Hirsch, Cory D; Evans, Joseph; Buell, C Robin; Hirsch, Candice N
Technology and software improvements in the last decade now provide methodologies to access the genome sequence of not only a single accession, but also multiple accessions of plant species. This provides a means to interrogate species diversity at the genome level. Ample diversity among accessions in a collection of species can be found, including single-nucleotide polymorphisms, insertions and deletions, copy number variation and presence/absence variation. For species with small, non-repetitive rich genomes, re-sequencing of query accessions is robust, highly informative, and economically feasible. However, for species with moderate to large sized repetitive-rich genomes, technical and economic barriers prevent en masse genome re-sequencing of accessions. Multiple approaches to access a focused subset of loci in species with larger genomes have been developed, including reduced representation sequencing, exome capture and transcriptome sequencing. Collectively, these approaches have enabled interrogation of diversity on a genome scale for large plant genomes, including crop species important to worldwide food security. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please email: firstname.lastname@example.org.
Trakadis Yannis J
Full Text Available Abstract Background The revolution in DNA sequencing technologies over the past decade has made it feasible to sequence an individual’s whole genome at a relatively low cost. The potential value of the information generated by genomic technologies for medicine and society is enormous. However, in order for exome sequencing, and eventually whole genome sequencing, to be implemented clinically, a number of major challenges need to be overcome. For instance, obtaining meaningful informed-consent, managing incidental findings and the great volume of data generated (including multiple findings with uncertain clinical significance, re-interpreting the genomic data and providing additional counselling to patients as genetic knowledge evolves are issues that need to be addressed. It appears that medical genetics is shifting from the present “phenotype-first” medical model to a “data-first” model which leads to multiple complexities. Discussion This manuscript discusses the different challenges associated with integrating genomic technologies into clinical practice and describes a “phenotype-first” approach, namely, “Individualized Mutation-weighed Phenotype Search”, and its benefits. The proposed approach allows for a more efficient prioritization of the genes to be tested in a clinical lab based on both the patient’s phenotype and his/her entire genomic data. It simplifies “informed-consent” for clinical use of genomic technologies and helps to protect the patient’s autonomy and privacy. Overall, this approach could potentially render widespread use of genomic technologies, in the immediate future, practical, ethical and clinically useful. Summary The “Individualized Mutation-weighed Phenotype Search” approach allows for an incremental integration of genomic technologies into clinical practice. It ensures that we do not over-medicalize genomic data but, rather, continue our current medical model which is based on serving
Full Text Available The development of the dorsal vessel in Drosophila is one of the first systems in which key mechanisms regulating cardiogenesis have been defined in great detail at the genetic and molecular level. Due to evolutionary conservation, these findings have also provided major inputs into studies of cardiogenesis in vertebrates. Many of the major components that control Drosophila cardiogenesis were discovered based on candidate gene approaches and their functions were defined by employing the outstanding genetic tools and molecular techniques available in this system. More recently, approaches have been taken that aim to interrogate the entire genome in order to identify novel components and describe genomic features that are pertinent to the regulation of heart development. Apart from classical forward genetic screens, the availability of the thoroughly annotated Drosophila genome sequence made new genome-wide approaches possible, which include the generation of massive numbers of RNA interference (RNAi reagents that were used in forward genetic screens, as well as studies of the transcriptomes and proteomes of the developing heart under normal and experimentally manipulated conditions. Moreover, genome-wide chromatin immunoprecipitation experiments have been performed with the aim to define the full set of genomic binding sites of the major cardiogenic transcription factors, their relevant target genes, and a more complete picture of the regulatory network that drives cardiogenesis. This review will give an overview on these genome-wide approaches to Drosophila heart development and on computational analyses of the obtained information that ultimately aim to provide a description of this process at the systems level.
Carillier-Jacquin, Céline; Larroque, Hélène; Robert-Granié, Christèle
Genomic best linear unbiased prediction methods assume that all markers explain the same fraction of the genetic variance and do not account effectively for genes with major effects such as the α s1 casein polymorphism in dairy goats. In this study, we investigated methods to include the available α s1 casein genotype effect in genomic evaluations of French dairy goats. First, the α s1 casein genotype was included as a fixed effect in genomic evaluation models based only on bucks that were genotyped at the α s1 casein locus. Less than 1 % of the females with phenotypes were genotyped at the α s1 casein gene. Thus, to incorporate these female phenotypes in the genomic evaluation, two methods that allowed for this large number of missing α s1 casein genotypes were investigated. Probabilities for each possible α s1 casein genotype were first estimated for each female of unknown genotype based on iterative peeling equations. The second method is based on a multiallelic gene content approach. For each model tested, we used three datasets each divided into a training and a validation set: (1) two-breed population (Alpine + Saanen), (2) Alpine population, and (3) Saanen population. The α s1 casein genotype had a significant effect on milk yield, fat content and protein content. Including an α s1 casein effect in genetic and genomic evaluations based only on male known α s1 casein genotypes improved accuracies (from 6 to 27 %). In genomic evaluations based on all female phenotypes, the gene content approach performed better than the other tested methods but the improvement in accuracy was only slightly better (from 1 to 14 %) than that of a genomic model without the α s1 casein effect. Including the α s1 casein effect in a genomic evaluation model for French dairy goats is possible and useful to improve accuracy. Difficulties in predicting the genotypes for ungenotyped animals limited the improvement in accuracy of the obtained estimated breeding values.
Lack, Justin B; Cardeno, Charis M; Crepeau, Marc W; Taylor, William; Corbett-Detig, Russell B; Stevens, Kristian A; Langley, Charles H; Pool, John E
Hundreds of wild-derived Drosophila melanogaster genomes have been published, but rigorous comparisons across data sets are precluded by differences in alignment methodology. The most common approach to reference-based genome assembly is a single round of alignment followed by quality filtering and variant detection. We evaluated variations and extensions of this approach and settled on an assembly strategy that utilizes two alignment programs and incorporates both substitutions and short indels to construct an updated reference for a second round of mapping prior to final variant detection. Utilizing this approach, we reassembled published D. melanogaster population genomic data sets and added unpublished genomes from several sub-Saharan populations. Most notably, we present aligned data from phase 3 of the Drosophila Population Genomics Project (DPGP3), which provides 197 genomes from a single ancestral range population of D. melanogaster (from Zambia). The large sample size, high genetic diversity, and potentially simpler demographic history of the DPGP3 sample will make this a highly valuable resource for fundamental population genetic research. The complete set of assemblies described here, termed the Drosophila Genome Nexus, presently comprises 623 consistently aligned genomes and is publicly available in multiple formats with supporting documentation and bioinformatic tools. This resource will greatly facilitate population genomic analysis in this model species by reducing the methodological differences between data sets. Copyright © 2015 by the Genetics Society of America.
Jorge A Huete-Pérez
Full Text Available Recent advances in genomic and post-genomic technologies have now established the new standard in medical and biotechnological research. The introduction of next-generation sequencing, NGS,has resulted in the generation of thousands of genomes from all domains of life, including the genomes of complex uncultured microbial communities revealed through metagenomics. Although the application of genomics to marine biodiversity remains poorly developed overall, some noteworthy progress has been made in recent years. The genomes of various model marine organisms have been published and a few more are underway. In addition, the recent large-scale analysis of marine microbes, along with transcriptomic and proteomic approaches to the study of teleost fishes, mollusks and crustaceans, to mention a few, has provided a better understanding of phenotypic variability and functional genomics. The past few years have also seen advances in applications relevant to marine aquaculture and fisheries. In this review we introduce several examples of recent discoveries and progress made towards engendering genomic resources aimed at enhancing our understanding of marine biodiversity and promoting the development of aquaculture. Finally, we discuss the need for auspicious science policies to address challenges confronting smaller nations in the appropriate oversight of this growing domain as they strive to guarantee food security and conservation of their natural resources.
Taylor, Alison M; Shih, Juliann; Ha, Gavin; Gao, Galen F; Zhang, Xiaoyang; Berger, Ashton C; Schumacher, Steven E; Wang, Chen; Hu, Hai; Liu, Jianfang; Lazar, Alexander J; Cherniack, Andrew D; Beroukhim, Rameen; Meyerson, Matthew
Aneuploidy, whole chromosome or chromosome arm imbalance, is a near-universal characteristic of human cancers. In 10,522 cancer genomes from The Cancer Genome Atlas, aneuploidy was correlated with TP53 mutation, somatic mutation rate, and expression of proliferation genes. Aneuploidy was anti-correlated with expression of immune signaling genes, due to decreased leukocyte infiltrates in high-aneuploidy samples. Chromosome arm-level alterations show cancer-specific patterns, including loss of chromosome arm 3p in squamous cancers. We applied genome engineering to delete 3p in lung cells, causing decreased proliferation rescued in part by chromosome 3 duplication. This study defines genomic and phenotypic correlates of cancer aneuploidy and provides an experimental approach to study chromosome arm aneuploidy. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Muhammad N. Sattar
Full Text Available The genetic modifications through breeding of crop plants have long been used to improve the yield and quality. However, precise genome editing (GE could be a very useful supplementary tool for improvement of crop plants by targeted genome modifications. Various GE techniques including ZFNs (zinc finger nucleases, TALENs (transcription activator-like effector nucleases, and most recently clustered regularly interspaced short palindromic repeats (CRISPR/Cas9 (CRISPR-associated protein 9-based approaches have been successfully employed for various crop plants including fruit trees. CRISPR/Cas9-based approaches hold great potential in GE due to their simplicity, competency, and versatility over other GE techniques. However, to the best of our knowledge no such genetic improvement has ever been developed in date palm—an important fruit crop in Oasis agriculture. The applications of CRISPR/Cas9 can be a challenging task in date palm GE due to its large and complex genome, high rate of heterozygosity and outcrossing, in vitro regeneration and screening of mutants, high frequency of single-nucleotide polymorphism in the genome and ultimately genetic instability. In this review, we addressed the potential application of CRISPR/Cas9-based approaches in date palm GE to improve the sustainable date palm production. The availability of the date palm whole genome sequence has made it feasible to use CRISPR/Cas9 GE approach for genetic improvement in this species. Moreover, the future prospects of GE application in date palm are also addressed in this review.
Su, G; Ma, P; Nielsen, U S; Aamand, G P; Wiggans, G; Guldbrandtsen, B; Lund, M S
Small reference populations limit the accuracy of genomic prediction in numerically small breeds, such like Danish Jersey. The objective of this study was to investigate two approaches to improve genomic prediction by increasing size of reference population in Danish Jersey. The first approach was to include North American Jersey bulls in Danish Jersey reference population. The second was to genotype cows and use them as reference animals. The validation of genomic prediction was carried out on bulls and cows, respectively. In validation on bulls, about 300 Danish bulls (depending on traits) born in 2005 and later were used as validation data, and the reference populations were: (1) about 1050 Danish bulls, (2) about 1050 Danish bulls and about 1150 US bulls. In validation on cows, about 3000 Danish cows from 87 young half-sib families were used as validation data, and the reference populations were: (1) about 1250 Danish bulls, (2) about 1250 Danish bulls and about 1150 US bulls, (3) about 1250 Danish bulls and about 4800 cows, (4) about 1250 Danish bulls, 1150 US bulls and 4800 Danish cows. Genomic best linear unbiased prediction model was used to predict breeding values. De-regressed proofs were used as response variables. In the validation on bulls for eight traits, the joint DK-US bull reference population led to higher reliability of genomic prediction than the DK bull reference population for six traits, but not for fertility and longevity. Averaged over the eight traits, the gain was 3 percentage points. In the validation on cows for six traits (fertility and longevity were not available), the gain from inclusion of US bull in reference population was 6.6 percentage points in average over the six traits, and the gain from inclusion of cows was 8.2 percentage points. However, the gains from cows and US bulls were not accumulative. The total gain of including both US bulls and Danish cows was 10.5 percentage points. The results indicate that sharing reference
Jun, Se-Ran; Wassenaar, Trudy M; Nookaew, Intawat; Hauser, Loren; Wanchai, Visanu; Land, Miriam; Timm, Collin M; Lu, Tse-Yuan S; Schadt, Christopher W; Doktycz, Mitchel J; Pelletier, Dale A; Ussery, David W
The Pseudomonas genus contains a metabolically versatile group of organisms that are known to occupy numerous ecological niches, including the rhizosphere and endosphere of many plants. Their diversity influences the phylogenetic diversity and heterogeneity of these communities. On the basis of average amino acid identity, comparative genome analysis of >1,000 Pseudomonas genomes, including 21 Pseudomonas strains isolated from the roots of native Populus deltoides (eastern cottonwood) trees resulted in consistent and robust genomic clusters with phylogenetic homogeneity. All Pseudomonas aeruginosa genomes clustered together, and these were clearly distinct from other Pseudomonas species groups on the basis of pangenome and core genome analyses. In contrast, the genomes of Pseudomonas fluorescens were organized into 20 distinct genomic clusters, representing enormous diversity and heterogeneity. Most of our 21 Populus-associated isolates formed three distinct subgroups within the major P. fluorescens group, supported by pathway profile analysis, while two isolates were more closely related to Pseudomonas chlororaphis and Pseudomonas putida. Genes specific to Populus-associated subgroups were identified. Genes specific to subgroup 1 include several sensory systems that act in two-component signal transduction, a TonB-dependent receptor, and a phosphorelay sensor. Genes specific to subgroup 2 contain hypothetical genes, and genes specific to subgroup 3 were annotated with hydrolase activity. This study justifies the need to sequence multiple isolates, especially from P. fluorescens, which displays the most genetic variation, in order to study functional capabilities from a pangenomic perspective. This information will prove useful when choosing Pseudomonas strains for use to promote growth and increase disease resistance in plants. Copyright © 2015 Jun et al.
