel heteroplasmic deletions (5.030 and 5.234kb) of the mtDNA. These deletions affect several protein-coding and tRNAs genes and could strongly lead to defects in mitochondrial polypeptides synthesis, and impair oxidative phosphorylation and energy metabolism in the respiratory chain in the studied patient. Copyright © 2011 Elsevier Inc. All rights reserved.

Exception to the Rule: Genomic Characterization of Naturally Occurring Unusual Vibrio cholerae Strains with a Single Chromosome

DOE PAGES

Xie, Gary; Johnson, Shannon Lyn; Davenport, Karen Walston; ...

2017-08-29

Here, the genetic make-up of most bacteria is encoded in a single chromosome while about 10% have more than one chromosome. Among these, Vibrio cholerae, with two chromosomes, has served as a model system to study various aspects of chromosome maintenance, mainly replication, and faithful partitioning of multipartite genomes. Here, we describe the genomic characterization of strains that are an exception to the two chromosome rules: naturally occurring single-chromosome V. cholerae. Whole genome sequence analyses of NSCV1 and NSCV2 (natural single-chromosome vibrio) revealed that the Chr1 and Chr2 fusion junctions contain prophages, IS elements, and direct repeats, in addition tomore » large-scale chromosomal rearrangements such as inversions, insertions, and long tandem repeats elsewhere in the chromosome compared to prototypical two chromosome V. cholerae genomes. Many of the known cholera virulence factors are absent. The two origins of replication and associated genes are generally intact with synonymous mutations in some genes, as arerecAand mismatch repair (MMR) genes dam, mutH, and mutL; MutS function is probably impaired in NSCV2. These strains are ideal tools for studying mechanistic aspects of maintenance of chromosomes with multiple origins and other rearrangements and the biological, functional, and evolutionary significance of multipartite genome architecture in general.« less

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.

Exception to the Rule: Genomic Characterization of Naturally Occurring Unusual Vibrio cholerae Strains with a Single Chromosome

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

Xie, Gary; Johnson, Shannon Lyn; Davenport, Karen Walston

Here, the genetic make-up of most bacteria is encoded in a single chromosome while about 10% have more than one chromosome. Among these, Vibrio cholerae, with two chromosomes, has served as a model system to study various aspects of chromosome maintenance, mainly replication, and faithful partitioning of multipartite genomes. Here, we describe the genomic characterization of strains that are an exception to the two chromosome rules: naturally occurring single-chromosome V. cholerae. Whole genome sequence analyses of NSCV1 and NSCV2 (natural single-chromosome vibrio) revealed that the Chr1 and Chr2 fusion junctions contain prophages, IS elements, and direct repeats, in addition tomore » large-scale chromosomal rearrangements such as inversions, insertions, and long tandem repeats elsewhere in the chromosome compared to prototypical two chromosome V. cholerae genomes. Many of the known cholera virulence factors are absent. The two origins of replication and associated genes are generally intact with synonymous mutations in some genes, as arerecAand mismatch repair (MMR) genes dam, mutH, and mutL; MutS function is probably impaired in NSCV2. These strains are ideal tools for studying mechanistic aspects of maintenance of chromosomes with multiple origins and other rearrangements and the biological, functional, and evolutionary significance of multipartite genome architecture in general.« less

Precision medicine for psychopharmacology: a general introduction.

PubMed

Shin, Cheolmin; Han, Changsu; Pae, Chi-Un; Patkar, Ashwin A

2016-07-01

Precision medicine is an emerging medical model that can provide accurate diagnoses and tailored therapeutic strategies for patients based on data pertaining to genes, microbiomes, environment, family history and lifestyle. Here, we provide basic information about precision medicine and newly introduced concepts, such as the precision medicine ecosystem and big data processing, and omics technologies including pharmacogenomics, pharamacometabolomics, pharmacoproteomics, pharmacoepigenomics, connectomics and exposomics. The authors review the current state of omics in psychiatry and the future direction of psychopharmacology as it moves towards precision medicine. Expert commentary: Advances in precision medicine have been facilitated by achievements in multiple fields, including large-scale biological databases, powerful methods for characterizing patients (such as genomics, proteomics, metabolomics, diverse cellular assays, and even social networks and mobile health technologies), and computer-based tools for analyzing large amounts of data.

Screensaver: an open source lab information management system (LIMS) for high throughput screening facilities

PubMed Central

2010-01-01

Background Shared-usage high throughput screening (HTS) facilities are becoming more common in academe as large-scale small molecule and genome-scale RNAi screening strategies are adopted for basic research purposes. These shared facilities require a unique informatics infrastructure that must not only provide access to and analysis of screening data, but must also manage the administrative and technical challenges associated with conducting numerous, interleaved screening efforts run by multiple independent research groups. Results We have developed Screensaver, a free, open source, web-based lab information management system (LIMS), to address the informatics needs of our small molecule and RNAi screening facility. Screensaver supports the storage and comparison of screening data sets, as well as the management of information about screens, screeners, libraries, and laboratory work requests. To our knowledge, Screensaver is one of the first applications to support the storage and analysis of data from both genome-scale RNAi screening projects and small molecule screening projects. Conclusions The informatics and administrative needs of an HTS facility may be best managed by a single, integrated, web-accessible application such as Screensaver. Screensaver has proven useful in meeting the requirements of the ICCB-Longwood/NSRB Screening Facility at Harvard Medical School, and has provided similar benefits to other HTS facilities. PMID:20482787

Screensaver: an open source lab information management system (LIMS) for high throughput screening facilities.

PubMed

Tolopko, Andrew N; Sullivan, John P; Erickson, Sean D; Wrobel, David; Chiang, Su L; Rudnicki, Katrina; Rudnicki, Stewart; Nale, Jennifer; Selfors, Laura M; Greenhouse, Dara; Muhlich, Jeremy L; Shamu, Caroline E

2010-05-18

Shared-usage high throughput screening (HTS) facilities are becoming more common in academe as large-scale small molecule and genome-scale RNAi screening strategies are adopted for basic research purposes. These shared facilities require a unique informatics infrastructure that must not only provide access to and analysis of screening data, but must also manage the administrative and technical challenges associated with conducting numerous, interleaved screening efforts run by multiple independent research groups. We have developed Screensaver, a free, open source, web-based lab information management system (LIMS), to address the informatics needs of our small molecule and RNAi screening facility. Screensaver supports the storage and comparison of screening data sets, as well as the management of information about screens, screeners, libraries, and laboratory work requests. To our knowledge, Screensaver is one of the first applications to support the storage and analysis of data from both genome-scale RNAi screening projects and small molecule screening projects. The informatics and administrative needs of an HTS facility may be best managed by a single, integrated, web-accessible application such as Screensaver. Screensaver has proven useful in meeting the requirements of the ICCB-Longwood/NSRB Screening Facility at Harvard Medical School, and has provided similar benefits to other HTS facilities.

Epigenomics of Hypertension

PubMed Central

Liang, Mingyu; Cowley, Allen W.; Mattson, David L.; Kotchen, Theodore A.; Liu, Yong

2013-01-01

Multiple genes and pathways are involved in the pathogenesis of hypertension. Epigenomic studies of hypertension are beginning to emerge and hold great promise of providing novel insights into the mechanisms underlying hypertension. Epigenetic marks or mediators including DNA methylation, histone modifications, and non-coding RNA can be studied at a genome or near-genome scale using epigenomic approaches. At the single gene level, several studies have identified changes in epigenetic modifications in genes expressed in the kidney that correlate with the development of hypertension. Systematic analysis and integration of epigenetic marks at the genome scale, demonstration of cellular and physiological roles of specific epigenetic modifications, and investigation of inheritance are among the major challenges and opportunities for future epigenomic and epigenetic studies of hypertension. Essential hypertension is a multifactorial disease involving multiple genetic and environmental factors and mediated by alterations in multiple biological pathways. Because the non-genetic mechanisms may involve epigenetic modifications, epigenomics is one of the latest concepts and approaches brought to bear on hypertension research. In this article, we summarize briefly the concepts and techniques for epigenomics, discuss the rationale for applying epigenomic approaches to study hypertension, and review the current state of this research area. PMID:24011581

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.

Phosphate steering by Flap Endonuclease 1 promotes 5'-flap specificity and incision to prevent genome instability

DOE PAGES

Tsutakawa, Susan E.; Thompson, Mark J.; Arvai, Andrew S.; ...

2017-06-27

DNA replication and repair enzyme Flap Endonuclease 1 (FEN1) is vital for genome integrity, and FEN1 mutations arise in multiple cancers. FEN1 precisely cleaves single-stranded (ss) 5'-flaps one nucleotide into duplex (ds) DNA. Yet, how FEN1 selects for but does not incise the ss 5'-flap was enigmatic. Here we combine crystallographic, biochemical and genetic analyses to show that two dsDNA binding sites set the 5'polarity and to reveal unexpected control of the DNA phosphodiester backbone by electrostatic interactions. Via phosphate steering', basic residues energetically steer an inverted ss 5'-flap through a gateway over FEN1's active site and shift dsDNA formore » catalysis. Mutations of these residues cause an 18,000-fold reduction in catalytic rate in vitro and large-scale trinucleotide (GAA) n repeat expansions in vivo, implying failed phosphate-steering promotes an unanticipated lagging-strand template-switch mechanism during replication. Thus, phosphate steering is an unappreciated FEN1 function that enforces 5'-flap specificity and catalysis, preventing genomic instability.« less

Phosphate steering by Flap Endonuclease 1 promotes 5'-flap specificity and incision to prevent genome instability

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

Tsutakawa, Susan E.; Thompson, Mark J.; Arvai, Andrew S.

DNA replication and repair enzyme Flap Endonuclease 1 (FEN1) is vital for genome integrity, and FEN1 mutations arise in multiple cancers. FEN1 precisely cleaves single-stranded (ss) 5'-flaps one nucleotide into duplex (ds) DNA. Yet, how FEN1 selects for but does not incise the ss 5'-flap was enigmatic. Here we combine crystallographic, biochemical and genetic analyses to show that two dsDNA binding sites set the 5'polarity and to reveal unexpected control of the DNA phosphodiester backbone by electrostatic interactions. Via phosphate steering', basic residues energetically steer an inverted ss 5'-flap through a gateway over FEN1's active site and shift dsDNA formore » catalysis. Mutations of these residues cause an 18,000-fold reduction in catalytic rate in vitro and large-scale trinucleotide (GAA) n repeat expansions in vivo, implying failed phosphate-steering promotes an unanticipated lagging-strand template-switch mechanism during replication. Thus, phosphate steering is an unappreciated FEN1 function that enforces 5'-flap specificity and catalysis, preventing genomic instability.« less

Comparative Genomics Analysis and Phenotypic Characterization of Shewanella putrefaciens W3-18-1: Anaerobic Respiration, Bacterial Microcompartments, and Lateral Flagella

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

Qiu, D.; Tu, Q.; He, Zhili

2010-05-17

Respiratory versatility and psychrophily are the hallmarks of Shewanella. The ability to utilize a wide range of electron acceptors for respiration is due to the large number of c-type cytochrome genes present in the genome of Shewanella strains. More recently the dissimilatory metal reduction of Shewanella species has been extensively and intensively studied for potential applications in the bioremediation of radioactive wastes of groundwater and subsurface environments. Multiple Shewanella genome sequences are now available in the public databases (Fredrickson et al., 2008). Most of the sequenced Shewanella strains were isolated from marine environments and this genus was believed to bemore » of marine origin (Hau and Gralnick, 2007). However, the well-characterized model strain, S. oneidensis MR-1, was isolated from the freshwater lake sediment of Lake Oneida, New York (Myers and Nealson, 1988) and similar bacteria have also been isolated from other freshwater environments (Venkateswaran et al., 1999). Here we comparatively analyzed the genome sequence and physiological characteristics of S. putrefaciens W3-18-1 and S. oneidensis MR-1, isolated from the marine and freshwater lake sediments, respectively. The anaerobic respirations, carbon source utilization, and cell motility have been experimentally investigated. Large scale horizontal gene transfers have been revealed and the genetic divergence between these two strains was considered to be critical to the bacterial adaptation to specific habitats, freshwater or marine sediments.« less

The Evolution of Campylobacter jejuni and Campylobacter coli

PubMed Central

Sheppard, Samuel K.; Maiden, Martin C.J.

2015-01-01

The global significance of Campylobacter jejuni and Campylobacter coli as gastrointestinal human pathogens has motivated numerous studies to characterize their population biology and evolution. These bacteria are a common component of the intestinal microbiota of numerous bird and mammal species and cause disease in humans, typically via consumption of contaminated meat products, especially poultry meat. Sequence-based molecular typing methods, such as multilocus sequence typing (MLST) and whole genome sequencing (WGS), have been instructive for understanding the epidemiology and evolution of these bacteria and how phenotypic variation relates to the high degree of genetic structuring in C. coli and C. jejuni populations. Here, we describe aspects of the relatively short history of coevolution between humans and pathogenic Campylobacter, by reviewing research investigating how mutation and lateral or horizontal gene transfer (LGT or HGT, respectively) interact to create the observed population structure. These genetic changes occur in a complex fitness landscape with divergent ecologies, including multiple host species, which can lead to rapid adaptation, for example, through frame-shift mutations that alter gene expression or the acquisition of novel genetic elements by HGT. Recombination is a particularly strong evolutionary force in Campylobacter, leading to the emergence of new lineages and even large-scale genome-wide interspecies introgression between C. jejuni and C. coli. The increasing availability of large genome datasets is enhancing understanding of Campylobacter evolution through the application of methods, such as genome-wide association studies, but MLST-derived clonal complex designations remain a useful method for describing population structure. PMID:26101080

Analysis of Genome-Wide Association Studies with Multiple Outcomes Using Penalization

PubMed Central

Liu, Jin; Huang, Jian; Ma, Shuangge

2012-01-01

Genome-wide association studies have been extensively conducted, searching for markers for biologically meaningful outcomes and phenotypes. Penalization methods have been adopted in the analysis of the joint effects of a large number of SNPs (single nucleotide polymorphisms) and marker identification. This study is partly motivated by the analysis of heterogeneous stock mice dataset, in which multiple correlated phenotypes and a large number of SNPs are available. Existing penalization methods designed to analyze a single response variable cannot accommodate the correlation among multiple response variables. With multiple response variables sharing the same set of markers, joint modeling is first employed to accommodate the correlation. The group Lasso approach is adopted to select markers associated with all the outcome variables. An efficient computational algorithm is developed. Simulation study and analysis of the heterogeneous stock mice dataset show that the proposed method can outperform existing penalization methods. PMID:23272092

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…

Developing eThread pipeline using SAGA-pilot abstraction for large-scale structural bioinformatics.

PubMed

Ragothaman, Anjani; Boddu, Sairam Chowdary; Kim, Nayong; Feinstein, Wei; Brylinski, Michal; 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.

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

WebMeV | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Web MeV (Multiple-experiment Viewer) is a web/cloud-based tool for genomic data analysis. Web MeV is being built to meet the challenge of exploring large public genomic data set with intuitive graphical interface providing access to state-of-the-art analytical tools.

A New Framework and Prototype Solution for Clinical Decision Support and Research in Genomics and Other Data-intensive Fields of Medicine.

PubMed

Evans, James P; Wilhelmsen, Kirk C; Berg, Jonathan; Schmitt, Charles P; Krishnamurthy, Ashok; Fecho, Karamarie; Ahalt, Stanley C

2016-01-01

In genomics and other fields, it is now possible to capture and store large amounts of data in electronic medical records (EMRs). However, it is not clear if the routine accumulation of massive amounts of (largely uninterpretable) data will yield any health benefits to patients. Nevertheless, the use of large-scale medical data is likely to grow. To meet emerging challenges and facilitate optimal use of genomic data, our institution initiated a comprehensive planning process that addresses the needs of all stakeholders (e.g., patients, families, healthcare providers, researchers, technical staff, administrators). Our experience with this process and a key genomics research project contributed to the proposed framework. We propose a two-pronged Genomic Clinical Decision Support System (CDSS) that encompasses the concept of the "Clinical Mendeliome" as a patient-centric list of genomic variants that are clinically actionable and introduces the concept of the "Archival Value Criterion" as a decision-making formalism that approximates the cost-effectiveness of capturing, storing, and curating genome-scale sequencing data. We describe a prototype Genomic CDSS that we developed as a first step toward implementation of the framework. The proposed framework and prototype solution are designed to address the perspectives of stakeholders, stimulate effective clinical use of genomic data, drive genomic research, and meet current and future needs. The framework also can be broadly applied to additional fields, including other '-omics' fields. We advocate for the creation of a Task Force on the Clinical Mendeliome, charged with defining Clinical Mendeliomes and drafting clinical guidelines for their use.

EGASP: the human ENCODE Genome Annotation Assessment Project

PubMed Central

Guigó, Roderic; Flicek, Paul; Abril, Josep F; Reymond, Alexandre; Lagarde, Julien; Denoeud, France; Antonarakis, Stylianos; Ashburner, Michael; Bajic, Vladimir B; Birney, Ewan; Castelo, Robert; Eyras, Eduardo; Ucla, Catherine; Gingeras, Thomas R; Harrow, Jennifer; Hubbard, Tim; Lewis, Suzanna E; Reese, Martin G

2006-01-01

Background We present the results of EGASP, a community experiment to assess the state-of-the-art in genome annotation within the ENCODE regions, which span 1% of the human genome sequence. The experiment had two major goals: the assessment of the accuracy of computational methods to predict protein coding genes; and the overall assessment of the completeness of the current human genome annotations as represented in the ENCODE regions. For the computational prediction assessment, eighteen groups contributed gene predictions. We evaluated these submissions against each other based on a 'reference set' of annotations generated as part of the GENCODE project. These annotations were not available to the prediction groups prior to the submission deadline, so that their predictions were blind and an external advisory committee could perform a fair assessment. Results The best methods had at least one gene transcript correctly predicted for close to 70% of the annotated genes. Nevertheless, the multiple transcript accuracy, taking into account alternative splicing, reached only approximately 40% to 50% accuracy. At the coding nucleotide level, the best programs reached an accuracy of 90% in both sensitivity and specificity. Programs relying on mRNA and protein sequences were the most accurate in reproducing the manually curated annotations. Experimental validation shows that only a very small percentage (3.2%) of the selected 221 computationally predicted exons outside of the existing annotation could be verified. Conclusion This is the first such experiment in human DNA, and we have followed the standards established in a similar experiment, GASP1, in Drosophila melanogaster. We believe the results presented here contribute to the value of ongoing large-scale annotation projects and should guide further experimental methods when being scaled up to the entire human genome sequence. PMID:16925836

Development of a high-throughput SNP resource to advance genomic, genetic and breeding research in carrot (Daucus carota L.)

USDA-ARS?s Scientific Manuscript database

The rapid advancement in high-throughput SNP genotyping technologies along with next generation sequencing (NGS) platforms has decreased the cost, improved the quality of large-scale genome surveys, and allowed specialty crops with limited genomic resources such as carrot (Daucus carota) to access t...

The Plant Genome Integrative Explorer Resource: PlantGenIE.org.

PubMed

Sundell, David; Mannapperuma, Chanaka; Netotea, Sergiu; Delhomme, Nicolas; Lin, Yao-Cheng; Sjödin, Andreas; Van de Peer, Yves; Jansson, Stefan; Hvidsten, Torgeir R; Street, Nathaniel R

2015-12-01

Accessing and exploring large-scale genomics data sets remains a significant challenge to researchers without specialist bioinformatics training. We present the integrated PlantGenIE.org platform for exploration of Populus, conifer and Arabidopsis genomics data, which includes expression networks and associated visualization tools. Standard features of a model organism database are provided, including genome browsers, gene list annotation, Blast homology searches and gene information pages. Community annotation updating is supported via integration of WebApollo. We have produced an RNA-sequencing (RNA-Seq) expression atlas for Populus tremula and have integrated these data within the expression tools. An updated version of the ComPlEx resource for performing comparative plant expression analyses of gene coexpression network conservation between species has also been integrated. The PlantGenIE.org platform provides intuitive access to large-scale and genome-wide genomics data from model forest tree species, facilitating both community contributions to annotation improvement and tools supporting use of the included data resources to inform biological insight. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Genome segregation and packaging machinery in Acanthamoeba polyphaga mimivirus is reminiscent of bacterial apparatus.

PubMed

Chelikani, Venkata; Ranjan, Tushar; Zade, Amrutraj; Shukla, Avi; Kondabagil, Kiran

2014-06-01

Genome packaging is a critical step in the virion assembly process. The putative ATP-driven genome packaging motor of Acanthamoeba polyphaga mimivirus (APMV) and other nucleocytoplasmic large DNA viruses (NCLDVs) is a distant ortholog of prokaryotic chromosome segregation motors, such as FtsK and HerA, rather than other viral packaging motors, such as large terminase. Intriguingly, APMV also encodes other components, i.e., three putative serine recombinases and a putative type II topoisomerase, all of which are essential for chromosome segregation in prokaryotes. Based on our analyses of these components and taking the limited available literature into account, here we propose for the first time a model for genome segregation and packaging in APMV that can possibly be extended to NCLDV subfamilies, except perhaps Poxviridae and Ascoviridae. This model might represent a unique variation of the prokaryotic system acquired and contrived by the large DNA viruses of eukaryotes. It is also consistent with previous observations that unicellular eukaryotes, such as amoebae, are melting pots for the advent of chimeric organisms with novel mechanisms. Extremely large viruses with DNA genomes infect a wide range of eukaryotes, from human beings to amoebae and from crocodiles to algae. These large DNA viruses, unlike their much smaller cousins, have the capability of making most of the protein components required for their multiplication. Once they infect the cell, these viruses set up viral replication centers, known as viral factories, to carry out their multiplication with very little help from the host. Our sequence analyses show that there is remarkable similarity between prokaryotes (bacteria and archaea) and large DNA viruses, such as mimivirus, vaccinia virus, and pandoravirus, in the way that they process their newly synthesized genetic material to make sure that only one copy of the complete genome is generated and is meticulously placed inside the newly synthesized viral particle. These findings have important evolutionary implications about the origin and evolution of large viruses.

Genome Segregation and Packaging Machinery in Acanthamoeba polyphaga Mimivirus Is Reminiscent of Bacterial Apparatus

PubMed Central

Chelikani, Venkata; Ranjan, Tushar; Zade, Amrutraj; Shukla, Avi

2014-01-01

ABSTRACT Genome packaging is a critical step in the virion assembly process. The putative ATP-driven genome packaging motor of Acanthamoeba polyphaga mimivirus (APMV) and other nucleocytoplasmic large DNA viruses (NCLDVs) is a distant ortholog of prokaryotic chromosome segregation motors, such as FtsK and HerA, rather than other viral packaging motors, such as large terminase. Intriguingly, APMV also encodes other components, i.e., three putative serine recombinases and a putative type II topoisomerase, all of which are essential for chromosome segregation in prokaryotes. Based on our analyses of these components and taking the limited available literature into account, here we propose for the first time a model for genome segregation and packaging in APMV that can possibly be extended to NCLDV subfamilies, except perhaps Poxviridae and Ascoviridae. This model might represent a unique variation of the prokaryotic system acquired and contrived by the large DNA viruses of eukaryotes. It is also consistent with previous observations that unicellular eukaryotes, such as amoebae, are melting pots for the advent of chimeric organisms with novel mechanisms. IMPORTANCE Extremely large viruses with DNA genomes infect a wide range of eukaryotes, from human beings to amoebae and from crocodiles to algae. These large DNA viruses, unlike their much smaller cousins, have the capability of making most of the protein components required for their multiplication. Once they infect the cell, these viruses set up viral replication centers, known as viral factories, to carry out their multiplication with very little help from the host. Our sequence analyses show that there is remarkable similarity between prokaryotes (bacteria and archaea) and large DNA viruses, such as mimivirus, vaccinia virus, and pandoravirus, in the way that they process their newly synthesized genetic material to make sure that only one copy of the complete genome is generated and is meticulously placed inside the newly synthesized viral particle. These findings have important evolutionary implications about the origin and evolution of large viruses. PMID:24623441

Efficient computation of the joint sample frequency spectra for multiple populations.

PubMed

Kamm, John A; Terhorst, Jonathan; Song, Yun S

2017-01-01

A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this paper, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study we demonstrate our improvements to numerical stability and computational complexity.

Efficient computation of the joint sample frequency spectra for multiple populations

PubMed Central

Kamm, John A.; Terhorst, Jonathan; Song, Yun S.

2016-01-01

A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this paper, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study we demonstrate our improvements to numerical stability and computational complexity. PMID:28239248

Genome diversity and divergence in Drosophila mauritiana: multiple signatures of faster X evolution.

PubMed

Garrigan, Daniel; Kingan, Sarah B; Geneva, Anthony J; Vedanayagam, Jeffrey P; Presgraves, Daven C

2014-09-04

Drosophila mauritiana is an Indian Ocean island endemic species that diverged from its two sister species, Drosophila simulans and Drosophila sechellia, approximately 240,000 years ago. Multiple forms of incomplete reproductive isolation have evolved among these species, including sexual, gametic, ecological, and intrinsic postzygotic barriers, with crosses among all three species conforming to Haldane's rule: F(1) hybrid males are sterile and F(1) hybrid females are fertile. Extensive genetic resources and the fertility of hybrid females have made D. mauritiana, in particular, an important model for speciation genetics. Analyses between D. mauritiana and both of its siblings have shown that the X chromosome makes a disproportionate contribution to hybrid male sterility. But why the X plays a special role in the evolution of hybrid sterility in these, and other, species remains an unsolved problem. To complement functional genetic analyses, we have investigated the population genomics of D. mauritiana, giving special attention to differences between the X and the autosomes. We present a de novo genome assembly of D. mauritiana annotated with RNAseq data and a whole-genome analysis of polymorphism and divergence from ten individuals. Our analyses show that, relative to the autosomes, the X chromosome has reduced nucleotide diversity but elevated nucleotide divergence; an excess of recurrent adaptive evolution at its protein-coding genes; an excess of recent, strong selective sweeps; and a large excess of satellite DNA. Interestingly, one of two centimorgan-scale selective sweeps on the D. mauritiana X chromosome spans a region containing two sex-ratio meiotic drive elements and a high concentration of satellite DNA. Furthermore, genes with roles in reproduction and chromosome biology are enriched among genes that have histories of recurrent adaptive protein evolution. Together, these genome-wide analyses suggest that genetic conflict and frequent positive natural selection on the X chromosome have shaped the molecular evolutionary history of D. mauritiana, refining our understanding of the possible causes of the large X-effect in speciation. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Educational Attainment: A Genome Wide Association Study in 9538 Australians

PubMed Central

Martin, Nicolas W.; Medland, Sarah E.; Verweij, Karin J. H.; Lee, S. Hong; Nyholt, Dale R.; Madden, Pamela A.; Heath, Andrew C.; Montgomery, Grant W.; Wright, Margaret J.; Martin, Nicholas G.

2011-01-01

Background Correlations between Educational Attainment (EA) and measures of cognitive performance are as high as 0.8. This makes EA an attractive alternative phenotype for studies wishing to map genes affecting cognition due to the ease of collecting EA data compared to other cognitive phenotypes such as IQ. Methodology In an Australian family sample of 9538 individuals we performed a genome-wide association scan (GWAS) using the imputed genotypes of ∼2.4 million single nucleotide polymorphisms (SNP) for a 6-point scale measure of EA. Top hits were checked for replication in an independent sample of 968 individuals. A gene-based test of association was then applied to the GWAS results. Additionally we performed prediction analyses using the GWAS results from our discovery sample to assess the percentage of EA and full scale IQ variance explained by the predicted scores. Results The best SNP fell short of having a genome-wide significant p-value (p = 9.77×10−7). In our independent replication sample six SNPs among the top 50 hits pruned for linkage disequilibrium (r2<0.8) had a p-value<0.05 but only one of these SNPs survived correction for multiple testing - rs7106258 (p = 9.7*10−4) located in an intergenic region of chromosome 11q14.1. The gene based test results were non-significant and our prediction analyses show that the predicted scores explained little variance in EA in our replication sample. Conclusion While we have identified a polymorphism chromosome 11q14.1 associated with EA, further replication is warranted. Overall, the absence of genome-wide significant p-values in our large discovery sample confirmed the high polygenic architecture of EA. Only the assembly of large samples or meta-analytic efforts will be able to assess the implication of common DNA polymorphisms in the etiology of EA. PMID:21694764

BIG: a large-scale data integration tool for renal physiology.

PubMed

Zhao, Yue; Yang, Chin-Rang; Raghuram, Viswanathan; Parulekar, Jaya; Knepper, Mark A

2016-10-01

Due to recent advances in high-throughput techniques, we and others have generated multiple proteomic and transcriptomic databases to describe and quantify gene expression, protein abundance, or cellular signaling on the scale of the whole genome/proteome in kidney cells. The existence of so much data from diverse sources raises the following question: "How can researchers find information efficiently for a given gene product over all of these data sets without searching each data set individually?" This is the type of problem that has motivated the "Big-Data" revolution in Data Science, which has driven progress in fields such as marketing. Here we present an online Big-Data tool called BIG (Biological Information Gatherer) that allows users to submit a single online query to obtain all relevant information from all indexed databases. BIG is accessible at http://big.nhlbi.nih.gov/.

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.

A sense of life: computational and experimental investigations with models of biochemical and evolutionary processes.

PubMed

Mishra, Bud; Daruwala, Raoul-Sam; Zhou, Yi; Ugel, Nadia; Policriti, Alberto; Antoniotti, Marco; Paxia, Salvatore; Rejali, Marc; Rudra, Archisman; Cherepinsky, Vera; Silver, Naomi; Casey, William; Piazza, Carla; Simeoni, Marta; Barbano, Paolo; Spivak, Marina; Feng, Jiawu; Gill, Ofer; Venkatesh, Mysore; Cheng, Fang; Sun, Bing; Ioniata, Iuliana; Anantharaman, Thomas; Hubbard, E Jane Albert; Pnueli, Amir; Harel, David; Chandru, Vijay; Hariharan, Ramesh; Wigler, Michael; Park, Frank; Lin, Shih-Chieh; Lazebnik, Yuri; Winkler, Franz; Cantor, Charles R; Carbone, Alessandra; Gromov, Mikhael

2003-01-01

We collaborate in a research program aimed at creating a rigorous framework, experimental infrastructure, and computational environment for understanding, experimenting with, manipulating, and modifying a diverse set of fundamental biological processes at multiple scales and spatio-temporal modes. The novelty of our research is based on an approach that (i) requires coevolution of experimental science and theoretical techniques and (ii) exploits a certain universality in biology guided by a parsimonious model of evolutionary mechanisms operating at the genomic level and manifesting at the proteomic, transcriptomic, phylogenic, and other higher levels. Our current program in "systems biology" endeavors to marry large-scale biological experiments with the tools to ponder and reason about large, complex, and subtle natural systems. To achieve this ambitious goal, ideas and concepts are combined from many different fields: biological experimentation, applied mathematical modeling, computational reasoning schemes, and large-scale numerical and symbolic simulations. From a biological viewpoint, the basic issues are many: (i) understanding common and shared structural motifs among biological processes; (ii) modeling biological noise due to interactions among a small number of key molecules or loss of synchrony; (iii) explaining the robustness of these systems in spite of such noise; and (iv) cataloging multistatic behavior and adaptation exhibited by many biological processes.

Development of a Knowledgebase (MetRxn) of Metabolites, Reactions and Atom Mappings to Accelerate Discovery and Redesign

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

Maranas, Costas D.

With advances in DNA sequencing and genome annotation techniques, the breadth of metabolic knowledge across all kingdoms of life is increasing. The construction of genome-scale models (GSMs) facilitates this distillation of knowledge by systematically accounting for reaction stoichiometry and directionality, gene to protein to reaction relationships, reaction localization among cellular organelles, metabolite transport costs and routes, transcriptional regulation, and biomass composition. Genome-scale reconstructions available now span across all kingdoms of life, from microbes to whole-plant models, and have become indispensable for driving informed metabolic designs and interventions. A key barrier to the pace of this development is our inability tomore » utilize metabolite/reaction information from databases such as BRENDA [1], KEGG [2], MetaCyc [3], etc. due to incompatibilities of representation, duplications, and errors. Duplicate entries constitute a major impediment, where the same metabolite is found with multiple names across databases and models, which significantly slows downs the collating of information from multiple data sources. This can also lead to serious modeling errors such as charge/mass imbalances [4,5] which can thwart model predictive abilities such as identifying synthetic lethal gene pairs and quantifying metabolic flows. Hence, we created the MetRxn database [6] that takes the next step in integrating data from multiple sources and formats to automatically create a standardized knowledgebase. We subsequently deployed this resource to bring about new paradigms in genome-scale metabolic model reconstruction, metabolic flux elucidation through MFA, modeling of microbial communities, and pathway prospecting. This research has enabled the PI’s group to continue building upon research milestones and reach new ones (see list of MetRxn-related publications below).« less

Leveraging Large-Scale Cancer Genomics Datasets for Germline Discovery - TCGA

Cancer.gov

The session will review how data types have changed over time, focusing on how next-generation sequencing is being employed to yield more precise information about the underlying genomic variation that influences tumor etiology and biology.

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.

Genetics of Resistant Hypertension: the Missing Heritability and Opportunities.

PubMed

Teixeira, Samantha K; Pereira, Alexandre C; Krieger, Jose E

2018-05-19

Blood pressure regulation in humans has long been known to be a genetically determined trait. The identification of causal genetic modulators for this trait has been unfulfilling at the least. Despite the recent advances of genome-wide genetic studies, loci associated with hypertension or blood pressure still explain a very low percentage of the overall variation of blood pressure in the general population. This has precluded the translation of discoveries in the genetics of human hypertension to clinical use. Here, we propose the combined use of resistant hypertension as a trait for mapping genetic determinants in humans and the integration of new large-scale technologies to approach in model systems the multidimensional nature of the problem. New large-scale efforts in the genetic and genomic arenas are paving the way for an increased and granular understanding of genetic determinants of hypertension. New technologies for whole genome sequence and large-scale forward genetic screens can help prioritize gene and gene-pathways for downstream characterization and large-scale population studies, and guided pharmacological design can be used to drive discoveries to the translational application through better risk stratification and new therapeutic approaches. Although significant challenges remain in the mapping and identification of genetic determinants of hypertension, new large-scale technological approaches have been proposed to surpass some of the shortcomings that have limited progress in the area for the last three decades. The incorporation of these technologies to hypertension research may significantly help in the understanding of inter-individual blood pressure variation and the deployment of new phenotyping and treatment approaches for the condition.

Genome-wide SNPs reveal the drivers of gene flow in an urban population of the Asian Tiger Mosquito, Aedes albopictus.

PubMed

Schmidt, Thomas L; Rašić, Gordana; Zhang, Dongjing; Zheng, Xiaoying; Xi, Zhiyong; Hoffmann, Ary A

2017-10-01

Aedes albopictus is a highly invasive disease vector with an expanding worldwide distribution. Genetic assays using low to medium resolution markers have found little evidence of spatial genetic structure even at broad geographic scales, suggesting frequent passive movement along human transportation networks. Here we analysed genetic structure of Aedes albopictus collected from 12 sample sites in Guangzhou, China, using thousands of genome-wide single nucleotide polymorphisms (SNPs). We found evidence for passive gene flow, with distance from shipping terminals being the strongest predictor of genetic distance among mosquitoes. As further evidence of passive dispersal, we found multiple pairs of full-siblings distributed between two sample sites 3.7 km apart. After accounting for geographical variability, we also found evidence for isolation by distance, previously undetectable in Ae. albopictus. These findings demonstrate how large SNP datasets and spatially-explicit hypothesis testing can be used to decipher processes at finer geographic scales than formerly possible. Our approach can be used to help predict new invasion pathways of Ae. albopictus and to refine strategies for vector control that involve the transformation or suppression of mosquito populations.

Genome Engineering and Modification Toward Synthetic Biology for the Production of Antibiotics.

PubMed

Zou, Xuan; Wang, Lianrong; Li, Zhiqiang; Luo, Jie; Wang, Yunfu; Deng, Zixin; Du, Shiming; Chen, Shi

2018-01-01

Antibiotic production is often governed by large gene clusters composed of genes related to antibiotic scaffold synthesis, tailoring, regulation, and resistance. With the expansion of genome sequencing, a considerable number of antibiotic gene clusters has been isolated and characterized. The emerging genome engineering techniques make it possible towards more efficient engineering of antibiotics. In addition to genomic editing, multiple synthetic biology approaches have been developed for the exploration and improvement of antibiotic natural products. Here, we review the progress in the development of these genome editing techniques used to engineer new antibiotics, focusing on three aspects of genome engineering: direct cloning of large genomic fragments, genome engineering of gene clusters, and regulation of gene cluster expression. This review will not only summarize the current uses of genomic engineering techniques for cloning and assembly of antibiotic gene clusters or for altering antibiotic synthetic pathways but will also provide perspectives on the future directions of rebuilding biological systems for the design of novel antibiotics. © 2017 Wiley Periodicals, Inc.

Transposable Element Proliferation and Genome Expansion Are Rare in Contemporary Sunflower Hybrid Populations Despite Widespread Transcriptional Activity of LTR Retrotransposons

PubMed Central

Kawakami, Takeshi; Dhakal, Preeti; Katterhenry, Angela N.; Heatherington, Chelsea A.; Ungerer, Mark C.

2011-01-01

Hybridization is a natural phenomenon that has been linked in several organismal groups to transposable element derepression and copy number amplification. A noteworthy example involves three diploid annual sunflower species from North America that have arisen via ancient hybridization between the same two parental taxa, Helianthus annuus and H. petiolaris. The genomes of the hybrid species have undergone large-scale increases in genome size attributable to long terminal repeat (LTR) retrotransposon proliferation. The parental species that gave rise to the hybrid taxa are widely distributed, often sympatric, and contemporary hybridization between them is common. Natural H. annuus × H. petiolaris hybrid populations likely served as source populations from which the hybrid species arose and, as such, represent excellent natural experiments for examining the potential role of hybridization in transposable element derepression and proliferation in this group. In the current report, we examine multiple H. annuus × H. petiolaris hybrid populations for evidence of genome expansion, LTR retrotransposon copy number increases, and LTR retrotransposon transcriptional activity. We demonstrate that genome expansion and LTR retrotransposon proliferation are rare in contemporary hybrid populations, despite independent proliferation events that took place in the genomes of the ancient hybrid species. Interestingly, LTR retrotransposon lineages that proliferated in the hybrid species genomes remain transcriptionally active in hybrid and nonhybrid genotypes across the entire sampling area. The finding of transcriptional activity but not copy number increases in hybrid genotypes suggests that proliferation and genome expansion in contemporary hybrid populations may be mitigated by posttranscriptional mechanisms of repression. PMID:21282712

Robust high-performance nanoliter-volume single-cell multiple displacement amplification on planar substrates.

PubMed

Leung, Kaston; Klaus, Anders; Lin, Bill K; Laks, Emma; Biele, Justina; Lai, Daniel; Bashashati, Ali; Huang, Yi-Fei; Aniba, Radhouane; Moksa, Michelle; Steif, Adi; Mes-Masson, Anne-Marie; Hirst, Martin; Shah, Sohrab P; Aparicio, Samuel; Hansen, Carl L

2016-07-26

The genomes of large numbers of single cells must be sequenced to further understanding of the biological significance of genomic heterogeneity in complex systems. Whole genome amplification (WGA) of single cells is generally the first step in such studies, but is prone to nonuniformity that can compromise genomic measurement accuracy. Despite recent advances, robust performance in high-throughput single-cell WGA remains elusive. Here, we introduce droplet multiple displacement amplification (MDA), a method that uses commercially available liquid dispensing to perform high-throughput single-cell MDA in nanoliter volumes. The performance of droplet MDA is characterized using a large dataset of 129 normal diploid cells, and is shown to exceed previously reported single-cell WGA methods in amplification uniformity, genome coverage, and/or robustness. We achieve up to 80% coverage of a single-cell genome at 5× sequencing depth, and demonstrate excellent single-nucleotide variant (SNV) detection using targeted sequencing of droplet MDA product to achieve a median allelic dropout of 15%, and using whole genome sequencing to achieve false and true positive rates of 9.66 × 10(-6) and 68.8%, respectively, in a G1-phase cell. We further show that droplet MDA allows for the detection of copy number variants (CNVs) as small as 30 kb in single cells of an ovarian cancer cell line and as small as 9 Mb in two high-grade serous ovarian cancer samples using only 0.02× depth. Droplet MDA provides an accessible and scalable method for performing robust and accurate CNV and SNV measurements on large numbers of single cells.

Base-By-Base: single nucleotide-level analysis of whole viral genome alignments.

PubMed

Brodie, Ryan; Smith, Alex J; Roper, Rachel L; Tcherepanov, Vasily; Upton, Chris

2004-07-14

With ever increasing numbers of closely related virus genomes being sequenced, it has become desirable to be able to compare two genomes at a level more detailed than gene content because two strains of an organism may share the same set of predicted genes but still differ in their pathogenicity profiles. For example, detailed comparison of multiple isolates of the smallpox virus genome (each approximately 200 kb, with 200 genes) is not feasible without new bioinformatics tools. A software package, Base-By-Base, has been developed that provides visualization tools to enable researchers to 1) rapidly identify and correct alignment errors in large, multiple genome alignments; and 2) generate tabular and graphical output of differences between the genomes at the nucleotide level. Base-By-Base uses detailed annotation information about the aligned genomes and can list each predicted gene with nucleotide differences, display whether variations occur within promoter regions or coding regions and whether these changes result in amino acid substitutions. Base-By-Base can connect to our mySQL database (Virus Orthologous Clusters; VOCs) to retrieve detailed annotation information about the aligned genomes or use information from text files. Base-By-Base enables users to quickly and easily compare large viral genomes; it highlights small differences that may be responsible for important phenotypic differences such as virulence. It is available via the Internet using Java Web Start and runs on Macintosh, PC and Linux operating systems with the Java 1.4 virtual machine.

Streamlining and Large Ancestral Genomes in Archaea Inferred with a Phylogenetic Birth-and-Death Model

PubMed Central

Miklós, István

2009-01-01

Homologous genes originate from a common ancestor through vertical inheritance, duplication, or horizontal gene transfer. Entire homolog families spawned by a single ancestral gene can be identified across multiple genomes based on protein sequence similarity. The sequences, however, do not always reveal conclusively the history of large families. To study the evolution of complete gene repertoires, we propose here a mathematical framework that does not rely on resolved gene family histories. We show that so-called phylogenetic profiles, formed by family sizes across multiple genomes, are sufficient to infer principal evolutionary trends. The main novelty in our approach is an efficient algorithm to compute the likelihood of a phylogenetic profile in a model of birth-and-death processes acting on a phylogeny. We examine known gene families in 28 archaeal genomes using a probabilistic model that involves lineage- and family-specific components of gene acquisition, duplication, and loss. The model enables us to consider all possible histories when inferring statistics about archaeal evolution. According to our reconstruction, most lineages are characterized by a net loss of gene families. Major increases in gene repertoire have occurred only a few times. Our reconstruction underlines the importance of persistent streamlining processes in shaping genome composition in Archaea. It also suggests that early archaeal genomes were as complex as typical modern ones, and even show signs, in the case of the methanogenic ancestor, of an extremely large gene repertoire. PMID:19570746

Annotated Draft Genome Assemblies for the Northern Bobwhite (Colinus virginianus) and the Scaled Quail (Callipepla squamata) Reveal Disparate Estimates of Modern Genome Diversity and Historic Effective Population Size.

PubMed

Oldeschulte, David L; Halley, Yvette A; Wilson, Miranda L; Bhattarai, Eric K; Brashear, Wesley; Hill, Joshua; Metz, Richard P; Johnson, Charles D; Rollins, Dale; Peterson, Markus J; Bickhart, Derek M; Decker, Jared E; Sewell, John F; Seabury, Christopher M

2017-09-07

Northern bobwhite ( Colinus virginianus ; hereafter bobwhite) and scaled quail ( Callipepla squamata ) populations have suffered precipitous declines across most of their US ranges. Illumina-based first- (v1.0) and second- (v2.0) generation draft genome assemblies for the scaled quail and the bobwhite produced N50 scaffold sizes of 1.035 and 2.042 Mb, thereby producing a 45-fold improvement in contiguity over the existing bobwhite assembly, and ≥90% of the assembled genomes were captured within 1313 and 8990 scaffolds, respectively. The scaled quail assembly (v1.0 = 1.045 Gb) was ∼20% smaller than the bobwhite (v2.0 = 1.254 Gb), which was supported by kmer-based estimates of genome size. Nevertheless, estimates of GC content (41.72%; 42.66%), genome-wide repetitive content (10.40%; 10.43%), and MAKER-predicted protein coding genes (17,131; 17,165) were similar for the scaled quail (v1.0) and bobwhite (v2.0) assemblies, respectively. BUSCO analyses utilizing 3023 single-copy orthologs revealed a high level of assembly completeness for the scaled quail (v1.0; 84.8%) and the bobwhite (v2.0; 82.5%), as verified by comparison with well-established avian genomes. We also detected 273 putative segmental duplications in the scaled quail genome (v1.0), and 711 in the bobwhite genome (v2.0), including some that were shared among both species. Autosomal variant prediction revealed ∼2.48 and 4.17 heterozygous variants per kilobase within the scaled quail (v1.0) and bobwhite (v2.0) genomes, respectively, and estimates of historic effective population size were uniformly higher for the bobwhite across all time points in a coalescent model. However, large-scale declines were predicted for both species beginning ∼15-20 KYA. Copyright © 2017 Oldeschulte et al.

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.

Global MLST of Salmonella Typhi Revisited in Post-genomic Era: Genetic Conservation, Population Structure, and Comparative Genomics of Rare Sequence Types.

PubMed

Yap, Kien-Pong; Ho, Wing S; Gan, Han M; Chai, Lay C; Thong, Kwai L

2016-01-01

Typhoid fever, caused by Salmonella enterica serovar Typhi, remains an important public health burden in Southeast Asia and other endemic countries. Various genotyping methods have been applied to study the genetic variations of this human-restricted pathogen. Multilocus sequence typing (MLST) is one of the widely accepted methods, and recently, there is a growing interest in the re-application of MLST in the post-genomic era. In this study, we provide the global MLST distribution of S. Typhi utilizing both publicly available 1,826 S. Typhi genome sequences in addition to performing conventional MLST on S. Typhi strains isolated from various endemic regions spanning over a century. Our global MLST analysis confirms the predominance of two sequence types (ST1 and ST2) co-existing in the endemic regions. Interestingly, S. Typhi strains with ST8 are currently confined within the African continent. Comparative genomic analyses of ST8 and other rare STs with genomes of ST1/ST2 revealed unique mutations in important virulence genes such as flhB, sipC, and tviD that may explain the variations that differentiate between seemingly successful (widespread) and unsuccessful (poor dissemination) S. Typhi populations. Large scale whole-genome phylogeny demonstrated evidence of phylogeographical structuring and showed that ST8 may have diverged from the earlier ancestral population of ST1 and ST2, which later lost some of its fitness advantages, leading to poor worldwide dissemination. In response to the unprecedented increase in genomic data, this study demonstrates and highlights the utility of large-scale genome-based MLST as a quick and effective approach to narrow the scope of in-depth comparative genomic analysis and consequently provide new insights into the fine scale of pathogen evolution and population structure.

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

PubMed

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

2015-02-01

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

Technologies and Approaches to Elucidate and Model the Virulence Program of Salmonella.

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

McDermott, Jason E.; Yoon, Hyunjin; Nakayasu, Ernesto S.

Salmonella is a primary cause of enteric diseases in a variety of animals. During its evolution into a pathogenic bacterium, Salmonella acquired an elaborate regulatory network that responds to multiple environmental stimuli within host animals and integrates them resulting in fine regulation of the virulence program. The coordinated action by this regulatory network involves numerous virulence regulators, necessitating genome-wide profiling analysis to assess and combine efforts from multiple regulons. In this review we discuss recent high-throughput analytic approaches to understand the regulatory network of Salmonella that controls virulence processes. Application of high-throughput analyses have generated a large amount of datamore » and driven development of computational approaches required for data integration. Therefore, we also cover computer-aided network analyses to infer regulatory networks, and demonstrate how genome-scale data can be used to construct regulatory and metabolic systems models of Salmonella pathogenesis. Genes that are coordinately controlled by multiple virulence regulators under infectious conditions are more likely to be important for pathogenesis. Thus, reconstructing the global regulatory network during infection or, at the very least, under conditions that mimic the host cellular environment not only provides a bird’s eye view of Salmonella survival strategy in response to hostile host environments but also serves as an efficient means to identify novel virulence factors that are essential for Salmonella to accomplish systemic infection in the host.« less

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.

Finite Adaptation and Multistep Moves in the Metropolis-Hastings Algorithm for Variable Selection in Genome-Wide Association Analysis

PubMed Central

Peltola, Tomi; Marttinen, Pekka; Vehtari, Aki

2012-01-01

High-dimensional datasets with large amounts of redundant information are nowadays available for hypothesis-free exploration of scientific questions. A particular case is genome-wide association analysis, where variations in the genome are searched for effects on disease or other traits. Bayesian variable selection has been demonstrated as a possible analysis approach, which can account for the multifactorial nature of the genetic effects in a linear regression model. Yet, the computation presents a challenge and application to large-scale data is not routine. Here, we study aspects of the computation using the Metropolis-Hastings algorithm for the variable selection: finite adaptation of the proposal distributions, multistep moves for changing the inclusion state of multiple variables in a single proposal and multistep move size adaptation. We also experiment with a delayed rejection step for the multistep moves. Results on simulated and real data show increase in the sampling efficiency. We also demonstrate that with application specific proposals, the approach can overcome a specific mixing problem in real data with 3822 individuals and 1,051,811 single nucleotide polymorphisms and uncover a variant pair with synergistic effect on the studied trait. Moreover, we illustrate multimodality in the real dataset related to a restrictive prior distribution on the genetic effect sizes and advocate a more flexible alternative. PMID:23166669

The octopus genome and the evolution of cephalopod neural and morphological novelties

PubMed Central

Albertin, Caroline B.; Simakov, Oleg; Mitros, Therese; Wang, Z. Yan; Pungor, Judit R.; Edsinger-Gonzalez, Eric; Brenner, Sydney; Ragsdale, Clifton W.; Rokhsar, Daniel S.

2016-01-01

Coleoid cephalopods (octopus, squid, and cuttlefish) are active, resourceful predators with a rich behavioral repertoire1. They have the largest nervous systems among the invertebrates2 and present other striking morphological innovations including camera-like eyes, prehensile arms, a highly derived early embryogenesis, and the most sophisticated adaptive coloration system among all animals1,3. To investigate the molecular bases of cephalopod brain and body innovations we sequenced the genome and multiple transcriptomes of the California two-spot octopus, Octopus bimaculoides. We found no evidence for hypothesized whole genome duplications in the octopus lineage4–6. The core developmental and neuronal gene repertoire of the octopus is broadly similar to that found across invertebrate bilaterians, except for massive expansions in two gene families formerly thought to be uniquely enlarged in vertebrates: the protocadherins, which regulate neuronal development, and the C2H2 superfamily of zinc finger transcription factors. Extensive mRNA editing generates transcript and protein diversity in genes involved in neural excitability, as previously described7, as well as in genes participating in a broad range of other cellular functions. We identified hundreds of cephalopod-specific genes, many of which showed elevated expression levels in such specialized structures as the skin, the suckers, and the nervous system. Finally, we found evidence for large-scale genomic rearrangements that are closely associated with transposable element expansions. Our analysis suggests that substantial expansion of a handful of gene families, along with extensive remodeling of genome linkage and repetitive content, played a critical role in the evolution of cephalopod morphological innovations, including their large and complex nervous systems. PMID:26268193

Enhancing knowledge discovery from cancer genomics data with Galaxy

PubMed Central

Albuquerque, Marco A.; Grande, Bruno M.; Ritch, Elie J.; Pararajalingam, Prasath; Jessa, Selin; Krzywinski, Martin; Grewal, Jasleen K.; Shah, Sohrab P.; Boutros, Paul C.

2017-01-01

Abstract The field of cancer genomics has demonstrated the power of massively parallel sequencing techniques to inform on the genes and specific alterations that drive tumor onset and progression. Although large comprehensive sequence data sets continue to be made increasingly available, data analysis remains an ongoing challenge, particularly for laboratories lacking dedicated resources and bioinformatics expertise. To address this, we have produced a collection of Galaxy tools that represent many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We developed new methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability and summarized their runtimes on multiple cloud service providers. Some tools represent extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate these to achieve data integration and visualizations are demonstrated on a cohort of 96 diffuse large B-cell lymphomas and enabled the discovery of multiple candidate lymphoma-related genes. Our toolkit is available from our GitHub repository as Galaxy tool and dependency definitions and has been deployed using virtualization on multiple platforms including Docker. PMID:28327945

Enhancing knowledge discovery from cancer genomics data with Galaxy.

PubMed

Albuquerque, Marco A; Grande, Bruno M; Ritch, Elie J; Pararajalingam, Prasath; Jessa, Selin; Krzywinski, Martin; Grewal, Jasleen K; Shah, Sohrab P; Boutros, Paul C; Morin, Ryan D

2017-05-01

The field of cancer genomics has demonstrated the power of massively parallel sequencing techniques to inform on the genes and specific alterations that drive tumor onset and progression. Although large comprehensive sequence data sets continue to be made increasingly available, data analysis remains an ongoing challenge, particularly for laboratories lacking dedicated resources and bioinformatics expertise. To address this, we have produced a collection of Galaxy tools that represent many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We developed new methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability and summarized their runtimes on multiple cloud service providers. Some tools represent extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate these to achieve data integration and visualizations are demonstrated on a cohort of 96 diffuse large B-cell lymphomas and enabled the discovery of multiple candidate lymphoma-related genes. Our toolkit is available from our GitHub repository as Galaxy tool and dependency definitions and has been deployed using virtualization on multiple platforms including Docker. © The Author 2017. Published by Oxford University Press.

Molecular inversion probe assay.

PubMed

Absalan, Farnaz; Ronaghi, Mostafa

2007-01-01

We have described molecular inversion probe technologies for large-scale genetic analyses. This technique provides a comprehensive and powerful tool for the analysis of genetic variation and enables affordable, large-scale studies that will help uncover the genetic basis of complex disease and explain the individual variation in response to therapeutics. Major applications of the molecular inversion probes (MIP) technologies include targeted genotyping from focused regions to whole-genome studies, and allele quantification of genomic rearrangements. The MIP technology (used in the HapMap project) provides an efficient, scalable, and affordable way to score polymorphisms in case/control populations for genetic studies. The MIP technology provides the highest commercially available multiplexing levels and assay conversion rates for targeted genotyping. This enables more informative, genome-wide studies with either the functional (direct detection) approach or the indirect detection approach.

Human Genomic Loci Important in Common Infectious Diseases: Role of High-Throughput Sequencing and Genome-Wide Association Studies

PubMed Central

Sserwadda, Ivan; Amujal, Marion; Namatovu, Norah

2018-01-01

HIV/AIDS, tuberculosis (TB), and malaria are 3 major global public health threats that undermine development in many resource-poor settings. Recently, the notion that positive selection during epidemics or longer periods of exposure to common infectious diseases may have had a major effect in modifying the constitution of the human genome is being interrogated at a large scale in many populations around the world. This positive selection from infectious diseases increases power to detect associations in genome-wide association studies (GWASs). High-throughput sequencing (HTS) has transformed both the management of infectious diseases and continues to enable large-scale functional characterization of host resistance/susceptibility alleles and loci; a paradigm shift from single candidate gene studies. Application of genome sequencing technologies and genomics has enabled us to interrogate the host-pathogen interface for improving human health. Human populations are constantly locked in evolutionary arms races with pathogens; therefore, identification of common infectious disease-associated genomic variants/markers is important in therapeutic, vaccine development, and screening susceptible individuals in a population. This review describes a range of host-pathogen genomic loci that have been associated with disease susceptibility and resistant patterns in the era of HTS. We further highlight potential opportunities for these genetic markers. PMID:29755620

Two Rounds of Whole Genome Duplication in the Ancestral Vertebrate

PubMed Central

Dehal, Paramvir; Boore, Jeffrey L

2005-01-01

The hypothesis that the relatively large and complex vertebrate genome was created by two ancient, whole genome duplications has been hotly debated, but remains unresolved. We reconstructed the evolutionary relationships of all gene families from the complete gene sets of a tunicate, fish, mouse, and human, and then determined when each gene duplicated relative to the evolutionary tree of the organisms. We confirmed the results of earlier studies that there remains little signal of these events in numbers of duplicated genes, gene tree topology, or the number of genes per multigene family. However, when we plotted the genomic map positions of only the subset of paralogous genes that were duplicated prior to the fish–tetrapod split, their global physical organization provides unmistakable evidence of two distinct genome duplication events early in vertebrate evolution indicated by clear patterns of four-way paralogous regions covering a large part of the human genome. Our results highlight the potential for these large-scale genomic events to have driven the evolutionary success of the vertebrate lineage. PMID:16128622

Mycotoxins: A fungal genomics perspective

USDA-ARS?s Scientific Manuscript database

The chemical and enzymatic diversity in the fungal kingdom is staggering. Large-scale fungal genome sequencing projects are generating a massive catalog of secondary metabolite biosynthetic genes and pathways. Fungal natural products are a boon and bane to man as valuable pharmaceuticals and harmful...

Evolution, revolution and heresy in the genetics of infectious disease susceptibility

PubMed Central

Hill, Adrian V. S.

2012-01-01

Infectious pathogens have long been recognized as potentially powerful agents impacting on the evolution of human genetic diversity. Analysis of large-scale case–control studies provides one of the most direct means of identifying human genetic variants that currently impact on susceptibility to particular infectious diseases. For over 50 years candidate gene studies have been used to identify loci for many major causes of human infectious mortality, including malaria, tuberculosis, human immunodeficiency virus/acquired immunodeficiency syndrome, bacterial pneumonia and hepatitis. But with the advent of genome-wide approaches, many new loci have been identified in diverse populations. Genome-wide linkage studies identified a few loci, but genome-wide association studies are proving more successful, and both exome and whole-genome sequencing now offer a revolutionary increase in power. Opinions differ on the extent to which the genetic component to common disease susceptibility is encoded by multiple high frequency or rare variants, and the heretical view that most infectious diseases might even be monogenic has been advocated recently. Review of findings to date suggests that the genetic architecture of infectious disease susceptibility may be importantly different from that of non-infectious diseases, and it is suggested that natural selection may be the driving force underlying this difference. PMID:22312051

Accurate prediction of protein–protein interactions from sequence alignments using a Bayesian method

PubMed Central

Burger, Lukas; van Nimwegen, Erik

2008-01-01

Accurate and large-scale prediction of protein–protein interactions directly from amino-acid sequences is one of the great challenges in computational biology. Here we present a new Bayesian network method that predicts interaction partners using only multiple alignments of amino-acid sequences of interacting protein domains, without tunable parameters, and without the need for any training examples. We first apply the method to bacterial two-component systems and comprehensively reconstruct two-component signaling networks across all sequenced bacteria. Comparisons of our predictions with known interactions show that our method infers interaction partners genome-wide with high accuracy. To demonstrate the general applicability of our method we show that it also accurately predicts interaction partners in a recent dataset of polyketide synthases. Analysis of the predicted genome-wide two-component signaling networks shows that cognates (interacting kinase/regulator pairs, which lie adjacent on the genome) and orphans (which lie isolated) form two relatively independent components of the signaling network in each genome. In addition, while most genes are predicted to have only a small number of interaction partners, we find that 10% of orphans form a separate class of ‘hub' nodes that distribute and integrate signals to and from up to tens of different interaction partners. PMID:18277381

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

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.

A New Framework and Prototype Solution for Clinical Decision Support and Research in Genomics and Other Data-intensive Fields of Medicine

PubMed Central

Evans, James P.; Wilhelmsen, Kirk C.; Berg, Jonathan; Schmitt, Charles P.; Krishnamurthy, Ashok; Fecho, Karamarie; Ahalt, Stanley C.

2016-01-01

Introduction: In genomics and other fields, it is now possible to capture and store large amounts of data in electronic medical records (EMRs). However, it is not clear if the routine accumulation of massive amounts of (largely uninterpretable) data will yield any health benefits to patients. Nevertheless, the use of large-scale medical data is likely to grow. To meet emerging challenges and facilitate optimal use of genomic data, our institution initiated a comprehensive planning process that addresses the needs of all stakeholders (e.g., patients, families, healthcare providers, researchers, technical staff, administrators). Our experience with this process and a key genomics research project contributed to the proposed framework. Framework: We propose a two-pronged Genomic Clinical Decision Support System (CDSS) that encompasses the concept of the “Clinical Mendeliome” as a patient-centric list of genomic variants that are clinically actionable and introduces the concept of the “Archival Value Criterion” as a decision-making formalism that approximates the cost-effectiveness of capturing, storing, and curating genome-scale sequencing data. We describe a prototype Genomic CDSS that we developed as a first step toward implementation of the framework. Conclusion: The proposed framework and prototype solution are designed to address the perspectives of stakeholders, stimulate effective clinical use of genomic data, drive genomic research, and meet current and future needs. The framework also can be broadly applied to additional fields, including other ‘-omics’ fields. We advocate for the creation of a Task Force on the Clinical Mendeliome, charged with defining Clinical Mendeliomes and drafting clinical guidelines for their use. PMID:27195307

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.

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.

Tissue-aware data integration approach for the inference of pathway interactions in metazoan organisms

PubMed Central

Park, Christopher Y.; Krishnan, Arjun; Zhu, Qian; Wong, Aaron K.; Lee, Young-Suk; Troyanskaya, Olga G.

2015-01-01

Motivation: Leveraging the large compendium of genomic data to predict biomedical pathways and specific mechanisms of protein interactions genome-wide in metazoan organisms has been challenging. In contrast to unicellular organisms, biological and technical variation originating from diverse tissues and cell-lineages is often the largest source of variation in metazoan data compendia. Therefore, a new computational strategy accounting for the tissue heterogeneity in the functional genomic data is needed to accurately translate the vast amount of human genomic data into specific interaction-level hypotheses. Results: We developed an integrated, scalable strategy for inferring multiple human gene interaction types that takes advantage of data from diverse tissue and cell-lineage origins. Our approach specifically predicts both the presence of a functional association and also the most likely interaction type among human genes or its protein products on a whole-genome scale. We demonstrate that directly incorporating tissue contextual information improves the accuracy of our predictions, and further, that such genome-wide results can be used to significantly refine regulatory interactions from primary experimental datasets (e.g. ChIP-Seq, mass spectrometry). Availability and implementation: An interactive website hosting all of our interaction predictions is publically available at http://pathwaynet.princeton.edu. Software was implemented using the open-source Sleipnir library, which is available for download at https://bitbucket.org/libsleipnir/libsleipnir.bitbucket.org. Contact: ogt@cs.princeton.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25431329

Genetic variance partitioning and genome-wide prediction with allele dosage information in autotetraploid potato

USDA-ARS?s Scientific Manuscript database

Potato breeding cycles typically last 6-7 years because of the modest seed multiplication rate and large number of traits required of new varieties. Genomic selection has the potential to increase genetic gain per unit of time, through higher accuracy and/or a shorter cycle. Both possibilities were ...

Micro-Plasticity of Genomes As Illustrated by the Evolution of Glutathione Transferases in 12 Drosophila Species

PubMed Central

Saisawang, Chonticha; Ketterman, Albert J.

2014-01-01

Glutathione transferases (GST) are an ancient superfamily comprising a large number of paralogous proteins in a single organism. This multiplicity of GSTs has allowed the copies to diverge for neofunctionalization with proposed roles ranging from detoxication and oxidative stress response to involvement in signal transduction cascades. We performed a comparative genomic analysis using FlyBase annotations and Drosophila melanogaster GST sequences as templates to further annotate the GST orthologs in the 12 Drosophila sequenced genomes. We found that GST genes in the Drosophila subgenera have undergone repeated local duplications followed by transposition, inversion, and micro-rearrangements of these copies. The colinearity and orientations of the orthologous GST genes appear to be unique in many of the species which suggests that genomic rearrangement events have occurred multiple times during speciation. The high micro-plasticity of the genomes appears to have a functional contribution utilized for evolution of this gene family. PMID:25310450

SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes.

PubMed

Mägi, Reedik; Suleimanov, Yury V; Clarke, Geraldine M; Kaakinen, Marika; Fischer, Krista; Prokopenko, Inga; Morris, Andrew P

2017-01-11

Genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) have been successful in identifying loci contributing genetic effects to a wide range of complex human diseases and quantitative traits. The traditional approach to GWAS analysis is to consider each phenotype separately, despite the fact that many diseases and quantitative traits are correlated with each other, and often measured in the same sample of individuals. Multivariate analyses of correlated phenotypes have been demonstrated, by simulation, to increase power to detect association with SNPs, and thus may enable improved detection of novel loci contributing to diseases and quantitative traits. We have developed the SCOPA software to enable GWAS analysis of multiple correlated phenotypes. The software implements "reverse regression" methodology, which treats the genotype of an individual at a SNP as the outcome and the phenotypes as predictors in a general linear model. SCOPA can be applied to quantitative traits and categorical phenotypes, and can accommodate imputed genotypes under a dosage model. The accompanying META-SCOPA software enables meta-analysis of association summary statistics from SCOPA across GWAS. Application of SCOPA to two GWAS of high-and low-density lipoprotein cholesterol, triglycerides and body mass index, and subsequent meta-analysis with META-SCOPA, highlighted stronger association signals than univariate phenotype analysis at established lipid and obesity loci. The META-SCOPA meta-analysis also revealed a novel signal of association at genome-wide significance for triglycerides mapping to GPC5 (lead SNP rs71427535, p = 1.1x10 -8 ), which has not been reported in previous large-scale GWAS of lipid traits. The SCOPA and META-SCOPA software enable discovery and dissection of multiple phenotype association signals through implementation of a powerful reverse regression approach.

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.

Operationalizing the Reciprocal Engagement Model of Genetic Counseling Practice: a Framework for the Scalable Delivery of Genomic Counseling and Testing.

PubMed

Schmidlen, Tara; Sturm, Amy C; Hovick, Shelly; Scheinfeldt, Laura; Scott Roberts, J; Morr, Lindsey; McElroy, Joseph; Toland, Amanda E; Christman, Michael; O'Daniel, Julianne M; Gordon, Erynn S; Bernhardt, Barbara A; Ormond, Kelly E; Sweet, Kevin

2018-02-19

With the advent of widespread genomic testing for diagnostic indications and disease risk assessment, there is increased need to optimize genetic counseling services to support the scalable delivery of precision medicine. Here, we describe how we operationalized the reciprocal engagement model of genetic counseling practice to develop a framework of counseling components and strategies for the delivery of genomic results. This framework was constructed based upon qualitative research with patients receiving genomic counseling following online receipt of potentially actionable complex disease and pharmacogenomics reports. Consultation with a transdisciplinary group of investigators, including practicing genetic counselors, was sought to ensure broad scope and applicability of these strategies for use with any large-scale genomic testing effort. We preserve the provision of pre-test education and informed consent as established in Mendelian/single-gene disease genetic counseling practice. Following receipt of genomic results, patients are afforded the opportunity to tailor the counseling agenda by selecting the specific test results they wish to discuss, specifying questions for discussion, and indicating their preference for counseling modality. The genetic counselor uses these patient preferences to set the genomic counseling session and to personalize result communication and risk reduction recommendations. Tailored visual aids and result summary reports divide areas of risk (genetic variant, family history, lifestyle) for each disease to facilitate discussion of multiple disease risks. Post-counseling, session summary reports are actively routed to both the patient and their physician team to encourage review and follow-up. Given the breadth of genomic information potentially resulting from genomic testing, this framework is put forth as a starting point to meet the need for scalable genetic counseling services in the delivery of precision medicine.

Large-scale linkage analysis of 1302 affected relative pairs with rheumatoid arthritis

PubMed Central

Hamshere, Marian L; Segurado, Ricardo; Moskvina, Valentina; Nikolov, Ivan; Glaser, Beate; Holmans, Peter A

2007-01-01

Rheumatoid arthritis is the most common systematic autoimmune disease and its etiology is believed to have both strong genetic and environmental components. We demonstrate the utility of including genetic and clinical phenotypes as covariates within a linkage analysis framework to search for rheumatoid arthritis susceptibility loci. The raw genotypes of 1302 affected relative pairs were combined from four large family-based samples (North American Rheumatoid Arthritis Consortium, United Kingdom, European Consortium on Rheumatoid Arthritis Families, and Canada). The familiality of the clinical phenotypes was assessed. The affected relative pairs were subjected to autosomal multipoint affected relative-pair linkage analysis. Covariates were included in the linkage analysis to take account of heterogeneity within the sample. Evidence of familiality was observed with age at onset (p << 0.001) and rheumatoid factor (RF) IgM (p << 0.001), but not definite erosions (p = 0.21). Genome-wide significant evidence for linkage was observed on chromosome 6. Genome-wide suggestive evidence for linkage was observed on chromosomes 13 and 20 when conditioning on age at onset, chromosome 15 conditional on gender, and chromosome 19 conditional on RF IgM after allowing for multiple testing of covariates. PMID:18466440

International network of cancer genome projects

PubMed Central

2010-01-01

The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumors from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of over 25,000 cancer genomes at the genomic, epigenomic, and transcriptomic levels will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically-relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies. PMID:20393554

Privacy Challenges of Genomic Big Data.