Martin P Schilling
Full Text Available 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-scale data acquisition and processing. Here we assess genomic sampling biases and the effects of various population-level data filtering strategies in a genotyping-by-sequencing (GBS protocol. We focus on data from two species of Populus, because this genus has a relatively small genome and is emerging as a target for population genomic studies. We estimate the proportions and patterns of genomic sampling by examining the Populus trichocarpa genome (Nisqually-1, and demonstrate a pronounced bias towards coding regions when using the methylation-sensitive ApeKI restriction enzyme in this species. Using population-level data from a closely related species (P. tremuloides, we also investigate various approaches for filtering GBS data to retain high-depth, informative SNPs that can be used for population genetic analyses. We find a data filter that includes the designation of ambiguous alleles resulted in metrics of population structure and Hardy-Weinberg equilibrium that were most consistent with previous studies of the same populations based on other genetic markers. Analyses of the filtered data (27,910 SNPs also resulted in patterns of heterozygosity and population structure similar to a previous study using microsatellites. Our application demonstrates that technically and analytically simple approaches can readily be developed for population genomics of natural populations.
Stucki, S; Orozco-terWengel, P; Forester, B R; Duruz, S; Colli, L; Masembe, C; Negrini, R; Landguth, E; Jones, M R; Bruford, M W; Taberlet, P; Joost, S
With the increasing availability of both molecular and topo-climatic data, the main challenges facing landscape genomics - that is the combination of landscape ecology with population genomics - include processing large numbers of models and distinguishing between selection and demographic processes (e.g. population structure). Several methods address the latter, either by estimating a null model of population history or by simultaneously inferring environmental and demographic effects. Here we present samβada, an approach designed to study signatures of local adaptation, with special emphasis on high performance computing of large-scale genetic and environmental data sets. samβada identifies candidate loci using genotype-environment associations while also incorporating multivariate analyses to assess the effect of many environmental predictor variables. This enables the inclusion of explanatory variables representing population structure into the models to lower the occurrences of spurious genotype-environment associations. In addition, samβada calculates local indicators of spatial association for candidate loci to provide information on whether similar genotypes tend to cluster in space, which constitutes a useful indication of the possible kinship between individuals. To test the usefulness of this approach, we carried out a simulation study and analysed a data set from Ugandan cattle to detect signatures of local adaptation with samβada, bayenv, lfmm and an F ST outlier method (FDIST approach in arlequin) and compare their results. samβada - an open source software for Windows, Linux and Mac OS X available at http://lasig.epfl.ch/sambada - outperforms other approaches and better suits whole-genome sequence data processing. © 2016 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd.
The ability to manipulate the genome with precise spatial and nucleotide resolution (genome editing) has been a powerful research tool. In the past decade, the tools and expertise for using genome editing in human somatic cells and pluripotent cells have increased to such an extent that the approach is now being developed widely as a strategy to treat human disease. The fundamental process depends on creating a site-specific DNA double-strand break (DSB) in the genome and then allowing the cell's endogenous DSB repair machinery to fix the break such that precise nucleotide changes are made to the DNA sequence. With the development and discovery of several different nuclease platforms and increasing knowledge of the parameters affecting different genome editing outcomes, genome editing frequencies now reach therapeutic relevance for a wide variety of diseases. Moreover, there is a series of complementary approaches to assessing the safety and toxicity of any genome editing process, irrespective of the underlying nuclease used. Finally, the development of genome editing has raised the issue of whether it should be used to engineer the human germline. Although such an approach could clearly prevent the birth of people with devastating and destructive genetic diseases, questions remain about whether human society is morally responsible enough to use this tool.
Galperin, Michael Y; Kristensen, David M; Makarova, Kira S; Wolf, Yuri I; Koonin, Eugene V
For the past 20 years, the Clusters of Orthologous Genes (COG) database had been a popular tool for microbial genome annotation and comparative genomics. Initially created for the purpose of evolutionary classification of protein families, the COG have been used, apart from straightforward functional annotation of sequenced genomes, for such tasks as (i) unification of genome annotation in groups of related organisms; (ii) identification of missing and/or undetected genes in complete microbial genomes; (iii) analysis of genomic neighborhoods, in many cases allowing prediction of novel functional systems; (iv) analysis of metabolic pathways and prediction of alternative forms of enzymes; (v) comparison of organisms by COG functional categories; and (vi) prioritization of targets for structural and functional characterization. Here we review the principles of the COG approach and discuss its key advantages and drawbacks in microbial genome analysis. Published by Oxford University Press 2017. This work is written by US Government employees and is in the public domain in the US.
Spatiotemporal organization of chromatin within the nucleus has so far remained elusive. Live visualization of nuclear remodeling could be a promising approach to understand its functional relevance in genome functions and mechanisms regulating genome architecture. Recent technological advances in live imaging of chromosomes begun to explore the biological roles of the movement of the chromatin within the nucleus. Here I describe a new technique, called TALE-mediated genome visualization (TGV), which allows us to visualize endogenous repetitive sequence including centromeric, pericentromeric, and telomeric repeats in living cells.
Visendi, Paul; Berkman, Paul J; Hayashi, Satomi; Golicz, Agnieszka A; Bayer, Philipp E; Ruperao, Pradeep; Hurgobin, Bhavna; Montenegro, Juan; Chan, Chon-Kit Kenneth; Staňková, Helena; Batley, Jacqueline; Šimková, Hana; Doležel, Jaroslav; Edwards, David
There has been an exponential growth in the number of genome sequencing projects since the introduction of next generation DNA sequencing technologies. Genome projects have increasingly involved assembly of whole genome data which produces inferior assemblies compared to traditional Sanger sequencing of genomic fragments cloned into bacterial artificial chromosomes (BACs). While whole genome shotgun sequencing using next generation sequencing (NGS) is relatively fast and inexpensive, this method is extremely challenging for highly complex genomes, where polyploidy or high repeat content confounds accurate assembly, or where a highly accurate 'gold' reference is required. Several attempts have been made to improve genome sequencing approaches by incorporating NGS methods, to variable success. We present the application of a novel BAC sequencing approach which combines indexed pools of BACs, Illumina paired read sequencing, a sequence assembler specifically designed for complex BAC assembly, and a custom bioinformatics pipeline. We demonstrate this method by sequencing and assembling BAC cloned fragments from bread wheat and sugarcane genomes. We demonstrate that our assembly approach is accurate, robust, cost effective and scalable, with applications for complete genome sequencing in large and complex genomes.
Bozinovic, Goran; Oleksiak, Marjorie F.
Transcriptomics and population genomics are two complementary genomic approaches that can be used to gain insight into pollutant effects in natural populations. Transcriptomics identify altered gene expression pathways while population genomics approaches more directly target the causative genomic polymorphisms. Neither approach is restricted to a pre-determined set of genes or loci. Instead, both approaches allow a broad overview of genomic processes. Transcriptomics and population genomic approaches have been used to explore genomic responses in populations of fish from polluted environments and have identified sets of candidate genes and loci that appear biologically important in response to pollution. Often differences in gene expression or loci between polluted and reference populations are not conserved among polluted populations suggesting a biological complexity that we do not yet fully understand. As genomic approaches become less expensive with the advent of new sequencing and genotyping technologies, they will be more widely used in complimentary studies. However, while these genomic approaches are immensely powerful for identifying candidate gene and loci, the challenge of determining biological mechanisms that link genotypes and phenotypes remains. PMID:21072843
McEwen, Jean E; Boyer, Joy T; Sun, Kathie Y
The ethical landscape in the field of genomics is rapidly shifting. Plummeting sequencing costs, along with ongoing advances in bioinformatics, now make it possible to generate an enormous volume of genomic data about vast numbers of people. The informational richness, complexity, and frequently uncertain meaning of these data, coupled with evolving norms surrounding the sharing of data and samples and persistent privacy concerns, have generated a range of approaches to the ethical management of genomic information. As calls increase for the expanded use of broad or even open consent, and as controversy grows about how best to handle incidental genomic findings, these approaches, informed by normative analysis and empirical data, will continue to evolve alongside the science. Published by Elsevier Ltd.
Fuentes-Pardo, Angela P; Ruzzante, Daniel E
Whole-genome resequencing (WGR) is a powerful method for addressing fundamental evolutionary biology questions that have not been fully resolved using traditional methods. WGR includes four approaches: the sequencing of individuals to a high depth of coverage with either unresolved or resolved haplotypes, the sequencing of population genomes to a high depth by mixing equimolar amounts of unlabelled-individual DNA (Pool-seq) and the sequencing of multiple individuals from a population to a low depth (lcWGR). These techniques require the availability of a reference genome. This, along with the still high cost of shotgun sequencing and the large demand for computing resources and storage, has limited their implementation in nonmodel species with scarce genomic resources and in fields such as conservation biology. Our goal here is to describe the various WGR methods, their pros and cons and potential applications in conservation biology. WGR offers an unprecedented marker density and surveys a wide diversity of genetic variations not limited to single nucleotide polymorphisms (e.g., structural variants and mutations in regulatory elements), increasing their power for the detection of signatures of selection and local adaptation as well as for the identification of the genetic basis of phenotypic traits and diseases. Currently, though, no single WGR approach fulfils all requirements of conservation genetics, and each method has its own limitations and sources of potential bias. We discuss proposed ways to minimize such biases. We envision a not distant future where the analysis of whole genomes becomes a routine task in many nonmodel species and fields including conservation biology. © 2017 John Wiley & Sons Ltd.
Fariello, María Inés; Boitard, Simon; Mercier, Sabine; Robelin, David; Faraut, Thomas; Arnould, Cécile; Recoquillay, Julien; Bouchez, Olivier; Salin, Gérald; Dehais, Patrice; Gourichon, David; Leroux, Sophie; Pitel, Frédérique; Leterrier, Christine; SanCristobal, Magali
Detecting genomic footprints of selection is an important step in the understanding of evolution. Accounting for linkage disequilibrium in genome scans increases detection power, but haplotype-based methods require individual genotypes and are not applicable on pool-sequenced samples. We propose to take advantage of the local score approach to account for linkage disequilibrium in genome scans for selection, cumulating (possibly small) signals from single markers over a genomic segment, to clearly pinpoint a selection signal. Using computer simulations, we demonstrate that this approach detects selection with higher power than several state-of-the-art single-marker, windowing or haplotype-based approaches. We illustrate this on two benchmark data sets including individual genotypes, for which we obtain similar results with the local score and one haplotype-based approach. Finally, we apply the local score approach to Pool-Seq data obtained from a divergent selection experiment on behaviour in quail and obtain precise and biologically coherent selection signals: while competing methods fail to highlight any clear selection signature, our method detects several regions involving genes known to act on social responsiveness or autistic traits. Although we focus here on the detection of positive selection from multiple population data, the local score approach is general and can be applied to other genome scans for selection or other genomewide analyses such as GWAS. © 2017 John Wiley & Sons Ltd.
Full Text Available Abstract Understanding the evolutionary plasticity of the genome requires a global, comparative approach in which genetic events are considered both in a phylogenetic framework and with regard to population genetics and environmental variables. In the mechanisms that generate adaptive and non-adaptive changes in genomes, segmental duplications (duplication of individual genes or genomic regions and polyploidization (whole genome duplications are well-known driving forces. The probability of fixation and maintenance of duplicates depends on many variables, including population sizes and selection regimes experienced by the corresponding genes: a combination of stochastic and adaptive mechanisms has shaped all genomes. A survey of experimental work shows that the distinction made between fixation and maintenance of duplicates still needs to be conceptualized and mathematically modeled. Here we review the mechanisms that increase or decrease the probability of fixation or maintenance of duplicated genes, and examine the outcome of these events on the adaptation of the organisms. Reviewers This article was reviewed by Dr. Etienne Joly, Dr. Lutz Walter and Dr. W. Ford Doolittle.