PubMed

Shen, Hong; Ma, Jian

2017-01-01

With the rapid advancement of high-throughput DNA sequencing technologies, genomics has become a big data discipline where large-scale genetic information of human individuals can be obtained efficiently with low cost. However, such massive amount of personal genomic data creates tremendous challenge for privacy, especially given the emergence of direct-to-consumer (DTC) industry that provides genetic testing services. Here we review the recent development in genomic big data and its implications on privacy. We also discuss the current dilemmas and future challenges of genomic privacy.

Integrative, multimodal analysis of glioblastoma using TCGA molecular data, pathology images, and clinical outcomes.

PubMed

Kong, Jun; Cooper, Lee A D; Wang, Fusheng; Gutman, David A; Gao, Jingjing; Chisolm, Candace; Sharma, Ashish; Pan, Tony; Van Meir, Erwin G; Kurc, Tahsin M; Moreno, Carlos S; Saltz, Joel H; Brat, Daniel J

2011-12-01

Multimodal, multiscale data synthesis is becoming increasingly critical for successful translational biomedical research. In this letter, we present a large-scale investigative initiative on glioblastoma, a high-grade brain tumor, with complementary data types using in silico approaches. We integrate and analyze data from The Cancer Genome Atlas Project on glioblastoma that includes novel nuclear phenotypic data derived from microscopic slides, genotypic signatures described by transcriptional class and genetic alterations, and clinical outcomes defined by response to therapy and patient survival. Our preliminary results demonstrate numerous clinically and biologically significant correlations across multiple data types, revealing the power of in silico multimodal data integration for cancer research.

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

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

Analyses of deep mammalian sequence alignments and constraint predictions for 1% of the human genome

PubMed Central

Margulies, Elliott H.; Cooper, Gregory M.; Asimenos, George; Thomas, Daryl J.; Dewey, Colin N.; Siepel, Adam; Birney, Ewan; Keefe, Damian; Schwartz, Ariel S.; Hou, Minmei; Taylor, James; Nikolaev, Sergey; Montoya-Burgos, Juan I.; Löytynoja, Ari; Whelan, Simon; Pardi, Fabio; Massingham, Tim; Brown, James B.; Bickel, Peter; Holmes, Ian; Mullikin, James C.; Ureta-Vidal, Abel; Paten, Benedict; Stone, Eric A.; Rosenbloom, Kate R.; Kent, W. James; Bouffard, Gerard G.; Guan, Xiaobin; Hansen, Nancy F.; Idol, Jacquelyn R.; Maduro, Valerie V.B.; Maskeri, Baishali; McDowell, Jennifer C.; Park, Morgan; Thomas, Pamela J.; Young, Alice C.; Blakesley, Robert W.; Muzny, Donna M.; Sodergren, Erica; Wheeler, David A.; Worley, Kim C.; Jiang, Huaiyang; Weinstock, George M.; Gibbs, Richard A.; Graves, Tina; Fulton, Robert; Mardis, Elaine R.; Wilson, Richard K.; Clamp, Michele; Cuff, James; Gnerre, Sante; Jaffe, David B.; Chang, Jean L.; Lindblad-Toh, Kerstin; Lander, Eric S.; Hinrichs, Angie; Trumbower, Heather; Clawson, Hiram; Zweig, Ann; Kuhn, Robert M.; Barber, Galt; Harte, Rachel; Karolchik, Donna; Field, Matthew A.; Moore, Richard A.; Matthewson, Carrie A.; Schein, Jacqueline E.; Marra, Marco A.; Antonarakis, Stylianos E.; Batzoglou, Serafim; Goldman, Nick; Hardison, Ross; Haussler, David; Miller, Webb; Pachter, Lior; Green, Eric D.; Sidow, Arend

2007-01-01

A key component of the ongoing ENCODE project involves rigorous comparative sequence analyses for the initially targeted 1% of the human genome. Here, we present orthologous sequence generation, alignment, and evolutionary constraint analyses of 23 mammalian species for all ENCODE targets. Alignments were generated using four different methods; comparisons of these methods reveal large-scale consistency but substantial differences in terms of small genomic rearrangements, sensitivity (sequence coverage), and specificity (alignment accuracy). We describe the quantitative and qualitative trade-offs concomitant with alignment method choice and the levels of technical error that need to be accounted for in applications that require multisequence alignments. Using the generated alignments, we identified constrained regions using three different methods. While the different constraint-detecting methods are in general agreement, there are important discrepancies relating to both the underlying alignments and the specific algorithms. However, by integrating the results across the alignments and constraint-detecting methods, we produced constraint annotations that were found to be robust based on multiple independent measures. Analyses of these annotations illustrate that most classes of experimentally annotated functional elements are enriched for constrained sequences; however, large portions of each class (with the exception of protein-coding sequences) do not overlap constrained regions. The latter elements might not be under primary sequence constraint, might not be constrained across all mammals, or might have expendable molecular functions. Conversely, 40% of the constrained sequences do not overlap any of the functional elements that have been experimentally identified. Together, these findings demonstrate and quantify how many genomic functional elements await basic molecular characterization. PMID:17567995

Origin and Reticulate Evolutionary Process of Wheatgrass Elymus trachycaulus (Triticeae: Poaceae)

PubMed Central

Zuo, Hongwei; Wu, Panpan; Wu, Dexiang; Sun, Genlou

2015-01-01

To study origin and evolutionary dynamics of tetraploid Elymus trachycaulus that has been cytologically defined as containing StH genomes, thirteen accessions of E. trachycaulus were analyzed using two low-copy nuclear gene Pepc (phosphoenolpyruvate carboxylase) and Rpb2 (the second largest subunit of RNA polymerase II), and one chloroplast region trnL–trnF (spacer between the tRNA Leu (UAA) gene and the tRNA-Phe (GAA) gene). Our chloroplast data indicated that Pseudoroegneria (St genome) was the maternal donor of E. trachycaulus. Rpb2 data indicated that the St genome in E. trachycaulus was originated from either P. strigosa, P. stipifolia, P. spicata or P. geniculate. The Hordeum (H genome)-like sequences of E. trachycaulus are polyphyletic in the Pepc tree, suggesting that the H genome in E. trachycaulus was contributed by multiple sources, whether due to multiple origins or introgression resulting from subsequent hybridization. Failure to recovering St copy of Pepc sequence in most accessions of E. trachycaulus might be caused by genome convergent evolution in allopolyploids. Multiple copies of H-like Pepc sequence from each accession with relative large deletions and insertions might be caused by either instability of Pepc sequence in H- genome or incomplete concerted evolution. Our results highlighted complex evolutionary history of E. trachycaulus. PMID:25946188

Coordinated phenotype switching with large-scale chromosome flip-flop inversion observed in bacteria.

PubMed

Cui, Longzhu; Neoh, Hui-min; Iwamoto, Akira; Hiramatsu, Keiichi

2012-06-19

Genome inversions are ubiquitous in organisms ranging from prokaryotes to eukaryotes. Typical examples can be identified by comparing the genomes of two or more closely related organisms, where genome inversion footprints are clearly visible. Although the evolutionary implications of this phenomenon are huge, little is known about the function and biological meaning of this process. Here, we report our findings on a bacterium that generates a reversible, large-scale inversion of its chromosome (about half of its total genome) at high frequencies of up to once every four generations. This inversion switches on or off bacterial phenotypes, including colony morphology, antibiotic susceptibility, hemolytic activity, and expression of dozens of genes. Quantitative measurements and mathematical analyses indicate that this reversible switching is stochastic but self-organized so as to maintain two forms of stable cell populations (i.e., small colony variant, normal colony variant) as a bet-hedging strategy. Thus, this heritable and reversible genome fluctuation seems to govern the bacterial life cycle; it has a profound impact on the course and outcomes of bacterial infections.

[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.

Genotyping-by-sequencing for Populus population genomics: An assessment of genome sampling patterns and filtering approaches

Treesearch

Martin P. Schilling; Paul G. Wolf; Aaron M. Duffy; Hardeep S. Rai; Carol A. Rowe; Bryce A. Richardson; Karen E. Mock

2014-01-01

Continuing advances in nucleotide sequencing technology are inspiring a suite of genomic approaches in studies of natural populations. Researchers are faced with data management and analytical scales that are increasing by orders of magnitude. With such dramatic advances comes a need to understand biases and error rates, which can be propagated and magnified in large-...

Analyzing large scale genomic data on the cloud with Sparkhit

PubMed Central

Huang, Liren; Krüger, Jan

2018-01-01

Abstract Motivation The increasing amount of next-generation sequencing data poses a fundamental challenge on large scale genomic analytics. Existing tools use different distributed computational platforms to scale-out bioinformatics workloads. However, the scalability of these tools is not efficient. Moreover, they have heavy run time overheads when pre-processing large amounts of data. To address these limitations, we have developed Sparkhit: a distributed bioinformatics framework built on top of the Apache Spark platform. Results Sparkhit integrates a variety of analytical methods. It is implemented in the Spark extended MapReduce model. It runs 92–157 times faster than MetaSpark on metagenomic fragment recruitment and 18–32 times faster than Crossbow on data pre-processing. We analyzed 100 terabytes of data across four genomic projects in the cloud in 21 h, which includes the run times of cluster deployment and data downloading. Furthermore, our application on the entire Human Microbiome Project shotgun sequencing data was completed in 2 h, presenting an approach to easily associate large amounts of public datasets with reference data. Availability and implementation Sparkhit is freely available at: https://rhinempi.github.io/sparkhit/. Contact asczyrba@cebitec.uni-bielefeld.de Supplementary information Supplementary data are available at Bioinformatics online. PMID:29253074

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

Reverse engineering and analysis of large genome-scale gene networks

PubMed Central

Aluru, Maneesha; Zola, Jaroslaw; Nettleton, Dan; Aluru, Srinivas

2013-01-01

Reverse engineering the whole-genome networks of complex multicellular organisms continues to remain a challenge. While simpler models easily scale to large number of genes and gene expression datasets, more accurate models are compute intensive limiting their scale of applicability. To enable fast and accurate reconstruction of large networks, we developed Tool for Inferring Network of Genes (TINGe), a parallel mutual information (MI)-based program. The novel features of our approach include: (i) B-spline-based formulation for linear-time computation of MI, (ii) a novel algorithm for direct permutation testing and (iii) development of parallel algorithms to reduce run-time and facilitate construction of large networks. We assess the quality of our method by comparison with ARACNe (Algorithm for the Reconstruction of Accurate Cellular Networks) and GeneNet and demonstrate its unique capability by reverse engineering the whole-genome network of Arabidopsis thaliana from 3137 Affymetrix ATH1 GeneChips in just 9 min on a 1024-core cluster. We further report on the development of a new software Gene Network Analyzer (GeNA) for extracting context-specific subnetworks from a given set of seed genes. Using TINGe and GeNA, we performed analysis of 241 Arabidopsis AraCyc 8.0 pathways, and the results are made available through the web. PMID:23042249

GDC 2: Compression of large collections of genomes

PubMed Central

Deorowicz, Sebastian; Danek, Agnieszka; Niemiec, Marcin

2015-01-01

The fall of prices of the high-throughput genome sequencing changes the landscape of modern genomics. A number of large scale projects aimed at sequencing many human genomes are in progress. Genome sequencing also becomes an important aid in the personalized medicine. One of the significant side effects of this change is a necessity of storage and transfer of huge amounts of genomic data. In this paper we deal with the problem of compression of large collections of complete genomic sequences. We propose an algorithm that is able to compress the collection of 1092 human diploid genomes about 9,500 times. This result is about 4 times better than what is offered by the other existing compressors. Moreover, our algorithm is very fast as it processes the data with speed 200 MB/s on a modern workstation. In a consequence the proposed algorithm allows storing the complete genomic collections at low cost, e.g., the examined collection of 1092 human genomes needs only about 700 MB when compressed, what can be compared to about 6.7 TB of uncompressed FASTA files. The source code is available at http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&project=gdc&subpage=about. PMID:26108279

GDC 2: Compression of large collections of genomes.

PubMed

Deorowicz, Sebastian; Danek, Agnieszka; Niemiec, Marcin

2015-06-25

The fall of prices of the high-throughput genome sequencing changes the landscape of modern genomics. A number of large scale projects aimed at sequencing many human genomes are in progress. Genome sequencing also becomes an important aid in the personalized medicine. One of the significant side effects of this change is a necessity of storage and transfer of huge amounts of genomic data. In this paper we deal with the problem of compression of large collections of complete genomic sequences. We propose an algorithm that is able to compress the collection of 1092 human diploid genomes about 9,500 times. This result is about 4 times better than what is offered by the other existing compressors. Moreover, our algorithm is very fast as it processes the data with speed 200 MB/s on a modern workstation. In a consequence the proposed algorithm allows storing the complete genomic collections at low cost, e.g., the examined collection of 1092 human genomes needs only about 700 MB when compressed, what can be compared to about 6.7 TB of uncompressed FASTA files. The source code is available at http://sun.aei.polsl.pl/REFRESH/index.php?page=projects&project=gdc&subpage=about.

Genome-scale reconstruction of the sigma factor network in Escherichia coli: topology and functional states

PubMed Central

2014-01-01

Background At the beginning of the transcription process, the RNA polymerase (RNAP) core enzyme requires a σ-factor to recognize the genomic location at which the process initiates. Although the crucial role of σ-factors has long been appreciated and characterized for many individual promoters, we do not yet have a genome-scale assessment of their function. Results Using multiple genome-scale measurements, we elucidated the network of σ-factor and promoter interactions in Escherichia coli. The reconstructed network includes 4,724 σ-factor-specific promoters corresponding to transcription units (TUs), representing an increase of more than 300% over what has been previously reported. The reconstructed network was used to investigate competition between alternative σ-factors (the σ70 and σ38 regulons), confirming the competition model of σ substitution and negative regulation by alternative σ-factors. Comparison with σ-factor binding in Klebsiella pneumoniae showed that transcriptional regulation of conserved genes in closely related species is unexpectedly divergent. Conclusions The reconstructed network reveals the regulatory complexity of the promoter architecture in prokaryotic genomes, and opens a path to the direct determination of the systems biology of their transcriptional regulatory networks. PMID:24461193

Short and long-term genome stability analysis of prokaryotic genomes.

PubMed

Brilli, Matteo; Liò, Pietro; Lacroix, Vincent; Sagot, Marie-France

2013-05-08

Gene organization dynamics is actively studied because it provides useful evolutionary information, makes functional annotation easier and often enables to characterize pathogens. There is therefore a strong interest in understanding the variability of this trait and the possible correlations with life-style. Two kinds of events affect genome organization: on one hand translocations and recombinations change the relative position of genes shared by two genomes (i.e. the backbone gene order); on the other, insertions and deletions leave the backbone gene order unchanged but they alter the gene neighborhoods by breaking the syntenic regions. A complete picture about genome organization evolution therefore requires to account for both kinds of events. We developed an approach where we model chromosomes as graphs on which we compute different stability estimators; we consider genome rearrangements as well as the effect of gene insertions and deletions. In a first part of the paper, we fit a measure of backbone gene order conservation (hereinafter called backbone stability) against phylogenetic distance for over 3000 genome comparisons, improving existing models for the divergence in time of backbone stability. Intra- and inter-specific comparisons were treated separately to focus on different time-scales. The use of multiple genomes of a same species allowed to identify genomes with diverging gene order with respect to their conspecific. The inter-species analysis indicates that pathogens are more often unstable with respect to non-pathogens. In a second part of the text, we show that in pathogens, gene content dynamics (insertions and deletions) have a much more dramatic effect on genome organization stability than backbone rearrangements. In this work, we studied genome organization divergence taking into account the contribution of both genome order rearrangements and genome content dynamics. By studying species with multiple sequenced genomes available, we were able to explore genome organization stability at different time-scales and to find significant differences for pathogen and non-pathogen species. The output of our framework also allows to identify the conserved gene clusters and/or partial occurrences thereof, making possible to explore how gene clusters assembled during evolution.

Pooled-DNA Sequencing for Elucidating New Genomic Risk Factors, Rare Variants Underlying Alzheimer's Disease.

PubMed

Jin, Sheng Chih; Benitez, Bruno A; Deming, Yuetiva; Cruchaga, Carlos

2016-01-01

Analyses of genome-wide association studies (GWAS) for complex disorders usually identify common variants with a relatively small effect size that only explain a small proportion of phenotypic heritability. Several studies have suggested that a significant fraction of heritability may be explained by low-frequency (minor allele frequency (MAF) of 1-5 %) and rare-variants that are not contained in the commercial GWAS genotyping arrays (Schork et al., Curr Opin Genet Dev 19:212, 2009). Rare variants can also have relatively large effects on risk for developing human diseases or disease phenotype (Cruchaga et al., PLoS One 7:e31039, 2012). However, it is necessary to perform next-generation sequencing (NGS) studies in a large population (>4,000 samples) to detect a significant rare-variant association. Several NGS methods, such as custom capture sequencing and amplicon-based sequencing, are designed to screen a small proportion of the genome, but most of these methods are limited in the number of samples that can be multiplexed (i.e. most sequencing kits only provide 96 distinct index). Additionally, the sequencing library preparation for 4,000 samples remains expensive and thus conducting NGS studies with the aforementioned methods are not feasible for most research laboratories.The need for low-cost large scale rare-variant detection makes pooled-DNA sequencing an ideally efficient and cost-effective technique to identify rare variants in target regions by sequencing hundreds to thousands of samples. Our recent work has demonstrated that pooled-DNA sequencing can accurately detect rare variants in targeted regions in multiple DNA samples with high sensitivity and specificity (Jin et al., Alzheimers Res Ther 4:34, 2012). In these studies we used a well-established pooled-DNA sequencing approach and a computational package, SPLINTER (short indel prediction by large deviation inference and nonlinear true frequency estimation by recursion) (Vallania et al., Genome Res 20:1711, 2010), for accurate identification of rare variants in large DNA pools. Given an average sequencing coverage of 30× per haploid genome, SPLINTER can detect rare variants and short indels up to 4 base pairs (bp) with high sensitivity and specificity (up to 1 haploid allele in a pool as large as 500 individuals). Step-by-step instructions on how to conduct pooled-DNA sequencing experiments and data analyses are described in this chapter.

Long-range barcode labeling-sequencing

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

Chen, Feng; Zhang, Tao; Singh, Kanwar K.

Methods for sequencing single large DNA molecules by clonal multiple displacement amplification using barcoded primers. Sequences are binned based on barcode sequences and sequenced using a microdroplet-based method for sequencing large polynucleotide templates to enable assembly of haplotype-resolved complex genomes and metagenomes.

Acid Stress Response Mechanisms of Group B Streptococci

PubMed Central

Shabayek, Sarah; Spellerberg, Barbara

2017-01-01

Group B streptococcus (GBS) is a leading cause of neonatal mortality and morbidity in the United States and Europe. It is part of the vaginal microbiota in up to 30% of pregnant women and can be passed on to the newborn through perinatal transmission. GBS has the ability to survive in multiple different host niches. The pathophysiology of this bacterium reveals an outstanding ability to withstand varying pH fluctuations of the surrounding environments inside the human host. GBS host pathogen interations include colonization of the acidic vaginal mucosa, invasion of the neutral human blood or amniotic fluid, breaching of the blood brain barrier as well as survival within the acidic phagolysosomal compartment of macrophages. However, investigations on GBS responses to acid stress are limited. Technologies, such as whole genome sequencing, genome-wide transcription and proteome mapping facilitate large scale identification of genes and proteins. Mechanisms enabling GBS to cope with acid stress have mainly been studied through these techniques and are summarized in the current review PMID:28936424

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.

BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions

PubMed Central

2010-01-01

Background Genome-scale metabolic reconstructions under the Constraint Based Reconstruction and Analysis (COBRA) framework are valuable tools for analyzing the metabolic capabilities of organisms and interpreting experimental data. As the number of such reconstructions and analysis methods increases, there is a greater need for data uniformity and ease of distribution and use. Description We describe BiGG, a knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest. Conclusions BiGG addresses a need in the systems biology community to have access to high quality curated metabolic models and reconstructions. It is freely available for academic use at http://bigg.ucsd.edu. PMID:20426874

Harnessing quantitative genetics and genomics for understanding and improving complex traits in crops

USDA-ARS?s Scientific Manuscript database

Classical quantitative genetics aids crop improvement by providing the means to estimate heritability, genetic correlations, and predicted responses to various selection schemes. Genomics has the potential to aid quantitative genetics and applied crop improvement programs via large-scale, high-thro...

BIG: a large-scale data integration tool for renal physiology

PubMed Central

Zhao, Yue; Yang, Chin-Rang; Raghuram, Viswanathan; Parulekar, Jaya

2016-01-01

Due to recent advances in high-throughput techniques, we and others have generated multiple proteomic and transcriptomic databases to describe and quantify gene expression, protein abundance, or cellular signaling on the scale of the whole genome/proteome in kidney cells. The existence of so much data from diverse sources raises the following question: “How can researchers find information efficiently for a given gene product over all of these data sets without searching each data set individually?” This is the type of problem that has motivated the “Big-Data” revolution in Data Science, which has driven progress in fields such as marketing. Here we present an online Big-Data tool called BIG (Biological Information Gatherer) that allows users to submit a single online query to obtain all relevant information from all indexed databases. BIG is accessible at http://big.nhlbi.nih.gov/. PMID:27279488

Predicting Response to Histone Deacetylase Inhibitors Using High-Throughput Genomics.

PubMed

Geeleher, Paul; Loboda, Andrey; Lenkala, Divya; Wang, Fan; LaCroix, Bonnie; Karovic, Sanja; Wang, Jacqueline; Nebozhyn, Michael; Chisamore, Michael; Hardwick, James; Maitland, Michael L; Huang, R Stephanie

2015-11-01

Many disparate biomarkers have been proposed as predictors of response to histone deacetylase inhibitors (HDI); however, all have failed when applied clinically. Rather than this being entirely an issue of reproducibility, response to the HDI vorinostat may be determined by the additive effect of multiple molecular factors, many of which have previously been demonstrated. We conducted a large-scale gene expression analysis using the Cancer Genome Project for discovery and generated another large independent cancer cell line dataset across different cancers for validation. We compared different approaches in terms of how accurately vorinostat response can be predicted on an independent out-of-batch set of samples and applied the polygenic marker prediction principles in a clinical trial. Using machine learning, the small effects that aggregate, resulting in sensitivity or resistance, can be recovered from gene expression data in a large panel of cancer cell lines.This approach can predict vorinostat response accurately, whereas single gene or pathway markers cannot. Our analyses recapitulated and contextualized many previous findings and suggest an important role for processes such as chromatin remodeling, autophagy, and apoptosis. As a proof of concept, we also discovered a novel causative role for CHD4, a helicase involved in the histone deacetylase complex that is associated with poor clinical outcome. As a clinical validation, we demonstrated that a common dose-limiting toxicity of vorinostat, thrombocytopenia, can be predicted (r = 0.55, P = .004) several days before it is detected clinically. Our work suggests a paradigm shift from single-gene/pathway evaluation to simultaneously evaluating multiple independent high-throughput gene expression datasets, which can be easily extended to other investigational compounds where similar issues are hampering clinical adoption. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Signatures of selection in the three-spined stickleback along a small-scale brackish water - freshwater transition zone.

PubMed

Konijnendijk, Nellie; Shikano, Takahito; Daneels, Dorien; Volckaert, Filip A M; Raeymaekers, Joost A M

2015-09-01

Local adaptation is often obvious when gene flow is impeded, such as observed at large spatial scales and across strong ecological contrasts. However, it becomes less certain at small scales such as between adjacent populations or across weak ecological contrasts, when gene flow is strong. While studies on genomic adaptation tend to focus on the former, less is known about the genomic targets of natural selection in the latter situation. In this study, we investigate genomic adaptation in populations of the three-spined stickleback Gasterosteus aculeatus L. across a small-scale ecological transition with salinities ranging from brackish to fresh. Adaptation to salinity has been repeatedly demonstrated in this species. A genome scan based on 87 microsatellite markers revealed only few signatures of selection, likely owing to the constraints that homogenizing gene flow puts on adaptive divergence. However, the detected loci appear repeatedly as targets of selection in similar studies of genomic adaptation in the three-spined stickleback. We conclude that the signature of genomic selection in the face of strong gene flow is weak, yet detectable. We argue that the range of studies of genomic divergence should be extended to include more systems characterized by limited geographical and ecological isolation, which is often a realistic setting in nature.

Draft De Novo Transcriptome of the Rat Kangaroo Potorous tridactylus as a Tool for Cell Biology

PubMed Central

Udy, Dylan B.; Voorhies, Mark; Chan, Patricia P.; Lowe, Todd M.; Dumont, Sophie

2015-01-01

The rat kangaroo (long-nosed potoroo, Potorous tridactylus) is a marsupial native to Australia. Cultured rat kangaroo kidney epithelial cells (PtK) are commonly used to study cell biological processes. These mammalian cells are large, adherent, and flat, and contain large and few chromosomes—and are thus ideal for imaging intra-cellular dynamics such as those of mitosis. Despite this, neither the rat kangaroo genome nor transcriptome have been sequenced, creating a challenge for probing the molecular basis of these cellular dynamics. Here, we present the sequencing, assembly and annotation of the draft rat kangaroo de novo transcriptome. We sequenced 679 million reads that mapped to 347,323 Trinity transcripts and 20,079 Unigenes. We present statistics emerging from transcriptome-wide analyses, and analyses suggesting that the transcriptome covers full-length sequences of most genes, many with multiple isoforms. We also validate our findings with a proof-of-concept gene knockdown experiment. We expect that this high quality transcriptome will make rat kangaroo cells a more tractable system for linking molecular-scale function and cellular-scale dynamics. PMID:26252667

Draft De Novo Transcriptome of the Rat Kangaroo Potorous tridactylus as a Tool for Cell Biology.

PubMed

Udy, Dylan B; Voorhies, Mark; Chan, Patricia P; Lowe, Todd M; Dumont, Sophie

2015-01-01

The rat kangaroo (long-nosed potoroo, Potorous tridactylus) is a marsupial native to Australia. Cultured rat kangaroo kidney epithelial cells (PtK) are commonly used to study cell biological processes. These mammalian cells are large, adherent, and flat, and contain large and few chromosomes-and are thus ideal for imaging intra-cellular dynamics such as those of mitosis. Despite this, neither the rat kangaroo genome nor transcriptome have been sequenced, creating a challenge for probing the molecular basis of these cellular dynamics. Here, we present the sequencing, assembly and annotation of the draft rat kangaroo de novo transcriptome. We sequenced 679 million reads that mapped to 347,323 Trinity transcripts and 20,079 Unigenes. We present statistics emerging from transcriptome-wide analyses, and analyses suggesting that the transcriptome covers full-length sequences of most genes, many with multiple isoforms. We also validate our findings with a proof-of-concept gene knockdown experiment. We expect that this high quality transcriptome will make rat kangaroo cells a more tractable system for linking molecular-scale function and cellular-scale dynamics.

Complete sequencing and pan-genomic analysis of Lactobacillus delbrueckii subsp. bulgaricus reveal its genetic basis for industrial yogurt production.

PubMed

Hao, Pei; Zheng, Huajun; Yu, Yao; Ding, Guohui; Gu, Wenyi; Chen, Shuting; Yu, Zhonghao; Ren, Shuangxi; Oda, Munehiro; Konno, Tomonobu; Wang, Shengyue; Li, Xuan; Ji, Zai-Si; Zhao, Guoping

2011-01-17

Lactobacillus delbrueckii subsp. bulgaricus (Lb. bulgaricus) is an important species of Lactic Acid Bacteria (LAB) used for cheese and yogurt fermentation. The genome of Lb. bulgaricus 2038, an industrial strain mainly used for yogurt production, was completely sequenced and compared against the other two ATCC collection strains of the same subspecies. Specific physiological properties of strain 2038, such as lysine biosynthesis, formate production, aspartate-related carbon-skeleton intermediate metabolism, unique EPS synthesis and efficient DNA restriction/modification systems, are all different from those of the collection strains that might benefit the industrial production of yogurt. Other common features shared by Lb. bulgaricus strains, such as efficient protocooperation with Streptococcus thermophilus and lactate production as well as well-equipped stress tolerance mechanisms may account for it being selected originally for yogurt fermentation industry. Multiple lines of evidence suggested that Lb. bulgaricus 2038 was genetically closer to the common ancestor of the subspecies than the other two sequenced collection strains, probably due to a strict industrial maintenance process for strain 2038 that might have halted its genome decay and sustained a gene network suitable for large scale yogurt production.

Complete Sequencing and Pan-Genomic Analysis of Lactobacillus delbrueckii subsp. bulgaricus Reveal Its Genetic Basis for Industrial Yogurt Production

PubMed Central

Ding, Guohui; Gu, Wenyi; Chen, Shuting; Yu, Zhonghao; Ren, Shuangxi; Oda, Munehiro; Konno, Tomonobu; Wang, Shengyue; Li, Xuan; Ji, Zai-Si; Zhao, Guoping

2011-01-01

Lactobacillus delbrueckii subsp. bulgaricus (Lb. bulgaricus) is an important species of Lactic Acid Bacteria (LAB) used for cheese and yogurt fermentation. The genome of Lb. bulgaricus 2038, an industrial strain mainly used for yogurt production, was completely sequenced and compared against the other two ATCC collection strains of the same subspecies. Specific physiological properties of strain 2038, such as lysine biosynthesis, formate production, aspartate-related carbon-skeleton intermediate metabolism, unique EPS synthesis and efficient DNA restriction/modification systems, are all different from those of the collection strains that might benefit the industrial production of yogurt. Other common features shared by Lb. bulgaricus strains, such as efficient protocooperation with Streptococcus thermophilus and lactate production as well as well-equipped stress tolerance mechanisms may account for it being selected originally for yogurt fermentation industry. Multiple lines of evidence suggested that Lb. bulgaricus 2038 was genetically closer to the common ancestor of the subspecies than the other two sequenced collection strains, probably due to a strict industrial maintenance process for strain 2038 that might have halted its genome decay and sustained a gene network suitable for large scale yogurt production. PMID:21264216

Simulating cyanobacterial phenotypes by integrating flux balance analysis, kinetics, and a light distribution function

DOE PAGES

He, Lian; Wu, Stephen G.; Wan, Ni; ...

2015-12-24

In this study, genome-scale models (GSMs) are widely used to predict cyanobacterial phenotypes in photobioreactors (PBRs). However, stoichiometric GSMs mainly focus on fluxome that result in maximal yields. Cyanobacterial metabolism is controlled by both intracellular enzymes and photobioreactor conditions. To connect both intracellular and extracellular information and achieve a better understanding of PBRs productivities, this study integrates a genome-scale metabolic model of Synechocystis 6803 with growth kinetics, cell movements, and a light distribution function. The hybrid platform not only maps flux dynamics in cells of sub-populations but also predicts overall production titer and rate in PBRs. Analysis of the integratedmore » GSM demonstrates several results. First, cyanobacteria are capable of reaching high biomass concentration (>20 g/L in 21 days) in PBRs without light and CO 2 mass transfer limitations. Second, fluxome in a single cyanobacterium may show stochastic changes due to random cell movements in PBRs. Third, insufficient light due to cell self-shading can activate the oxidative pentose phosphate pathway in subpopulation cells. Fourth, the model indicates that the removal of glycogen synthesis pathway may not improve cyanobacterial bio-production in large-size PBRs, because glycogen can support cell growth in the dark zones. Based on experimental data, the integrated GSM estimates that Synechocystis 6803 in shake flask conditions has a photosynthesis efficiency of ~2.7 %. Conclusions: The multiple-scale integrated GSM, which examines both intracellular and extracellular domains, can be used to predict production yield/rate/titer in large-size PBRs. More importantly, genetic engineering strategies predicted by a traditional GSM may work well only in optimal growth conditions. In contrast, the integrated GSM may reveal mutant physiologies in diverse bioreactor conditions, leading to the design of robust strains with high chances of success in industrial settings.« less

SQC: secure quality control for meta-analysis of genome-wide association studies.

PubMed

Huang, Zhicong; Lin, Huang; Fellay, Jacques; Kutalik, Zoltán; Hubaux, Jean-Pierre

2017-08-01

Due to the limited power of small-scale genome-wide association studies (GWAS), researchers tend to collaborate and establish a larger consortium in order to perform large-scale GWAS. Genome-wide association meta-analysis (GWAMA) is a statistical tool that aims to synthesize results from multiple independent studies to increase the statistical power and reduce false-positive findings of GWAS. However, it has been demonstrated that the aggregate data of individual studies are subject to inference attacks, hence privacy concerns arise when researchers share study data in GWAMA. In this article, we propose a secure quality control (SQC) protocol, which enables checking the quality of data in a privacy-preserving way without revealing sensitive information to a potential adversary. SQC employs state-of-the-art cryptographic and statistical techniques for privacy protection. We implement the solution in a meta-analysis pipeline with real data to demonstrate the efficiency and scalability on commodity machines. The distributed execution of SQC on a cluster of 128 cores for one million genetic variants takes less than one hour, which is a modest cost considering the 10-month time span usually observed for the completion of the QC procedure that includes timing of logistics. SQC is implemented in Java and is publicly available at https://github.com/acs6610987/secureqc. jean-pierre.hubaux@epfl.ch. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Genome-wide map of Apn1 binding sites under oxidative stress in Saccharomyces cerevisiae.

PubMed

Morris, Lydia P; Conley, Andrew B; Degtyareva, Natalya; Jordan, I King; Doetsch, Paul W

2017-11-01

The DNA is cells is continuously exposed to reactive oxygen species resulting in toxic and mutagenic DNA damage. Although the repair of oxidative DNA damage occurs primarily through the base excision repair (BER) pathway, the nucleotide excision repair (NER) pathway processes some of the same lesions. In addition, damage tolerance mechanisms, such as recombination and translesion synthesis, enable cells to tolerate oxidative DNA damage, especially when BER and NER capacities are exceeded. Thus, disruption of BER alone or disruption of BER and NER in Saccharomyces cerevisiae leads to increased mutations as well as large-scale genomic rearrangements. Previous studies demonstrated that a particular region of chromosome II is susceptible to chronic oxidative stress-induced chromosomal rearrangements, suggesting the existence of DNA damage and/or DNA repair hotspots. Here we investigated the relationship between oxidative damage and genomic instability utilizing chromatin immunoprecipitation combined with DNA microarray technology to profile DNA repair sites along yeast chromosomes under different oxidative stress conditions. We targeted the major yeast AP endonuclease Apn1 as a representative BER protein. Our results indicate that Apn1 target sequences are enriched for cytosine and guanine nucleotides. We predict that BER protects these sites in the genome because guanines and cytosines are thought to be especially susceptible to oxidative attack, thereby preventing large-scale genome destabilization from chronic accumulation of DNA damage. Information from our studies should provide insight into how regional deployment of oxidative DNA damage management systems along chromosomes protects against large-scale rearrangements. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

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.

Defining the diverse spectrum of inversions, complex structural variation, and chromothripsis in the morbid human genome.