Frederico Schmitt Kremer
Full Text Available Abstract The introduction of next-generation sequencing (NGS had a significant effect on the availability of genomic information, leading to an increase in the number of sequenced genomes from a large spectrum of organisms. Unfortunately, due to the limitations implied by the short-read sequencing platforms, most of these newly sequenced genomes remained as “drafts”, incomplete representations of the whole genetic content. The previous genome sequencing studies indicated that finishing a genome sequenced by NGS, even bacteria, may require additional sequencing to fill the gaps, making the entire process very expensive. As such, several in silico approaches have been developed to optimize the genome assemblies and facilitate the finishing process. The present review aims to explore some free (open source, in many cases tools that are available to facilitate genome finishing.
Kremer, Frederico Schmitt; McBride, Alan John Alexander; Pinto, Luciano da Silva
The introduction of next-generation sequencing (NGS) had a significant effect on the availability of genomic information, leading to an increase in the number of sequenced genomes from a large spectrum of organisms. Unfortunately, due to the limitations implied by the short-read sequencing platforms, most of these newly sequenced genomes remained as "drafts", incomplete representations of the whole genetic content. The previous genome sequencing studies indicated that finishing a genome sequenced by NGS, even bacteria, may require additional sequencing to fill the gaps, making the entire process very expensive. As such, several in silico approaches have been developed to optimize the genome assemblies and facilitate the finishing process. The present review aims to explore some free (open source, in many cases) tools that are available to facilitate genome finishing.
Full Text Available The emergence and re-emergence of plant pathogenic microorganisms are processes that imply perturbations in both host and pathogen ecological niches. Global change is largely assumed to drive the emergence of new etiological agents by altering the equilibrium of the ecological habitats which in turn places hosts more in contact with pathogen reservoirs. In this context, the number of epidemics is expected to increase dramatically in the next coming decades both in wild and crop plants. Under these considerations, the identification of the genetic variants underlying natural variation of resistance is a pre-requisite to estimate the adaptive potential of wild plant populations and to develop new breeding resistant cultivars. On the other hand, the prediction of pathogen's genetic determinants underlying disease emergence can help to identify plant resistance alleles. In the genomic era, whole genome sequencing combined with the development of statistical methods led to the emergence of Genome Wide Association (GWA mapping, a powerful tool for detecting genomic regions associated with natural variation of disease resistance in both wild and cultivated plants. However, GWA mapping has been less employed for the detection of genetic variants associated with pathogenicity in microbes. Here, we reviewed GWA studies performed either in plants or in pathogenic microorganisms (bacteria, fungi and oomycetes. In addition, we highlighted the benefits and caveats of the emerging joint GWA mapping approach that allows for the simultaneous identification of genes interacting between genomes of both partners. Finally, based on co-evolutionary processes in wild populations, we highlighted a phenotyping-free joint GWA mapping approach as a promising tool for describing the molecular landscape underlying plant - microbe interactions.
Wang, Qingguo; Jia, Peilin; Zhao, Zhongming
Fueled by widespread applications of high-throughput next generation sequencing (NGS) technologies and urgent need to counter threats of pathogenic viruses, large-scale studies were conducted recently to investigate virus integration in host genomes (for example, human tumor genomes) that may cause carcinogenesis or other diseases. A limiting factor in these studies, however, is rapid virus evolution and resulting polymorphisms, which prevent reads from aligning readily to commonly used virus reference genomes, and, accordingly, make virus integration sites difficult to detect. Another confounding factor is host genomic instability as a result of virus insertions. To tackle these challenges and improve our capability to identify cryptic virus-host fusions, we present a new approach that detects Virus intEgration sites through iterative Reference SEquence customization (VERSE). To the best of our knowledge, VERSE is the first approach to improve detection through customizing reference genomes. Using 19 human tumors and cancer cell lines as test data, we demonstrated that VERSE substantially enhanced the sensitivity of virus integration site detection. VERSE is implemented in the open source package VirusFinder 2 that is available at http://bioinfo.mc.vanderbilt.edu/VirusFinder/.
Full Text Available Abstract Background DNA rearrangement events have been widely studied in comparative genomic for many years. The importance of these events resides not only in the study about relatedness among different species, but also to determine the mechanisms behind evolution. Although there are many methods to identify genome-rearrangements (GR, the refinement of their borders has become a huge challenge. Until now no accepted method exists to achieve accurate fine-tuning: i.e. the notion of breakpoint (BP is still an open issue, and despite repeated regions are vital to understand evolution they are not taken into account in most of the GR detection and refinement methods. Methods and results We propose a method to refine the borders of GR including repeated regions. Instead of removing these repetitions to facilitate computation, we take advantage of them using a consensus alignment sequence of the repeated region in between two blocks. Using the concept of identity vectors for Synteny Blocks (SB and repetitions, a Finite State Machine is designed to detect transition points in the difference between such vectors. The method does not force the BP to be a region or a point but depends on the alignment transitions within the SBs and repetitions. Conclusion The accurate definition of the borders of SB and repeated genomic regions and consequently the detection of BP might help to understand the evolutionary model of species. In this manuscript we present a new proposal for such a refinement. Features of the SBs borders and BPs are different and fit with what is expected. SBs with more diversity in annotations and BPs short and richer in DNA replication and stress response, which are strongly linked with rearrangements.
Apr 20, 2009 ... Here, we reviewed recent advances in the efforts to understand ... expression regulation in E. histolytica by using genomic approaches based on microarray technology ... tic abscesses that result in approximately 70,000 -.
Full Text Available Background/objectives: Whole genome sequencing (WGS has proven to be a powerful subtyping tool for foodborne pathogenic bacteria like L. monocytogenes. The interests of genome-scale analysis for national surveillance, outbreak detection or source tracking has been largely documented. The genomic data however can be exploited with many different bioinformatics methods like single nucleotide polymorphism (SNP, core-genome multi locus sequence typing (cgMLST, whole-genome multi locus sequence typing (wgMLST or multi locus predicted protein sequence typing (MLPPST on either core-genome (cgMLPPST or pan-genome (wgMLPPST. Currently, there are little comparisons studies of these different analytical approaches. Our objective was to assess and compare different genomic methods that can be implemented in order to cluster isolates of L. monocytogenes.Methods: The clustering methods were evaluated on a collection of 207 L. monocytogenes genomes of food origin representative of the genetic diversity of the Anses collection. The trees were then compared using robust statistical analyses.Results: The backward comparability between conventional typing methods and genomic methods revealed a near-perfect concordance. The importance of selecting a proper reference when calling SNPs was highlighted, although distances between strains remained identical. The analysis also revealed that the topology of the phylogenetic trees between wgMLST and cgMLST were remarkably similar. The comparison between SNP and cgMLST or SNP and wgMLST approaches showed that the topologies of phylogenic trees were statistically similar with an almost equivalent clustering.Conclusion: Our study revealed high concordance between wgMLST, cgMLST, and SNP approaches which are all suitable for typing of L. monocytogenes. The comparable clustering is an important observation considering that the two approaches have been variously implemented among reference laboratories.
Oud, Bart; Maris, Antonius J A; Daran, Jean-Marc; Pronk, Jack T
Successful reverse engineering of mutants that have been obtained by nontargeted strain improvement has long presented a major challenge in yeast biotechnology. This paper reviews the use of genome-wide approaches for analysis of Saccharomyces cerevisiae strains originating from evolutionary engineering or random mutagenesis. On the basis of an evaluation of the strengths and weaknesses of different methods, we conclude that for the initial identification of relevant genetic changes, whole genome sequencing is superior to other analytical techniques, such as transcriptome, metabolome, proteome, or array-based genome analysis. Key advantages of this technique over gene expression analysis include the independency of genome sequences on experimental context and the possibility to directly and precisely reproduce the identified changes in naive strains. The predictive value of genome-wide analysis of strains with industrially relevant characteristics can be further improved by classical genetics or simultaneous analysis of strains derived from parallel, independent strain improvement lineages. PMID:22152095
Oud, Bart; van Maris, Antonius J A; Daran, Jean-Marc; Pronk, Jack T
Successful reverse engineering of mutants that have been obtained by nontargeted strain improvement has long presented a major challenge in yeast biotechnology. This paper reviews the use of genome-wide approaches for analysis of Saccharomyces cerevisiae strains originating from evolutionary engineering or random mutagenesis. On the basis of an evaluation of the strengths and weaknesses of different methods, we conclude that for the initial identification of relevant genetic changes, whole genome sequencing is superior to other analytical techniques, such as transcriptome, metabolome, proteome, or array-based genome analysis. Key advantages of this technique over gene expression analysis include the independency of genome sequences on experimental context and the possibility to directly and precisely reproduce the identified changes in naive strains. The predictive value of genome-wide analysis of strains with industrially relevant characteristics can be further improved by classical genetics or simultaneous analysis of strains derived from parallel, independent strain improvement lineages. © 2011 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.
Song, Yinglei; Liu, Chunmei; Malmberg, Russell; Pan, Fangfang; Cai, Liming
Searching genomes for RNA secondary structure with computational methods has become an important approach to the annotation of non-coding RNAs. However, due to the lack of efficient algorithms for accurate RNA structure-sequence alignment, computer programs capable of fast and effectively searching genomes for RNA secondary structures have not been available. In this paper, a novel RNA structure profiling model is introduced based on the notion of a conformational graph to specify the consensus structure of an RNA family. Tree decomposition yields a small tree width t for such conformation graphs (e.g., t = 2 for stem loops and only a slight increase for pseudo-knots). Within this modelling framework, the optimal alignment of a sequence to the structure model corresponds to finding a maximum valued isomorphic subgraph and consequently can be accomplished through dynamic programming on the tree decomposition of the conformational graph in time O(k(t)N(2)), where k is a small parameter; and N is the size of the projiled RNA structure. Experiments show that the application of the alignment algorithm to search in genomes yields the same search accuracy as methods based on a Covariance model with a significant reduction in computation time. In particular; very accurate searches of tmRNAs in bacteria genomes and of telomerase RNAs in yeast genomes can be accomplished in days, as opposed to months required by other methods. The tree decomposition based searching tool is free upon request and can be downloaded at our site h t t p ://w.uga.edu/RNA-informatics/software/index.php.
Full Text Available BACKGROUND: Genomics studies are being revolutionized by the next generation sequencing technologies, which have made whole genome sequencing much more accessible to the average researcher. Whole genome sequencing with the new technologies is a developing art that, despite the large volumes of data that can be produced, may still fail to provide a clear and thorough map of a genome. The Plantagora project was conceived to address specifically the gap between having the technical tools for genome sequencing and knowing precisely the best way to use them. METHODOLOGY/PRINCIPAL FINDINGS: For Plantagora, a platform was created for generating simulated reads from several different plant genomes of different sizes. The resulting read files mimicked either 454 or Illumina reads, with varying paired end spacing. Thousands of datasets of reads were created, most derived from our primary model genome, rice chromosome one. All reads were assembled with different software assemblers, including Newbler, Abyss, and SOAPdenovo, and the resulting assemblies were evaluated by an extensive battery of metrics chosen for these studies. The metrics included both statistics of the assembly sequences and fidelity-related measures derived by alignment of the assemblies to the original genome source for the reads. The results were presented in a website, which includes a data graphing tool, all created to help the user compare rapidly the feasibility and effectiveness of different sequencing and assembly strategies prior to testing an approach in the lab. Some of our own conclusions regarding the different strategies were also recorded on the website. CONCLUSIONS/SIGNIFICANCE: Plantagora provides a substantial body of information for comparing different approaches to sequencing a plant genome, and some conclusions regarding some of the specific approaches. Plantagora also provides a platform of metrics and tools for studying the process of sequencing and assembly
de Vries, Ronald P; Benoit, Isabelle; Doehlemann, Gunther; Kobayashi, Tetsuo; Magnuson, Jon K; Panisko, Ellen A; Baker, Scott E; Lebrun, Marc-Henri
Fungi inhabit every natural and anthropogenic environment on Earth. They have highly varied life-styles including saprobes (using only dead biomass as a nutrient source), pathogens (feeding on living biomass), and symbionts (co-existing with other organisms). These distinctions are not absolute as many species employ several life styles (e.g. saprobe and opportunistic pathogen, saprobe and mycorrhiza). To efficiently survive in these different and often changing environments, fungi need to be able to modify their physiology and in some cases will even modify their local environment. Understanding the interaction between fungi and their environments has been a topic of study for many decades. However, recently these studies have reached a new dimension. The availability of fungal genomes and development of post-genomic technologies for fungi, such as transcriptomics, proteomics and metabolomics, have enabled more detailed studies into this topic resulting in new insights. Based on a Special Interest Group session held during IMC9, this paper provides examples of the recent advances in using (post-)genomic approaches to better understand fungal interactions with their environments.
Han, Yumiao; Garcia, Benjamin A
Epigenetics is the study of changes in gene expression or cellular phenotype that do not change the DNA sequence. In this review, current methods, both genomic and proteomic, associated with epigenetics research are discussed. Among them, chromatin immunoprecipitation (ChIP) followed by sequencing and other ChIP-based techniques are powerful techniques for genome-wide profiling of DNA-binding proteins, histone post-translational modifications or nucleosome positions. However, mass spectrometry-based proteomics is increasingly being used in functional biological studies and has proved to be an indispensable tool to characterize histone modifications, as well as DNA–protein and protein–protein interactions. With the development of genomic and proteomic approaches, combination of ChIP and mass spectrometry has the potential to expand our knowledge of epigenetics research to a higher level. PMID:23895656
Hagen, J; Lee, E F; Fairlie, W D; Kalinna, B H
As research on parasitic helminths is moving into the post-genomic era, an enormous effort is directed towards deciphering gene function and to achieve gene annotation. The sequences that are available in public databases undoubtedly hold information that can be utilized for new interventions and control but the exploitation of these resources has until recently remained difficult. Only now, with the emergence of methods to genetically manipulate and transform parasitic worms will it be possible to gain a comprehensive understanding of the molecular mechanisms involved in nutrition, metabolism, developmental switches/maturation and interaction with the host immune system. This review focuses on functional genomics approaches in parasitic helminths that are currently used, to highlight potential applications of these technologies in the areas of cell biology, systems biology and immunobiology of parasitic helminths. © 2011 Blackwell Publishing Ltd.
Wang, Lin; Maranas, Costas D
Genome minimized strains offer advantages as production chassis by reducing transcriptional cost, eliminating competing functions and limiting unwanted regulatory interactions. Existing approaches for identifying stretches of DNA to remove are largely ad hoc based on information on presumably dispensable regions through experimentally determined nonessential genes and comparative genomics. Here we introduce a versatile genome reduction algorithm MinGenome that implements a mixed-integer linear programming (MILP) algorithm to identify in size descending order all dispensable contiguous sequences without affecting the organism's growth or other desirable traits. Known essential genes or genes that cause significant fitness or performance loss can be flagged and their deletion can be prohibited. MinGenome also preserves needed transcription factors and promoter regions ensuring that retained genes will be properly transcribed while also avoiding the simultaneous deletion of synthetic lethal pairs. The potential benefit of removing even larger contiguous stretches of DNA if only one or two essential genes (to be reinserted elsewhere) are within the deleted sequence is explored. We applied the algorithm to design a minimized E. coli strain and found that we were able to recapitulate the long deletions identified in previous experimental studies and discover alternative combinations of deletions that have not yet been explored in vivo.
Vorapreeda, Tayvich; Thammarongtham, Chinae; Laoteng, Kobkul
Lipid-degrading or lipolytic enzymes have gained enormous attention in academic and industrial sectors. Several efforts are underway to discover new lipase enzymes from a variety of microorganisms with particular catalytic properties to be used for extensive applications. In addition, various tools and strategies have been implemented to unravel the functional relevance of the versatile lipid-degrading enzymes for special purposes. This review highlights the study of microbial lipid-degrading enzymes through an integrative computational approach. The identification of putative lipase genes from microbial genomes and metagenomic libraries using homology-based mining is discussed, with an emphasis on sequence analysis of conserved motifs and enzyme topology. Molecular modelling of three-dimensional structure on the basis of sequence similarity is shown to be a potential approach for exploring the structural and functional relationships of candidate lipase enzymes. The perspectives on a discriminative framework of cutting-edge tools and technologies, including bioinformatics, computational biology, functional genomics and functional proteomics, intended to facilitate rapid progress in understanding lipolysis mechanism and to discover novel lipid-degrading enzymes of microorganisms are discussed.
Winsor, Geoffrey L; Griffiths, Emma J; Lo, Raymond; Dhillon, Bhavjinder K; Shay, Julie A; Brinkman, Fiona S L
The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
Genomics-based methods are now commonplace in natural products research. A phylogeny-guided mining approach provides a means to quickly screen a large number of microbial genomes or metagenomes in search of new biosynthetic gene clusters of interest. In this approach, biosynthetic genes serve as molecular markers, and phylogenetic trees built with known and unknown marker gene sequences are used to quickly prioritize biosynthetic gene clusters for their metabolites characterization. An increase in the use of this approach has been observed for the last couple of years along with the emergence of low cost sequencing technologies. The aim of this review is to discuss the basic concept of a phylogeny-guided mining approach, and also to provide examples in which this approach was successfully applied to discover new natural products from microbial genomes and metagenomes. I believe that the phylogeny-guided mining approach will continue to play an important role in genomics-based natural products research.
Full Text Available Abstract Background Information on the occurrence of sequence features in genomes is crucial to comparative genomics, evolutionary analysis, the analyses of regulatory sequences and the quantitative evaluation of sequences. Computing the frequencies and the occurrences of a pattern in complete genomes is time-consuming. Results The proposed database provides information about sequence features generated by exhaustively computing the sequences of the complete genome. The repetitive elements in the eukaryotic genomes, such as LINEs, SINEs, Alu and LTR, are obtained from Repbase. The database supports various complete genomes including human, yeast, worm, and 128 microbial genomes. Conclusions This investigation presents and implements an efficiently computational approach to accumulate the occurrences of the oligonucleotides or patterns in complete genomes. A database is established to maintain the information of the sequence features, including the distributions of oligonucleotide, the gene distribution, the distribution of repetitive elements in genomes and the occurrences of the oligonucleotides. The database can provide more effective and efficient way to access the repetitive features in genomes.
King, E.; Karaoz, U.; Molins, S.; Bouskill, N.; Anantharaman, K.; Beller, H. R.; Banfield, J. F.; Steefel, C. I.; Brodie, E.
The biogeochemical functioning of ecosystems is shaped in part by genomic information stored in the subsurface microbiome. Cultivation-independent approaches allow us to extract this information through reconstruction of thousands of genomes from a microbial community. Analysis of these genomes, in turn, gives an indication of the organisms present and their functional roles. However, metagenomic analyses can currently deliver thousands of different genomes that range in abundance/importance, requiring the identification and assimilation of key physiologies and metabolisms to be represented as traits for successful simulation of subsurface processes. Here we focus on incorporating -omics information into BioCrunch, a genome-informed trait-based model that represents the diversity of microbial functional processes within a reactive transport framework. This approach models the rate of nutrient uptake and the thermodynamics of coupled electron donors and acceptors for a range of microbial metabolisms including heterotrophs and chemolithotrophs. Metabolism of exogenous substrates fuels catabolic and anabolic processes, with the proportion of energy used for cellular maintenance, respiration, biomass development, and enzyme production based upon dynamic intracellular and environmental conditions. This internal resource partitioning represents a trade-off against biomass formation and results in microbial community emergence across a fitness landscape. Biocrunch was used here in simulations that included organisms and metabolic pathways derived from a dataset of ~1200 non-redundant genomes reflecting a microbial community in a floodplain aquifer. Metagenomic data was directly used to parameterize trait values related to growth and to identify trait linkages associated with respiration, fermentation, and key enzymatic functions such as plant polymer degradation. Simulations spanned a range of metabolic complexities and highlight benefits originating from simulations
Henri, Clementine; Leekitcharoenphon, Pimlapas; Carleton, Heather A.
Background/objectives: Whole genome sequencing (WGS) has proven to be a powerful subtyping tool for foodborne pathogenic bacteria like L. monocytogenes. The interests of genome-scale analysis for national surveillance, outbreak detection or source tracking has been largely documented. The genomic......MLPPST) or pan genome (wgMLPPST). Currently, there are little comparisons studies of these different analytical approaches. Our objective was to assess and compare different genomic methods that can be implemented in order to cluster isolates of L monocytogenes.Methods: The clustering methods were evaluated...... on a collection of 207 L. monocytogenes genomes of food origin representative of the genetic diversity of the Anses collection. The trees were then compared using robust statistical analyses.Results: The backward comparability between conventional typing methods and genomic methods revealed a near...
Rodríguez-Luna, Stefany Daniela; Cruz Vázquez, Angélica Patricia; Jiménez Suárez, Verónica; Rodríguez-Sanoja, Romina; Alvarez-Buylla, Elena R.; Sánchez, Sergio
Endophytic bacteria are wide-spread and associated with plant physiological benefits, yet their genomes and secondary metabolites remain largely unidentified. In this study, we explored the genome of the endophyte Streptomyces scabrisporus NF3 for discovery of potential novel molecules as well as genes and metabolites involved in host interactions. The complete genomes of seven Streptomyces and three other more distantly related bacteria were used to define the functional landscape of this unique microbe. The S. scabrisporus NF3 genome is larger than the average Streptomyces genome and not structured for an obligate endosymbiotic lifestyle; this and the fact that can grow in R2YE media implies that it could include a soil-living stage. The genome displays an enrichment of genes associated with amino acid production, protein secretion, secondary metabolite and antioxidants production and xenobiotic degradation, indicating that S. scabrisporus NF3 could contribute to the metabolic enrichment of soil microbial communities and of its hosts. Importantly, besides its metabolic advantages, the genome showed evidence for differential functional specificity and diversification of plant interaction molecules, including genes for the production of plant hormones, stress resistance molecules, chitinases, antibiotics and siderophores. Given the diversity of S. scabrisporus mechanisms for host upkeep, we propose that these strategies were necessary for its adaptation to plant hosts and to face changes in environmental conditions. PMID:29447216
Corina Diana Ceapă
Full Text Available Endophytic bacteria are wide-spread and associated with plant physiological benefits, yet their genomes and secondary metabolites remain largely unidentified. In this study, we explored the genome of the endophyte Streptomyces scabrisporus NF3 for discovery of potential novel molecules as well as genes and metabolites involved in host interactions. The complete genomes of seven Streptomyces and three other more distantly related bacteria were used to define the functional landscape of this unique microbe. The S. scabrisporus NF3 genome is larger than the average Streptomyces genome and not structured for an obligate endosymbiotic lifestyle; this and the fact that can grow in R2YE media implies that it could include a soil-living stage. The genome displays an enrichment of genes associated with amino acid production, protein secretion, secondary metabolite and antioxidants production and xenobiotic degradation, indicating that S. scabrisporus NF3 could contribute to the metabolic enrichment of soil microbial communities and of its hosts. Importantly, besides its metabolic advantages, the genome showed evidence for differential functional specificity and diversification of plant interaction molecules, including genes for the production of plant hormones, stress resistance molecules, chitinases, antibiotics and siderophores. Given the diversity of S. scabrisporus mechanisms for host upkeep, we propose that these strategies were necessary for its adaptation to plant hosts and to face changes in environmental conditions.
Akdemir, Deniz; Sánchez, Julio I
Selection in breeding programs can be done by using phenotypes (phenotypic selection), pedigree relationship (breeding value selection) or molecular markers (marker assisted selection or genomic selection). All these methods are based on truncation selection, focusing on the best performance of parents before mating. In this article we proposed an approach to breeding, named genomic mating, which focuses on mating instead of truncation selection. Genomic mating uses information in a similar fashion to genomic selection but includes information on complementation of parents to be mated. Following the efficiency frontier surface, genomic mating uses concepts of estimated breeding values, risk (usefulness) and coefficient of ancestry to optimize mating between parents. We used a genetic algorithm to find solutions to this optimization problem and the results from our simulations comparing genomic selection, phenotypic selection and the mating approach indicate that current approach for breeding complex traits is more favorable than phenotypic and genomic selection. Genomic mating is similar to genomic selection in terms of estimating marker effects, but in genomic mating the genetic information and the estimated marker effects are used to decide which genotypes should be crossed to obtain the next breeding population.
Hedge, Jessica; Wilson, Daniel J.
Microbial genome evolution is shaped by a variety of selective pressures. Understanding how these processes occur can help to address important problems in microbiology by explaining observed differences in phenotypes, including virulence and resistance to antibiotics. Greater access to whole-genome sequencing provides microbiologists with the opportunity to perform large-scale analyses of selection in novel settings, such as within individual hosts. This tutorial aims to guide researchers th...