PubMed

Collins, Ryan L; Brand, Harrison; Redin, Claire E; Hanscom, Carrie; Antolik, Caroline; Stone, Matthew R; Glessner, Joseph T; Mason, Tamara; Pregno, Giulia; Dorrani, Naghmeh; Mandrile, Giorgia; Giachino, Daniela; Perrin, Danielle; Walsh, Cole; Cipicchio, Michelle; Costello, Maura; Stortchevoi, Alexei; An, Joon-Yong; Currall, Benjamin B; Seabra, Catarina M; Ragavendran, Ashok; Margolin, Lauren; Martinez-Agosto, Julian A; Lucente, Diane; Levy, Brynn; Sanders, Stephan J; Wapner, Ronald J; Quintero-Rivera, Fabiola; Kloosterman, Wigard; Talkowski, Michael E

2017-03-06

Structural variation (SV) influences genome organization and contributes to human disease. However, the complete mutational spectrum of SV has not been routinely captured in disease association studies. We sequenced 689 participants with autism spectrum disorder (ASD) and other developmental abnormalities to construct a genome-wide map of large SV. Using long-insert jumping libraries at 105X mean physical coverage and linked-read whole-genome sequencing from 10X Genomics, we document seven major SV classes at ~5 kb SV resolution. Our results encompass 11,735 distinct large SV sites, 38.1% of which are novel and 16.8% of which are balanced or complex. We characterize 16 recurrent subclasses of complex SV (cxSV), revealing that: (1) cxSV are larger and rarer than canonical SV; (2) each genome harbors 14 large cxSV on average; (3) 84.4% of large cxSVs involve inversion; and (4) most large cxSV (93.8%) have not been delineated in previous studies. Rare SVs are more likely to disrupt coding and regulatory non-coding loci, particularly when truncating constrained and disease-associated genes. We also identify multiple cases of catastrophic chromosomal rearrangements known as chromoanagenesis, including somatic chromoanasynthesis, and extreme balanced germline chromothripsis events involving up to 65 breakpoints and 60.6 Mb across four chromosomes, further defining rare categories of extreme cxSV. These data provide a foundational map of large SV in the morbid human genome and demonstrate a previously underappreciated abundance and diversity of cxSV that should be considered in genomic studies of human disease.

Scaling up the 454 Titanium Library Construction and Pooling of Barcoded Libraries

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

Phung, Wilson; Hack, Christopher; Shapiro, Harris

2009-03-23

We have been developing a high throughput 454 library construction process at the Joint Genome Institute to meet the needs of de novo sequencing a large number of microbial and eukaryote genomes, EST, and metagenome projects. We have been focusing efforts in three areas: (1) modifying the current process to allow the construction of 454 standard libraries on a 96-well format; (2) developing a robotic platform to perform the 454 library construction; and (3) designing molecular barcodes to allow pooling and sorting of many different samples. In the development of a high throughput process to scale up the number ofmore » libraries by adapting the process to a 96-well plate format, the key process change involves the replacement of gel electrophoresis for size selection with Solid Phase Reversible Immobilization (SPRI) beads. Although the standard deviation of the insert sizes increases, the overall quality sequence and distribution of the reads in the genome has not changed. The manual process of constructing 454 shotgun libraries on 96-well plates is a time-consuming, labor-intensive, and ergonomically hazardous process; we have been experimenting to program a BioMek robot to perform the library construction. This will not only enable library construction to be completed in a single day, but will also minimize any ergonomic risk. In addition, we have implemented a set of molecular barcodes (AKA Multiple Identifiers or MID) and a pooling process that allows us to sequence many targets simultaneously. Here we will present the testing of pooling a set of selected fosmids derived from the endomycorrhizal fungus Glomus intraradices. By combining the robotic library construction process and the use of molecular barcodes, it is now possible to sequence hundreds of fosmids that represent a minimal tiling path of this genome. Here we present the progress and the challenges of developing these scaled-up processes.« less

Low-pass sequencing for microbial comparative genomics

PubMed Central

Goo, Young Ah; Roach, Jared; Glusman, Gustavo; Baliga, Nitin S; Deutsch, Kerry; Pan, Min; Kennedy, Sean; DasSarma, Shiladitya; Victor Ng, Wailap; Hood, Leroy

2004-01-01

Background We studied four extremely halophilic archaea by low-pass shotgun sequencing: (1) the metabolically versatile Haloarcula marismortui; (2) the non-pigmented Natrialba asiatica; (3) the psychrophile Halorubrum lacusprofundi and (4) the Dead Sea isolate Halobaculum gomorrense. Approximately one thousand single pass genomic sequences per genome were obtained. The data were analyzed by comparative genomic analyses using the completed Halobacterium sp. NRC-1 genome as a reference. Low-pass shotgun sequencing is a simple, inexpensive, and rapid approach that can readily be performed on any cultured microbe. Results As expected, the four archaeal halophiles analyzed exhibit both bacterial and eukaryotic characteristics as well as uniquely archaeal traits. All five halophiles exhibit greater than sixty percent GC content and low isoelectric points (pI) for their predicted proteins. Multiple insertion sequence (IS) elements, often involved in genome rearrangements, were identified in H. lacusprofundi and H. marismortui. The core biological functions that govern cellular and genetic mechanisms of H. sp. NRC-1 appear to be conserved in these four other halophiles. Multiple TATA box binding protein (TBP) and transcription factor IIB (TFB) homologs were identified from most of the four shotgunned halophiles. The reconstructed molecular tree of all five halophiles shows a large divergence between these species, but with the closest relationship being between H. sp. NRC-1 and H. lacusprofundi. Conclusion Despite the diverse habitats of these species, all five halophiles share (1) high GC content and (2) low protein isoelectric points, which are characteristics associated with environmental exposure to UV radiation and hypersalinity, respectively. Identification of multiple IS elements in the genome of H. lacusprofundi and H. marismortui suggest that genome structure and dynamic genome reorganization might be similar to that previously observed in the IS-element rich genome of H. sp. NRC-1. Identification of multiple TBP and TFB homologs in these four halophiles are consistent with the hypothesis that different types of complex transcriptional regulation may occur through multiple TBP-TFB combinations in response to rapidly changing environmental conditions. Low-pass shotgun sequence analyses of genomes permit extensive and diverse analyses, and should be generally useful for comparative microbial genomics. PMID:14718067

Relation of genomic variants for Alzheimer disease dementia to common neuropathologies

PubMed Central

Yu, Lei; Buchman, Aron S.; Schneider, Julie A.; De Jager, Philip L.; Bennett, David A.

2016-01-01

Objective: To investigate the associations of previously reported Alzheimer disease (AD) dementia genomic variants with common neuropathologies. Methods: This is a postmortem study including 1,017 autopsied participants from 2 clinicopathologic cohorts. Analyses focused on 22 genomic variants associated with AD dementia in large-scale case-control genome-wide association study (GWAS) meta-analyses. The neuropathologic traits of interest were a pathologic diagnosis of AD according to NIA-Reagan criteria, macroscopic and microscopic infarcts, Lewy bodies (LB), and hippocampal sclerosis. For each variant, multiple logistic regression was used to investigate its association with neuropathologic traits, adjusting for age, sex, and subpopulation structure. We also conducted power analyses to estimate the sample sizes required to detect genome-wide significance (p < 5 × 10−8) for pathologic AD for all variants. Results: APOE ε4 allele was associated with greater odds of pathologic AD (odds ratio [OR] 3.82, 95% confidence interval [CI] 2.67–5.46, p = 1.9 × 10−13), while ε2 allele was associated with lower odds of pathologic AD (OR 0.42, 95% CI 0.30–0.61, p = 3.1 × 10−6). Four additional genomic variants including rs6656401 (CR1), rs1476679 (ZCWPW1), rs35349669 (INPP5D), and rs17125944 (FERMT2) had p values less than 0.05. Remarkably, half of the previously reported AD dementia variants are not likely to be detected for association with pathologic AD with a sample size in excess of the largest GWAS meta-analyses of AD dementia. Conclusions: Many recently discovered genomic variants for AD dementia are not associated with the pathology of AD. Some genomic variants for AD dementia appear to be associated with other common neuropathologies. PMID:27371493

Relation of genomic variants for Alzheimer disease dementia to common neuropathologies.

PubMed

Farfel, Jose M; Yu, Lei; Buchman, Aron S; Schneider, Julie A; De Jager, Philip L; Bennett, David A

2016-08-02

To investigate the associations of previously reported Alzheimer disease (AD) dementia genomic variants with common neuropathologies. This is a postmortem study including 1,017 autopsied participants from 2 clinicopathologic cohorts. Analyses focused on 22 genomic variants associated with AD dementia in large-scale case-control genome-wide association study (GWAS) meta-analyses. The neuropathologic traits of interest were a pathologic diagnosis of AD according to NIA-Reagan criteria, macroscopic and microscopic infarcts, Lewy bodies (LB), and hippocampal sclerosis. For each variant, multiple logistic regression was used to investigate its association with neuropathologic traits, adjusting for age, sex, and subpopulation structure. We also conducted power analyses to estimate the sample sizes required to detect genome-wide significance (p < 5 × 10(-8)) for pathologic AD for all variants. APOE ε4 allele was associated with greater odds of pathologic AD (odds ratio [OR] 3.82, 95% confidence interval [CI] 2.67-5.46, p = 1.9 × 10(-13)), while ε2 allele was associated with lower odds of pathologic AD (OR 0.42, 95% CI 0.30-0.61, p = 3.1 × 10(-6)). Four additional genomic variants including rs6656401 (CR1), rs1476679 (ZCWPW1), rs35349669 (INPP5D), and rs17125944 (FERMT2) had p values less than 0.05. Remarkably, half of the previously reported AD dementia variants are not likely to be detected for association with pathologic AD with a sample size in excess of the largest GWAS meta-analyses of AD dementia. Many recently discovered genomic variants for AD dementia are not associated with the pathology of AD. Some genomic variants for AD dementia appear to be associated with other common neuropathologies. © 2016 American Academy of Neurology.

DNA Resection at Chromosome Breaks Promotes Genome Stability by Constraining Non-Allelic Homologous Recombination

PubMed Central

Koshland, Douglas

2012-01-01

DNA double-strand breaks impact genome stability by triggering many of the large-scale genome rearrangements associated with evolution and cancer. One of the first steps in repairing this damage is 5′→3′ resection beginning at the break site. Recently, tools have become available to study the consequences of not extensively resecting double-strand breaks. Here we examine the role of Sgs1- and Exo1-dependent resection on genome stability using a non-selective assay that we previously developed using diploid yeast. We find that Saccharomyces cerevisiae lacking Sgs1 and Exo1 retains a very efficient repair process that is highly mutagenic to genome structure. Specifically, 51% of cells lacking Sgs1 and Exo1 repair a double-strand break using repetitive sequences 12–48 kb distal from the initial break site, thereby generating a genome rearrangement. These Sgs1- and Exo1-independent rearrangements depend partially upon a Rad51-mediated homologous recombination pathway. Furthermore, without resection a robust cell cycle arrest is not activated, allowing a cell with a single double-strand break to divide before repair, potentially yielding multiple progeny each with a different rearrangement. This profusion of rearranged genomes suggests that cells tolerate any dangers associated with extensive resection to inhibit mutagenic pathways such as break-distal recombination. The activation of break-distal recipient repeats and amplification of broken chromosomes when resection is limited raise the possibility that genome regions that are difficult to resect may be hotspots for rearrangements. These results may also explain why mutations in resection machinery are associated with cancer. PMID:22479212

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).

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...

PeanutBase and other bioinformatic resources for peanut

USDA-ARS?s Scientific Manuscript database

Large-scale genomic data for peanut have only become available in the last few years, with the advent of low-cost sequencing technologies. To make the data accessible to researchers and to integrate across diverse types of data, the International Peanut Genomics Consortium funded the development of ...

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).

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.

CloVR: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing.

PubMed

Angiuoli, Samuel V; Matalka, Malcolm; Gussman, Aaron; Galens, Kevin; Vangala, Mahesh; Riley, David R; Arze, Cesar; White, James R; White, Owen; Fricke, W Florian

2011-08-30

Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.

Network Analysis of Epidermal Growth Factor Signaling Using Integrated Genomic, Proteomic and Phosphorylation Data

PubMed Central

Waters, Katrina M.; Liu, Tao; Quesenberry, Ryan D.; Willse, Alan R.; Bandyopadhyay, Somnath; Kathmann, Loel E.; Weber, Thomas J.; Smith, Richard D.; Wiley, H. Steven; Thrall, Brian D.

2012-01-01

To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF) using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response. PMID:22479638

B-CAN: a resource sharing platform to improve the operation, visualization and integrated analysis of TCGA breast cancer data.

PubMed

Wen, Can-Hong; Ou, Shao-Min; Guo, Xiao-Bo; Liu, Chen-Feng; Shen, Yan-Bo; You, Na; Cai, Wei-Hong; Shen, Wen-Jun; Wang, Xue-Qin; Tan, Hai-Zhu

2017-12-12

Breast cancer is a high-risk heterogeneous disease with myriad subtypes and complicated biological features. The Cancer Genome Atlas (TCGA) breast cancer database provides researchers with the large-scale genome and clinical data via web portals and FTP services. Researchers are able to gain new insights into their related fields, and evaluate experimental discoveries with TCGA. However, it is difficult for researchers who have little experience with database and bioinformatics to access and operate on because of TCGA's complex data format and diverse files. For ease of use, we build the breast cancer (B-CAN) platform, which enables data customization, data visualization, and private data center. The B-CAN platform runs on Apache server and interacts with the backstage of MySQL database by PHP. Users can customize data based on their needs by combining tables from original TCGA database and selecting variables from each table. The private data center is applicable for private data and two types of customized data. A key feature of the B-CAN is that it provides single table display and multiple table display. Customized data with one barcode corresponding to many records and processed customized data are allowed in Multiple Tables Display. The B-CAN is an intuitive and high-efficient data-sharing platform.

Molecular Epidemiology and Evolution of Influenza Viruses Circulating within European Swine between 2009 and 2013.

PubMed

Watson, Simon J; Langat, Pinky; Reid, Scott M; Lam, Tommy Tsan-Yuk; Cotten, Matthew; Kelly, Michael; Van Reeth, Kristien; Qiu, Yu; Simon, Gaëlle; Bonin, Emilie; Foni, Emanuela; Chiapponi, Chiara; Larsen, Lars; Hjulsager, Charlotte; Markowska-Daniel, Iwona; Urbaniak, Kinga; Dürrwald, Ralf; Schlegel, Michael; Huovilainen, Anita; Davidson, Irit; Dán, Ádám; Loeffen, Willie; Edwards, Stephanie; Bublot, Michel; Vila, Thais; Maldonado, Jaime; Valls, Laura; Brown, Ian H; Pybus, Oliver G; Kellam, Paul

2015-10-01

The emergence in humans of the A(H1N1)pdm09 influenza virus, a complex reassortant virus of swine origin, highlighted the importance of worldwide influenza virus surveillance in swine. To date, large-scale surveillance studies have been reported for southern China and North America, but such data have not yet been described for Europe. We report the first large-scale genomic characterization of 290 swine influenza viruses collected from 14 European countries between 2009 and 2013. A total of 23 distinct genotypes were identified, with the 7 most common comprising 82% of the incidence. Contrasting epidemiological dynamics were observed for two of these genotypes, H1huN2 and H3N2, with the former showing multiple long-lived geographically isolated lineages, while the latter had short-lived geographically diffuse lineages. At least 32 human-swine transmission events have resulted in A(H1N1)pdm09 becoming established at a mean frequency of 8% across European countries. Notably, swine in the United Kingdom have largely had a replacement of the endemic Eurasian avian virus-like ("avian-like") genotypes with A(H1N1)pdm09-derived genotypes. The high number of reassortant genotypes observed in European swine, combined with the identification of a genotype similar to the A(H3N2)v genotype in North America, underlines the importance of continued swine surveillance in Europe for the purposes of maintaining public health. This report further reveals that the emergences and drivers of virus evolution in swine differ at the global level. The influenza A(H1N1)pdm09 virus contains a reassortant genome with segments derived from separate virus lineages that evolved in different regions of the world. In particular, its neuraminidase and matrix segments were derived from the Eurasian avian virus-like ("avian-like") lineage that emerged in European swine in the 1970s. However, while large-scale genomic characterization of swine has been reported for southern China and North America, no equivalent study has yet been reported for Europe. Surveillance of swine herds across Europe between 2009 and 2013 revealed that the A(H1N1)pdm09 virus is established in European swine, increasing the number of circulating lineages in the region and increasing the possibility of the emergence of a genotype with human pandemic potential. It also has implications for veterinary health, making prevention through vaccination more challenging. The identification of a genotype similar to the A(H3N2)v genotype, causing zoonoses at North American agricultural fairs, underlines the importance of continued genomic characterization in European swine. Copyright © 2015 Watson et al.

Molecular Epidemiology and Evolution of Influenza Viruses Circulating within European Swine between 2009 and 2013

PubMed Central

Watson, Simon J.; Langat, Pinky; Reid, Scott M.; Lam, Tommy Tsan-Yuk; Cotten, Matthew; Kelly, Michael; Van Reeth, Kristien; Qiu, Yu; Simon, Gaëlle; Bonin, Emilie; Foni, Emanuela; Chiapponi, Chiara; Larsen, Lars; Hjulsager, Charlotte; Markowska-Daniel, Iwona; Urbaniak, Kinga; Dürrwald, Ralf; Schlegel, Michael; Huovilainen, Anita; Davidson, Irit; Dán, Ádám; Loeffen, Willie; Edwards, Stephanie; Bublot, Michel; Vila, Thais; Maldonado, Jaime; Valls, Laura; Brown, Ian H.; Pybus, Oliver G.

2015-01-01

ABSTRACT The emergence in humans of the A(H1N1)pdm09 influenza virus, a complex reassortant virus of swine origin, highlighted the importance of worldwide influenza virus surveillance in swine. To date, large-scale surveillance studies have been reported for southern China and North America, but such data have not yet been described for Europe. We report the first large-scale genomic characterization of 290 swine influenza viruses collected from 14 European countries between 2009 and 2013. A total of 23 distinct genotypes were identified, with the 7 most common comprising 82% of the incidence. Contrasting epidemiological dynamics were observed for two of these genotypes, H1huN2 and H3N2, with the former showing multiple long-lived geographically isolated lineages, while the latter had short-lived geographically diffuse lineages. At least 32 human-swine transmission events have resulted in A(H1N1)pdm09 becoming established at a mean frequency of 8% across European countries. Notably, swine in the United Kingdom have largely had a replacement of the endemic Eurasian avian virus-like (“avian-like”) genotypes with A(H1N1)pdm09-derived genotypes. The high number of reassortant genotypes observed in European swine, combined with the identification of a genotype similar to the A(H3N2)v genotype in North America, underlines the importance of continued swine surveillance in Europe for the purposes of maintaining public health. This report further reveals that the emergences and drivers of virus evolution in swine differ at the global level. IMPORTANCE The influenza A(H1N1)pdm09 virus contains a reassortant genome with segments derived from separate virus lineages that evolved in different regions of the world. In particular, its neuraminidase and matrix segments were derived from the Eurasian avian virus-like (“avian-like”) lineage that emerged in European swine in the 1970s. However, while large-scale genomic characterization of swine has been reported for southern China and North America, no equivalent study has yet been reported for Europe. Surveillance of swine herds across Europe between 2009 and 2013 revealed that the A(H1N1)pdm09 virus is established in European swine, increasing the number of circulating lineages in the region and increasing the possibility of the emergence of a genotype with human pandemic potential. It also has implications for veterinary health, making prevention through vaccination more challenging. The identification of a genotype similar to the A(H3N2)v genotype, causing zoonoses at North American agricultural fairs, underlines the importance of continued genomic characterization in European swine. PMID:26202246

Optical mapping and its potential for large-scale sequencing projects.

PubMed

Aston, C; Mishra, B; Schwartz, D C

1999-07-01

Physical mapping has been rediscovered as an important component of large-scale sequencing projects. Restriction maps provide landmark sequences at defined intervals, and high-resolution restriction maps can be assembled from ensembles of single molecules by optical means. Such optical maps can be constructed from both large-insert clones and genomic DNA, and are used as a scaffold for accurately aligning sequence contigs generated by shotgun sequencing.

GPU Accelerated Browser for Neuroimaging Genomics.

PubMed

Zigon, Bob; Li, Huang; Yao, Xiaohui; Fang, Shiaofen; Hasan, Mohammad Al; Yan, Jingwen; Moore, Jason H; Saykin, Andrew J; Shen, Li

2018-04-25

Neuroimaging genomics is an emerging field that provides exciting opportunities to understand the genetic basis of brain structure and function. The unprecedented scale and complexity of the imaging and genomics data, however, have presented critical computational bottlenecks. In this work we present our initial efforts towards building an interactive visual exploratory system for mining big data in neuroimaging genomics. A GPU accelerated browsing tool for neuroimaging genomics is created that implements the ANOVA algorithm for single nucleotide polymorphism (SNP) based analysis and the VEGAS algorithm for gene-based analysis, and executes them at interactive rates. The ANOVA algorithm is 110 times faster than the 4-core OpenMP version, while the VEGAS algorithm is 375 times faster than its 4-core OpenMP counter part. This approach lays a solid foundation for researchers to address the challenges of mining large-scale imaging genomics datasets via interactive visual exploration.

Single cell Hi-C reveals cell-to-cell variability in chromosome structure

PubMed Central

Schoenfelder, Stefan; Yaffe, Eitan; Dean, Wendy; Laue, Ernest D.; Tanay, Amos; Fraser, Peter

2013-01-01

Large-scale chromosome structure and spatial nuclear arrangement have been linked to control of gene expression and DNA replication and repair. Genomic techniques based on chromosome conformation capture assess contacts for millions of loci simultaneously, but do so by averaging chromosome conformations from millions of nuclei. Here we introduce single cell Hi-C, combined with genome-wide statistical analysis and structural modeling of single copy X chromosomes, to show that individual chromosomes maintain domain organisation at the megabase scale, but show variable cell-to-cell chromosome territory structures at larger scales. Despite this structural stochasticity, localisation of active gene domains to boundaries of territories is a hallmark of chromosomal conformation. Single cell Hi-C data bridge current gaps between genomics and microscopy studies of chromosomes, demonstrating how modular organisation underlies dynamic chromosome structure, and how this structure is probabilistically linked with genome activity patterns. PMID:24067610

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

Simultaneous non-contiguous deletions using large synthetic DNA and site-specific recombinases

PubMed Central

Krishnakumar, Radha; Grose, Carissa; Haft, Daniel H.; Zaveri, Jayshree; Alperovich, Nina; Gibson, Daniel G.; Merryman, Chuck; Glass, John I.

2014-01-01

Toward achieving rapid and large scale genome modification directly in a target organism, we have developed a new genome engineering strategy that uses a combination of bioinformatics aided design, large synthetic DNA and site-specific recombinases. Using Cre recombinase we swapped a target 126-kb segment of the Escherichia coli genome with a 72-kb synthetic DNA cassette, thereby effectively eliminating over 54 kb of genomic DNA from three non-contiguous regions in a single recombination event. We observed complete replacement of the native sequence with the modified synthetic sequence through the action of the Cre recombinase and no competition from homologous recombination. Because of the versatility and high-efficiency of the Cre-lox system, this method can be used in any organism where this system is functional as well as adapted to use with other highly precise genome engineering systems. Compared to present-day iterative approaches in genome engineering, we anticipate this method will greatly speed up the creation of reduced, modularized and optimized genomes through the integration of deletion analyses data, transcriptomics, synthetic biology and site-specific recombination. PMID:24914053

ODMedit: uniform semantic annotation for data integration in medicine based on a public metadata repository.

PubMed

Dugas, Martin; Meidt, Alexandra; Neuhaus, Philipp; Storck, Michael; Varghese, Julian

2016-06-01

The volume and complexity of patient data - especially in personalised medicine - is steadily increasing, both regarding clinical data and genomic profiles: Typically more than 1,000 items (e.g., laboratory values, vital signs, diagnostic tests etc.) are collected per patient in clinical trials. In oncology hundreds of mutations can potentially be detected for each patient by genomic profiling. Therefore data integration from multiple sources constitutes a key challenge for medical research and healthcare. Semantic annotation of data elements can facilitate to identify matching data elements in different sources and thereby supports data integration. Millions of different annotations are required due to the semantic richness of patient data. These annotations should be uniform, i.e., two matching data elements shall contain the same annotations. However, large terminologies like SNOMED CT or UMLS don't provide uniform coding. It is proposed to develop semantic annotations of medical data elements based on a large-scale public metadata repository. To achieve uniform codes, semantic annotations shall be re-used if a matching data element is available in the metadata repository. A web-based tool called ODMedit ( https://odmeditor.uni-muenster.de/ ) was developed to create data models with uniform semantic annotations. It contains ~800,000 terms with semantic annotations which were derived from ~5,800 models from the portal of medical data models (MDM). The tool was successfully applied to manually annotate 22 forms with 292 data items from CDISC and to update 1,495 data models of the MDM portal. Uniform manual semantic annotation of data models is feasible in principle, but requires a large-scale collaborative effort due to the semantic richness of patient data. A web-based tool for these annotations is available, which is linked to a public metadata repository.

Multiple recent horizontal transfers of a large genomic region in cheese making fungi.

PubMed

Cheeseman, Kevin; Ropars, Jeanne; Renault, Pierre; Dupont, Joëlle; Gouzy, Jérôme; Branca, Antoine; Abraham, Anne-Laure; Ceppi, Maurizio; Conseiller, Emmanuel; Debuchy, Robert; Malagnac, Fabienne; Goarin, Anne; Silar, Philippe; Lacoste, Sandrine; Sallet, Erika; Bensimon, Aaron; Giraud, Tatiana; Brygoo, Yves

2014-01-01

While the extent and impact of horizontal transfers in prokaryotes are widely acknowledged, their importance to the eukaryotic kingdom is unclear and thought by many to be anecdotal. Here we report multiple recent transfers of a huge genomic island between Penicillium spp. found in the food environment. Sequencing of the two leading filamentous fungi used in cheese making, P. roqueforti and P. camemberti, and comparison with the penicillin producer P. rubens reveals a 575 kb long genomic island in P. roqueforti--called Wallaby--present as identical fragments at non-homologous loci in P. camemberti and P. rubens. Wallaby is detected in Penicillium collections exclusively in strains from food environments. Wallaby encompasses about 250 predicted genes, some of which are probably involved in competition with microorganisms. The occurrence of multiple recent eukaryotic transfers in the food environment provides strong evidence for the importance of this understudied and probably underestimated phenomenon in eukaryotes.

Multiple recent horizontal transfers of a large genomic region in cheese making fungi

PubMed Central

Cheeseman, Kevin; Ropars, Jeanne; Renault, Pierre; Dupont, Joëlle; Gouzy, Jérôme; Branca, Antoine; Abraham, Anne-Laure; Ceppi, Maurizio; Conseiller, Emmanuel; Debuchy, Robert; Malagnac, Fabienne; Goarin, Anne; Silar, Philippe; Lacoste, Sandrine; Sallet, Erika; Bensimon, Aaron; Giraud, Tatiana; Brygoo, Yves

2014-01-01

While the extent and impact of horizontal transfers in prokaryotes are widely acknowledged, their importance to the eukaryotic kingdom is unclear and thought by many to be anecdotal. Here we report multiple recent transfers of a huge genomic island between Penicillium spp. found in the food environment. Sequencing of the two leading filamentous fungi used in cheese making, P. roqueforti and P. camemberti, and comparison with the penicillin producer P. rubens reveals a 575 kb long genomic island in P. roqueforti—called Wallaby—present as identical fragments at non-homologous loci in P. camemberti and P. rubens. Wallaby is detected in Penicillium collections exclusively in strains from food environments. Wallaby encompasses about 250 predicted genes, some of which are probably involved in competition with microorganisms. The occurrence of multiple recent eukaryotic transfers in the food environment provides strong evidence for the importance of this understudied and probably underestimated phenomenon in eukaryotes. PMID:24407037

Initial genome sequencing and analysis of multiple myeloma

PubMed Central

Chapman, Michael A.; Lawrence, Michael S.; Keats, Jonathan J.; Cibulskis, Kristian; Sougnez, Carrie; Schinzel, Anna C.; Harview, Christina L.; Brunet, Jean-Philippe; Ahmann, Gregory J.; Adli, Mazhar; Anderson, Kenneth C.; Ardlie, Kristin G.; Auclair, Daniel; Baker, Angela; Bergsagel, P. Leif; Bernstein, Bradley E.; Drier, Yotam; Fonseca, Rafael; Gabriel, Stacey B.; Hofmeister, Craig C.; Jagannath, Sundar; Jakubowiak, Andrzej J.; Krishnan, Amrita; Levy, Joan; Liefeld, Ted; Lonial, Sagar; Mahan, Scott; Mfuko, Bunmi; Monti, Stefano; Perkins, Louise M.; Onofrio, Robb; Pugh, Trevor J.; Vincent Rajkumar, S.; Ramos, Alex H.; Siegel, David S.; Sivachenko, Andrey; Trudel, Suzanne; Vij, Ravi; Voet, Douglas; Winckler, Wendy; Zimmerman, Todd; Carpten, John; Trent, Jeff; Hahn, William C.; Garraway, Levi A.; Meyerson, Matthew; Lander, Eric S.; Getz, Gad; Golub, Todd R.

2013-01-01

Multiple myeloma is an incurable malignancy of plasma cells, and its pathogenesis is poorly understood. Here we report the massively parallel sequencing of 38 tumor genomes and their comparison to matched normal DNAs. Several new and unexpected oncogenic mechanisms were suggested by the pattern of somatic mutation across the dataset. These include the mutation of genes involved in protein translation (seen in nearly half of the patients), genes involved in histone methylation, and genes involved in blood coagulation. In addition, a broader than anticipated role of NF-κB signaling was suggested by mutations in 11 members of the NF-κB pathway. Of potential immediate clinical relevance, activating mutations of the kinase BRAF were observed in 4% of patients, suggesting the evaluation of BRAF inhibitors in multiple myeloma clinical trials. These results indicate that cancer genome sequencing of large collections of samples will yield new insights into cancer not anticipated by existing knowledge. PMID:21430775

Kernel methods for large-scale genomic data analysis

PubMed Central

Xing, Eric P.; Schaid, Daniel J.

2015-01-01

Machine learning, particularly kernel methods, has been demonstrated as a promising new tool to tackle the challenges imposed by today’s explosive data growth in genomics. They provide a practical and principled approach to learning how a large number of genetic variants are associated with complex phenotypes, to help reveal the complexity in the relationship between the genetic markers and the outcome of interest. In this review, we highlight the potential key role it will have in modern genomic data processing, especially with regard to integration with classical methods for gene prioritizing, prediction and data fusion. PMID:25053743

PSP: rapid identification of orthologous coding genes under positive selection across multiple closely related prokaryotic genomes.

PubMed

Su, Fei; Ou, Hong-Yu; Tao, Fei; Tang, Hongzhi; Xu, Ping

2013-12-27

With genomic sequences of many closely related bacterial strains made available by deep sequencing, it is now possible to investigate trends in prokaryotic microevolution. Positive selection is a sub-process of microevolution, in which a particular mutation is favored, causing the allele frequency to continuously shift in one direction. Wide scanning of prokaryotic genomes has shown that positive selection at the molecular level is much more frequent than expected. Genes with significant positive selection may play key roles in bacterial adaption to different environmental pressures. However, selection pressure analyses are computationally intensive and awkward to configure. Here we describe an open access web server, which is designated as PSP (Positive Selection analysis for Prokaryotic genomes) for performing evolutionary analysis on orthologous coding genes, specially designed for rapid comparison of dozens of closely related prokaryotic genomes. Remarkably, PSP facilitates functional exploration at the multiple levels by assignments and enrichments of KO, GO or COG terms. To illustrate this user-friendly tool, we analyzed Escherichia coli and Bacillus cereus genomes and found that several genes, which play key roles in human infection and antibiotic resistance, show significant evidence of positive selection. PSP is freely available to all users without any login requirement at: http://db-mml.sjtu.edu.cn/PSP/. PSP ultimately allows researchers to do genome-scale analysis for evolutionary selection across multiple prokaryotic genomes rapidly and easily, and identify the genes undergoing positive selection, which may play key roles in the interactions of host-pathogen and/or environmental adaptation.

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

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.

Genomics of adaptation to host-plants in herbivorous insects.

PubMed

Simon, Jean-Christophe; d'Alençon, Emmanuelle; Guy, Endrick; Jacquin-Joly, Emmanuelle; Jaquiéry, Julie; Nouhaud, Pierre; Peccoud, Jean; Sugio, Akiko; Streiff, Réjane

2015-11-01

Herbivorous insects represent the most species-rich lineages of metazoans. The high rate of diversification in herbivorous insects is thought to result from their specialization to distinct host-plants, which creates conditions favorable for the build-up of reproductive isolation and speciation. These conditions rely on constraints against the optimal use of a wide range of plant species, as each must constitute a viable food resource, oviposition site and mating site for an insect. Utilization of plants involves many essential traits of herbivorous insects, as they locate and select their hosts, overcome their defenses and acquire nutrients while avoiding intoxication. Although advances in understanding insect-plant molecular interactions have been limited by the complexity of insect traits involved in host use and the lack of genomic resources and functional tools, recent studies at the molecular level, combined with large-scale genomics studies at population and species levels, are revealing the genetic underpinning of plant specialization and adaptive divergence in non-model insect herbivores. Here, we review the recent advances in the genomics of plant adaptation in hemipterans and lepidopterans, two major insect orders, each of which includes a large number of crop pests. We focus on how genomics and post-genomics have improved our understanding of the mechanisms involved in insect-plant interactions by reviewing recent molecular discoveries in sensing, feeding, digesting and detoxifying strategies. We also present the outcomes of large-scale genomics approaches aimed at identifying loci potentially involved in plant adaptation in these insects. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Dictyostelium mobile elements: strategies to amplify in a compact genome.

PubMed

Winckler, T; Dingermann, T; Glöckner, G

2002-12-01

Dictyostelium discoideum is a eukaryotic microorganism that is attractive for the study of fundamental biological phenomena such as cell-cell communication, formation of multicellularity, cell differentiation and morphogenesis. Large-scale sequencing of the D. discoideum genome has provided new insights into evolutionary strategies evolved by transposable elements (TEs) to settle in compact microbial genomes and to maintain active populations over evolutionary time. The high gene density (about 1 gene/2.6 kb) of the D. discoideum genome leaves limited space for selfish molecular invaders to move and amplify without causing deleterious mutations that eradicate their host. Targeting of transfer RNA (tRNA) gene loci appears to be a generally successful strategy for TEs residing in compact genomes to insert away from coding regions. In D. discoideum, tRNA gene-targeted retrotransposition has evolved independently at least three times by both non-long terminal repeat (LTR) retrotransposons and retrovirus-like LTR retrotransposons. Unlike the nonspecifically inserting D. discoideum TEs, which have a strong tendency to insert into preexisting TE copies and form large and complex clusters near the ends of chromosomes, the tRNA gene-targeted retrotransposons have managed to occupy 75% of the tRNA gene loci spread on chromosome 2 and represent 80% of the TEs recognized on the assembled central 6.5-Mb part of chromosome 2. In this review we update the available information about D. discoideum TEs which emerges both from previous work and current large-scale genome sequencing, with special emphasis on the fact that tRNA genes are principal determinants of retrotransposon insertions into the D. discoideum genome.

Cellular Factors Shape 3D Genome Landscape

Cancer.gov

Researchers, using novel large-scale imaging technology, have mapped the spatial location of individual genes in the nucleus of human cells and identified 50 cellular factors required for the proper 3D positioning of genes. These spatial locations play important roles in gene expression, DNA repair, genome stability, and other cellular activities.

Developing a Drosophila Model of Schwannomatosis

DTIC Science & Technology

2012-08-01

the entire Drosophila melanogaster genome and compared...et al., 2009; Hanahan and Weinberg, 2011). Over the last decade, the fruit fly Drosophila melanogaster has become an important model system for cancer...studies. Reduced redundancy in the Drosophila genome compared with that of humans, coupled with the ability to conduct large-scale genetic screens

A Glance at Microsatellite Motifs from 454 Sequencing Reads of Watermelon Genomic DNA

USDA-ARS?s Scientific Manuscript database

A single 454 (Life Sciences Sequencing Technology) run of Charleston Gray watermelon (Citrullus lanatus var. lanatus) genomic DNA was performed and sequence data were assembled. A large scale identification of simple sequence repeat (SSR) was performed and SSR sequence data were used for the develo...

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...

Discovery of novel phosphonate natural products and their biosynthetic pathways by large-scale genome mining

USDA-ARS?s Scientific Manuscript database

Genome mining has revolutionized the field of natural products, providing hope that new antibiotics can be discovered in time before all remainders are rendered useless against multidrug resistant pathogens. While this approach has been successful in academic settings focused on small collections or...

Variation in Recombination Rate and Its Genetic Determinism in Sheep Populations

PubMed Central

Petit, Morgane; Astruc, Jean-Michel; Sarry, Julien; Drouilhet, Laurence; Fabre, Stéphane; Moreno, Carole R.; Servin, Bertrand

2017-01-01

Recombination is a complex biological process that results from a cascade of multiple events during meiosis. Understanding the genetic determinism of recombination can help to understand if and how these events are interacting. To tackle this question, we studied the patterns of recombination in sheep, using multiple approaches and data sets. We constructed male recombination maps in a dairy breed from the south of France (the Lacaune breed) at a fine scale by combining meiotic recombination rates from a large pedigree genotyped with a 50K SNP array and historical recombination rates from a sample of unrelated individuals genotyped with a 600K SNP array. This analysis revealed recombination patterns in sheep similar to other mammals but also genome regions that have likely been affected by directional and diversifying selection. We estimated the average recombination rate of Lacaune sheep at 1.5 cM/Mb, identified ∼50,000 crossover hotspots on the genome, and found a high correlation between historical and meiotic recombination rate estimates. A genome-wide association study revealed two major loci affecting interindividual variation in recombination rate in Lacaune, including the RNF212 and HEI10 genes and possibly two other loci of smaller effects including the KCNJ15 and FSHR genes. The comparison of these new results to those obtained previously in a distantly related population of domestic sheep (the Soay) revealed that Soay and Lacaune males have a very similar distribution of recombination along the genome. The two data sets were thus combined to create more precise male meiotic recombination maps in Sheep. However, despite their similar recombination maps, Soay and Lacaune males were found to exhibit different heritabilities and QTL effects for interindividual variation in genome-wide recombination rates. This highlights the robustness of recombination patterns to underlying variation in their genetic determinism. PMID:28978774

Variation in Recombination Rate and Its Genetic Determinism in Sheep Populations.

PubMed

Petit, Morgane; Astruc, Jean-Michel; Sarry, Julien; Drouilhet, Laurence; Fabre, Stéphane; Moreno, Carole R; Servin, Bertrand

2017-10-01

Recombination is a complex biological process that results from a cascade of multiple events during meiosis. Understanding the genetic determinism of recombination can help to understand if and how these events are interacting. To tackle this question, we studied the patterns of recombination in sheep, using multiple approaches and data sets. We constructed male recombination maps in a dairy breed from the south of France (the Lacaune breed) at a fine scale by combining meiotic recombination rates from a large pedigree genotyped with a 50K SNP array and historical recombination rates from a sample of unrelated individuals genotyped with a 600K SNP array. This analysis revealed recombination patterns in sheep similar to other mammals but also genome regions that have likely been affected by directional and diversifying selection. We estimated the average recombination rate of Lacaune sheep at 1.5 cM/Mb, identified ∼50,000 crossover hotspots on the genome, and found a high correlation between historical and meiotic recombination rate estimates. A genome-wide association study revealed two major loci affecting interindividual variation in recombination rate in Lacaune, including the RNF212 and HEI10 genes and possibly two other loci of smaller effects including the KCNJ15 and FSHR genes. The comparison of these new results to those obtained previously in a distantly related population of domestic sheep (the Soay) revealed that Soay and Lacaune males have a very similar distribution of recombination along the genome. The two data sets were thus combined to create more precise male meiotic recombination maps in Sheep. However, despite their similar recombination maps, Soay and Lacaune males were found to exhibit different heritabilities and QTL effects for interindividual variation in genome-wide recombination rates. This highlights the robustness of recombination patterns to underlying variation in their genetic determinism. Copyright © 2017 by the Genetics Society of America.

Evolution and Epidemiology of Multidrug-Resistant Klebsiella pneumoniae in the United Kingdom and Ireland

PubMed Central

Moradigaravand, Danesh; Martin, Veronique; Peacock, Sharon J.

2017-01-01

ABSTRACT Klebsiella pneumoniae is a human commensal and opportunistic pathogen that has become a leading causative agent of hospital-based infections over the past few decades. The emergence and global expansion of hypervirulent and multidrug-resistant (MDR) clones of K. pneumoniae have been increasingly reported in community-acquired and nosocomial infections. Despite this, the population genomics and epidemiology of MDR K. pneumoniae at the national level are still poorly understood. To obtain insights into these, we analyzed a systematic large-scale collection of invasive MDR K. pneumoniae isolates from hospitals across the United Kingdom and Ireland. Using whole-genome phylogenetic analysis, we placed these in the context of previously sequenced K. pneumoniae populations from geographically diverse countries and identified their virulence and drug resistance determinants. Our results demonstrate that United Kingdom and Ireland MDR isolates are a highly diverse population drawn from across the global phylogenetic tree of K. pneumoniae and represent multiple recent international introductions that are mainly from Europe but in some cases from more distant countries. In addition, we identified novel genetic determinants underlying resistance to beta-lactams, gentamicin, ciprofloxacin, and tetracyclines, indicating that both increased virulence and resistance have emerged independently multiple times throughout the population. Our data show that MDR K. pneumoniae isolates in the United Kingdom and Ireland have multiple distinct origins and appear to be part of a globally circulating K. pneumoniae population. PMID:28223459

Aligning the unalignable: bacteriophage whole genome alignments.

PubMed

Bérard, Sèverine; Chateau, Annie; Pompidor, Nicolas; Guertin, Paul; Bergeron, Anne; Swenson, Krister M

2016-01-13

In recent years, many studies focused on the description and comparison of large sets of related bacteriophage genomes. Due to the peculiar mosaic structure of these genomes, few informative approaches for comparing whole genomes exist: dot plots diagrams give a mostly qualitative assessment of the similarity/dissimilarity between two or more genomes, and clustering techniques are used to classify genomes. Multiple alignments are conspicuously absent from this scene. Indeed, whole genome aligners interpret lack of similarity between sequences as an indication of rearrangements, insertions, or losses. This behavior makes them ill-prepared to align bacteriophage genomes, where even closely related strains can accomplish the same biological function with highly dissimilar sequences. In this paper, we propose a multiple alignment strategy that exploits functional collinearity shared by related strains of bacteriophages, and uses partial orders to capture mosaicism of sets of genomes. As classical alignments do, the computed alignments can be used to predict that genes have the same biological function, even in the absence of detectable similarity. The Alpha aligner implements these ideas in visual interactive displays, and is used to compute several examples of alignments of Staphylococcus aureus and Mycobacterium bacteriophages, involving up to 29 genomes. Using these datasets, we prove that Alpha alignments are at least as good as those computed by standard aligners. Comparison with the progressive Mauve aligner - which implements a partial order strategy, but whose alignments are linearized - shows a greatly improved interactive graphic display, while avoiding misalignments. Multiple alignments of whole bacteriophage genomes work, and will become an important conceptual and visual tool in comparative genomics of sets of related strains. A python implementation of Alpha, along with installation instructions for Ubuntu and OSX, is available on bitbucket (https://bitbucket.org/thekswenson/alpha).

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

Pfarao: a web application for protein family analysis customized for cytoskeletal and motor proteins (CyMoBase).

PubMed

Odronitz, Florian; Kollmar, Martin

2006-11-29

Annotation of protein sequences of eukaryotic organisms is crucial for the understanding of their function in the cell. Manual annotation is still by far the most accurate way to correctly predict genes. The classification of protein sequences, their phylogenetic relation and the assignment of function involves information from various sources. This often leads to a collection of heterogeneous data, which is hard to track. Cytoskeletal and motor proteins consist of large and diverse superfamilies comprising up to several dozen members per organism. Up to date there is no integrated tool available to assist in the manual large-scale comparative genomic analysis of protein families. Pfarao (Protein Family Application for Retrieval, Analysis and Organisation) is a database driven online working environment for the analysis of manually annotated protein sequences and their relationship. Currently, the system can store and interrelate a wide range of information about protein sequences, species, phylogenetic relations and sequencing projects as well as links to literature and domain predictions. Sequences can be imported from multiple sequence alignments that are generated during the annotation process. A web interface allows to conveniently browse the database and to compile tabular and graphical summaries of its content. We implemented a protein sequence-centric web application to store, organize, interrelate, and present heterogeneous data that is generated in manual genome annotation and comparative genomics. The application has been developed for the analysis of cytoskeletal and motor proteins (CyMoBase) but can easily be adapted for any protein.

A greedy, graph-based algorithm for the alignment of multiple homologous gene lists.

PubMed

Fostier, Jan; Proost, Sebastian; Dhoedt, Bart; Saeys, Yvan; Demeester, Piet; Van de Peer, Yves; Vandepoele, Klaas

2011-03-15

Many comparative genomics studies rely on the correct identification of homologous genomic regions using accurate alignment tools. In such case, the alphabet of the input sequences consists of complete genes, rather than nucleotides or amino acids. As optimal multiple sequence alignment is computationally impractical, a progressive alignment strategy is often employed. However, such an approach is susceptible to the propagation of alignment errors in early pairwise alignment steps, especially when dealing with strongly diverged genomic regions. In this article, we present a novel accurate and efficient greedy, graph-based algorithm for the alignment of multiple homologous genomic segments, represented as ordered gene lists. Based on provable properties of the graph structure, several heuristics are developed to resolve local alignment conflicts that occur due to gene duplication and/or rearrangement events on the different genomic segments. The performance of the algorithm is assessed by comparing the alignment results of homologous genomic segments in Arabidopsis thaliana to those obtained by using both a progressive alignment method and an earlier graph-based implementation. Especially for datasets that contain strongly diverged segments, the proposed method achieves a substantially higher alignment accuracy, and proves to be sufficiently fast for large datasets including a few dozens of eukaryotic genomes. http://bioinformatics.psb.ugent.be/software. The algorithm is implemented as a part of the i-ADHoRe 3.0 package.

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

PubMed

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

2013-05-15

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

Parallel workflow manager for non-parallel bioinformatic applications to solve large-scale biological problems on a supercomputer.

PubMed

Suplatov, Dmitry; Popova, Nina; Zhumatiy, Sergey; Voevodin, Vladimir; Švedas, Vytas

2016-04-01

Rapid expansion of online resources providing access to genomic, structural, and functional information associated with biological macromolecules opens an opportunity to gain a deeper understanding of the mechanisms of biological processes due to systematic analysis of large datasets. This, however, requires novel strategies to optimally utilize computer processing power. Some methods in bioinformatics and molecular modeling require extensive computational resources. Other algorithms have fast implementations which take at most several hours to analyze a common input on a modern desktop station, however, due to multiple invocations for a large number of subtasks the full task requires a significant computing power. Therefore, an efficient computational solution to large-scale biological problems requires both a wise parallel implementation of resource-hungry methods as well as a smart workflow to manage multiple invocations of relatively fast algorithms. In this work, a new computer software mpiWrapper has been developed to accommodate non-parallel implementations of scientific algorithms within the parallel supercomputing environment. The Message Passing Interface has been implemented to exchange information between nodes. Two specialized threads - one for task management and communication, and another for subtask execution - are invoked on each processing unit to avoid deadlock while using blocking calls to MPI. The mpiWrapper can be used to launch all conventional Linux applications without the need to modify their original source codes and supports resubmission of subtasks on node failure. We show that this approach can be used to process huge amounts of biological data efficiently by running non-parallel programs in parallel mode on a supercomputer. The C++ source code and documentation are available from http://biokinet.belozersky.msu.ru/mpiWrapper .

EUPAN enables pan-genome studies of a large number of eukaryotic genomes.

PubMed

Hu, Zhiqiang; Sun, Chen; Lu, Kuang-Chen; Chu, Xixia; Zhao, Yue; Lu, Jinyuan; Shi, Jianxin; Wei, Chaochun

2017-08-01

Pan-genome analyses are routinely carried out for bacteria to interpret the within-species gene presence/absence variations (PAVs). However, pan-genome analyses are rare for eukaryotes due to the large sizes and higher complexities of their genomes. Here we proposed EUPAN, a eukaryotic pan-genome analysis toolkit, enabling automatic large-scale eukaryotic pan-genome analyses and detection of gene PAVs at a relatively low sequencing depth. In the previous studies, we demonstrated the effectiveness and high accuracy of EUPAN in the pan-genome analysis of 453 rice genomes, in which we also revealed widespread gene PAVs among individual rice genomes. Moreover, EUPAN can be directly applied to the current re-sequencing projects primarily focusing on single nucleotide polymorphisms. EUPAN is implemented in Perl, R and C ++. It is supported under Linux and preferred for a computer cluster with LSF and SLURM job scheduling system. EUPAN together with its standard operating procedure (SOP) is freely available for non-commercial use (CC BY-NC 4.0) at http://cgm.sjtu.edu.cn/eupan/index.html . ccwei@sjtu.edu.cn or jianxin.shi@sjtu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Extensive de novo mutation rate variation between individuals and across the genome of Chlamydomonas reinhardtii

PubMed Central

Ness, Rob W.; Morgan, Andrew D.; Vasanthakrishnan, Radhakrishnan B.; Colegrave, Nick; Keightley, Peter D.

2015-01-01

Describing the process of spontaneous mutation is fundamental for understanding the genetic basis of disease, the threat posed by declining population size in conservation biology, and much of evolutionary biology. Directly studying spontaneous mutation has been difficult, however, because new mutations are rare. Mutation accumulation (MA) experiments overcome this by allowing mutations to build up over many generations in the near absence of natural selection. Here, we sequenced the genomes of 85 MA lines derived from six genetically diverse strains of the green alga Chlamydomonas reinhardtii. We identified 6843 new mutations, more than any other study of spontaneous mutation. We observed sevenfold variation in the mutation rate among strains and that mutator genotypes arose, increasing the mutation rate approximately eightfold in some replicates. We also found evidence for fine-scale heterogeneity in the mutation rate, with certain sequence motifs mutating at much higher rates, and clusters of multiple mutations occurring at closely linked sites. There was little evidence, however, for mutation rate heterogeneity between chromosomes or over large genomic regions of 200 kbp. We generated a predictive model of the mutability of sites based on their genomic properties, including local GC content, gene expression level, and local sequence context. Our model accurately predicted the average mutation rate and natural levels of genetic diversity of sites across the genome. Notably, trinucleotides vary 17-fold in rate between the most and least mutable sites. Our results uncover a rich heterogeneity in the process of spontaneous mutation both among individuals and across the genome. PMID:26260971

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.

Successful application of FTA Classic Card technology and use of bacteriophage phi29 DNA polymerase for large-scale field sampling and cloning of complete maize streak virus genomes.

PubMed

Owor, Betty E; Shepherd, Dionne N; Taylor, Nigel J; Edema, Richard; Monjane, Adérito L; Thomson, Jennifer A; Martin, Darren P; Varsani, Arvind

2007-03-01

Leaf samples from 155 maize streak virus (MSV)-infected maize plants were collected from 155 farmers' fields in 23 districts in Uganda in May/June 2005 by leaf-pressing infected samples onto FTA Classic Cards. Viral DNA was successfully extracted from cards stored at room temperature for 9 months. The diversity of 127 MSV isolates was analysed by PCR-generated RFLPs. Six representative isolates having different RFLP patterns and causing either severe, moderate or mild disease symptoms, were chosen for amplification from FTA cards by bacteriophage phi29 DNA polymerase using the TempliPhi system. Full-length genomes were inserted into a cloning vector using a unique restriction enzyme site, and sequenced. The 1.3-kb PCR product amplified directly from FTA-eluted DNA and used for RFLP analysis was also cloned and sequenced. Comparison of cloned whole genome sequences with those of the original PCR products indicated that the correct virus genome had been cloned and that no errors were introduced by the phi29 polymerase. This is the first successful large-scale application of FTA card technology to the field, and illustrates the ease with which large numbers of infected samples can be collected and stored for downstream molecular applications such as diversity analysis and cloning of potentially new virus genomes.

First Large-Scale Proteogenomic Study of Breast Cancer Provides Insight into Potential Therapeutic Targets | Office of Cancer Clinical Proteomics Research

Cancer.gov

News Release: May 25, 2016 — Building on data from The Cancer Genome Atlas (TCGA) project, a multi-institutional team of scientists has completed the first large-scale “proteogenomic” study of breast cancer, linking DNA mutations to protein signaling and helping pinpoint the genes that drive cancer.

CTD² in Action: Translating High-Content Genomic Data into New Therapies | Office of Cancer Genomics

Cancer.gov

Large-scale molecular analyses have provided an unprecedented global view of the molecular defects in cancers and promise to revolutionize precision cancer medicine by guiding the development of therapies that are matched to genomic alterations in tumors. Cancer is a heterogeneous disease which explains why there are varying responses to therapy. This heterogeneity poses a daunting challenge for clinicians managing a patient’s disease.

Continuing Evolution of Burkholderia mallei Through Genome Reduction and Large-Scale Rearrangements

DTIC Science & Technology

2010-01-22

in Materials and Methods. b NRPS, nonribosomal peptide synthase ; PKS, polyketide synthase ; RND, resistance nodulation-division like pump. Losada et al...genomics, genome erosion, bacterial virulence. ª The Author(s) 2010. Published by Oxford University Press on behalf of the Society for Molecular Biology...creativecommons.org/licenses/by-nc/ 2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original

Draft Genome Sequences of 510 Listeria monocytogenes Strains from Food Isolates and Human Listeriosis Cases from Northern Italy.

PubMed

Lomonaco, Sara; Gallina, Silvia; Filipello, Virginia; Sanchez Leon, Maria; Kastanis, George John; Allard, Marc; Brown, Eric; Amato, Ettore; Pontello, Mirella; Decastelli, Lucia

2018-01-18

Listeriosis outbreaks are frequently multistate/multicountry outbreaks, underlining the importance of molecular typing data for several diverse and well-characterized isolates. Large-scale whole-genome sequencing studies on Listeria monocytogenes isolates from non-U.S. locations have been limited. Herein, we describe the draft genome sequences of 510 L. monocytogenes isolates from northern Italy from different sources.

Integrated Database And Knowledge Base For Genomic Prospective Cohort Study In Tohoku Medical Megabank Toward Personalized Prevention And Medicine.

PubMed

Ogishima, Soichi; Takai, Takako; Shimokawa, Kazuro; Nagaie, Satoshi; Tanaka, Hiroshi; Nakaya, Jun

2015-01-01

The Tohoku Medical Megabank project is a national project to revitalization of the disaster area in the Tohoku region by the Great East Japan Earthquake, and have conducted large-scale prospective genome-cohort study. Along with prospective genome-cohort study, we have developed integrated database and knowledge base which will be key database for realizing personalized prevention and medicine.

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses

PubMed Central

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-01-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. PMID:24462600

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses.

PubMed

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-06-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. Copyright © 2014 Elsevier Inc. All rights reserved.

The USC Epigenome Center.

PubMed

Laird, Peter W

2009-10-01

The University of Southern California (USC, CA, USA) has a long tradition of excellence in epigenetics. With the recent explosive growth and technological maturation of the field of epigenetics, it became clear that a dedicated high-throughput epigenomic data production facility would be needed to remain at the forefront of epigenetic research. To address this need, USC launched the USC Epigenome Center as the first large-scale center in academics dedicated to epigenomic research. The Center is providing high-throughput data production for large-scale genomic and epigenomic studies, and developing novel analysis tools for epigenomic research. This unique facility promises to be a valuable resource for multidisciplinary research, education and training in genomics, epigenomics, bioinformatics, and translational medicine.

Surviving an Identity Crisis: A Revised View of Chromatin Insulators in the Genomics Era

PubMed Central

Matzat, Leah H.; Lei, Elissa P.

2013-01-01

The control of complex, developmentally regulated loci and partitioning of the genome into active and silent domains is in part accomplished through the activity of DNA-protein complexes termed chromatin insulators. Together, the multiple, well-studied classes of insulators in Drosophila melanogaster appear to be generally functionally conserved. In this review, we discuss recent genomic-scale experiments and attempt to reconcile these newer findings in the context of previously defined insulator characteristics based on classical genetic analyses and transgenic approaches. Finally, we discuss the emerging understanding of mechanisms of chromatin insulator regulation. PMID:24189492

Prediction of Multiple-Trait and Multiple-Environment Genomic Data Using Recommender Systems.

PubMed

Montesinos-López, Osval A; Montesinos-López, Abelardo; Crossa, José; Montesinos-López, José C; Mota-Sanchez, David; Estrada-González, Fermín; Gillberg, Jussi; Singh, Ravi; Mondal, Suchismita; Juliana, Philomin

2018-01-04

In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. In current genomic selection, although researchers have a large amount of information and appropriate statistical models to process it, there is still limited computing efficiency to do so. Although some statistical models are usually mathematically elegant, many of them are also computationally inefficient, and they are impractical for many traits, lines, environments, and years because they need to sample from huge normal multivariate distributions. For these reasons, this study explores two recommender systems: item-based collaborative filtering (IBCF) and the matrix factorization algorithm (MF) in the context of multiple traits and multiple environments. The IBCF and MF methods were compared with two conventional methods on simulated and real data. Results of the simulated and real data sets show that the IBCF technique was slightly better in terms of prediction accuracy than the two conventional methods and the MF method when the correlation was moderately high. The IBCF technique is very attractive because it produces good predictions when there is high correlation between items (environment-trait combinations) and its implementation is computationally feasible, which can be useful for plant breeders who deal with very large data sets. Copyright © 2018 Montesinos-Lopez et al.

Prediction of Multiple-Trait and Multiple-Environment Genomic Data Using Recommender Systems

PubMed Central

Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, José; Montesinos-López, José C.; Mota-Sanchez, David; Estrada-González, Fermín; Gillberg, Jussi; Singh, Ravi; Mondal, Suchismita; Juliana, Philomin

2018-01-01

In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. In current genomic selection, although researchers have a large amount of information and appropriate statistical models to process it, there is still limited computing efficiency to do so. Although some statistical models are usually mathematically elegant, many of them are also computationally inefficient, and they are impractical for many traits, lines, environments, and years because they need to sample from huge normal multivariate distributions. For these reasons, this study explores two recommender systems: item-based collaborative filtering (IBCF) and the matrix factorization algorithm (MF) in the context of multiple traits and multiple environments. The IBCF and MF methods were compared with two conventional methods on simulated and real data. Results of the simulated and real data sets show that the IBCF technique was slightly better in terms of prediction accuracy than the two conventional methods and the MF method when the correlation was moderately high. The IBCF technique is very attractive because it produces good predictions when there is high correlation between items (environment–trait combinations) and its implementation is computationally feasible, which can be useful for plant breeders who deal with very large data sets. PMID:29097376

Comparative genomics and evolution of eukaryotic phospholipidbiosynthesis

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

Lykidis, Athanasios

2006-12-01

Phospholipid biosynthetic enzymes produce diverse molecular structures and are often present in multiple forms encoded by different genes. This work utilizes comparative genomics and phylogenetics for exploring the distribution, structure and evolution of phospholipid biosynthetic genes and pathways in 26 eukaryotic genomes. Although the basic structure of the pathways was formed early in eukaryotic evolution, the emerging picture indicates that individual enzyme families followed unique evolutionary courses. For example, choline and ethanolamine kinases and cytidylyltransferases emerged in ancestral eukaryotes, whereas, multiple forms of the corresponding phosphatidyltransferases evolved mainly in a lineage specific manner. Furthermore, several unicellular eukaryotes maintain bacterial-type enzymesmore » and reactions for the synthesis of phosphatidylglycerol and cardiolipin. Also, base-exchange phosphatidylserine synthases are widespread and ancestral enzymes. The multiplicity of phospholipid biosynthetic enzymes has been largely generated by gene expansion in a lineage specific manner. Thus, these observations suggest that phospholipid biosynthesis has been an actively evolving system. Finally, comparative genomic analysis indicates the existence of novel phosphatidyltransferases and provides a candidate for the uncharacterized eukaryotic phosphatidylglycerol phosphate phosphatase.« less

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.

Mitochondrial genome deletions and minicircles are common in lice (Insecta: Phthiraptera)

PubMed Central

2011-01-01

Background The gene composition, gene order and structure of the mitochondrial genome are remarkably stable across bilaterian animals. Lice (Insecta: Phthiraptera) are a major exception to this genomic stability in that the canonical single chromosome with 37 genes found in almost all other bilaterians has been lost in multiple lineages in favour of multiple, minicircular chromosomes with less than 37 genes on each chromosome. Results Minicircular mt genomes are found in six of the ten louse species examined to date and three types of minicircles were identified: heteroplasmic minicircles which coexist with full sized mt genomes (type 1); multigene chromosomes with short, simple control regions, we infer that the genome consists of several such chromosomes (type 2); and multiple, single to three gene chromosomes with large, complex control regions (type 3). Mapping minicircle types onto a phylogenetic tree of lice fails to show a pattern of their occurrence consistent with an evolutionary series of minicircle types. Analysis of the nuclear-encoded, mitochondrially-targetted genes inferred from the body louse, Pediculus, suggests that the loss of mitochondrial single-stranded binding protein (mtSSB) may be responsible for the presence of minicircles in at least species with the most derived type 3 minicircles (Pediculus, Damalinia). Conclusions Minicircular mt genomes are common in lice and appear to have arisen multiple times within the group. Life history adaptive explanations which attribute minicircular mt genomes in lice to the adoption of blood-feeding in the Anoplura are not supported by this expanded data set as minicircles are found in multiple non-blood feeding louse groups but are not found in the blood-feeding genus Heterodoxus. In contrast, a mechanist explanation based on the loss of mtSSB suggests that minicircles may be selectively favoured due to the incapacity of the mt replisome to synthesize long replicative products without mtSSB and thus the loss of this gene lead to the formation of minicircles in lice. PMID:21813020

Mitochondrial genome deletions and minicircles are common in lice (Insecta: Phthiraptera).

PubMed

Cameron, Stephen L; Yoshizawa, Kazunori; Mizukoshi, Atsushi; Whiting, Michael F; Johnson, Kevin P

2011-08-04

The gene composition, gene order and structure of the mitochondrial genome are remarkably stable across bilaterian animals. Lice (Insecta: Phthiraptera) are a major exception to this genomic stability in that the canonical single chromosome with 37 genes found in almost all other bilaterians has been lost in multiple lineages in favour of multiple, minicircular chromosomes with less than 37 genes on each chromosome. Minicircular mt genomes are found in six of the ten louse species examined to date and three types of minicircles were identified: heteroplasmic minicircles which coexist with full sized mt genomes (type 1); multigene chromosomes with short, simple control regions, we infer that the genome consists of several such chromosomes (type 2); and multiple, single to three gene chromosomes with large, complex control regions (type 3). Mapping minicircle types onto a phylogenetic tree of lice fails to show a pattern of their occurrence consistent with an evolutionary series of minicircle types. Analysis of the nuclear-encoded, mitochondrially-targetted genes inferred from the body louse, Pediculus, suggests that the loss of mitochondrial single-stranded binding protein (mtSSB) may be responsible for the presence of minicircles in at least species with the most derived type 3 minicircles (Pediculus, Damalinia). Minicircular mt genomes are common in lice and appear to have arisen multiple times within the group. Life history adaptive explanations which attribute minicircular mt genomes in lice to the adoption of blood-feeding in the Anoplura are not supported by this expanded data set as minicircles are found in multiple non-blood feeding louse groups but are not found in the blood-feeding genus Heterodoxus. In contrast, a mechanist explanation based on the loss of mtSSB suggests that minicircles may be selectively favoured due to the incapacity of the mt replisome to synthesize long replicative products without mtSSB and thus the loss of this gene lead to the formation of minicircles in lice.

A Protocol for Generating and Exchanging (Genome-Scale) Metabolic Resource Allocation Models.

PubMed

Reimers, Alexandra-M; Lindhorst, Henning; Waldherr, Steffen

2017-09-06

In this article, we present a protocol for generating a complete (genome-scale) metabolic resource allocation model, as well as a proposal for how to represent such models in the systems biology markup language (SBML). Such models are used to investigate enzyme levels and achievable growth rates in large-scale metabolic networks. Although the idea of metabolic resource allocation studies has been present in the field of systems biology for some years, no guidelines for generating such a model have been published up to now. This paper presents step-by-step instructions for building a (dynamic) resource allocation model, starting with prerequisites such as a genome-scale metabolic reconstruction, through building protein and noncatalytic biomass synthesis reactions and assigning turnover rates for each reaction. In addition, we explain how one can use SBML level 3 in combination with the flux balance constraints and our resource allocation modeling annotation to represent such models.

The Methanosarcina barkeri genome: comparative analysis withMethanosarcina acetivorans and Methanosarcina mazei reveals extensiverearrangement within methanosarcinal genomes

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

Maeder, Dennis L.; Anderson, Iain; Brettin, Thomas S.

2006-05-19

We report here a comparative analysis of the genome sequence of Methanosarcina barkeri with those of Methanosarcina acetivorans and Methanosarcina mazei. All three genomes share a conserved double origin of replication and many gene clusters. M. barkeri is distinguished by having an organization that is well conserved with respect to the other Methanosarcinae in the region proximal to the origin of replication with interspecies gene similarities as high as 95%. However it is disordered and marked by increased transposase frequency and decreased gene synteny and gene density in the proximal semi-genome. Of the 3680 open reading frames in M. barkeri,more » 678 had paralogs with better than 80% similarity to both M. acetivorans and M. mazei while 128 nonhypothetical orfs were unique (non-paralogous) amongst these species including a complete formate dehydrogenase operon, two genes required for N-acetylmuramic acid synthesis, a 14 gene gas vesicle cluster and a bacterial P450-specific ferredoxin reductase cluster not previously observed or characterized in this genus. A cryptic 36 kbp plasmid sequence was detected in M. barkeri that contains an orc1 gene flanked by a presumptive origin of replication consisting of 38 tandem repeats of a 143 nt motif. Three-way comparison of these genomes reveals differing mechanisms for the accrual of changes. Elongation of the large M. acetivorans is the result of multiple gene-scale insertions and duplications uniformly distributed in that genome, while M. barkeri is characterized by localized inversions associated with the loss of gene content. In contrast, the relatively short M. mazei most closely approximates the ancestral organizational state.« less

New generation pharmacogenomic tools: a SNP linkage disequilibrium Map, validated SNP assay resource, and high-throughput instrumentation system for large-scale genetic studies.

PubMed

De La Vega, Francisco M; Dailey, David; Ziegle, Janet; Williams, Julie; Madden, Dawn; Gilbert, Dennis A

2002-06-01

Since public and private efforts announced the first draft of the human genome last year, researchers have reported great numbers of single nucleotide polymorphisms (SNPs). We believe that the availability of well-mapped, quality SNP markers constitutes the gateway to a revolution in genetics and personalized medicine that will lead to better diagnosis and treatment of common complex disorders. A new generation of tools and public SNP resources for pharmacogenomic and genetic studies--specifically for candidate-gene, candidate-region, and whole-genome association studies--will form part of the new scientific landscape. This will only be possible through the greater accessibility of SNP resources and superior high-throughput instrumentation-assay systems that enable affordable, highly productive large-scale genetic studies. We are contributing to this effort by developing a high-quality linkage disequilibrium SNP marker map and an accompanying set of ready-to-use, validated SNP assays across every gene in the human genome. This effort incorporates both the public sequence and SNP data sources, and Celera Genomics' human genome assembly and enormous resource ofphysically mapped SNPs (approximately 4,000,000 unique records). This article discusses our approach and methodology for designing the map, choosing quality SNPs, designing and validating these assays, and obtaining population frequency ofthe polymorphisms. We also discuss an advanced, high-performance SNP assay chemisty--a new generation of the TaqMan probe-based, 5' nuclease assay-and high-throughput instrumentation-software system for large-scale genotyping. We provide the new SNP map and validation information, validated SNP assays and reagents, and instrumentation systems as a novel resource for genetic discoveries.

Genome-wide heterogeneity of nucleotide substitution model fit.

PubMed

Arbiza, Leonardo; Patricio, Mateus; Dopazo, Hernán; Posada, David

2011-01-01

At a genomic scale, the patterns that have shaped molecular evolution are believed to be largely heterogeneous. Consequently, comparative analyses should use appropriate probabilistic substitution models that capture the main features under which different genomic regions have evolved. While efforts have concentrated in the development and understanding of model selection techniques, no descriptions of overall relative substitution model fit at the genome level have been reported. Here, we provide a characterization of best-fit substitution models across three genomic data sets including coding regions from mammals, vertebrates, and Drosophila (24,000 alignments). According to the Akaike Information Criterion (AIC), 82 of 88 models considered were selected as best-fit models at least in one occasion, although with very different frequencies. Most parameter estimates also varied broadly among genes. Patterns found for vertebrates and Drosophila were quite similar and often more complex than those found in mammals. Phylogenetic trees derived from models in the 95% confidence interval set showed much less variance and were significantly closer to the tree estimated under the best-fit model than trees derived from models outside this interval. Although alternative criteria selected simpler models than the AIC, they suggested similar patterns. All together our results show that at a genomic scale, different gene alignments for the same set of taxa are best explained by a large variety of different substitution models and that model choice has implications on different parameter estimates including the inferred phylogenetic trees. After taking into account the differences related to sample size, our results suggest a noticeable diversity in the underlying evolutionary process. All together, we conclude that the use of model selection techniques is important to obtain consistent phylogenetic estimates from real data at a genomic scale.