Krzywinski, Martin; Bosdet, Ian; Mathewson, Carrie; Wye, Natasja; Brebner, Jay; Chiu, Readman; Corbett, Richard; Field, Matthew; Lee, Darlene; Pugh, Trevor; Volik, Stas; Siddiqui, Asim; Jones, Steven; Schein, Jacquie; Collins, Collin; Marra, Marco
We present a method, called fingerprint profiling (FPP), that uses restriction digest fingerprints of bacterial artificial chromosome clones to detect and classify rearrangements in the human genome. The approach uses alignment of experimental fingerprint patterns to in silico digests of the sequence assembly and is capable of detecting micro-deletions (1-5 kb) and balanced rearrangements. Our method has compelling potential for use as a whole-genome method for the identification and characterization of human genome rearrangements. PMID:17953769
Fragoulakis, Vasilios; Mitropoulou, Christina; van Schaik, Ron H; Maniadakis, Nikolaos; Patrinos, George P
Genomic Medicine aims to improve therapeutic interventions and diagnostics, the quality of life of patients, but also to rationalize healthcare costs. To reach this goal, careful assessment and identification of evidence gaps for public health genomics priorities are required so that a more efficient healthcare environment is created. Here, we propose a public health genomics-driven approach to adjust the classical healthcare decision making process with an alternative methodological approach of cost-effectiveness analysis, which is particularly helpful for genomic medicine interventions. By combining classical cost-effectiveness analysis with budget constraints, social preferences, and patient ethics, we demonstrate the application of this model, the Genome Economics Model (GEM), based on a previously reported genome-guided intervention from a developing country environment. The model and the attendant rationale provide a practical guide by which all major healthcare stakeholders could ensure the sustainability of funding for genome-guided interventions, their adoption and coverage by health insurance funds, and prioritization of Genomic Medicine research, development, and innovation, given the restriction of budgets, particularly in developing countries and low-income healthcare settings in developed countries. The implications of the GEM for the policy makers interested in Genomic Medicine and new health technology and innovation assessment are also discussed.
Chen, Yan; Yin, Xiaoshi; Li, Zhoujun; Hu, Xiaohua; Huang, Jimmy Xiangji
In the biomedical domain, there are immense data and tremendous increase of genomics and biomedical relevant publications. The wealth of information has led to an increasing amount of interest in and need for applying information retrieval techniques to access the scientific literature in genomics and related biomedical disciplines. In many cases, the desired information of a query asked by biologists is a list of a certain type of entities covering different aspects that are related to the question, such as cells, genes, diseases, proteins, mutations, etc. Hence, it is important of a biomedical IR system to be able to provide relevant and diverse answers to fulfill biologists' information needs. However traditional IR model only concerns with the relevance between retrieved documents and user query, but does not take redundancy between retrieved documents into account. This will lead to high redundancy and low diversity in the retrieval ranked lists. In this paper, we propose an approach which employs a topic generative model called Latent Dirichlet Allocation (LDA) to promoting ranking diversity for biomedical information retrieval. Different from other approaches or models which consider aspects on word level, our approach assumes that aspects should be identified by the topics of retrieved documents. We present LDA model to discover topic distribution of retrieval passages and word distribution of each topic dimension, and then re-rank retrieval results with topic distribution similarity between passages based on N-size slide window. We perform our approach on TREC 2007 Genomics collection and two distinctive IR baseline runs, which can achieve 8% improvement over the highest Aspect MAP reported in TREC 2007 Genomics track. The proposed method is the first study of adopting topic model to genomics information retrieval, and demonstrates its effectiveness in promoting ranking diversity as well as in improving relevance of ranked lists of genomics search
Raubeso, Linda A.; Peery, Rhiannon; Chumley, Timothy W.; Dziubek,Chris; Fourcade, H. Matthew; Boore, Jeffrey L.; Jansen, Robert K.
The number of completely sequenced plastid genomes available is growing rapidly. This new array of sequences presents new opportunities to perform comparative analyses. In comparative studies, it is most useful to compare across wide phylogenetic spans and, within angiosperms, to include representatives from basally diverging lineages such as the new genomes reported here: Nuphar advena (from a basal-most lineage) and Ranunculus macranthus (from the basal group of eudicots). We report these two new plastid genome sequences and make comparisons (within angiosperms, seed plants, or all photosynthetic lineages) to evaluate features such as the status of ycf15 and ycf68 as protein coding genes, the distribution of simple sequence repeats (SSRs) and longer dispersed repeats (SDR), and patterns of nucleotide composition.
Ilia J. Leitch
Full Text Available Monocot genomic diversity includes striking variation at many levels. This paper compares various genomic characters (e.g., range of chromosome numbers and ploidy levels, occurrence of endopolyploidy, GC content, chromosome packaging and organization, genome size between monocots and the remaining angiosperms to discern just how distinctive monocot genomes are. One of the most notable features of monocots is their wide range and diversity of genome sizes, including the species with the largest genome so far reported in plants. This genomic character is analysed in greater detail, within a phylogenetic context. By surveying available genome size and chromosome data it is apparent that different monocot orders follow distinctive modes of genome size and chromosome evolution. Further insights into genome size-evolution and dynamics were obtained using statistical modelling approaches to reconstruct the ancestral genome size at key nodes across the monocot phylogenetic tree. Such approaches reveal that while the ancestral genome size of all monocots was small (1C=1.9 pg, there have been several major increases and decreases during monocot evolution. In addition, notable increases in the rates of genome size-evolution were found in Asparagales and Poales compared with other monocot lineages.
Li, Yingrui; Zheng, Hancheng; Luo, Ruibang
Here we use whole-genome de novo assembly of second-generation sequencing reads to map structural variation (SV) in an Asian genome and an African genome. Our approach identifies small- and intermediate-size homozygous variants (1-50 kb) including insertions, deletions, inversions and their precise...
Sauer, Sascha; Konthur, Zoltán; Lehrach, Hans
The problems we face today in public health as a result of the -- fortunately -- increasing age of people and the requirements of developing countries create an urgent need for new and innovative approaches in medicine and in agronomics. Genomic and functional genomic approaches have a great potential to at least partially solve these problems in the future. Important progress has been made by procedures to decode genomic information of humans, but also of other key organisms. The basic comprehension of genomic information (and its transfer) should now give us the possibility to pursue the next important step in life science eventually leading to a basic understanding of biological information flow; the elucidation of the function of all genes and correlative products encoded in the genome, as well as the discovery of their interactions in a molecular context and the response to environmental factors. As a result of the sequencing projects, we are now able to ask important questions about sequence variation and can start to comprehensively study the function of expressed genes on different levels such as RNA, protein or the cell in a systematic context including underlying networks. In this article we review and comment on current trends in large-scale systematic biological research. A particular emphasis is put on technology developments that can provide means to accomplish the tasks of future lines of functional genomics.
Toussaint, Ariane; Chandler, Mick
The importance of horizontal/lateral gene transfer (LGT) in shaping the genomes of prokaryotic organisms has been recognized in recent years as a result of analysis of the increasing number of available genome sequences. LGT is largely due to the transfer and recombination activities of mobile genetic elements (MGEs). Bacterial and archaeal genomes are mosaics of vertically and horizontally transmitted DNA segments. This generates reticulate relationships between members of the prokaryotic world that are better represented by networks than by "classical" phylogenetic trees. In this review we summarize the nature and activities of MGEs, and the problems that presently limit their analysis on a large scale. We propose routes to improve their annotation in the flow of genomic and metagenomic sequences that currently exist and those that become available. We describe network analysis of evolutionary relationships among some MGE categories and sketch out possible developments of this type of approach to get more insight into the role of the mobilome in bacterial adaptation and evolution.
Lardi, Martina; Pessi, Gabriella
Biological nitrogen fixation gives legumes a pronounced growth advantage in nitrogen-deprived soils and is of considerable ecological and economic interest. In exchange for reduced atmospheric nitrogen, typically given to the plant in the form of amides or ureides, the legume provides nitrogen-fixing rhizobia with nutrients and highly specialised root structures called nodules. To elucidate the molecular basis underlying physiological adaptations on a genome-wide scale, functional genomics approaches, such as transcriptomics, proteomics, and metabolomics, have been used. This review presents an overview of the different functional genomics approaches that have been performed on rhizobial symbiosis, with a focus on studies investigating the molecular mechanisms used by the bacterial partner to interact with the legume. While rhizobia belonging to the alpha-proteobacterial group (alpha-rhizobia) have been well studied, few studies to date have investigated this process in beta-proteobacteria (beta-rhizobia).
Lin, Hsin-Hung; Liao, Yu-Chieh
Despite the ever-increasing output of next-generation sequencing data along with developing assemblers, dozens to hundreds of gaps still exist in de novo microbial assemblies due to uneven coverage and large genomic repeats. Third-generation single-molecule, real-time (SMRT) sequencing technology avoids amplification artifacts and generates kilobase-long reads with the potential to complete microbial genome assembly. However, due to the low accuracy (~85%) of third-generation sequences, a considerable amount of long reads (>50X) are required for self-correction and for subsequent de novo assembly. Recently-developed hybrid approaches, using next-generation sequencing data and as few as 5X long reads, have been proposed to improve the completeness of microbial assembly. In this study we have evaluated the contemporary hybrid approaches and demonstrated that assembling corrected long reads (by runCA) produced the best assembly compared to long-read scaffolding (e.g., AHA, Cerulean and SSPACE-LongRead) and gap-filling (SPAdes). For generating corrected long reads, we further examined long-read correction tools, such as ECTools, LSC, LoRDEC, PBcR pipeline and proovread. We have demonstrated that three microbial genomes including Escherichia coli K12 MG1655, Meiothermus ruber DSM1279 and Pdeobacter heparinus DSM2366 were successfully hybrid assembled by runCA into near-perfect assemblies using ECTools-corrected long reads. In addition, we developed a tool, Patch, which implements corrected long reads and pre-assembled contigs as inputs, to enhance microbial genome assemblies. With the additional 20X long reads, short reads of S. cerevisiae W303 were hybrid assembled into 115 contigs using the verified strategy, ECTools + runCA. Patch was subsequently applied to upgrade the assembly to a 35-contig draft genome. Our evaluation of the hybrid approaches shows that assembling the ECTools-corrected long reads via runCA generates near complete microbial genomes, suggesting
Minari, Jusaku; Shirai, Tetsuya; Kato, Kazuto
As evidenced by high-throughput sequencers, genomic technologies have recently undergone radical advances. These technologies enable comprehensive sequencing of personal genomes considerably more efficiently and less expensively than heretofore. These developments present a challenge to the conventional framework of biomedical ethics; under these changing circumstances, each research project has to develop a pragmatic research policy. Based on the experience with a new large-scale project-the Genome Science Project-this article presents a novel approach to conducting a specific policy for personal genome research in the Japanese context. In creating an original informed-consent form template for the project, we present a two-tiered process: making the draft of the template following an analysis of national and international policies; refining the draft template in conjunction with genome project researchers for practical application. Through practical use of the template, we have gained valuable experience in addressing challenges in the ethical review process, such as the importance of sharing details of the latest developments in genomics with members of research ethics committees. We discuss certain limitations of the conventional concept of informed consent and its governance system and suggest the potential of an alternative process using information technology.
Cho, Seoae; Kim, Haseong; Oh, Sohee; Kim, Kyunga; Park, Taesung
The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. However, many challenges exist in detecting disease-causing genes among the thousands of SNPs. Examples include multicollinearity and multiple testing issues, especially when a large number of correlated SNPs are simultaneously tested. Multicollinearity can often occur when predictor variables in a multiple regression model are highly correlated, and can cause imprecise estimation of association. In this study, we propose a simple stepwise procedure that identifies disease-causing SNPs simultaneously by employing elastic-net regularization, a variable selection method that allows one to address multicollinearity. At Step 1, the single-marker association analysis was conducted to screen SNPs. At Step 2, the multiple-marker association was scanned based on the elastic-net regularization. The proposed approach was applied to the rheumatoid arthritis (RA) case-control data set of Genetic Analysis Workshop 16. While the selected SNPs at the screening step are located mostly on chromosome 6, the elastic-net approach identified putative RA-related SNPs on other chromosomes in an increased proportion. For some of those putative RA-related SNPs, we identified the interactions with sex, a well known factor affecting RA susceptibility.
Kristopher J. L. Irizarry
Full Text Available Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management.
Irizarry, Kristopher J L; Bryant, Doug; Kalish, Jordan; Eng, Curtis; Schmidt, Peggy L; Barrett, Gini; Barr, Margaret C
Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs) that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management.
Greub, Gilbert; Kebbi-Beghdadi, Carole; Bertelli, Claire; Collyn, François; Riederer, Beat M; Yersin, Camille; Croxatto, Antony; Raoult, Didier
With the availability of new generation sequencing technologies, bacterial genome projects have undergone a major boost. Still, chromosome completion needs a costly and time-consuming gap closure, especially when containing highly repetitive elements. However, incomplete genome data may be sufficiently informative to derive the pursued information. For emerging pathogens, i.e. newly identified pathogens, lack of release of genome data during gap closure stage is clearly medically counterproductive. We thus investigated the feasibility of a dirty genome approach, i.e. the release of unfinished genome sequences to develop serological diagnostic tools. We showed that almost the whole genome sequence of the emerging pathogen Parachlamydia acanthamoebae was retrieved even with relatively short reads from Genome Sequencer 20 and Solexa. The bacterial proteome was analyzed to select immunogenic proteins, which were then expressed and used to elaborate the first steps of an ELISA. This work constitutes the proof of principle for a dirty genome approach, i.e. the use of unfinished genome sequences of pathogenic bacteria, coupled with proteomics to rapidly identify new immunogenic proteins useful to develop in the future specific diagnostic tests such as ELISA, immunohistochemistry and direct antigen detection. Although applied here to an emerging pathogen, this combined dirty genome sequencing/proteomic approach may be used for any pathogen for which better diagnostics are needed. These genome sequences may also be very useful to develop DNA based diagnostic tests. All these diagnostic tools will allow further evaluations of the pathogenic potential of this obligate intracellular bacterium.
Full Text Available BACKGROUND: With the availability of new generation sequencing technologies, bacterial genome projects have undergone a major boost. Still, chromosome completion needs a costly and time-consuming gap closure, especially when containing highly repetitive elements. However, incomplete genome data may be sufficiently informative to derive the pursued information. For emerging pathogens, i.e. newly identified pathogens, lack of release of genome data during gap closure stage is clearly medically counterproductive. METHODS/PRINCIPAL FINDINGS: We thus investigated the feasibility of a dirty genome approach, i.e. the release of unfinished genome sequences to develop serological diagnostic tools. We showed that almost the whole genome sequence of the emerging pathogen Parachlamydia acanthamoebae was retrieved even with relatively short reads from Genome Sequencer 20 and Solexa. The bacterial proteome was analyzed to select immunogenic proteins, which were then expressed and used to elaborate the first steps of an ELISA. CONCLUSIONS/SIGNIFICANCE: This work constitutes the proof of principle for a dirty genome approach, i.e. the use of unfinished genome sequences of pathogenic bacteria, coupled with proteomics to rapidly identify new immunogenic proteins useful to develop in the future specific diagnostic tests such as ELISA, immunohistochemistry and direct antigen detection. Although applied here to an emerging pathogen, this combined dirty genome sequencing/proteomic approach may be used for any pathogen for which better diagnostics are needed. These genome sequences may also be very useful to develop DNA based diagnostic tests. All these diagnostic tools will allow further evaluations of the pathogenic potential of this obligate intracellular bacterium.
Chandonia, John-Marc; Brenner, Steven E.
The structural genomics project is an international effort to determine the three-dimensional shapes of all important biological macromolecules, with a primary focus on proteins. Target proteins should be selected according to a strategy which is medically and biologically relevant, of good value, and tractable. As an option to consider, we present the Pfam5000 strategy, which involves selecting the 5000 most important families from the Pfam database as sources for targets. We compare the Pfam5000 strategy to several other proposed strategies that would require similar numbers of targets. These include including complete solution of several small to moderately sized bacterial proteomes, partial coverage of the human proteome, and random selection of approximately 5000 targets from sequenced genomes. We measure the impact that successful implementation of these strategies would have upon structural interpretation of the proteins in Swiss-Prot, TrEMBL, and 131 complete proteomes (including 10 of eukaryotes) from the Proteome Analysis database at EBI. Solving the structures of proteins from the 5000 largest Pfam families would allow accurate fold assignment for approximately 68 percent of all prokaryotic proteins (covering 59 percent of residues) and 61 percent of eukaryotic proteins (40 percent of residues). More fine-grained coverage which would allow accurate modeling of these proteins would require an order of magnitude more targets. The Pfam5000 strategy may be modified in several ways, for example to focus on larger families, bacterial sequences, or eukaryotic sequences; as long as secondary consideration is given to large families within Pfam, coverage results vary only slightly. In contrast, focusing structural genomics on a single tractable genome would have only a limited impact in structural knowledge of other proteomes: a significant fraction (about 30-40 percent of the proteins, and 40-60 percent of the residues) of each proteome is classified in small
Barrero, Roberto A; Guerrero, Felix D; Black, Michael; McCooke, John; Chapman, Brett; Schilkey, Faye; Pérez de León, Adalberto A; Miller, Robert J; Bruns, Sara; Dobry, Jason; Mikhaylenko, Galina; Stormo, Keith; Bell, Callum; Tao, Quanzhou; Bogden, Robert; Moolhuijzen, Paula M; Hunter, Adam; Bellgard, Matthew I
The genome of the cattle tick Rhipicephalus microplus, an ectoparasite with global distribution, is estimated to be 7.1Gbp in length and consists of approximately 70% repetitive DNA. We report the draft assembly of a tick genome that utilized a hybrid sequencing and assembly approach to capture the repetitive fractions of the genome. Our hybrid approach produced an assembly consisting of 2.0Gbp represented in 195,170 scaffolds with a N50 of 60,284bp. The Rmi v2.0 assembly is 51.46% repetitive with a large fraction of unclassified repeats, short interspersed elements, long interspersed elements and long terminal repeats. We identified 38,827 putative R. microplus gene loci, of which 24,758 were protein coding genes (≥100 amino acids). OrthoMCL comparative analysis against 11 selected species including insects and vertebrates identified 10,835 and 3,423 protein coding gene loci that are unique to R. microplus or common to both R. microplus and Ixodes scapularis ticks, respectively. We identified 191 microRNA loci, of which 168 have similarity to known miRNAs and 23 represent novel miRNA families. We identified the genomic loci of several highly divergent R. microplus esterases with sequence similarity to acetylcholinesterase. Additionally we report the finding of a novel cytochrome P450 CYP41 homolog that shows similar protein folding structures to known CYP41 proteins known to be involved in acaricide resistance. Copyright © 2017 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.
Jeremy Schmutz of the HudsonAlpha Institute for Biotechnology on New approaches and technologies to sequence de novo plant reference genomes at the 8th Annual Genomics of Energy Environment Meeting on March 27, 2013 in Walnut Creek, CA.
Hedge, Jessica; Wilson, Daniel J
Microbial genome evolution is shaped by a variety of selective pressures. Understanding how these processes occur can help to address important problems in microbiology by explaining observed differences in phenotypes, including virulence and resistance to antibiotics. Greater access to whole-genome sequencing provides microbiologists with the opportunity to perform large-scale analyses of selection in novel settings, such as within individual hosts. This tutorial aims to guide researchers through the fundamentals underpinning popular methods for measuring selection in pathogens. These methods are transferable to a wide variety of organisms, and the exercises provided are designed for researchers with any level of programming experience.
Convergent functional genomics (CFG) is a translational methodology that integrates in a Bayesian fashion multiple lines of evidence from studies in human and animal models to get a better understanding of the genetics of a disease or pathological behavior. Here the integration of data sets that derive from forward genetics in animals and genetic association studies including genome wide association studies (GWAS) in humans is described for addictive behavior. The aim of forward genetics in animals and association studies in humans is to identify mutations (e.g. SNPs) that produce a certain phenotype; i.e. "from phenotype to genotype". Most powerful in terms of forward genetics is combined quantitative trait loci (QTL) analysis and gene expression profiling in recombinant inbreed rodent lines or genetically selected animals for a specific phenotype, e.g. high vs. low drug consumption. By Bayesian scoring genomic information from forward genetics in animals is then combined with human GWAS data on a similar addiction-relevant phenotype. This integrative approach generates a robust candidate gene list that has to be functionally validated by means of reverse genetics in animals; i.e. "from genotype to phenotype". It is proposed that studying addiction relevant phenotypes and endophenotypes by this CFG approach will allow a better determination of the genetics of addictive behavior.
Bakker, Freek T.; Lei, Di; Yu, Jiaying
Herbarium genomics is proving promising as next-generation sequencing approaches are well suited to deal with the usually fragmented nature of archival DNA. We show that routine assembly of partial plastome sequences from herbarium specimens is feasible, from total DNA extracts and with specimens...... up to 146 years old. We use genome skimming and an automated assembly pipeline, Iterative Organelle Genome Assembly, that assembles paired-end reads into a series of candidate assemblies, the best one of which is selected based on likelihood estimation. We used 93 specimens from 12 different...... correlation between plastome coverage and nuclear genome size (C value) in our samples, but the range of C values included is limited. Finally, we conclude that routine plastome sequencing from herbarium specimens is feasible and cost-effective (compared with Sanger sequencing or plastome...
Choi, Si-Sun; Katsuyama, Yohei; Bai, Linquan; Deng, Zixin; Ohnishi, Yasuo; Kim, Eung-Soo
The discovery and development of microbial natural products (MNPs) have played pivotal roles in the fields of human medicine and its related biotechnology sectors over the past several decades. The post-genomic era has witnessed the development of microbial genome mining approaches to isolate previously unsuspected MNP biosynthetic gene clusters (BGCs) hidden in the genome, followed by various BGC awakening techniques to visualize compound production. Additional microbial genome engineering techniques have allowed higher MNP production titers, which could complement a traditional culture-based MNP chasing approach. Here, we describe recent developments in the MNP research paradigm, including microbial genome mining, NP BGC activation, and NP overproducing cell factory design. Copyright © 2018 Elsevier Ltd. All rights reserved.
Brown, Steven D [ORNL; Nagaraju, Shilpa [LanzaTech; Utturkar, Sagar M [ORNL; De Tissera, Sashini [LanzaTech; Segovia, Simón [LanzaTech; Mitchell, Wayne [LanzaTech; Land, Miriam L [ORNL; Dassanayake, Asela [LanzaTech; Köpke, Michael [LanzaTech
Background Clostridium autoethanogenum strain JA1-1 (DSM 10061) is an acetogen capable of fermenting CO, CO2 and H2 (e.g. from syngas or waste gases) into biofuel ethanol and commodity chemicals such as 2,3-butanediol. A draft genome sequence consisting of 100 contigs has been published. Results A closed, high-quality genome sequence for C. autoethanogenum DSM10061 was generated using only the latest single-molecule DNA sequencing technology and without the need for manual finishing. It is assigned to the most complex genome classification based upon genome features such as repeats, prophage, nine copies of the rRNA gene operons. It has a low G + C content of 31.1%. Illumina, 454, Illumina/454 hybrid assemblies were generated and then compared to the draft and PacBio assemblies using summary statistics, CGAL, QUAST and REAPR bioinformatics tools and comparative genomic approaches. Assemblies based upon shorter read DNA technologies were confounded by the large number repeats and their size, which in the case of the rRNA gene operons were ~5 kb. CRISPR (Clustered Regularly Interspaced Short Paloindromic Repeats) systems among biotechnologically relevant Clostridia were classified and related to plasmid content and prophages. Potential associations between plasmid content and CRISPR systems may have implications for historical industrial scale Acetone-Butanol-Ethanol (ABE) fermentation failures and future large scale bacterial fermentations. While C. autoethanogenum contains an active CRISPR system, no such system is present in the closely related Clostridium ljungdahlii DSM 13528. A common prophage inserted into the Arg-tRNA shared between the strains suggests a common ancestor. However, C. ljungdahlii contains several additional putative prophages and it has more than double the amount of prophage DNA compared to C. autoethanogenum. Other differences include important metabolic genes for central metabolism (as an additional hydrogenase and the absence of a
Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien
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.
Skvortsova, Ksenia; Zotenko, Elena; Luu, Phuc-Loi; Gould, Cathryn M; Nair, Shalima S; Clark, Susan J; Stirzaker, Clare
The discovery that 5-methylcytosine (5mC) can be oxidized to 5-hydroxymethylcytosine (5hmC) by the ten-eleven translocation (TET) proteins has prompted wide interest in the potential role of 5hmC in reshaping the mammalian DNA methylation landscape. The gold-standard bisulphite conversion technologies to study DNA methylation do not distinguish between 5mC and 5hmC. However, new approaches to mapping 5hmC genome-wide have advanced rapidly, although it is unclear how the different methods compare in accurately calling 5hmC. In this study, we provide a comparative analysis on brain DNA using three 5hmC genome-wide approaches, namely whole-genome bisulphite/oxidative bisulphite sequencing (WG Bis/OxBis-seq), Infinium HumanMethylation450 BeadChip arrays coupled with oxidative bisulphite (HM450K Bis/OxBis) and antibody-based immunoprecipitation and sequencing of hydroxymethylated DNA (hMeDIP-seq). We also perform loci-specific TET-assisted bisulphite sequencing (TAB-seq) for validation of candidate regions. We show that whole-genome single-base resolution approaches are advantaged in providing precise 5hmC values but require high sequencing depth to accurately measure 5hmC, as this modification is commonly in low abundance in mammalian cells. HM450K arrays coupled with oxidative bisulphite provide a cost-effective representation of 5hmC distribution, at CpG sites with 5hmC levels >~10%. However, 5hmC analysis is restricted to the genomic location of the probes, which is an important consideration as 5hmC modification is commonly enriched at enhancer elements. Finally, we show that the widely used hMeDIP-seq method provides an efficient genome-wide profile of 5hmC and shows high correlation with WG Bis/OxBis-seq 5hmC distribution in brain DNA. However, in cell line DNA with low levels of 5hmC, hMeDIP-seq-enriched regions are not detected by WG Bis/OxBis or HM450K, either suggesting misinterpretation of 5hmC calls by hMeDIP or lack of sensitivity of the latter methods. We
Felder, Marius; Romualdi, Alessandro; Petzold, Andreas; Platzer, Matthias; Sühnel, Jürgen; Glöckner, Gernot
Many sequence data repositories can give a quick and easily accessible overview on genomes and their annotations. Less widespread is the possibility to compare related genomes with each other in a common database environment. We have previously described the GenColors database system (http://gencolors.fli-leibniz.de) and its applications to a number of bacterial genomes such as Borrelia, Legionella, Leptospira and Treponema. This system has an emphasis on genome comparison. It combines data from related genomes and provides the user with an extensive set of visualization and analysis tools. Eukaryote genomes are normally larger than prokaryote genomes and thus pose additional challenges for such a system. We have, therefore, adapted GenColors to also handle larger datasets of small eukaryotic genomes and to display eukaryotic gene structures. Further recent developments include whole genome views, genome list options and, for bacterial genome browsers, the display of horizontal gene transfer predictions. Two new GenColors-based databases for two fungal species (http://fgb.fli-leibniz.de) and for four social amoebas (http://sacgb.fli-leibniz.de) were set up. Both new resources open up a single entry point for related genomes for the amoebozoa and fungal research communities and other interested users. Comparative genomics approaches are greatly facilitated by these resources.