Piggy: a rapid, large-scale pan-genome analysis tool for intergenic regions in bacteria.

PubMed

Thorpe, Harry A; Bayliss, Sion C; Sheppard, Samuel K; Feil, Edward J

2018-04-01

The concept of the "pan-genome," which refers to the total complement of genes within a given sample or species, is well established in bacterial genomics. Rapid and scalable pipelines are available for managing and interpreting pan-genomes from large batches of annotated assemblies. However, despite overwhelming evidence that variation in intergenic regions in bacteria can directly influence phenotypes, most current approaches for analyzing pan-genomes focus exclusively on protein-coding sequences. To address this we present Piggy, a novel pipeline that emulates Roary except that it is based only on intergenic regions. A key utility provided by Piggy is the detection of highly divergent ("switched") intergenic regions (IGRs) upstream of genes. We demonstrate the use of Piggy on large datasets of clinically important lineages of Staphylococcus aureus and Escherichia coli. For S. aureus, we show that highly divergent (switched) IGRs are associated with differences in gene expression and we establish a multilocus reference database of IGR alleles (igMLST; implemented in BIGSdb).

Addition of a breeding database in the Genome Database for Rosaceae

PubMed Central

Evans, Kate; Jung, Sook; Lee, Taein; Brutcher, Lisa; Cho, Ilhyung; Peace, Cameron; Main, Dorrie

2013-01-01

Breeding programs produce large datasets that require efficient management systems to keep track of performance, pedigree, geographical and image-based data. With the development of DNA-based screening technologies, more breeding programs perform genotyping in addition to phenotyping for performance evaluation. The integration of breeding data with other genomic and genetic data is instrumental for the refinement of marker-assisted breeding tools, enhances genetic understanding of important crop traits and maximizes access and utility by crop breeders and allied scientists. Development of new infrastructure in the Genome Database for Rosaceae (GDR) was designed and implemented to enable secure and efficient storage, management and analysis of large datasets from the Washington State University apple breeding program and subsequently expanded to fit datasets from other Rosaceae breeders. The infrastructure was built using the software Chado and Drupal, making use of the Natural Diversity module to accommodate large-scale phenotypic and genotypic data. Breeders can search accessions within the GDR to identify individuals with specific trait combinations. Results from Search by Parentage lists individuals with parents in common and results from Individual Variety pages link to all data available on each chosen individual including pedigree, phenotypic and genotypic information. Genotypic data are searchable by markers and alleles; results are linked to other pages in the GDR to enable the user to access tools such as GBrowse and CMap. This breeding database provides users with the opportunity to search datasets in a fully targeted manner and retrieve and compare performance data from multiple selections, years and sites, and to output the data needed for variety release publications and patent applications. The breeding database facilitates efficient program management. Storing publicly available breeding data in a database together with genomic and genetic data will further accelerate the cross-utilization of diverse data types by researchers from various disciplines. Database URL: http://www.rosaceae.org/breeders_toolbox PMID:24247530

Addition of a breeding database in the Genome Database for Rosaceae.

PubMed

Evans, Kate; Jung, Sook; Lee, Taein; Brutcher, Lisa; Cho, Ilhyung; Peace, Cameron; Main, Dorrie

2013-01-01

Breeding programs produce large datasets that require efficient management systems to keep track of performance, pedigree, geographical and image-based data. With the development of DNA-based screening technologies, more breeding programs perform genotyping in addition to phenotyping for performance evaluation. The integration of breeding data with other genomic and genetic data is instrumental for the refinement of marker-assisted breeding tools, enhances genetic understanding of important crop traits and maximizes access and utility by crop breeders and allied scientists. Development of new infrastructure in the Genome Database for Rosaceae (GDR) was designed and implemented to enable secure and efficient storage, management and analysis of large datasets from the Washington State University apple breeding program and subsequently expanded to fit datasets from other Rosaceae breeders. The infrastructure was built using the software Chado and Drupal, making use of the Natural Diversity module to accommodate large-scale phenotypic and genotypic data. Breeders can search accessions within the GDR to identify individuals with specific trait combinations. Results from Search by Parentage lists individuals with parents in common and results from Individual Variety pages link to all data available on each chosen individual including pedigree, phenotypic and genotypic information. Genotypic data are searchable by markers and alleles; results are linked to other pages in the GDR to enable the user to access tools such as GBrowse and CMap. This breeding database provides users with the opportunity to search datasets in a fully targeted manner and retrieve and compare performance data from multiple selections, years and sites, and to output the data needed for variety release publications and patent applications. The breeding database facilitates efficient program management. Storing publicly available breeding data in a database together with genomic and genetic data will further accelerate the cross-utilization of diverse data types by researchers from various disciplines. Database URL: http://www.rosaceae.org/breeders_toolbox.

A high resolution atlas of gene expression in the domestic sheep (Ovis aries)

PubMed Central

Farquhar, Iseabail L.; Young, Rachel; Lefevre, Lucas; Pridans, Clare; Tsang, Hiu G.; Afrasiabi, Cyrus; Watson, Mick; Whitelaw, C. Bruce; Freeman, Tom C.; Archibald, Alan L.; Hume, David A.

2017-01-01

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of ‘guilt by association’ was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages. PMID:28915238

A high resolution atlas of gene expression in the domestic sheep (Ovis aries).

PubMed

Clark, Emily L; Bush, Stephen J; McCulloch, Mary E B; Farquhar, Iseabail L; Young, Rachel; Lefevre, Lucas; Pridans, Clare; Tsang, Hiu G; Wu, Chunlei; Afrasiabi, Cyrus; Watson, Mick; Whitelaw, C Bruce; Freeman, Tom C; Summers, Kim M; Archibald, Alan L; Hume, David A

2017-09-01

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of 'guilt by association' was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages.

Fine-scale population structure and the era of next-generation sequencing.

PubMed

Henn, Brenna M; Gravel, Simon; Moreno-Estrada, Andres; Acevedo-Acevedo, Suehelay; Bustamante, Carlos D

2010-10-15

Fine-scale population structure characterizes most continents and is especially pronounced in non-cosmopolitan populations. Roughly half of the world's population remains non-cosmopolitan and even populations within cities often assort along ethnic and linguistic categories. Barriers to random mating can be ecologically extreme, such as the Sahara Desert, or cultural, such as the Indian caste system. In either case, subpopulations accumulate genetic differences if the barrier is maintained over multiple generations. Genome-wide polymorphism data, initially with only a few hundred autosomal microsatellites, have clearly established differences in allele frequency not only among continental regions, but also within continents and within countries. We review recent evidence from the analysis of genome-wide polymorphism data for genetic boundaries delineating human population structure and the main demographic and genomic processes shaping variation, and discuss the implications of population structure for the distribution and discovery of disease-causing genetic variants, in the light of the imminent availability of sequencing data for a multitude of diverse human genomes.

An improved model for whole genome phylogenetic analysis by Fourier transform.

PubMed

Yin, Changchuan; Yau, Stephen S-T

2015-10-07

DNA sequence similarity comparison is one of the major steps in computational phylogenetic studies. The sequence comparison of closely related DNA sequences and genomes is usually performed by multiple sequence alignments (MSA). While the MSA method is accurate for some types of sequences, it may produce incorrect results when DNA sequences undergone rearrangements as in many bacterial and viral genomes. It is also limited by its computational complexity for comparing large volumes of data. Previously, we proposed an alignment-free method that exploits the full information contents of DNA sequences by Discrete Fourier Transform (DFT), but still with some limitations. Here, we present a significantly improved method for the similarity comparison of DNA sequences by DFT. In this method, we map DNA sequences into 2-dimensional (2D) numerical sequences and then apply DFT to transform the 2D numerical sequences into frequency domain. In the 2D mapping, the nucleotide composition of a DNA sequence is a determinant factor and the 2D mapping reduces the nucleotide composition bias in distance measure, and thus improving the similarity measure of DNA sequences. To compare the DFT power spectra of DNA sequences with different lengths, we propose an improved even scaling algorithm to extend shorter DFT power spectra to the longest length of the underlying sequences. After the DFT power spectra are evenly scaled, the spectra are in the same dimensionality of the Fourier frequency space, then the Euclidean distances of full Fourier power spectra of the DNA sequences are used as the dissimilarity metrics. The improved DFT method, with increased computational performance by 2D numerical representation, can be applicable to any DNA sequences of different length ranges. We assess the accuracy of the improved DFT similarity measure in hierarchical clustering of different DNA sequences including simulated and real datasets. The method yields accurate and reliable phylogenetic trees and demonstrates that the improved DFT dissimilarity measure is an efficient and effective similarity measure of DNA sequences. Due to its high efficiency and accuracy, the proposed DFT similarity measure is successfully applied on phylogenetic analysis for individual genes and large whole bacterial genomes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Improved technique that allows the performance of large-scale SNP genotyping on DNA immobilized by FTA technology.

PubMed

He, Hongbin; Argiro, Laurent; Dessein, Helia; Chevillard, Christophe

2007-01-01

FTA technology is a novel method designed to simplify the collection, shipment, archiving and purification of nucleic acids from a wide variety of biological sources. The number of punches that can normally be obtained from a single specimen card are often however, insufficient for the testing of the large numbers of loci required to identify genetic factors that control human susceptibility or resistance to multifactorial diseases. In this study, we propose an improved technique to perform large-scale SNP genotyping. We applied a whole genome amplification method to amplify DNA from buccal cell samples stabilized using FTA technology. The results show that using the improved technique it is possible to perform up to 15,000 genotypes from one buccal cell sample. Furthermore, the procedure is simple. We consider this improved technique to be a promising methods for performing large-scale SNP genotyping because the FTA technology simplifies the collection, shipment, archiving and purification of DNA, while whole genome amplification of FTA card bound DNA produces sufficient material for the determination of thousands of SNP genotypes.

Integrating environmental covariates and crop modeling into the genomic selection framework to predict genotype by environment interactions.

PubMed

Heslot, Nicolas; Akdemir, Deniz; Sorrells, Mark E; Jannink, Jean-Luc

2014-02-01

Development of models to predict genotype by environment interactions, in unobserved environments, using environmental covariates, a crop model and genomic selection. Application to a large winter wheat dataset. Genotype by environment interaction (G*E) is one of the key issues when analyzing phenotypes. The use of environment data to model G*E has long been a subject of interest but is limited by the same problems as those addressed by genomic selection methods: a large number of correlated predictors each explaining a small amount of the total variance. In addition, non-linear responses of genotypes to stresses are expected to further complicate the analysis. Using a crop model to derive stress covariates from daily weather data for predicted crop development stages, we propose an extension of the factorial regression model to genomic selection. This model is further extended to the marker level, enabling the modeling of quantitative trait loci (QTL) by environment interaction (Q*E), on a genome-wide scale. A newly developed ensemble method, soft rule fit, was used to improve this model and capture non-linear responses of QTL to stresses. The method is tested using a large winter wheat dataset, representative of the type of data available in a large-scale commercial breeding program. Accuracy in predicting genotype performance in unobserved environments for which weather data were available increased by 11.1% on average and the variability in prediction accuracy decreased by 10.8%. By leveraging agronomic knowledge and the large historical datasets generated by breeding programs, this new model provides insight into the genetic architecture of genotype by environment interactions and could predict genotype performance based on past and future weather scenarios.

A resource of large-scale molecular markers for monitoring Agropyron cristatum chromatin introgression in wheat background based on transcriptome sequences.

PubMed

Zhang, Jinpeng; Liu, Weihua; Lu, Yuqing; Liu, Qunxing; Yang, Xinming; Li, Xiuquan; Li, Lihui

2017-09-20

Agropyron cristatum is a wild grass of the tribe Triticeae and serves as a gene donor for wheat improvement. However, very few markers can be used to monitor A. cristatum chromatin introgressions in wheat. Here, we reported a resource of large-scale molecular markers for tracking alien introgressions in wheat based on transcriptome sequences. By aligning A. cristatum unigenes with the Chinese Spring reference genome sequences, we designed 9602 A. cristatum expressed sequence tag-sequence-tagged site (EST-STS) markers for PCR amplification and experimental screening. As a result, 6063 polymorphic EST-STS markers were specific for the A. cristatum P genome in the single-receipt wheat background. A total of 4956 randomly selected polymorphic EST-STS markers were further tested in eight wheat variety backgrounds, and 3070 markers displaying stable and polymorphic amplification were validated. These markers covered more than 98% of the A. cristatum genome, and the marker distribution density was approximately 1.28 cM. An application case of all EST-STS markers was validated on the A. cristatum 6 P chromosome. These markers were successfully applied in the tracking of alien A. cristatum chromatin. Altogether, this study provided a universal method of large-scale molecular marker development to monitor wild relative chromatin in wheat.

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

PubMed

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

2016-07-01

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

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

Mammalian Synthetic Biology: Time for Big MACs.

PubMed

Martella, Andrea; Pollard, Steven M; Dai, Junbiao; Cai, Yizhi

2016-10-21

The enabling technologies of synthetic biology are opening up new opportunities for engineering and enhancement of mammalian cells. This will stimulate diverse applications in many life science sectors such as regenerative medicine, development of biosensing cell lines, therapeutic protein production, and generation of new synthetic genetic regulatory circuits. Harnessing the full potential of these new engineering-based approaches requires the design and assembly of large DNA constructs-potentially up to chromosome scale-and the effective delivery of these large DNA payloads to the host cell. Random integration of large transgenes, encoding therapeutic proteins or genetic circuits into host chromosomes, has several drawbacks such as risks of insertional mutagenesis, lack of control over transgene copy-number and position-specific effects; these can compromise the intended functioning of genetic circuits. The development of a system orthogonal to the endogenous genome is therefore beneficial. Mammalian artificial chromosomes (MACs) are functional, add-on chromosomal elements, which behave as normal chromosomes-being replicating and portioned to daughter cells at each cell division. They are deployed as useful gene expression vectors as they remain independent from the host genome. MACs are maintained as a single-copy and can accommodate multiple gene expression cassettes of, in theory, unlimited DNA size (MACs up to 10 megabases have been constructed). MACs therefore enabled control over ectopic gene expression and represent an excellent platform to rapidly prototype and characterize novel synthetic gene circuits without recourse to engineering the host genome. This review describes the obstacles synthetic biologists face when working with mammalian systems and how the development of improved MACs can overcome these-particularly given the spectacular advances in DNA synthesis and assembly that are fuelling this research area.

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...

Usage Patterns of Open Genomic Data

ERIC Educational Resources Information Center

Xia, Jingfeng; Liu, Ying

2013-01-01

This paper uses Genome Expression Omnibus (GEO), a data repository in biomedical sciences, to examine the usage patterns of open data repositories. It attempts to identify the degree of recognition of data reuse value and understand how e-science has impacted a large-scale scholarship. By analyzing a list of 1,211 publications that cite GEO data…

Evidence of evolutionary history and selective sweeps in the genome of Meishan pig reveals its genetic and phenotypic characterization

USDA-ARS?s Scientific Manuscript database

Meishan is a famous Chinese indigenous pig breed known for its extremely high fecundity. To explore if Meishan has unique evolutionary process and genome characteristics differing from other pig breeds, we systematically analyzed its genetic divergence, and demographic history by large-scale reseque...

An integrative and applicable phylogenetic footprinting framework for cis-regulatory motifs identification in prokaryotic genomes.

PubMed

Liu, Bingqiang; Zhang, Hanyuan; Zhou, Chuan; Li, Guojun; Fennell, Anne; Wang, Guanghui; Kang, Yu; Liu, Qi; Ma, Qin

2016-08-09

Phylogenetic footprinting is an important computational technique for identifying cis-regulatory motifs in orthologous regulatory regions from multiple genomes, as motifs tend to evolve slower than their surrounding non-functional sequences. Its application, however, has several difficulties for optimizing the selection of orthologous data and reducing the false positives in motif prediction. Here we present an integrative phylogenetic footprinting framework for accurate motif predictions in prokaryotic genomes (MP(3)). The framework includes a new orthologous data preparation procedure, an additional promoter scoring and pruning method and an integration of six existing motif finding algorithms as basic motif search engines. Specifically, we collected orthologous genes from available prokaryotic genomes and built the orthologous regulatory regions based on sequence similarity of promoter regions. This procedure made full use of the large-scale genomic data and taxonomy information and filtered out the promoters with limited contribution to produce a high quality orthologous promoter set. The promoter scoring and pruning is implemented through motif voting by a set of complementary predicting tools that mine as many motif candidates as possible and simultaneously eliminate the effect of random noise. We have applied the framework to Escherichia coli k12 genome and evaluated the prediction performance through comparison with seven existing programs. This evaluation was systematically carried out at the nucleotide and binding site level, and the results showed that MP(3) consistently outperformed other popular motif finding tools. We have integrated MP(3) into our motif identification and analysis server DMINDA, allowing users to efficiently identify and analyze motifs in 2,072 completely sequenced prokaryotic genomes. The performance evaluation indicated that MP(3) is effective for predicting regulatory motifs in prokaryotic genomes. Its application may enhance progress in elucidating transcription regulation mechanism, thus provide benefit to the genomic research community and prokaryotic genome researchers in particular.

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

BLAST Ring Image Generator (BRIG): simple prokaryote genome comparisons

PubMed Central

2011-01-01

Background Visualisation of genome comparisons is invaluable for helping to determine genotypic differences between closely related prokaryotes. New visualisation and abstraction methods are required in order to improve the validation, interpretation and communication of genome sequence information; especially with the increasing amount of data arising from next-generation sequencing projects. Visualising a prokaryote genome as a circular image has become a powerful means of displaying informative comparisons of one genome to a number of others. Several programs, imaging libraries and internet resources already exist for this purpose, however, most are either limited in the number of comparisons they can show, are unable to adequately utilise draft genome sequence data, or require a knowledge of command-line scripting for implementation. Currently, there is no freely available desktop application that enables users to rapidly visualise comparisons between hundreds of draft or complete genomes in a single image. Results BLAST Ring Image Generator (BRIG) can generate images that show multiple prokaryote genome comparisons, without an arbitrary limit on the number of genomes compared. The output image shows similarity between a central reference sequence and other sequences as a set of concentric rings, where BLAST matches are coloured on a sliding scale indicating a defined percentage identity. Images can also include draft genome assembly information to show read coverage, assembly breakpoints and collapsed repeats. In addition, BRIG supports the mapping of unassembled sequencing reads against one or more central reference sequences. Many types of custom data and annotations can be shown using BRIG, making it a versatile approach for visualising a range of genomic comparison data. BRIG is readily accessible to any user, as it assumes no specialist computational knowledge and will perform all required file parsing and BLAST comparisons automatically. Conclusions There is a clear need for a user-friendly program that can produce genome comparisons for a large number of prokaryote genomes with an emphasis on rapidly utilising unfinished or unassembled genome data. Here we present BRIG, a cross-platform application that enables the interactive generation of comparative genomic images via a simple graphical-user interface. BRIG is freely available for all operating systems at http://sourceforge.net/projects/brig/. PMID:21824423

BLAST Ring Image Generator (BRIG): simple prokaryote genome comparisons.

PubMed

Alikhan, Nabil-Fareed; Petty, Nicola K; Ben Zakour, Nouri L; Beatson, Scott A

2011-08-08

Visualisation of genome comparisons is invaluable for helping to determine genotypic differences between closely related prokaryotes. New visualisation and abstraction methods are required in order to improve the validation, interpretation and communication of genome sequence information; especially with the increasing amount of data arising from next-generation sequencing projects. Visualising a prokaryote genome as a circular image has become a powerful means of displaying informative comparisons of one genome to a number of others. Several programs, imaging libraries and internet resources already exist for this purpose, however, most are either limited in the number of comparisons they can show, are unable to adequately utilise draft genome sequence data, or require a knowledge of command-line scripting for implementation. Currently, there is no freely available desktop application that enables users to rapidly visualise comparisons between hundreds of draft or complete genomes in a single image. BLAST Ring Image Generator (BRIG) can generate images that show multiple prokaryote genome comparisons, without an arbitrary limit on the number of genomes compared. The output image shows similarity between a central reference sequence and other sequences as a set of concentric rings, where BLAST matches are coloured on a sliding scale indicating a defined percentage identity. Images can also include draft genome assembly information to show read coverage, assembly breakpoints and collapsed repeats. In addition, BRIG supports the mapping of unassembled sequencing reads against one or more central reference sequences. Many types of custom data and annotations can be shown using BRIG, making it a versatile approach for visualising a range of genomic comparison data. BRIG is readily accessible to any user, as it assumes no specialist computational knowledge and will perform all required file parsing and BLAST comparisons automatically. There is a clear need for a user-friendly program that can produce genome comparisons for a large number of prokaryote genomes with an emphasis on rapidly utilising unfinished or unassembled genome data. Here we present BRIG, a cross-platform application that enables the interactive generation of comparative genomic images via a simple graphical-user interface. BRIG is freely available for all operating systems at http://sourceforge.net/projects/brig/.

Accuracy improvement in laser stripe extraction for large-scale triangulation scanning measurement system

NASA Astrophysics Data System (ADS)

Zhang, Yang; Liu, Wei; Li, Xiaodong; Yang, Fan; Gao, Peng; Jia, Zhenyuan

2015-10-01

Large-scale triangulation scanning measurement systems are widely used to measure the three-dimensional profile of large-scale components and parts. The accuracy and speed of the laser stripe center extraction are essential for guaranteeing the accuracy and efficiency of the measuring system. However, in the process of large-scale measurement, multiple factors can cause deviation of the laser stripe center, including the spatial light intensity distribution, material reflectivity characteristics, and spatial transmission characteristics. A center extraction method is proposed for improving the accuracy of the laser stripe center extraction based on image evaluation of Gaussian fitting structural similarity and analysis of the multiple source factors. First, according to the features of the gray distribution of the laser stripe, evaluation of the Gaussian fitting structural similarity is estimated to provide a threshold value for center compensation. Then using the relationships between the gray distribution of the laser stripe and the multiple source factors, a compensation method of center extraction is presented. Finally, measurement experiments for a large-scale aviation composite component are carried out. The experimental results for this specific implementation verify the feasibility of the proposed center extraction method and the improved accuracy for large-scale triangulation scanning measurements.

Next-Generation Sequencing: The Translational Medicine Approach from “Bench to Bedside to Population”

PubMed Central

Beigh, Mohammad Muzafar

2016-01-01

Humans have predicted the relationship between heredity and diseases for a long time. Only in the beginning of the last century, scientists begin to discover the connotations between different genes and disease phenotypes. Recent trends in next-generation sequencing (NGS) technologies have brought a great momentum in biomedical research that in turn has remarkably augmented our basic understanding of human biology and its associated diseases. State-of-the-art next generation biotechnologies have started making huge strides in our current understanding of mechanisms of various chronic illnesses like cancers, metabolic disorders, neurodegenerative anomalies, etc. We are experiencing a renaissance in biomedical research primarily driven by next generation biotechnologies like genomics, transcriptomics, proteomics, metabolomics, lipidomics etc. Although genomic discoveries are at the forefront of next generation omics technologies, however, their implementation into clinical arena had been painstakingly slow mainly because of high reaction costs and unavailability of requisite computational tools for large-scale data analysis. However rapid innovations and steadily lowering cost of sequence-based chemistries along with the development of advanced bioinformatics tools have lately prompted launching and implementation of large-scale massively parallel genome sequencing programs in different fields ranging from medical genetics, infectious biology, agriculture sciences etc. Recent advances in large-scale omics-technologies is bringing healthcare research beyond the traditional “bench to bedside” approach to more of a continuum that will include improvements, in public healthcare and will be primarily based on predictive, preventive, personalized, and participatory medicine approach (P4). Recent large-scale research projects in genetic and infectious disease biology have indicated that massively parallel whole-genome/whole-exome sequencing, transcriptome analysis, and other functional genomic tools can reveal large number of unique functional elements and/or markers that otherwise would be undetected by traditional sequencing methodologies. Therefore, latest trends in the biomedical research is giving birth to the new branch in medicine commonly referred to as personalized and/or precision medicine. Developments in the post-genomic era are believed to completely restructure the present clinical pattern of disease prevention and treatment as well as methods of diagnosis and prognosis. The next important step in the direction of the precision/personalized medicine approach should be its early adoption in clinics for future medical interventions. Consequently, in coming year’s next generation biotechnologies will reorient medical practice more towards disease prediction and prevention approaches rather than curing them at later stages of their development and progression, even at wider population level(s) for general public healthcare system. PMID:28930123

PLEXdb: Gene expression resources for plants and plant pathogens

USDA-ARS?s Scientific Manuscript database

PLEXdb (Plant Expression Database), in partnership with community databases, supports comparisons of gene expression across multiple plant and pathogen species, promoting individuals and/or consortia to upload genome-scale data sets to contrast them to previously archived data. These analyses facili...

Phylogenomics of the carrot genus (Daucus, Apiaceae)

USDA-ARS?s Scientific Manuscript database

Molecular phylogenetics of genome-scale data sets (phylogenomics) often produces phylogenetic trees with unprecedented resolution. We here explore the utility of multiple nuclear orthologs for the taxonomic resolution of a wide variety of Daucus species and outgroups. We studied the phylogeny of 89 ...

CORALINA: a universal method for the generation of gRNA libraries for CRISPR-based screening.

PubMed

Köferle, Anna; Worf, Karolina; Breunig, Christopher; Baumann, Valentin; Herrero, Javier; Wiesbeck, Maximilian; Hutter, Lukas H; Götz, Magdalena; Fuchs, Christiane; Beck, Stephan; Stricker, Stefan H

2016-11-14

The bacterial CRISPR system is fast becoming the most popular genetic and epigenetic engineering tool due to its universal applicability and adaptability. The desire to deploy CRISPR-based methods in a large variety of species and contexts has created an urgent need for the development of easy, time- and cost-effective methods enabling large-scale screening approaches. Here we describe CORALINA (comprehensive gRNA library generation through controlled nuclease activity), a method for the generation of comprehensive gRNA libraries for CRISPR-based screens. CORALINA gRNA libraries can be derived from any source of DNA without the need of complex oligonucleotide synthesis. We show the utility of CORALINA for human and mouse genomic DNA, its reproducibility in covering the most relevant genomic features including regulatory, coding and non-coding sequences and confirm the functionality of CORALINA generated gRNAs. The simplicity and cost-effectiveness make CORALINA suitable for any experimental system. The unprecedented sequence complexities obtainable with CORALINA libraries are a necessary pre-requisite for less biased large scale genomic and epigenomic screens.

Divergent copies of the large inverted repeat in the chloroplast genomes of ulvophycean green algae.

PubMed

Turmel, Monique; Otis, Christian; Lemieux, Claude

2017-04-20

The chloroplast genomes of many algae and almost all land plants carry two identical copies of a large inverted repeat (IR) sequence that can pair for flip-flop recombination and undergo expansion/contraction. Although the IR has been lost multiple times during the evolution of the green algae, the underlying mechanisms are still largely unknown. A recent comparison of IR-lacking and IR-containing chloroplast genomes of chlorophytes from the Ulvophyceae (Ulotrichales) suggested that differential elimination of genes from the IR copies might lead to IR loss. To gain deeper insights into the evolutionary history of the chloroplast genome in the Ulvophyceae, we analyzed the genomes of Ignatius tetrasporus and Pseudocharacium americanum (Ignatiales, an order not previously sampled), Dangemannia microcystis (Oltmannsiellopsidales), Pseudoneochloris marina (Ulvales) and also Chamaetrichon capsulatum and Trichosarcina mucosa (Ulotrichales). Our comparison of these six chloroplast genomes with those previously reported for nine ulvophyceans revealed unsuspected variability. All newly examined genomes feature an IR, but remarkably, the copies of the IR present in the Ignatiales, Pseudoneochloris, and Chamaetrichon diverge in sequence, with the tRNA genes from the rRNA operon missing in one IR copy. The implications of this unprecedented finding for the mechanism of IR loss and flip-flop recombination are discussed.

Revealing Less Derived Nature of Cartilaginous Fish Genomes with Their Evolutionary Time Scale Inferred with Nuclear Genes

PubMed Central

Renz, Adina J.; Meyer, Axel; Kuraku, Shigehiro

2013-01-01

Cartilaginous fishes, divided into Holocephali (chimaeras) and Elasmoblanchii (sharks, rays and skates), occupy a key phylogenetic position among extant vertebrates in reconstructing their evolutionary processes. Their accurate evolutionary time scale is indispensable for better understanding of the relationship between phenotypic and molecular evolution of cartilaginous fishes. However, our current knowledge on the time scale of cartilaginous fish evolution largely relies on estimates using mitochondrial DNA sequences. In this study, making the best use of the still partial, but large-scale sequencing data of cartilaginous fish species, we estimate the divergence times between the major cartilaginous fish lineages employing nuclear genes. By rigorous orthology assessment based on available genomic and transcriptomic sequence resources for cartilaginous fishes, we selected 20 protein-coding genes in the nuclear genome, spanning 2973 amino acid residues. Our analysis based on the Bayesian inference resulted in the mean divergence time of 421 Ma, the late Silurian, for the Holocephali-Elasmobranchii split, and 306 Ma, the late Carboniferous, for the split between sharks and rays/skates. By applying these results and other documented divergence times, we measured the relative evolutionary rate of the Hox A cluster sequences in the cartilaginous fish lineages, which resulted in a lower substitution rate with a factor of at least 2.4 in comparison to tetrapod lineages. The obtained time scale enables mapping phenotypic and molecular changes in a quantitative framework. It is of great interest to corroborate the less derived nature of cartilaginous fish at the molecular level as a genome-wide phenomenon. PMID:23825540

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

PubMed

Renz, Adina J; Meyer, Axel; Kuraku, Shigehiro

2013-01-01

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

Construction of a large-scale Burkholderia cenocepacia J2315 transposon mutant library

NASA Astrophysics Data System (ADS)

Wong, Yee-Chin; Pain, Arnab; Nathan, Sheila

2014-09-01

Burkholderia cenocepacia, a pathogenic member of the Burkholderia cepacia complex (Bcc), has emerged as a significant threat towards cystic fibrosis patients, where infection often leads to the fatal clinical manifestation known as cepacia syndrome. Many studies have investigated the pathogenicity of B. cenocepacia as well as its ability to become highly resistant towards many of the antibiotics currently in use. In addition, studies have also been undertaken to understand the pathogen's capacity to adapt and survive in a broad range of environments. Transposon based mutagenesis has been widely used in creating insertional knock-out mutants and coupled with recent advances in sequencing technology, robust tools to study gene function in a genome-wide manner have been developed based on the assembly of saturated transposon mutant libraries. In this study, we describe the construction of a large-scale library of B. cenocepacia transposon mutants. To create transposon mutants of B. cenocepacia strain J2315, electrocompetent bacteria were electrotransformed with the EZ-Tn5 transposome. Tetracyline resistant colonies were harvested off selective agar and pooled. Mutants were generated in multiple batches with each batch consisting of ˜20,000 to 40,000 mutants. Transposon insertion was validated by PCR amplification of the transposon region. In conclusion, a saturated B. cenocepacia J2315 transposon mutant library with an estimated total number of 500,000 mutants was successfully constructed. This mutant library can now be further exploited as a genetic tool to assess the function of every gene in the genome, facilitating the discovery of genes important for bacterial survival and adaptation, as well as virulence.

Accuracy of genomic breeding values in multibreed beef cattle populations derived from deregressed breeding values and phenotypes.

PubMed

Weber, K L; Thallman, R M; Keele, J W; Snelling, W M; Bennett, G L; Smith, T P L; McDaneld, T G; Allan, M F; Van Eenennaam, A L; Kuehn, L A

2012-12-01

Genomic selection involves the assessment of genetic merit through prediction equations that allocate genetic variation with dense marker genotypes. It has the potential to provide accurate breeding values for selection candidates at an early age and facilitate selection for expensive or difficult to measure traits. Accurate across-breed prediction would allow genomic selection to be applied on a larger scale in the beef industry, but the limited availability of large populations for the development of prediction equations has delayed researchers from providing genomic predictions that are accurate across multiple beef breeds. In this study, the accuracy of genomic predictions for 6 growth and carcass traits were derived and evaluated using 2 multibreed beef cattle populations: 3,358 crossbred cattle of the U.S. Meat Animal Research Center Germplasm Evaluation Program (USMARC_GPE) and 1,834 high accuracy bull sires of the 2,000 Bull Project (2000_BULL) representing influential breeds in the U.S. beef cattle industry. The 2000_BULL EPD were deregressed, scaled, and weighted to adjust for between- and within-breed heterogeneous variance before use in training and validation. Molecular breeding values (MBV) trained in each multibreed population and in Angus and Hereford purebred sires of 2000_BULL were derived using the GenSel BayesCπ function (Fernando and Garrick, 2009) and cross-validated. Less than 10% of large effect loci were shared between prediction equations trained on (USMARC_GPE) relative to 2000_BULL although locus effects were moderately to highly correlated for most traits and the traits themselves were highly correlated between populations. Prediction of MBV accuracy was low and variable between populations. For growth traits, MBV accounted for up to 18% of genetic variation in a pooled, multibreed analysis and up to 28% in single breeds. For carcass traits, MBV explained up to 8% of genetic variation in a pooled, multibreed analysis and up to 42% in single breeds. Prediction equations trained in multibreed populations were more accurate for Angus and Hereford subpopulations because those were the breeds most highly represented in the training populations. Accuracies were less for prediction equations trained in a single breed due to the smaller number of records derived from a single breed in the training populations.

A new method to cluster genomes based on cumulative Fourier power spectrum.

PubMed

Dong, Rui; Zhu, Ziyue; Yin, Changchuan; He, Rong L; Yau, Stephen S-T

2018-06-20

Analyzing phylogenetic relationships using mathematical methods has always been of importance in bioinformatics. Quantitative research may interpret the raw biological data in a precise way. Multiple Sequence Alignment (MSA) is used frequently to analyze biological evolutions, but is very time-consuming. When the scale of data is large, alignment methods cannot finish calculation in reasonable time. Therefore, we present a new method using moments of cumulative Fourier power spectrum in clustering the DNA sequences. Each sequence is translated into a vector in Euclidean space. Distances between the vectors can reflect the relationships between sequences. The mapping between the spectra and moment vector is one-to-one, which means that no information is lost in the power spectra during the calculation. We cluster and classify several datasets including Influenza A, primates, and human rhinovirus (HRV) datasets to build up the phylogenetic trees. Results show that the new proposed cumulative Fourier power spectrum is much faster and more accurately than MSA and another alignment-free method known as k-mer. The research provides us new insights in the study of phylogeny, evolution, and efficient DNA comparison algorithms for large genomes. The computer programs of the cumulative Fourier power spectrum are available at GitHub (https://github.com/YaulabTsinghua/cumulative-Fourier-power-spectrum). Copyright © 2018. Published by Elsevier B.V.

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.

GenomeVx: simple web-based creation of editable circular chromosome maps.