Schulz-Streeck, Torben; Ogutu, Joseph O; Piepho, Hans-Peter
Genomic selection (GS) is a method for predicting breeding values of plants or animals using many molecular markers that is commonly implemented in two stages. In plant breeding the first stage usually involves computation of adjusted means for genotypes which are then used to predict genomic breeding values in the second stage. We compared two classical stage-wise approaches, which either ignore or approximate correlations among the means by a diagonal matrix, and a new method, to a single-stage analysis for GS using ridge regression best linear unbiased prediction (RR-BLUP). The new stage-wise method rotates (orthogonalizes) the adjusted means from the first stage before submitting them to the second stage. This makes the errors approximately independently and identically normally distributed, which is a prerequisite for many procedures that are potentially useful for GS such as machine learning methods (e.g. boosting) and regularized regression methods (e.g. lasso). This is illustrated in this paper using componentwise boosting. The componentwise boosting method minimizes squared error loss using least squares and iteratively and automatically selects markers that are most predictive of genomic breeding values. Results are compared with those of RR-BLUP using fivefold cross-validation. The new stage-wise approach with rotated means was slightly more similar to the single-stage analysis than the classical two-stage approaches based on non-rotated means for two unbalanced datasets. This suggests that rotation is a worthwhile pre-processing step in GS for the two-stage approaches for unbalanced datasets. Moreover, the predictive accuracy of stage-wise RR-BLUP was higher (5.0-6.1%) than that of componentwise boosting.
Full Text Available Rapid advances in high-throughput sequencing techniques have created interesting computational challenges in bioinformatics. One of them refers to management of massive amounts of data generated by automatic sequencers. We need to deal with the persistency of genomic data, particularly storing and analyzing these large-scale processed data. To find an alternative to the frequently considered relational database model becomes a compelling task. Other data models may be more effective when dealing with a very large amount of nonconventional data, especially for writing and retrieving operations. In this paper, we discuss the Cassandra NoSQL database approach for storing genomic data. We perform an analysis of persistency and I/O operations with real data, using the Cassandra database system. We also compare the results obtained with a classical relational database system and another NoSQL database approach, MongoDB.
Aniceto, Rodrigo; Xavier, Rene; Guimarães, Valeria; Hondo, Fernanda; Holanda, Maristela; Walter, Maria Emilia; Lifschitz, Sérgio
Rapid advances in high-throughput sequencing techniques have created interesting computational challenges in bioinformatics. One of them refers to management of massive amounts of data generated by automatic sequencers. We need to deal with the persistency of genomic data, particularly storing and analyzing these large-scale processed data. To find an alternative to the frequently considered relational database model becomes a compelling task. Other data models may be more effective when dealing with a very large amount of nonconventional data, especially for writing and retrieving operations. In this paper, we discuss the Cassandra NoSQL database approach for storing genomic data. We perform an analysis of persistency and I/O operations with real data, using the Cassandra database system. We also compare the results obtained with a classical relational database system and another NoSQL database approach, MongoDB. PMID:26558254
Aniceto, Rodrigo; Xavier, Rene; Guimarães, Valeria; Hondo, Fernanda; Holanda, Maristela; Walter, Maria Emilia; Lifschitz, Sérgio
Rapid advances in high-throughput sequencing techniques have created interesting computational challenges in bioinformatics. One of them refers to management of massive amounts of data generated by automatic sequencers. We need to deal with the persistency of genomic data, particularly storing and analyzing these large-scale processed data. To find an alternative to the frequently considered relational database model becomes a compelling task. Other data models may be more effective when dealing with a very large amount of nonconventional data, especially for writing and retrieving operations. In this paper, we discuss the Cassandra NoSQL database approach for storing genomic data. We perform an analysis of persistency and I/O operations with real data, using the Cassandra database system. We also compare the results obtained with a classical relational database system and another NoSQL database approach, MongoDB.
Pappa, I.; St Pourcain, B.; Benke, K.S.; Cavadino, A.; Hakulinen, C.; Nivard, M.G.; Nolte, I.M.; Tiesler, C.M.T.; Bakermans-Kranenburg, M.J.; Davies, G.E.; Evans, D.M.; Geoffroy, M.C.; Grallert, H.; Blokhuis, M.M.; Hudziak, J.J.; Kemp, J.P.; Keltikangas-Järvinen, L.; McMahon, G.; Mileva-Seitz, V.R.; Motazedi, E.; Power, C.; Raitakari, O.T.; Ring, S.M.; Rivadeneira, F.; Rodriguez, A.; Scheet, P.; Seppälä, I.; Snieder, H.; Standl, M.; Thiering, E.; Timpson, N.J.; Veenstra, R.; Velders, F.P.; Whitehouse, A.J.O.; Davey Smith, G.; Heinrich, J.; Hypponen, E.; Lehtimäki, T.; Middeldorp, C.M.; Oldehinkel, A.J.; Pennell, C.E.; Boomsma, D.I.; Tiemeier, H.
Individual differences in aggressive behavior emerge in early childhood and predict persisting behavioral problems and disorders. Studies of antisocial and severe aggression in adulthood indicate substantial underlying biology. However, little attention has been given to genome-wide approaches of
Gopinath, G R; Cinar, H N; Murphy, H R; Durigan, M; Almeria, M; Tall, B D; DaSilva, A J
Cyclospora cayetanensis is a coccidian parasite associated with large and complex foodborne outbreaks worldwide. Linking samples from cyclosporiasis patients during foodborne outbreaks with suspected contaminated food sources, using conventional epidemiological methods, has been a persistent challenge. To address this issue, development of new methods based on potential genomically-derived markers for strain-level identification has been a priority for the food safety research community. The absence of reference genomes to identify nucleotide and structural variants with a high degree of confidence has limited the application of using sequencing data for source tracking during outbreak investigations. In this work, we determined the quality of a high resolution, curated, public mitochondrial genome assembly to be used as a reference genome by applying bioinformatic analyses. Using this reference genome, three new mitochondrial genome assemblies were built starting with metagenomic reads generated by sequencing DNA extracted from oocysts present in stool samples from cyclosporiasis patients. Nucleotide variants were identified in the new and other publicly available genomes in comparison with the mitochondrial reference genome. A consolidated workflow, presented here, to generate new mitochondrion genomes using our reference-guided de novo assembly approach could be useful in facilitating the generation of other mitochondrion sequences, and in their application for subtyping C. cayetanensis strains during foodborne outbreak investigations.
Full Text Available Microbial genome evolution is shaped by a variety of selective pressures. Understanding how these processes occur can help to address important problems in microbiology by explaining observed differences in phenotypes, including virulence and resistance to antibiotics. Greater access to whole-genome sequencing provides microbiologists with the opportunity to perform large-scale analyses of selection in novel settings, such as within individual hosts. This tutorial aims to guide researchers through the fundamentals underpinning popular methods for measuring selection in pathogens. These methods are transferable to a wide variety of organisms, and the exercises provided are designed for researchers with any level of programming experience.
Heather E Wheeler
Full Text Available Chemotherapeutic agents are used in the treatment of many cancers, yet variable resistance and toxicities among individuals limit successful outcomes. Several studies have indicated outcome differences associated with ancestry among patients with various cancer types. Using both traditional SNP-based and newly developed gene-based genome-wide approaches, we investigated the genetics of chemotherapeutic susceptibility in lymphoblastoid cell lines derived from 83 African Americans, a population for which there is a disparity in the number of genome-wide studies performed. To account for population structure in this admixed population, we incorporated local ancestry information into our association model. We tested over 2 million SNPs and identified 325, 176, 240, and 190 SNPs that were suggestively associated with cytarabine-, 5'-deoxyfluorouridine (5'-DFUR-, carboplatin-, and cisplatin-induced cytotoxicity, respectively (p≤10(-4. Importantly, some of these variants are found only in populations of African descent. We also show that cisplatin-susceptibility SNPs are enriched for carboplatin-susceptibility SNPs. Using a gene-based genome-wide association approach, we identified 26, 11, 20, and 41 suggestive candidate genes for association with cytarabine-, 5'-DFUR-, carboplatin-, and cisplatin-induced cytotoxicity, respectively (p≤10(-3. Fourteen of these genes showed evidence of association with their respective chemotherapeutic phenotypes in the Yoruba from Ibadan, Nigeria (p<0.05, including TP53I11, COPS5 and GAS8, which are known to be involved in tumorigenesis. Although our results require further study, we have identified variants and genes associated with chemotherapeutic susceptibility in African Americans by using an approach that incorporates local ancestry information.
Nordberg, Henrik [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Cantor, Michael [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Dusheyko, Serge [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Hua, Susan [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Poliakov, Alexander [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Shabalov, Igor [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Smirnova, Tatyana [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Grigoriev, Igor V. [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Dubchak, Inna [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States)
The U.S. Department of Energy (DOE) Joint Genome Institute (JGI), a national user facility, serves the diverse scientific community by providing integrated high-throughput sequencing and computational analysis to enable system-based scientific approaches in support of DOE missions related to clean energy generation and environmental characterization. The JGI Genome Portal (http://genome.jgi.doe.gov) provides unified access to all JGI genomic databases and analytical tools. The JGI maintains extensive data management systems and specialized analytical capabilities to manage and interpret complex genomic data. A user can search, download and explore multiple data sets available for all DOE JGI sequencing projects including their status, assemblies and annotations of sequenced genomes. In this paper, we describe major updates of the Genome Portal in the past 2 years with a specific emphasis on efficient handling of the rapidly growing amount of diverse genomic data accumulated in JGI.
Villar, Margarita; Mateos-Hernandez, Lourdes; de la Fuente, Jose
Why an autoimmune disease that is the main cause of the acute neuromuscular paralysis worldwide has not yet a well-characterized cause or an effective treatment? The existence of different clinical variants for the Guillain-Barré syndrome (GBS) coupled with the fact that a high number of pathogens can cause an infection that sometimes, but not always, precedes the development of the syndrome, confers a high degree of uncertainty for both prognosis and treatment. In the post-genomic era, the development of omics technologies for the high-throughput analysis of biological molecules is allowing the characterization of biological systems in a degree of depth unimaginable before. In this context, this work summarize the application of post-genomics technologies to the study of GBS. We performed a structured search of bibliographic databases for peer-reviewed research literature to outline the state of the art with regard the application of post-genomics technologies to the study of GBS. The quality of retrieved papers was assessed using standard tools and thirty-four were included in the review. To date, transcriptomics and proteomics have been the unique post-genomics approaches applied to GBS study. Most of these studies have been performed on cerebrospinal fluid samples and only few studies have been conducted with other samples such as serum, Schwann cells and human peripheral nerve. In the post-genomics era, transcriptomics and proteomics have shown the possibilities that omics technologies can offer for a better understanding of the immunological and pathological mechanisms involved in GBS and the identification of potential biomarkers, but these results have only shown the tip of the iceberg and there is still a long way to exploit the full potential that post-genomics approaches could offer to the study of the GBS. The integration of different omics datasets through a systems biology approach could allow network-based analyses to describe the complexity and
Gardner, Shea [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Slezak, Tom [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
With the flood of whole genome finished and draft microbial sequences, we need faster, more scalable bioinformatics tools for sequence comparison. An algorithm is described to find single nucleotide polymorphisms (SNPs) in whole genome data. It scales to hundreds of bacterial or viral genomes, and can be used for finished and/or draft genomes available as unassembled contigs. The method is fast to compute, finding SNPs and building a SNP phylogeny in seconds to hours. We use it to identify thousands of putative SNPs from all publicly available Filoviridae, Poxviridae, foot-and-mouth disease virus, Bacillus, and Escherichia coli genomes and plasmids. The SNP-based trees that result are consistent with known taxonomy and trees determined in other studies. The approach we describe can handle as input hundreds of gigabases of sequence in a single run. The algorithm is based on k-mer analysis using a suffix array, so we call it saSNP.