PubMed

Conant, Gavin C; Wolfe, Kenneth H

2008-03-15

We describe GenomeVx, a web-based tool for making editable, publication-quality, maps of mitochondrial and chloroplast genomes and of large plasmids. These maps show the location of genes and chromosomal features as well as a position scale. The program takes as input either raw feature positions or GenBank records. In the latter case, features are automatically extracted and colored, an example of which is given. Output is in the Adobe Portable Document Format (PDF) and can be edited by programs such as Adobe Illustrator. GenomeVx is available at http://wolfe.gen.tcd.ie/GenomeVx

RSAT matrix-clustering: dynamic exploration and redundancy reduction of transcription factor binding motif collections

PubMed Central

Jaeger, Sébastien; Thieffry, Denis

2017-01-01

Abstract Transcription factor (TF) databases contain multitudes of binding motifs (TFBMs) from various sources, from which non-redundant collections are derived by manual curation. The advent of high-throughput methods stimulated the production of novel collections with increasing numbers of motifs. Meta-databases, built by merging these collections, contain redundant versions, because available tools are not suited to automatically identify and explore biologically relevant clusters among thousands of motifs. Motif discovery from genome-scale data sets (e.g. ChIP-seq) also produces redundant motifs, hampering the interpretation of results. We present matrix-clustering, a versatile tool that clusters similar TFBMs into multiple trees, and automatically creates non-redundant TFBM collections. A feature unique to matrix-clustering is its dynamic visualisation of aligned TFBMs, and its capability to simultaneously treat multiple collections from various sources. We demonstrate that matrix-clustering considerably simplifies the interpretation of combined results from multiple motif discovery tools, and highlights biologically relevant variations of similar motifs. We also ran a large-scale application to cluster ∼11 000 motifs from 24 entire databases, showing that matrix-clustering correctly groups motifs belonging to the same TF families, and drastically reduced motif redundancy. matrix-clustering is integrated within the RSAT suite (http://rsat.eu/), accessible through a user-friendly web interface or command-line for its integration in pipelines. PMID:28591841

Comparison of the genomic sequence of the microminipig, a novel breed of swine, with the genomic database for conventional pig.

PubMed

Miura, Naoki; Kucho, Ken-Ichi; Noguchi, Michiko; Miyoshi, Noriaki; Uchiumi, Toshiki; Kawaguchi, Hiroaki; Tanimoto, Akihide

2014-01-01

The microminipig, which weighs less than 10 kg at an early stage of maturity, has been reported as a potential experimental model animal. Its extremely small size and other distinct characteristics suggest the possibility of a number of differences between the genome of the microminipig and that of conventional pigs. In this study, we analyzed the genomes of two healthy microminipigs using a next-generation sequencer SOLiD™ system. We then compared the obtained genomic sequences with a genomic database for the domestic pig (Sus scrofa). The mapping coverage of sequenced tag from the microminipig to conventional pig genomic sequences was greater than 96% and we detected no clear, substantial genomic variance from these data. The results may indicate that the distinct characteristics of the microminipig derive from small-scale alterations in the genome, such as Single Nucleotide Polymorphisms or translational modifications, rather than large-scale deletion or insertion polymorphisms. Further investigation of the entire genomic sequence of the microminipig with methods enabling deeper coverage is required to elucidate the genetic basis of its distinct phenotypic traits. Copyright © 2014 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

BLOOM: BLoom filter based oblivious outsourced matchings.

PubMed

Ziegeldorf, Jan Henrik; Pennekamp, Jan; Hellmanns, David; Schwinger, Felix; Kunze, Ike; Henze, Martin; Hiller, Jens; Matzutt, Roman; Wehrle, Klaus

2017-07-26

Whole genome sequencing has become fast, accurate, and cheap, paving the way towards the large-scale collection and processing of human genome data. Unfortunately, this dawning genome era does not only promise tremendous advances in biomedical research but also causes unprecedented privacy risks for the many. Handling storage and processing of large genome datasets through cloud services greatly aggravates these concerns. Current research efforts thus investigate the use of strong cryptographic methods and protocols to implement privacy-preserving genomic computations. We propose FHE-BLOOM and PHE-BLOOM, two efficient approaches for genetic disease testing using homomorphically encrypted Bloom filters. Both approaches allow the data owner to securely outsource storage and computation to an untrusted cloud. FHE-BLOOM is fully secure in the semi-honest model while PHE-BLOOM slightly relaxes security guarantees in a trade-off for highly improved performance. We implement and evaluate both approaches on a large dataset of up to 50 patient genomes each with up to 1000000 variations (single nucleotide polymorphisms). For both implementations, overheads scale linearly in the number of patients and variations, while PHE-BLOOM is faster by at least three orders of magnitude. For example, testing disease susceptibility of 50 patients with 100000 variations requires only a total of 308.31 s (σ=8.73 s) with our first approach and a mere 0.07 s (σ=0.00 s) with the second. We additionally discuss security guarantees of both approaches and their limitations as well as possible extensions towards more complex query types, e.g., fuzzy or range queries. Both approaches handle practical problem sizes efficiently and are easily parallelized to scale with the elastic resources available in the cloud. The fully homomorphic scheme, FHE-BLOOM, realizes a comprehensive outsourcing to the cloud, while the partially homomorphic scheme, PHE-BLOOM, trades a slight relaxation of security guarantees against performance improvements by at least three orders of magnitude.

Meta-analysis methods for combining multiple expression profiles: comparisons, statistical characterization and an application guideline

PubMed Central

2013-01-01

Background As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application; the decision essentially requires both statistical and biological considerations. Results We performed 12 microarray meta-analysis methods for combining multiple simulated expression profiles, and such methods can be categorized for different hypothesis setting purposes: (1) HS A : DE genes with non-zero effect sizes in all studies, (2) HS B : DE genes with non-zero effect sizes in one or more studies and (3) HS r : DE gene with non-zero effect in "majority" of studies. We then performed a comprehensive comparative analysis through six large-scale real applications using four quantitative statistical evaluation criteria: detection capability, biological association, stability and robustness. We elucidated hypothesis settings behind the methods and further apply multi-dimensional scaling (MDS) and an entropy measure to characterize the meta-analysis methods and data structure, respectively. Conclusions The aggregated results from the simulation study categorized the 12 methods into three hypothesis settings (HS A , HS B , and HS r ). Evaluation in real data and results from MDS and entropy analyses provided an insightful and practical guideline to the choice of the most suitable method in a given application. All source files for simulation and real data are available on the author’s publication website. PMID:24359104

Meta-analysis methods for combining multiple expression profiles: comparisons, statistical characterization and an application guideline.

PubMed

Chang, Lun-Ching; Lin, Hui-Min; Sibille, Etienne; Tseng, George C

2013-12-21

As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application; the decision essentially requires both statistical and biological considerations. We performed 12 microarray meta-analysis methods for combining multiple simulated expression profiles, and such methods can be categorized for different hypothesis setting purposes: (1) HS(A): DE genes with non-zero effect sizes in all studies, (2) HS(B): DE genes with non-zero effect sizes in one or more studies and (3) HS(r): DE gene with non-zero effect in "majority" of studies. We then performed a comprehensive comparative analysis through six large-scale real applications using four quantitative statistical evaluation criteria: detection capability, biological association, stability and robustness. We elucidated hypothesis settings behind the methods and further apply multi-dimensional scaling (MDS) and an entropy measure to characterize the meta-analysis methods and data structure, respectively. The aggregated results from the simulation study categorized the 12 methods into three hypothesis settings (HS(A), HS(B), and HS(r)). Evaluation in real data and results from MDS and entropy analyses provided an insightful and practical guideline to the choice of the most suitable method in a given application. All source files for simulation and real data are available on the author's publication website.

Lightweight genome viewer: portable software for browsing genomics data in its chromosomal context

PubMed Central

Faith, Jeremiah J; Olson, Andrew J; Gardner, Timothy S; Sachidanandam, Ravi

2007-01-01

Background Lightweight genome viewer (lwgv) is a web-based tool for visualization of sequence annotations in their chromosomal context. It performs most of the functions of larger genome browsers, while relying on standard flat-file formats and bypassing the database needs of most visualization tools. Visualization as an aide to discovery requires display of novel data in conjunction with static annotations in their chromosomal context. With database-based systems, displaying dynamic results requires temporary tables that need to be tracked for removal. Results lwgv simplifies the visualization of user-generated results on a local computer. The dynamic results of these analyses are written to transient files, which can import static content from a more permanent file. lwgv is currently used in many different applications, from whole genome browsers to single-gene RNAi design visualization, demonstrating its applicability in a large variety of contexts and scales. Conclusion lwgv provides a lightweight alternative to large genome browsers for visualizing biological annotations and dynamic analyses in their chromosomal context. It is particularly suited for applications ranging from short sequences to medium-sized genomes when the creation and maintenance of a large software and database infrastructure is not necessary or desired. PMID:17877794

Lightweight genome viewer: portable software for browsing genomics data in its chromosomal context.

PubMed

Faith, Jeremiah J; Olson, Andrew J; Gardner, Timothy S; Sachidanandam, Ravi

2007-09-18

Lightweight genome viewer (lwgv) is a web-based tool for visualization of sequence annotations in their chromosomal context. It performs most of the functions of larger genome browsers, while relying on standard flat-file formats and bypassing the database needs of most visualization tools. Visualization as an aide to discovery requires display of novel data in conjunction with static annotations in their chromosomal context. With database-based systems, displaying dynamic results requires temporary tables that need to be tracked for removal. lwgv simplifies the visualization of user-generated results on a local computer. The dynamic results of these analyses are written to transient files, which can import static content from a more permanent file. lwgv is currently used in many different applications, from whole genome browsers to single-gene RNAi design visualization, demonstrating its applicability in a large variety of contexts and scales. lwgv provides a lightweight alternative to large genome browsers for visualizing biological annotations and dynamic analyses in their chromosomal context. It is particularly suited for applications ranging from short sequences to medium-sized genomes when the creation and maintenance of a large software and database infrastructure is not necessary or desired.

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.

Recapitulating phylogenies using k-mers: from trees to networks.

PubMed

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

2016-01-01

Ernst Haeckel based his landmark Tree of Life on the supposed ontogenic recapitulation of phylogeny, i.e. that successive embryonic stages during the development of an organism re-trace the morphological forms of its ancestors over the course of evolution. Much of this idea has since been discredited. Today, phylogenies are often based on families of molecular sequences. The standard approach starts with a multiple sequence alignment, in which the sequences are arranged relative to each other in a way that maximises a measure of similarity position-by-position along their entire length. A tree (or sometimes a network) is then inferred. Rigorous multiple sequence alignment is computationally demanding, and evolutionary processes that shape the genomes of many microbes (bacteria, archaea and some morphologically simple eukaryotes) can add further complications. In particular, recombination, genome rearrangement and lateral genetic transfer undermine the assumptions that underlie multiple sequence alignment, and imply that a tree-like structure may be too simplistic. Here, using genome sequences of 143 bacterial and archaeal genomes, we construct a network of phylogenetic relatedness based on the number of shared k -mers (subsequences at fixed length k ). Our findings suggest that the network captures not only key aspects of microbial genome evolution as inferred from a tree, but also features that are not treelike. The method is highly scalable, allowing for investigation of genome evolution across a large number of genomes. Instead of using specific regions or sequences from genome sequences, or indeed Haeckel's idea of ontogeny, we argue that genome phylogenies can be inferred using k -mers from whole-genome sequences. Representing these networks dynamically allows biological questions of interest to be formulated and addressed quickly and in a visually intuitive manner.

Wetlands as large-scale nature-based solutions: status and future challenges for research and management

NASA Astrophysics Data System (ADS)

Thorslund, Josefin; Jarsjö, Jerker; Destouni, Georgia

2017-04-01

Wetlands are often considered as nature-based solutions that can provide a multitude of services of great social, economic and environmental value to humankind. The services may include recreation, greenhouse gas sequestration, contaminant retention, coastal protection, groundwater level and soil moisture regulation, flood regulation and biodiversity support. Changes in land-use, water use and climate can all impact wetland functions and occur at scales extending well beyond the local scale of an individual wetland. However, in practical applications, management decisions usually regard and focus on individual wetland sites and local conditions. To understand the potential usefulness and services of wetlands as larger-scale nature-based solutions, e.g. for mitigating negative impacts from large-scale change pressures, one needs to understand the combined function multiple wetlands at the relevant large scales. We here systematically investigate if and to what extent research so far has addressed the large-scale dynamics of landscape systems with multiple wetlands, which are likely to be relevant for understanding impacts of regional to global change. Our investigation regards key changes and impacts of relevance for nature-based solutions, such as large-scale nutrient and pollution retention, flow regulation and coastal protection. Although such large-scale knowledge is still limited, evidence suggests that the aggregated functions and effects of multiple wetlands in the landscape can differ considerably from those observed at individual wetlands. Such scale differences may have important implications for wetland function-effect predictability and management under large-scale change pressures and impacts, such as those of climate change.

Estimated allele substitution effects underlying genomic evaluation models depend on the scaling of allele counts.

PubMed

Bouwman, Aniek C; Hayes, Ben J; Calus, Mario P L

2017-10-30

Genomic evaluation is used to predict direct genomic values (DGV) for selection candidates in breeding programs, but also to estimate allele substitution effects (ASE) of single nucleotide polymorphisms (SNPs). Scaling of allele counts influences the estimated ASE, because scaling of allele counts results in less shrinkage towards the mean for low minor allele frequency (MAF) variants. Scaling may become relevant for estimating ASE as more low MAF variants will be used in genomic evaluations. We show the impact of scaling on estimates of ASE using real data and a theoretical framework, and in terms of power, model fit and predictive performance. In a dairy cattle dataset with 630 K SNP genotypes, the correlation between DGV for stature from a random regression model using centered allele counts (RRc) and centered and scaled allele counts (RRcs) was 0.9988, whereas the overall correlation between ASE using RRc and RRcs was 0.27. The main difference in ASE between both methods was found for SNPs with a MAF lower than 0.01. Both the ratio (ASE from RRcs/ASE from RRc) and the regression coefficient (regression of ASE from RRcs on ASE from RRc) were much higher than 1 for low MAF SNPs. Derived equations showed that scenarios with a high heritability, a large number of individuals and a small number of variants have lower ratios between ASE from RRc and RRcs. We also investigated the optimal scaling parameter [from - 1 (RRcs) to 0 (RRc) in steps of 0.1] in the bovine stature dataset. We found that the log-likelihood was maximized with a scaling parameter of - 0.8, while the mean squared error of prediction was minimized with a scaling parameter of - 1, i.e., RRcs. Large differences in estimated ASE were observed for low MAF SNPs when allele counts were scaled or not scaled because there is less shrinkage towards the mean for scaled allele counts. We derived a theoretical framework that shows that the difference in ASE due to shrinkage is heavily influenced by the power of the data. Increasing the power results in smaller differences in ASE whether allele counts are scaled or not.

ENGINES: exploring single nucleotide variation in entire human genomes.

PubMed

Amigo, Jorge; Salas, Antonio; Phillips, Christopher

2011-04-19

Next generation ultra-sequencing technologies are starting to produce extensive quantities of data from entire human genome or exome sequences, and therefore new software is needed to present and analyse this vast amount of information. The 1000 Genomes project has recently released raw data for 629 complete genomes representing several human populations through their Phase I interim analysis and, although there are certain public tools available that allow exploration of these genomes, to date there is no tool that permits comprehensive population analysis of the variation catalogued by such data. We have developed a genetic variant site explorer able to retrieve data for Single Nucleotide Variation (SNVs), population by population, from entire genomes without compromising future scalability and agility. ENGINES (ENtire Genome INterface for Exploring SNVs) uses data from the 1000 Genomes Phase I to demonstrate its capacity to handle large amounts of genetic variation (>7.3 billion genotypes and 28 million SNVs), as well as deriving summary statistics of interest for medical and population genetics applications. The whole dataset is pre-processed and summarized into a data mart accessible through a web interface. The query system allows the combination and comparison of each available population sample, while searching by rs-number list, chromosome region, or genes of interest. Frequency and FST filters are available to further refine queries, while results can be visually compared with other large-scale Single Nucleotide Polymorphism (SNP) repositories such as HapMap or Perlegen. ENGINES is capable of accessing large-scale variation data repositories in a fast and comprehensive manner. It allows quick browsing of whole genome variation, while providing statistical information for each variant site such as allele frequency, heterozygosity or FST values for genetic differentiation. Access to the data mart generating scripts and to the web interface is granted from http://spsmart.cesga.es/engines.php. © 2011 Amigo et al; licensee BioMed Central Ltd.

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

MACSIMS : multiple alignment of complete sequences information management system

PubMed Central

Thompson, Julie D; Muller, Arnaud; Waterhouse, Andrew; Procter, Jim; Barton, Geoffrey J; Plewniak, Frédéric; Poch, Olivier

2006-01-01

Background In the post-genomic era, systems-level studies are being performed that seek to explain complex biological systems by integrating diverse resources from fields such as genomics, proteomics or transcriptomics. New information management systems are now needed for the collection, validation and analysis of the vast amount of heterogeneous data available. Multiple alignments of complete sequences provide an ideal environment for the integration of this information in the context of the protein family. Results MACSIMS is a multiple alignment-based information management program that combines the advantages of both knowledge-based and ab initio sequence analysis methods. Structural and functional information is retrieved automatically from the public databases. In the multiple alignment, homologous regions are identified and the retrieved data is evaluated and propagated from known to unknown sequences with these reliable regions. In a large-scale evaluation, the specificity of the propagated sequence features is estimated to be >99%, i.e. very few false positive predictions are made. MACSIMS is then used to characterise mutations in a test set of 100 proteins that are known to be involved in human genetic diseases. The number of sequence features associated with these proteins was increased by 60%, compared to the features available in the public databases. An XML format output file allows automatic parsing of the MACSIM results, while a graphical display using the JalView program allows manual analysis. Conclusion MACSIMS is a new information management system that incorporates detailed analyses of protein families at the structural, functional and evolutionary levels. MACSIMS thus provides a unique environment that facilitates knowledge extraction and the presentation of the most pertinent information to the biologist. A web server and the source code are available at . PMID:16792820

A pipeline for the de novo assembly of the Themira biloba (Sepsidae: Diptera) transcriptome using a multiple k-mer length approach.

PubMed

Melicher, Dacotah; Torson, Alex S; Dworkin, Ian; Bowsher, Julia H

2014-03-12

The Sepsidae family of flies is a model for investigating how sexual selection shapes courtship and sexual dimorphism in a comparative framework. However, like many non-model systems, there are few molecular resources available. Large-scale sequencing and assembly have not been performed in any sepsid, and the lack of a closely related genome makes investigation of gene expression challenging. Our goal was to develop an automated pipeline for de novo transcriptome assembly, and to use that pipeline to assemble and analyze the transcriptome of the sepsid Themira biloba. Our bioinformatics pipeline uses cloud computing services to assemble and analyze the transcriptome with off-site data management, processing, and backup. It uses a multiple k-mer length approach combined with a second meta-assembly to extend transcripts and recover more bases of transcript sequences than standard single k-mer assembly. We used 454 sequencing to generate 1.48 million reads from cDNA generated from embryo, larva, and pupae of T. biloba and assembled a transcriptome consisting of 24,495 contigs. Annotation identified 16,705 transcripts, including those involved in embryogenesis and limb patterning. We assembled transcriptomes from an additional three non-model organisms to demonstrate that our pipeline assembled a higher-quality transcriptome than single k-mer approaches across multiple species. The pipeline we have developed for assembly and analysis increases contig length, recovers unique transcripts, and assembles more base pairs than other methods through the use of a meta-assembly. The T. biloba transcriptome is a critical resource for performing large-scale RNA-Seq investigations of gene expression patterns, and is the first transcriptome sequenced in this Dipteran family.

Multiscale Integration of -Omic, Imaging, and Clinical Data in Biomedical Informatics

PubMed Central

Phan, John H.; Quo, Chang F.; Cheng, Chihwen; Wang, May Dongmei

2016-01-01

This paper reviews challenges and opportunities in multiscale data integration for biomedical informatics. Biomedical data can come from different biological origins, data acquisition technologies, and clinical applications. Integrating such data across multiple scales (e.g., molecular, cellular/tissue, and patient) can lead to more informed decisions for personalized, predictive, and preventive medicine. However, data heterogeneity, community standards in data acquisition, and computational complexity are big challenges for such decision making. This review describes genomic and proteomic (i.e., molecular), histopathological imaging (i.e., cellular/tissue), and clinical (i.e., patient) data; it includes case studies for single-scale (e.g., combining genomic or histopathological image data), multiscale (e.g., combining histopathological image and clinical data), and multiscale and multiplatform (e.g., the Human Protein Atlas and The Cancer Genome Atlas) data integration. Numerous opportunities exist in biomedical informatics research focusing on integration of multiscale and multiplatform data. PMID:23231990

Multiscale integration of -omic, imaging, and clinical data in biomedical informatics.

PubMed

Phan, John H; Quo, Chang F; Cheng, Chihwen; Wang, May Dongmei

2012-01-01

This paper reviews challenges and opportunities in multiscale data integration for biomedical informatics. Biomedical data can come from different biological origins, data acquisition technologies, and clinical applications. Integrating such data across multiple scales (e.g., molecular, cellular/tissue, and patient) can lead to more informed decisions for personalized, predictive, and preventive medicine. However, data heterogeneity, community standards in data acquisition, and computational complexity are big challenges for such decision making. This review describes genomic and proteomic (i.e., molecular), histopathological imaging (i.e., cellular/tissue), and clinical (i.e., patient) data; it includes case studies for single-scale (e.g., combining genomic or histopathological image data), multiscale (e.g., combining histopathological image and clinical data), and multiscale and multiplatform (e.g., the Human Protein Atlas and The Cancer Genome Atlas) data integration. Numerous opportunities exist in biomedical informatics research focusing on integration of multiscale and multiplatform data.

An improved ChIP-seq peak detection system for simultaneously identifying post-translational modified transcription factors by combinatorial fusion, using SUMOylation as an example.

PubMed

Cheng, Chia-Yang; Chu, Chia-Han; Hsu, Hung-Wei; Hsu, Fang-Rong; Tang, Chung Yi; Wang, Wen-Ching; Kung, Hsing-Jien; Chang, Pei-Ching

2014-01-01

Post-translational modification (PTM) of transcriptional factors and chromatin remodelling proteins is recognized as a major mechanism by which transcriptional regulation occurs. Chromatin immunoprecipitation (ChIP) in combination with high-throughput sequencing (ChIP-seq) is being applied as a gold standard when studying the genome-wide binding sites of transcription factor (TFs). This has greatly improved our understanding of protein-DNA interactions on a genomic-wide scale. However, current ChIP-seq peak calling tools are not sufficiently sensitive and are unable to simultaneously identify post-translational modified TFs based on ChIP-seq analysis; this is largely due to the wide-spread presence of multiple modified TFs. Using SUMO-1 modification as an example; we describe here an improved approach that allows the simultaneous identification of the particular genomic binding regions of all TFs with SUMO-1 modification. Traditional peak calling methods are inadequate when identifying multiple TF binding sites that involve long genomic regions and therefore we designed a ChIP-seq processing pipeline for the detection of peaks via a combinatorial fusion method. Then, we annotate the peaks with known transcription factor binding sites (TFBS) using the Transfac Matrix Database (v7.0), which predicts potential SUMOylated TFs. Next, the peak calling result was further analyzed based on the promoter proximity, TFBS annotation, a literature review, and was validated by ChIP-real-time quantitative PCR (qPCR) and ChIP-reChIP real-time qPCR. The results show clearly that SUMOylated TFs are able to be pinpointed using our pipeline. A methodology is presented that analyzes SUMO-1 ChIP-seq patterns and predicts related TFs. Our analysis uses three peak calling tools. The fusion of these different tools increases the precision of the peak calling results. TFBS annotation method is able to predict potential SUMOylated TFs. Here, we offer a new approach that enhances ChIP-seq data analysis and allows the identification of multiple SUMOylated TF binding sites simultaneously, which can then be utilized for other functional PTM binding site prediction in future.

Cost-effective cloud computing: a case study using the comparative genomics tool, roundup.

PubMed

Kudtarkar, Parul; Deluca, Todd F; Fusaro, Vincent A; Tonellato, Peter J; Wall, Dennis P

2010-12-22

Comparative genomics resources, such as ortholog detection tools and repositories are rapidly increasing in scale and complexity. Cloud computing is an emerging technological paradigm that enables researchers to dynamically build a dedicated virtual cluster and may represent a valuable alternative for large computational tools in bioinformatics. In the present manuscript, we optimize the computation of a large-scale comparative genomics resource-Roundup-using cloud computing, describe the proper operating principles required to achieve computational efficiency on the cloud, and detail important procedures for improving cost-effectiveness to ensure maximal computation at minimal costs. Utilizing the comparative genomics tool, Roundup, as a case study, we computed orthologs among 902 fully sequenced genomes on Amazon's Elastic Compute Cloud. For managing the ortholog processes, we designed a strategy to deploy the web service, Elastic MapReduce, and maximize the use of the cloud while simultaneously minimizing costs. Specifically, we created a model to estimate cloud runtime based on the size and complexity of the genomes being compared that determines in advance the optimal order of the jobs to be submitted. We computed orthologous relationships for 245,323 genome-to-genome comparisons on Amazon's computing cloud, a computation that required just over 200 hours and cost $8,000 USD, at least 40% less than expected under a strategy in which genome comparisons were submitted to the cloud randomly with respect to runtime. Our cost savings projections were based on a model that not only demonstrates the optimal strategy for deploying RSD to the cloud, but also finds the optimal cluster size to minimize waste and maximize usage. Our cost-reduction model is readily adaptable for other comparative genomics tools and potentially of significant benefit to labs seeking to take advantage of the cloud as an alternative to local computing infrastructure.

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.

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

A Tool for Multiple Targeted Genome Deletions that Is Precise, Scar-Free, and Suitable for Automation.

PubMed

Aubrey, Wayne; Riley, Michael C; Young, Michael; King, Ross D; Oliver, Stephen G; Clare, Amanda

2015-01-01

Many advances in synthetic biology require the removal of a large number of genomic elements from a genome. Most existing deletion methods leave behind markers, and as there are a limited number of markers, such methods can only be applied a fixed number of times. Deletion methods that recycle markers generally are either imprecise (remove untargeted sequences), or leave scar sequences which can cause genome instability and rearrangements. No existing marker recycling method is automation-friendly. We have developed a novel openly available deletion tool that consists of: 1) a method for deleting genomic elements that can be repeatedly used without limit, is precise, scar-free, and suitable for automation; and 2) software to design the method's primers. Our tool is sequence agnostic and could be used to delete large numbers of coding sequences, promoter regions, transcription factor binding sites, terminators, etc in a single genome. We have validated our tool on the deletion of non-essential open reading frames (ORFs) from S. cerevisiae. The tool is applicable to arbitrary genomes, and we provide primer sequences for the deletion of: 90% of the ORFs from the S. cerevisiae genome, 88% of the ORFs from S. pombe genome, and 85% of the ORFs from the L. lactis genome.

A Tool for Multiple Targeted Genome Deletions that Is Precise, Scar-Free, and Suitable for Automation

PubMed Central

Aubrey, Wayne; Riley, Michael C.; Young, Michael; King, Ross D.; Oliver, Stephen G.; Clare, Amanda

2015-01-01

Many advances in synthetic biology require the removal of a large number of genomic elements from a genome. Most existing deletion methods leave behind markers, and as there are a limited number of markers, such methods can only be applied a fixed number of times. Deletion methods that recycle markers generally are either imprecise (remove untargeted sequences), or leave scar sequences which can cause genome instability and rearrangements. No existing marker recycling method is automation-friendly. We have developed a novel openly available deletion tool that consists of: 1) a method for deleting genomic elements that can be repeatedly used without limit, is precise, scar-free, and suitable for automation; and 2) software to design the method’s primers. Our tool is sequence agnostic and could be used to delete large numbers of coding sequences, promoter regions, transcription factor binding sites, terminators, etc in a single genome. We have validated our tool on the deletion of non-essential open reading frames (ORFs) from S. cerevisiae. The tool is applicable to arbitrary genomes, and we provide primer sequences for the deletion of: 90% of the ORFs from the S. cerevisiae genome, 88% of the ORFs from S. pombe genome, and 85% of the ORFs from the L. lactis genome. PMID:26630677

Precision medicine for advanced prostate cancer

PubMed Central

Mullane, Stephanie A.; Van Allen, Eliezer M.

2016-01-01

Purpose of review Precision cancer medicine, the use of genomic profiling of patient tumors at the point-of-care to inform treatment decisions, is rapidly changing treatment strategies across cancer types. Precision medicine for advanced prostate cancer may identify new treatment strategies and change clinical practice. In this review, we discuss the potential and challenges of precision medicine in advanced prostate cancer. Recent findings Although primary prostate cancers do not harbor highly recurrent targetable genomic alterations, recent reports on the genomics of metastatic castration-resistant prostate cancer has shown multiple targetable alterations in castration-resistant prostate cancer metastatic biopsies. Therapeutic implications include targeting prevalent DNA repair pathway alterations with PARP-1 inhibition in genomically defined subsets of patients, among other genomically stratified targets. In addition, multiple recent efforts have demonstrated the promise of liquid tumor profiling (e.g., profiling circulating tumor cells or cell-free tumor DNA) and highlighted the necessary steps to scale these approaches in prostate cancer. Summary Although still in the initial phase of precision medicine for prostate cancer, there is extraordinary potential for clinical impact. Efforts to overcome current scientific and clinical barriers will enable widespread use of precision medicine approaches for advanced prostate cancer patients. PMID:26909474

Precision medicine for advanced prostate cancer.

PubMed

Mullane, Stephanie A; Van Allen, Eliezer M

2016-05-01

Precision cancer medicine, the use of genomic profiling of patient tumors at the point-of-care to inform treatment decisions, is rapidly changing treatment strategies across cancer types. Precision medicine for advanced prostate cancer may identify new treatment strategies and change clinical practice. In this review, we discuss the potential and challenges of precision medicine in advanced prostate cancer. Although primary prostate cancers do not harbor highly recurrent targetable genomic alterations, recent reports on the genomics of metastatic castration-resistant prostate cancer has shown multiple targetable alterations in castration-resistant prostate cancer metastatic biopsies. Therapeutic implications include targeting prevalent DNA repair pathway alterations with PARP-1 inhibition in genomically defined subsets of patients, among other genomically stratified targets. In addition, multiple recent efforts have demonstrated the promise of liquid tumor profiling (e.g., profiling circulating tumor cells or cell-free tumor DNA) and highlighted the necessary steps to scale these approaches in prostate cancer. Although still in the initial phase of precision medicine for prostate cancer, there is extraordinary potential for clinical impact. Efforts to overcome current scientific and clinical barriers will enable widespread use of precision medicine approaches for advanced prostate cancer patients.

New Genes and New Insights from Old Genes: Update on Alzheimer Disease

PubMed Central

Ringman, John M.; Coppola, Giovanni

2013-01-01

Purpose of Review: This article discusses the current status of knowledge regarding the genetic basis of Alzheimer disease (AD) with a focus on clinically relevant aspects. Recent Findings: The genetic architecture of AD is complex, as it includes multiple susceptibility genes and likely nongenetic factors. Rare but highly penetrant autosomal dominant mutations explain a small minority of the cases but have allowed tremendous advances in understanding disease pathogenesis. The identification of a strong genetic risk factor, APOE, reshaped the field and introduced the notion of genetic risk for AD. More recently, large-scale genome-wide association studies are adding to the picture a number of common variants with very small effect sizes. Large-scale resequencing studies are expected to identify additional risk factors, including rare susceptibility variants and structural variation. Summary: Genetic assessment is currently of limited utility in clinical practice because of the low frequency (Mendelian mutations) or small effect size (common risk factors) of the currently known susceptibility genes. However, genetic studies are identifying with confidence a number of novel risk genes, and this will further our understanding of disease biology and possibly the identification of therapeutic targets. PMID:23558482

Skate Genome Project: Cyber-Enabled Bioinformatics Collaboration

PubMed Central

Vincent, J.

2011-01-01

The Skate Genome Project, a pilot project of the North East Cyber infrastructure Consortium, aims to produce a draft genome sequence of Leucoraja erinacea, the Little Skate. The pilot project was designed to also develop expertise in large scale collaborations across the NECC region. An overview of the bioinformatics and infrastructure challenges faced during the first year of the project will be presented. Results to date and lessons learned from the perspective of a bioinformatics core will be highlighted.

Comparison of Penalty Functions for Sparse Canonical Correlation Analysis

PubMed Central

Chalise, Prabhakar; Fridley, Brooke L.

2011-01-01

Canonical correlation analysis (CCA) is a widely used multivariate method for assessing the association between two sets of variables. However, when the number of variables far exceeds the number of subjects, such in the case of large-scale genomic studies, the traditional CCA method is not appropriate. In addition, when the variables are highly correlated the sample covariance matrices become unstable or undefined. To overcome these two issues, sparse canonical correlation analysis (SCCA) for multiple data sets has been proposed using a Lasso type of penalty. However, these methods do not have direct control over sparsity of solution. An additional step that uses Bayesian Information Criterion (BIC) has also been suggested to further filter out unimportant features. In this paper, a comparison of four penalty functions (Lasso, Elastic-net, SCAD and Hard-threshold) for SCCA with and without the BIC filtering step have been carried out using both real and simulated genotypic and mRNA expression data. This study indicates that the SCAD penalty with BIC filter would be a preferable penalty function for application of SCCA to genomic data. PMID:21984855

Conversion events in gene clusters

PubMed Central

2011-01-01

Background Gene clusters containing multiple similar genomic regions in close proximity are of great interest for biomedical studies because of their associations with inherited diseases. However, such regions are difficult to analyze due to their structural complexity and their complicated evolutionary histories, reflecting a variety of large-scale mutational events. In particular, conversion events can mislead inferences about the relationships among these regions, as traced by traditional methods such as construction of phylogenetic trees or multi-species alignments. Results To correct the distorted information generated by such methods, we have developed an automated pipeline called CHAP (Cluster History Analysis Package) for detecting conversion events. We used this pipeline to analyze the conversion events that affected two well-studied gene clusters (α-globin and β-globin) and three gene clusters for which comparative sequence data were generated from seven primate species: CCL (chemokine ligand), IFN (interferon), and CYP2abf (part of cytochrome P450 family 2). CHAP is freely available at http://www.bx.psu.edu/miller_lab. Conclusions These studies reveal the value of characterizing conversion events in the context of studying gene clusters in complex genomes. PMID:21798034

A geographically-diverse collection of 418 human gut microbiome pathway genome databases

PubMed Central

Hahn, Aria S.; Altman, Tomer; Konwar, Kishori M.; Hanson, Niels W.; Kim, Dongjae; Relman, David A.; Dill, David L.; Hallam, Steven J.

2017-01-01

Advances in high-throughput sequencing are reshaping how we perceive microbial communities inhabiting the human body, with implications for therapeutic interventions. Several large-scale datasets derived from hundreds of human microbiome samples sourced from multiple studies are now publicly available. However, idiosyncratic data processing methods between studies introduce systematic differences that confound comparative analyses. To overcome these challenges, we developed GutCyc, a compendium of environmental pathway genome databases (ePGDBs) constructed from 418 assembled human microbiome datasets using MetaPathways, enabling reproducible functional metagenomic annotation. We also generated metabolic network reconstructions for each metagenome using the Pathway Tools software, empowering researchers and clinicians interested in visualizing and interpreting metabolic pathways encoded by the human gut microbiome. For the first time, GutCyc provides consistent annotations and metabolic pathway predictions, making possible comparative community analyses between health and disease states in inflammatory bowel disease, Crohn’s disease, and type 2 diabetes. GutCyc data products are searchable online, or may be downloaded and explored locally using MetaPathways and Pathway Tools. PMID:28398290

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

Comparative genome-wide analysis reveals that Burkholderia contaminans MS14 possesses multiple antimicrobial biosynthesis genes but not major genetic loci required for pathogenesis.

PubMed

Deng, Peng; Wang, Xiaoqiang; Baird, Sonya M; Showmaker, Kurt C; Smith, Leif; Peterson, Daniel G; Lu, Shien

2016-06-01

Burkholderia contaminans MS14 shows significant antimicrobial activities against plant and animal pathogenic fungi and bacteria. The antifungal agent occidiofungin produced by MS14 has great potential for development of biopesticides and pharmaceutical drugs. However, the use of Burkholderia species as biocontrol agent in agriculture is restricted due to the difficulties in distinguishing between plant growth-promoting bacteria and the pathogenic bacteria. The complete MS14 genome was sequenced and analyzed to find what beneficial and virulence-related genes it harbors. The phylogenetic relatedness of B. contaminans MS14 and other 17 Burkholderia species was also analyzed. To research MS14's potential virulence, the gene regions related to the antibiotic production, antibiotic resistance, and virulence were compared between MS14 and other Burkholderia genomes. The genome of B. contaminans MS14 was sequenced and annotated. The genomic analyses reveal the presence of multiple gene sets for antimicrobial biosynthesis, which contribute to its antimicrobial activities. BLAST results indicate that the MS14 genome harbors a large number of unique regions. MS14 is closely related to another plant growth-promoting Burkholderia strain B. lata 383 according to the average nucleotide identity data. Moreover, according to the phylogenetic analysis, plant growth-promoting species isolated from soils and mammalian pathogenic species are clustered together, respectively. MS14 has multiple antimicrobial activity-related genes identified from the genome, but it lacks key virulence-related gene loci found in the pathogenic strains. Additionally, plant growth-promoting Burkholderia species have one or more antimicrobial biosynthesis genes in their genomes as compared with nonplant growth-promoting soil-isolated Burkholderia species. On the other hand, pathogenic species harbor multiple virulence-associated gene loci that are not present in nonpathogenic Burkholderia species. The MS14 genome as well as Burkholderia species genome show considerable diversity. Multiple antimicrobial agent biosynthesis genes were identified in the genome of plant growth-promoting species of Burkholderia. In addition, by comparing to nonpathogenic Burkholderia species, pathogenic Burkholderia species have more characterized homologs of the gene loci known to contribute to pathogenicity and virulence to plant and animals. © 2016 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Robust decentralized hybrid adaptive output feedback fuzzy control for a class of large-scale MIMO nonlinear systems and its application to AHS.

PubMed

Huang, Yi-Shao; Liu, Wel-Ping; Wu, Min; Wang, Zheng-Wu

2014-09-01

This paper presents a novel observer-based decentralized hybrid adaptive fuzzy control scheme for a class of large-scale continuous-time multiple-input multiple-output (MIMO) uncertain nonlinear systems whose state variables are unmeasurable. The scheme integrates fuzzy logic systems, state observers, and strictly positive real conditions to deal with three issues in the control of a large-scale MIMO uncertain nonlinear system: algorithm design, controller singularity, and transient response. Then, the design of the hybrid adaptive fuzzy controller is extended to address a general large-scale uncertain nonlinear system. It is shown that the resultant closed-loop large-scale system keeps asymptotically stable and the tracking error converges to zero. The better characteristics of our scheme are demonstrated by simulations. Copyright © 2014. Published by Elsevier Ltd.

Software engineering the mixed model for genome-wide association studies on large samples.

PubMed

Zhang, Zhiwu; Buckler, Edward S; Casstevens, Terry M; Bradbury, Peter J

2009-11-01

Mixed models improve the ability to detect phenotype-genotype associations in the presence of population stratification and multiple levels of relatedness in genome-wide association studies (GWAS), but for large data sets the resource consumption becomes impractical. At the same time, the sample size and number of markers used for GWAS is increasing dramatically, resulting in greater statistical power to detect those associations. The use of mixed models with increasingly large data sets depends on the availability of software for analyzing those models. While multiple software packages implement the mixed model method, no single package provides the best combination of fast computation, ability to handle large samples, flexible modeling and ease of use. Key elements of association analysis with mixed models are reviewed, including modeling phenotype-genotype associations using mixed models, population stratification, kinship and its estimation, variance component estimation, use of best linear unbiased predictors or residuals in place of raw phenotype, improving efficiency and software-user interaction. The available software packages are evaluated, and suggestions made for future software development.

Parallel Continuous Flow: A Parallel Suffix Tree Construction Tool for Whole Genomes

PubMed Central

Farreras, Montse

2014-01-01

Abstract The construction of suffix trees for very long sequences is essential for many applications, and it plays a central role in the bioinformatic domain. With the advent of modern sequencing technologies, biological sequence databases have grown dramatically. Also the methodologies required to analyze these data have become more complex everyday, requiring fast queries to multiple genomes. In this article, we present parallel continuous flow (PCF), a parallel suffix tree construction method that is suitable for very long genomes. We tested our method for the suffix tree construction of the entire human genome, about 3GB. We showed that PCF can scale gracefully as the size of the input genome grows. Our method can work with an efficiency of 90% with 36 processors and 55% with 172 processors. We can index the human genome in 7 minutes using 172 processes. PMID:24597675

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.

PGMapper: a web-based tool linking phenotype to genes.

PubMed

Xiong, Qing; Qiu, Yuhui; Gu, Weikuan

2008-04-01

With the availability of whole genome sequence in many species, linkage analysis, positional cloning and microarray are gradually becoming powerful tools for investigating the links between phenotype and genotype or genes. However, in these methods, causative genes underlying a quantitative trait locus, or a disease, are usually located within a large genomic region or a large set of genes. Examining the function of every gene is very time consuming and needs to retrieve and integrate the information from multiple databases or genome resources. PGMapper is a software tool for automatically matching phenotype to genes from a defined genome region or a group of given genes by combining the mapping information from the Ensembl database and gene function information from the OMIM and PubMed databases. PGMapper is currently available for candidate gene search of human, mouse, rat, zebrafish and 12 other species. Available online at http://www.genediscovery.org/pgmapper/index.jsp.

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

CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing

PubMed Central

2011-01-01

Background Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. Results We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. Conclusion The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing. PMID:21878105

B-CAN: a resource sharing platform to improve the operation, visualization and integrated analysis of TCGA breast cancer data

PubMed Central

Wen, Can-Hong; Ou, Shao-Min; Guo, Xiao-Bo; Liu, Chen-Feng; Shen, Yan-Bo; You, Na; Cai, Wei-Hong; Shen, Wen-Jun; Wang, Xue-Qin; Tan, Hai-Zhu

2017-01-01

Breast cancer is a high-risk heterogeneous disease with myriad subtypes and complicated biological features. The Cancer Genome Atlas (TCGA) breast cancer database provides researchers with the large-scale genome and clinical data via web portals and FTP services. Researchers are able to gain new insights into their related fields, and evaluate experimental discoveries with TCGA. However, it is difficult for researchers who have little experience with database and bioinformatics to access and operate on because of TCGA’s complex data format and diverse files. For ease of use, we build the breast cancer (B-CAN) platform, which enables data customization, data visualization, and private data center. The B-CAN platform runs on Apache server and interacts with the backstage of MySQL database by PHP. Users can customize data based on their needs by combining tables from original TCGA database and selecting variables from each table. The private data center is applicable for private data and two types of customized data. A key feature of the B-CAN is that it provides single table display and multiple table display. Customized data with one barcode corresponding to many records and processed customized data are allowed in Multiple Tables Display. The B-CAN is an intuitive and high-efficient data-sharing platform. PMID:29312567

Lessons learnt on the analysis of large sequence data in animal genomics.

PubMed

Biscarini, F; Cozzi, P; Orozco-Ter Wengel, P

2018-04-06

The 'omics revolution has made a large amount of sequence data available to researchers and the industry. This has had a profound impact in the field of bioinformatics, stimulating unprecedented advancements in this discipline. Mostly, this is usually looked at from the perspective of human 'omics, in particular human genomics. Plant and animal genomics, however, have also been deeply influenced by next-generation sequencing technologies, with several genomics applications now popular among researchers and the breeding industry. Genomics tends to generate huge amounts of data, and genomic sequence data account for an increasing proportion of big data in biological sciences, due largely to decreasing sequencing and genotyping costs and to large-scale sequencing and resequencing projects. The analysis of big data poses a challenge to scientists, as data gathering currently takes place at a faster pace than does data processing and analysis, and the associated computational burden is increasingly taxing, making even simple manipulation, visualization and transferring of data a cumbersome operation. The time consumed by the processing and analysing of huge data sets may be at the expense of data quality assessment and critical interpretation. Additionally, when analysing lots of data, something is likely to go awry-the software may crash or stop-and it can be very frustrating to track the error. We herein review the most relevant issues related to tackling these challenges and problems, from the perspective of animal genomics, and provide researchers that lack extensive computing experience with guidelines that will help when processing large genomic data sets. © 2018 Stichting International Foundation for Animal Genetics.

Insights from 20 years of bacterial genome sequencing

DOE PAGES

Land, Miriam L.; Hauser, Loren; Jun, Se-Ran; ...

2015-02-27

Since the first two complete bacterial genome sequences were published in 1995, the science of bacteria has dramatically changed. Using third-generation DNA sequencing, it is possible to completely sequence a bacterial genome in a few hours and identify some types of methylation sites along the genome as well. Sequencing of bacterial genome sequences is now a standard procedure, and the information from tens of thousands of bacterial genomes has had a major impact on our views of the bacterial world. In this review, we explore a series of questions to highlight some insights that comparative genomics has produced. To date,more » there are genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. However, the distribution is quite skewed towards a few phyla that contain model organisms. But the breadth is continuing to improve, with projects dedicated to filling in less characterized taxonomic groups. The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas system provides bacteria with immunity against viruses, which outnumber bacteria by tenfold. How fast can we go? Second-generation sequencing has produced a large number of draft genomes (close to 90 % of bacterial genomes in GenBank are currently not complete); third-generation sequencing can potentially produce a finished genome in a few hours, and at the same time provide methlylation sites along the entire chromosome. The diversity of bacterial communities is extensive as is evident from the genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. Genome sequencing can help in classifying an organism, and in the case where multiple genomes of the same species are available, it is possible to calculate the pan- and core genomes; comparison of more than 2000 Escherichia coli genomes finds an E. coli core genome of about 3100 gene families and a total of about 89,000 different gene families. Why do we care about bacterial genome sequencing? There are many practical applications, such as genome-scale metabolic modeling, biosurveillance, bioforensics, and infectious disease epidemiology. In the near future, high-throughput sequencing of patient metagenomic samples could revolutionize medicine in terms of speed and accuracy of finding pathogens and knowing how to treat them.« less

Insights from 20 years of bacterial genome sequencing

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

Land, Miriam L.; Hauser, Loren; Jun, Se-Ran

Since the first two complete bacterial genome sequences were published in 1995, the science of bacteria has dramatically changed. Using third-generation DNA sequencing, it is possible to completely sequence a bacterial genome in a few hours and identify some types of methylation sites along the genome as well. Sequencing of bacterial genome sequences is now a standard procedure, and the information from tens of thousands of bacterial genomes has had a major impact on our views of the bacterial world. In this review, we explore a series of questions to highlight some insights that comparative genomics has produced. To date,more » there are genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. However, the distribution is quite skewed towards a few phyla that contain model organisms. But the breadth is continuing to improve, with projects dedicated to filling in less characterized taxonomic groups. The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas system provides bacteria with immunity against viruses, which outnumber bacteria by tenfold. How fast can we go? Second-generation sequencing has produced a large number of draft genomes (close to 90 % of bacterial genomes in GenBank are currently not complete); third-generation sequencing can potentially produce a finished genome in a few hours, and at the same time provide methlylation sites along the entire chromosome. The diversity of bacterial communities is extensive as is evident from the genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. Genome sequencing can help in classifying an organism, and in the case where multiple genomes of the same species are available, it is possible to calculate the pan- and core genomes; comparison of more than 2000 Escherichia coli genomes finds an E. coli core genome of about 3100 gene families and a total of about 89,000 different gene families. Why do we care about bacterial genome sequencing? There are many practical applications, such as genome-scale metabolic modeling, biosurveillance, bioforensics, and infectious disease epidemiology. In the near future, high-throughput sequencing of patient metagenomic samples could revolutionize medicine in terms of speed and accuracy of finding pathogens and knowing how to treat them.« less

Alignment-free genome tree inference by learning group-specific distance metrics.

PubMed

Patil, Kaustubh R; McHardy, Alice C

2013-01-01

Understanding the evolutionary relationships between organisms is vital for their in-depth study. Gene-based methods are often used to infer such relationships, which are not without drawbacks. One can now attempt to use genome-scale information, because of the ever increasing number of genomes available. This opportunity also presents a challenge in terms of computational efficiency. Two fundamentally different methods are often employed for sequence comparisons, namely alignment-based and alignment-free methods. Alignment-free methods rely on the genome signature concept and provide a computationally efficient way that is also applicable to nonhomologous sequences. The genome signature contains evolutionary signal as it is more similar for closely related organisms than for distantly related ones. We used genome-scale sequence information to infer taxonomic distances between organisms without additional information such as gene annotations. We propose a method to improve genome tree inference by learning specific distance metrics over the genome signature for groups of organisms with similar phylogenetic, genomic, or ecological properties. Specifically, our method learns a Mahalanobis metric for a set of genomes and a reference taxonomy to guide the learning process. By applying this method to more than a thousand prokaryotic genomes, we showed that, indeed, better distance metrics could be learned for most of the 18 groups of organisms tested here. Once a group-specific metric is available, it can be used to estimate the taxonomic distances for other sequenced organisms from the group. This study also presents a large scale comparison between 10 methods--9 alignment-free and 1 alignment-based.

Identification and Functional Prediction of Large Intergenic Noncoding RNAs (lincRNAs) in Rainbow Trout (Oncorhynchus mykiss)

USDA-ARS?s Scientific Manuscript database

Long noncoding RNAs (lncRNAs) have been recognized in recent years as key regulators of diverse cellular processes. Genome-wide large-scale projects have uncovered thousands of lncRNAs in many model organisms. Large intergenic noncoding RNAs (lincRNAs) are lncRNAs that are transcribed from intergeni...

Secure searching of biomarkers through hybrid homomorphic encryption scheme.

PubMed

Kim, Miran; Song, Yongsoo; Cheon, Jung Hee

2017-07-26

As genome sequencing technology develops rapidly, there has lately been an increasing need to keep genomic data secure even when stored in the cloud and still used for research. We are interested in designing a protocol for the secure outsourcing matching problem on encrypted data. We propose an efficient method to securely search a matching position with the query data and extract some information at the position. After decryption, only a small amount of comparisons with the query information should be performed in plaintext state. We apply this method to find a set of biomarkers in encrypted genomes. The important feature of our method is to encode a genomic database as a single element of polynomial ring. Since our method requires a single homomorphic multiplication of hybrid scheme for query computation, it has the advantage over the previous methods in parameter size, computation complexity, and communication cost. In particular, the extraction procedure not only prevents leakage of database information that has not been queried by user but also reduces the communication cost by half. We evaluate the performance of our method and verify that the computation on large-scale personal data can be securely and practically outsourced to a cloud environment during data analysis. It takes about 3.9 s to search-and-extract the reference and alternate sequences at the queried position in a database of size 4M. Our solution for finding a set of biomarkers in DNA sequences shows the progress of cryptographic techniques in terms of their capability can support real-world genome data analysis in a cloud environment.

Metabolic versatility of small archaea Micrarchaeota and Parvarchaeota

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

Chen, Lin-Xing; Mendez-Garcia, Celia; Dombrowski, Nina

Small acidophilic archaea belonging to Micrarchaeota and Parvarchaeota phyla are known to physically interact with some Thermoplasmatales members in nature. However, due to a lack of cultivation and limited genomes on hand, their biodiversity, metabolisms, and physiologies remain largely unresolved. For this study, we obtained 39 genomes from acid mine drainage (AMD) and hot spring environments around the world. 16S rRNA gene based analyses revealed that Parvarchaeota were only detected in AMD and hot spring habitats, while Micrarchaeota were also detected in others including soil, peat, hypersaline mat, and freshwater, suggesting a considerable higher diversity and broader than expected habitatmore » distribution for this phylum. Despite their small genomes (0.64-1.08 Mb), these archaea may contribute to carbon and nitrogen cycling by degrading multiple saccharides and proteins, and produce ATP via aerobic respiration and fermentation. Additionally, we identified several syntenic genes with homology to those involved in iron oxidation in six Parvarchae ota genomes, suggesting their potential role in iron cycling. However, both phyla lack biosynthetic pathways for amino acids and nucleotides, suggesting that they likely scavenge these biomolecules from the environment and/or other community members. Moreover, low-oxygen enrichments in laboratory confirmed our speculation that both phyla are microaerobic/anaerobic, based on several specific genes identified in them. Furthermore, phylogenetic analyses provide insights into the close evolutionary history of energy related functionalities between both phyla with Thermoplasmatales. These results expand our understanding of these elusive archaea by revealing their involvement in carbon, nitrogen, and iron cycling, and suggest their potential interactions with Thermoplasmatales on genomic scale.« less

Metabolic versatility of small archaea Micrarchaeota and Parvarchaeota.

PubMed

Chen, Lin-Xing; Méndez-García, Celia; Dombrowski, Nina; Servín-Garcidueñas, Luis E; Eloe-Fadrosh, Emiley A; Fang, Bao-Zhu; Luo, Zhen-Hao; Tan, Sha; Zhi, Xiao-Yang; Hua, Zheng-Shuang; Martinez-Romero, Esperanza; Woyke, Tanja; Huang, Li-Nan; Sánchez, Jesús; Peláez, Ana Isabel; Ferrer, Manuel; Baker, Brett J; Shu, Wen-Sheng

2018-03-01

Small acidophilic archaea belonging to Micrarchaeota and Parvarchaeota phyla are known to physically interact with some Thermoplasmatales members in nature. However, due to a lack of cultivation and limited genomes on hand, their biodiversity, metabolisms, and physiologies remain largely unresolved. Here, we obtained 39 genomes from acid mine drainage (AMD) and hot spring environments around the world. 16S rRNA gene based analyses revealed that Parvarchaeota were only detected in AMD and hot spring habitats, while Micrarchaeota were also detected in others including soil, peat, hypersaline mat, and freshwater, suggesting a considerable higher diversity and broader than expected habitat distribution for this phylum. Despite their small genomes (0.64-1.08 Mb), these archaea may contribute to carbon and nitrogen cycling by degrading multiple saccharides and proteins, and produce ATP via aerobic respiration and fermentation. Additionally, we identified several syntenic genes with homology to those involved in iron oxidation in six Parvarchaeota genomes, suggesting their potential role in iron cycling. However, both phyla lack biosynthetic pathways for amino acids and nucleotides, suggesting that they likely scavenge these biomolecules from the environment and/or other community members. Moreover, low-oxygen enrichments in laboratory confirmed our speculation that both phyla are microaerobic/anaerobic, based on several specific genes identified in them. Furthermore, phylogenetic analyses provide insights into the close evolutionary history of energy related functionalities between both phyla with Thermoplasmatales. These results expand our understanding of these elusive archaea by revealing their involvement in carbon, nitrogen, and iron cycling, and suggest their potential interactions with Thermoplasmatales on genomic scale.

Metabolic versatility of small archaea Micrarchaeota and Parvarchaeota

DOE PAGES

Chen, Lin-Xing; Mendez-Garcia, Celia; Dombrowski, Nina; ...

2017-12-08

Small acidophilic archaea belonging to Micrarchaeota and Parvarchaeota phyla are known to physically interact with some Thermoplasmatales members in nature. However, due to a lack of cultivation and limited genomes on hand, their biodiversity, metabolisms, and physiologies remain largely unresolved. For this study, we obtained 39 genomes from acid mine drainage (AMD) and hot spring environments around the world. 16S rRNA gene based analyses revealed that Parvarchaeota were only detected in AMD and hot spring habitats, while Micrarchaeota were also detected in others including soil, peat, hypersaline mat, and freshwater, suggesting a considerable higher diversity and broader than expected habitatmore » distribution for this phylum. Despite their small genomes (0.64-1.08 Mb), these archaea may contribute to carbon and nitrogen cycling by degrading multiple saccharides and proteins, and produce ATP via aerobic respiration and fermentation. Additionally, we identified several syntenic genes with homology to those involved in iron oxidation in six Parvarchae ota genomes, suggesting their potential role in iron cycling. However, both phyla lack biosynthetic pathways for amino acids and nucleotides, suggesting that they likely scavenge these biomolecules from the environment and/or other community members. Moreover, low-oxygen enrichments in laboratory confirmed our speculation that both phyla are microaerobic/anaerobic, based on several specific genes identified in them. Furthermore, phylogenetic analyses provide insights into the close evolutionary history of energy related functionalities between both phyla with Thermoplasmatales. These results expand our understanding of these elusive archaea by revealing their involvement in carbon, nitrogen, and iron cycling, and suggest their potential interactions with Thermoplasmatales on genomic scale.« less

Representation matters: quantitative behavioral variation in wild worm strains

NASA Astrophysics Data System (ADS)

Brown, Andre

Natural genetic variation in populations is the basis of genome-wide association studies, an approach that has been applied in large studies of humans to study the genetic architecture of complex traits including disease risk. Of course, the traits you choose to measure determine which associated genes you discover (or miss). In large-scale human studies, the measured traits are usually taken as a given during the association step because they are expensive to collect and standardize. Working with the nematode worm C. elegans, we do not have the same constraints. In this talk I will describe how large-scale imaging of worm behavior allows us to develop alternative representations of behavior that vary differently across wild populations. The alternative representations yield novel traits that can be used for genome-wide association studies and may reveal basic properties of the genotype-phenotype map that are obscured if only a small set of fixed traits are used.

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

Detection of DNA Methylation by Whole-Genome Bisulfite Sequencing.

PubMed

Li, Qing; Hermanson, Peter J; Springer, Nathan M

2018-01-01

DNA methylation plays an important role in the regulation of the expression of transposons and genes. Various methods have been developed to assay DNA methylation levels. Bisulfite sequencing is considered to be the "gold standard" for single-base resolution measurement of DNA methylation levels. Coupled with next-generation sequencing, whole-genome bisulfite sequencing (WGBS) allows DNA methylation to be evaluated at a genome-wide scale. Here, we described a protocol for WGBS in plant species with large genomes. This protocol has been successfully applied to assay genome-wide DNA methylation levels in maize and barley. This protocol has also been successfully coupled with sequence capture technology to assay DNA methylation levels in a targeted set of genomic regions.

Parallel and serial computing tools for testing single-locus and epistatic SNP effects of quantitative traits in genome-wide association studies

PubMed Central

Ma, Li; Runesha, H Birali; Dvorkin, Daniel; Garbe, John R; Da, Yang

2008-01-01

Background Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers provide opportunities to detect epistatic SNPs associated with quantitative traits and to detect the exact mode of an epistasis effect. Computational difficulty is the main bottleneck for epistasis testing in large scale GWAS. Results The EPISNPmpi and EPISNP computer programs were developed for testing single-locus and epistatic SNP effects on quantitative traits in GWAS, including tests of three single-locus effects for each SNP (SNP genotypic effect, additive and dominance effects) and five epistasis effects for each pair of SNPs (two-locus interaction, additive × additive, additive × dominance, dominance × additive, and dominance × dominance) based on the extended Kempthorne model. EPISNPmpi is the parallel computing program for epistasis testing in large scale GWAS and achieved excellent scalability for large scale analysis and portability for various parallel computing platforms. EPISNP is the serial computing program based on the EPISNPmpi code for epistasis testing in small scale GWAS using commonly available operating systems and computer hardware. Three serial computing utility programs were developed for graphical viewing of test results and epistasis networks, and for estimating CPU time and disk space requirements. Conclusion The EPISNPmpi parallel computing program provides an effective computing tool for epistasis testing in large scale GWAS, and the epiSNP serial computing programs are convenient tools for epistasis analysis in small scale GWAS using commonly available computer hardware. PMID:18644146

Cloud computing for comparative genomics

PubMed Central

2010-01-01

Background Large comparative genomics studies and tools are becoming increasingly more compute-expensive as the number of available genome sequences continues to rise. The capacity and cost of local computing infrastructures are likely to become prohibitive with the increase, especially as the breadth of questions continues to rise. Alternative computing architectures, in particular cloud computing environments, may help alleviate this increasing pressure and enable fast, large-scale, and cost-effective comparative genomics strategies going forward. To test this, we redesigned a typical comparative genomics algorithm, the reciprocal smallest distance algorithm (RSD), to run within Amazon's Elastic Computing Cloud (EC2). We then employed the RSD-cloud for ortholog calculations across a wide selection of fully sequenced genomes. Results We ran more than 300,000 RSD-cloud processes within the EC2. These jobs were farmed simultaneously to 100 high capacity compute nodes using the Amazon Web Service Elastic Map Reduce and included a wide mix of large and small genomes. The total computation time took just under 70 hours and cost a total of $6,302 USD. Conclusions The effort to transform existing comparative genomics algorithms from local compute infrastructures is not trivial. However, the speed and flexibility of cloud computing environments provides a substantial boost with manageable cost. The procedure designed to transform the RSD algorithm into a cloud-ready application is readily adaptable to similar comparative genomics problems. PMID:20482786

Cloud computing for comparative genomics.

PubMed

Wall, Dennis P; Kudtarkar, Parul; Fusaro, Vincent A; Pivovarov, Rimma; Patil, Prasad; Tonellato, Peter J

2010-05-18

Large comparative genomics studies and tools are becoming increasingly more compute-expensive as the number of available genome sequences continues to rise. The capacity and cost of local computing infrastructures are likely to become prohibitive with the increase, especially as the breadth of questions continues to rise. Alternative computing architectures, in particular cloud computing environments, may help alleviate this increasing pressure and enable fast, large-scale, and cost-effective comparative genomics strategies going forward. To test this, we redesigned a typical comparative genomics algorithm, the reciprocal smallest distance algorithm (RSD), to run within Amazon's Elastic Computing Cloud (EC2). We then employed the RSD-cloud for ortholog calculations across a wide selection of fully sequenced genomes. We ran more than 300,000 RSD-cloud processes within the EC2. These jobs were farmed simultaneously to 100 high capacity compute nodes using the Amazon Web Service Elastic Map Reduce and included a wide mix of large and small genomes. The total computation time took just under 70 hours and cost a total of $6,302 USD. The effort to transform existing comparative genomics algorithms from local compute infrastructures is not trivial. However, the speed and flexibility of cloud computing environments provides a substantial boost with manageable cost. The procedure designed to transform the RSD algorithm into a cloud-ready application is readily adaptable to similar comparative genomics problems.

Transcriptome characterisation of Pinus tabuliformis and evolution of genes in the Pinus phylogeny

PubMed Central

2013-01-01

Background The Chinese pine (Pinus tabuliformis) is an indigenous conifer species in northern China but is relatively underdeveloped as a genomic resource; thus, limiting gene discovery and breeding. Large-scale transcriptome data were obtained using a next-generation sequencing platform to compensate for the lack of P. tabuliformis genomic information. Results The increasing amount of transcriptome data on Pinus provides an excellent resource for multi-gene phylogenetic analysis and studies on how conserved genes and functions are maintained in the face of species divergence. The first P. tabuliformis transcriptome from a normalised cDNA library of multiple tissues and individuals was sequenced in a full 454 GS-FLX run, producing 911,302 sequencing reads. The high quality overlapping expressed sequence tags (ESTs) were assembled into 46,584 putative transcripts, and more than 700 SSRs and 92,000 SNPs/InDels were characterised. Comparative analysis of the transcriptome of six conifer species yielded 191 orthologues, from which we inferred a phylogenetic tree, evolutionary patterns and calculated rates of gene diversion. We also identified 938 fast evolving sequences that may be useful for identifying genes that perhaps evolved in response to positive selection and might be responsible for speciation in the Pinus lineage. Conclusions A large collection of high-quality ESTs was obtained, de novo assembled and characterised, which represents a dramatic expansion of the current transcript catalogues of P. tabuliformis and which will gradually be applied in breeding programs of P. tabuliformis. Furthermore, these data will facilitate future studies of the comparative genomics of P. tabuliformis and other related species. PMID:23597112

Pfarao: a web application for protein family analysis customized for cytoskeletal and motor proteins (CyMoBase)

PubMed Central

Odronitz, Florian; Kollmar, Martin

2006-01-01

Background Annotation of protein sequences of eukaryotic organisms is crucial for the understanding of their function in the cell. Manual annotation is still by far the most accurate way to correctly predict genes. The classification of protein sequences, their phylogenetic relation and the assignment of function involves information from various sources. This often leads to a collection of heterogeneous data, which is hard to track. Cytoskeletal and motor proteins consist of large and diverse superfamilies comprising up to several dozen members per organism. Up to date there is no integrated tool available to assist in the manual large-scale comparative genomic analysis of protein families. Description Pfarao (Protein Family Application for Retrieval, Analysis and Organisation) is a database driven online working environment for the analysis of manually annotated protein sequences and their relationship. Currently, the system can store and interrelate a wide range of information about protein sequences, species, phylogenetic relations and sequencing projects as well as links to literature and domain predictions. Sequences can be imported from multiple sequence alignments that are generated during the annotation process. A web interface allows to conveniently browse the database and to compile tabular and graphical summaries of its content. Conclusion We implemented a protein sequence-centric web application to store, organize, interrelate, and present heterogeneous data that is generated in manual genome annotation and comparative genomics. The application has been developed for the analysis of cytoskeletal and motor proteins (CyMoBase) but can easily be adapted for any protein. PMID:17134497

Global analysis of exon creation versus loss and the role of alternative splicing in 17 vertebrate genomes

PubMed Central

Alekseyenko, Alexander V.; Kim, Namshin; Lee, Christopher J.

2007-01-01

Association of alternative splicing (AS) with accelerated rates of exon evolution in some organisms has recently aroused widespread interest in its role in evolution of eukaryotic gene structure. Previous studies were limited to analysis of exon creation or lost events in mouse and/or human only. Our multigenome approach provides a way for (1) distinguishing creation and loss events on the large scale; (2) uncovering details of the evolutionary mechanisms involved; (3) estimating the corresponding rates over a wide range of evolutionary times and organisms; and (4) assessing the impact of AS on those evolutionary rates. We use previously unpublished independent analyses of alternative splicing in five species (human, mouse, dog, cow, and zebrafish) from the ASAP database combined with genomewide multiple alignment of 17 genomes to analyze exon creation and loss of both constitutively and alternatively spliced exons in mammals, fish, and birds. Our analysis provides a comprehensive database of exon creation and loss events over 360 million years of vertebrate evolution, including tens of thousands of alternative and constitutive exons. We find that exon inclusion level is inversely related to the rate of exon creation. In addition, we provide a detailed in-depth analysis of mechanisms of exon creation and loss, which suggests that a large fraction of nonrepetitive created exons are results of ab initio creation from purely intronic sequences. Our data indicate an important role for alternative splicing in creation of new exons and provide a useful novel database resource for future genome evolution research. PMID:17369312

CAS-viewer: web-based tool for splicing-guided integrative analysis of multi-omics cancer data.

PubMed

Han, Seonggyun; Kim, Dongwook; Kim, Youngjun; Choi, Kanghoon; Miller, Jason E; Kim, Dokyoon; Lee, Younghee

2018-04-20

The Cancer Genome Atlas (TCGA) project is a public resource that provides transcriptomic, DNA sequence, methylation, and clinical data for 33 cancer types. Transforming the large size and high complexity of TCGA cancer genome data into integrated knowledge can be useful to promote cancer research. Alternative splicing (AS) is a key regulatory mechanism of genes in human cancer development and in the interaction with epigenetic factors. Therefore, AS-guided integration of existing TCGA data sets will make it easier to gain insight into the genetic architecture of cancer risk and related outcomes. There are already existing tools analyzing and visualizing alternative mRNA splicing patterns for large-scale RNA-seq experiments. However, these existing web-based tools are limited to the analysis of individual TCGA data sets at a time, such as only transcriptomic information. We implemented CAS-viewer (integrative analysis of Cancer genome data based on Alternative Splicing), a web-based tool leveraging multi-cancer omics data from TCGA. It illustrates alternative mRNA splicing patterns along with methylation, miRNAs, and SNPs, and then provides an analysis tool to link differential transcript expression ratio to methylation, miRNA, and splicing regulatory elements for 33 cancer types. Moreover, one can analyze AS patterns with clinical data to identify potential transcripts associated with different survival outcome for each cancer. CAS-viewer is a web-based application for transcript isoform-driven integration of multi-omics data in multiple cancer types and will aid in the visualization and possible discovery of biomarkers for cancer by integrating multi-omics data from TCGA.

A Case Study into Microbial Genome Assembly Gap Sequences and Finishing Strategies.

PubMed

Utturkar, Sagar M; Klingeman, Dawn M; Hurt, Richard A; Brown, Steven D

2017-01-01

This study characterized regions of DNA which remained unassembled by either PacBio and Illumina sequencing technologies for seven bacterial genomes. Two genomes were manually finished using bioinformatics and PCR/Sanger sequencing approaches and regions not assembled by automated software were analyzed. Gaps present within Illumina assemblies mostly correspond to repetitive DNA regions such as multiple rRNA operon sequences. PacBio gap sequences were evaluated for several properties such as GC content, read coverage, gap length, ability to form strong secondary structures, and corresponding annotations. Our hypothesis that strong secondary DNA structures blocked DNA polymerases and contributed to gap sequences was not accepted. PacBio assemblies had few limitations overall and gaps were explained as cumulative effect of lower than average sequence coverage and repetitive sequences at contig termini. An important aspect of the present study is the compilation of biological features that interfered with assembly and included active transposons, multiple plasmid sequences, phage DNA integration, and large sequence duplication. Our targeted genome finishing approach and systematic evaluation of the unassembled DNA will be useful for others looking to close, finish, and polish microbial genome sequences.