The overall focus of this chapter will be the application of functional genomic approaches for the study of the imprinted gene family in swine. While there are varied definitions of “functional genomics” in general they focus on the application of genomic approaches such as DNA microarrays, single n...
Manolio, Teri A
Increasing knowledge about the influence of genetic variation on human health and growing availability of reliable, cost-effective genetic testing have spurred the implementation of genomic medicine in the clinic. As defined by the National Human Genome Research Institute (NHGRI), genomic medicine uses an individual's genetic information in his or her clinical care, and has begun to be applied effectively in areas such as cancer genomics, pharmacogenomics, and rare and undiagnosed diseases. In 2011 NHGRI published its strategic vision for the future of genomic research, including an ambitious research agenda to facilitate and promote the implementation of genomic medicine. To realize this agenda, NHGRI is consulting and facilitating collaborations with the external research community through a series of "Genomic Medicine Meetings," under the guidance and leadership of the National Advisory Council on Human Genome Research. These meetings have identified and begun to address significant obstacles to implementation, such as lack of evidence of efficacy, limited availability of genomics expertise and testing, lack of standards, and difficulties in integrating genomic results into electronic medical records. The six research and dissemination initiatives comprising NHGRI's genomic research portfolio are designed to speed the evaluation and incorporation, where appropriate, of genomic technologies and findings into routine clinical care. Actual adoption of successful approaches in clinical care will depend upon the willingness, interest, and energy of professional societies, practitioners, patients, and payers to promote their responsible use and share their experiences in doing so. Published by Elsevier Ireland Ltd.
Choi, Yongwook; Chan, Agnes P; Kirkness, Ewen; Telenti, Amalio; Schork, Nicholas J
Humans are a diploid species that inherit one set of chromosomes paternally and one homologous set of chromosomes maternally. Unfortunately, most human sequencing initiatives ignore this fact in that they do not directly delineate the nucleotide content of the maternal and paternal copies of the 23 chromosomes individuals possess (i.e., they do not 'phase' the genome) often because of the costs and complexities of doing so. We compared 11 different widely-used approaches to phasing human genomes using the publicly available 'Genome-In-A-Bottle' (GIAB) phased version of the NA12878 genome as a gold standard. The phasing strategies we compared included laboratory-based assays that prepare DNA in unique ways to facilitate phasing as well as purely computational approaches that seek to reconstruct phase information from general sequencing reads and constructs or population-level haplotype frequency information obtained through a reference panel of haplotypes. To assess the performance of the 11 approaches, we used metrics that included, among others, switch error rates, haplotype block lengths, the proportion of fully phase-resolved genes, phasing accuracy and yield between pairs of SNVs. Our comparisons suggest that a hybrid or combined approach that leverages: 1. population-based phasing using the SHAPEIT software suite, 2. either genome-wide sequencing read data or parental genotypes, and 3. a large reference panel of variant and haplotype frequencies, provides a fast and efficient way to produce highly accurate phase-resolved individual human genomes. We found that for population-based approaches, phasing performance is enhanced with the addition of genome-wide read data; e.g., whole genome shotgun and/or RNA sequencing reads. Further, we found that the inclusion of parental genotype data within a population-based phasing strategy can provide as much as a ten-fold reduction in phasing errors. We also considered a majority voting scheme for the construction of a
Panzenhagen, P H N; Cabral, C C; Suffys, P N; Franco, R M; Rodrigues, D P; Conte-Junior, C A
Salmonella pathogenicity relies on virulence factors many of which are clustered within the Salmonella pathogenicity islands. Salmonella also harbours mobile genetic elements such as virulence plasmids, prophage-like elements and antimicrobial resistance genes which can contribute to increase its pathogenicity. Here, we have genetically characterized a selected S. Typhimurium strain (CCRJ_26) from our previous study with Multiple Drugs Resistant profile and high-frequency PFGE clonal profile which apparently persists in the pork production centre of Rio de Janeiro State, Brazil. By whole-genome sequencing, we described the strain's genome virulent content and characterized the repertoire of bacterial plasmids, antibiotic resistance genes and prophage-like elements. Here, we have shown evidence that strain CCRJ_26 genome possible represent a virulence-associated phenotype which may be potentially virulent in human infection. Whole-genome sequencing technologies are still costly and remain underexplored for applied microbiology in Brazil. Hence, this genomic description of S. Typhimurium strain CCRJ_26 will provide help in future molecular epidemiological studies. The analysis described here reveals a quick and useful pipeline for bacterial virulence characterization using whole-genome sequencing approach. © 2018 The Society for Applied Microbiology.
Yang, Xiaohan; Tschaplinski, Timothy J.; Hurst, Gregory B.; Jawdy, Sara; Abraham, Paul E.; Lankford, Patricia K.; Adams, Rachel M.; Shah, Manesh B.; Hettich, Robert L.; Lindquist, Erika; Kalluri, Udaya C.; Gunter, Lee E.; Pennacchio, Christa; Tuskan, Gerald A.
Small proteins (10 200 amino acids aa in length) encoded by short open reading frames (sORF) play important regulatory roles in various biological processes, including tumor progression, stress response, flowering, and hormone signaling. However, ab initio discovery of small proteins has been relatively overlooked. Recent advances in deep transcriptome sequencing make it possible to efficiently identify sORFs at the genome level. In this study, we obtained 2.6 million expressed sequence tag (EST) reads from Populus deltoides leaf transcriptome and reconstructed full-length transcripts from the EST sequences. We identified an initial set of 12,852 sORFs encoding proteins of 10 200 aa in length. Three computational approaches were then used to enrich for bona fide protein-coding sORFs from the initial sORF set: (1) codingpotential prediction, (2) evolutionary conservation between P. deltoides and other plant species, and (3) gene family clustering within P. deltoides. As a result, a high-confidence sORF candidate set containing 1469 genes was obtained. Analysis of the protein domains, non-protein-coding RNA motifs, sequence length distribution, and protein mass spectrometry data supported this high-confidence sORF set. In the high-confidence sORF candidate set, known protein domains were identified in 1282 genes (higher-confidence sORF candidate set), out of which 611 genes, designated as highest-confidence candidate sORF set, were supported by proteomics data. Of the 611 highest-confidence candidate sORF genes, 56 were new to the current Populus genome annotation. This study not only demonstrates that there are potential sORF candidates to be annotated in sequenced genomes, but also presents an efficient strategy for discovery of sORFs in species with no genome annotation yet available.
Pan-Genome Analysis of Human Gastric Pathogen H. pylori: Comparative Genomics and Pathogenomics Approaches to Identify Regions Associated with Pathogenicity and Prediction of Potential Core Therapeutic Targets
Ali, Amjad; Naz, Anam; Soares, Siomar C.
-genome approach; the predicted conserved gene families (1,193) constitute similar to 77% of the average H. pylori genome and 45% of the global gene repertoire of the species. Reverse vaccinology strategies have been adopted to identify and narrow down the potential core-immunogenic candidates. Total of 28 nonhost....... Pan-genome analyses of the global representative H. pylori isolates consisting of 39 complete genomes are presented in this paper. Phylogenetic analyses have revealed close relationships among geographically diverse strains of H. pylori. The conservation among these genomes was further analyzed by pan...
Full Text Available 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.
Barbasiewicz, Anna; Liu, Lin; Lang, B Franz; Burger, Gertraud
GOBASE is a relational database that integrates data associated with mitochondria and chloroplasts. The most important data in GOBASE, i. e., molecular sequences and taxonomic information, are obtained from the public sequence data repository at the National Center for Biotechnology Information (NCBI), and are validated by our experts. Maintaining a curated genomic database comes with a towering labor cost, due to the shear volume of available genomic sequences and the plethora of annotation errors and omissions in records retrieved from public repositories. Here we describe our approach to increase automation of the database population process, thereby reducing manual intervention. As a first step, we used Unified Modeling Language (UML) to construct a list of potential errors. Each case was evaluated independently, and an expert solution was devised, and represented as a diagram. Subsequently, the UML diagrams were used as templates for writing object-oriented automation programs in the Java programming language.
Dahl, Carol A.; Strausberg, Robert L.
The Human Genome Project (HGP) is an international project to develop genetic, physical, and sequence-based maps of the human genome. Since the inception of the HGP it has been clear that substantially improved technology would be required to meet the scientific goals, particularly in order to acquire the complete sequence of the human genome, and that these technologies coupled with the information forthcoming from the project would have a dramatic effect on the way biomedical research is performed in the future. In this paper, we discuss the state-of-the-art for genomic DNA sequencing, technological challenges that remain, and the potential technological paths that could yield substantially improved genomic sequencing technology. The impact of the technology developed from the HGP is broad-reaching and a discussion of other research and medical applications that are leveraging HGP-derived DNA analysis technologies is included. The multidisciplinary approach to the development of new technologies that has been successful for the HGP provides a paradigm for facilitating new genomic approaches toward understanding the biological role of functional elements and systems within the cell, including those encoded within genomic DNA and their molecular products.
Hyman, David M.; Taylor, Barry S.; Baselga, José
Early successes in identifying and targeting individual oncogenic drivers, together with the increasing feasibility of sequencing tumor genomes, have brought forth the promise of genome-driven oncology care. As we expand the breadth and depth of genomic analyses, the biological and clinical complexity of its implementation will be unparalleled. Challenges include target credentialing and validation, implementing drug combinations, clinical trial designs, targeting tumor heterogeneity, and deploying technologies beyond DNA sequencing, among others. We review how contemporary approaches are tackling these challenges and will ultimately serve as an engine for biological discovery and increase our insight into cancer and its treatment. PMID:28187282
Zhou, Shiguo [Univ. Wisc.-Madison; Kile, A. [Univ. Wisc.-Madison; Bechner, M. [Univ. Wisc.-Madison; Kvikstad, E. [Univ. Wisc.-Madison; Deng, W. [Univ. Wisc.-Madison; Wei, J. [Univ. Wisc.-Madison; Severin, J. [Univ. Wisc.-Madison; Runnheim, R. [Univ. Wisc.-Madison; Churas, C. [Univ. Wisc.-Madison; Forrest, D. [Univ. Wisc.-Madison; Dimalanta, E. [Univ. Wisc.-Madison; Lamers, C. [Univ. Wisc.-Madison; Burland, V. [Univ. Wisc.-Madison; Blattner, F. R. [Univ. Wisc.-Madison; Schwartz, David C. [Univ. Wisc.-Madison
Modern comparative genomics has been established, in part, by the sequencing and annotation of a broad range of microbial species. To gain further insights, new sequencing efforts are now dealing with the variety of strains or isolates that gives a species definition and range; however, this number vastly outstrips our ability to sequence them. Given the availability of a large number of microbial species, new whole genome approaches must be developed to fully leverage this information at the level of strain diversity that maximize discovery. Here, we describe how optical mapping, a single-molecule system, was used to identify and annotate chromosomal alterations between bacterial strains represented by several species. Since whole-genome optical maps are ordered restriction maps, sequenced strains of Shigella flexneri serotype 2a (2457T and 301), Yersinia pestis (CO 92 and KIM), and Escherichia coli were aligned as maps to identify regions of homology and to further characterize them as possible insertions, deletions, inversions, or translocations. Importantly, an unsequenced Shigella flexneri strain (serotype Y strain AMC[328Y]) was optically mapped and aligned with two sequenced ones to reveal one novel locus implicated in serotype conversion and several other loci containing insertion sequence elements or phage-related gene insertions. Our results suggest that genomic rearrangements and chromosomal breakpoints are readily identified and annotated against a prototypic sequenced strain by using the tools of optical mapping.
Manolio, Teri A.
Increasing knowledge about the influence of genetic variation on human health and growing availability of reliable, cost-effective genetic testing have spurred the implementation of genomic medicine in the clinic. As defined by the National Human Genome Research Institute (NHGRI), genomic medicine uses an individual’s genetic information in his or her clinical care, and has begun to be applied effectively in areas such as cancer genomics, pharmacogenomics, and rare and undiagnosed diseases. In 2011 NHGRI published its strategic vision for the future of genomic research, including an ambitious research agenda to facilitate and promote the implementation of genomic medicine. To realize this agenda, NHGRI is consulting and facilitating collaborations with the external research community through a series of “Genomic Medicine Meetings,” under the guidance and leadership of the National Advisory Council on Human Genome Research. These meetings have identified and begun to address significant obstacles to implementation, such as lack of evidence of efficacy, limited availability of genomics expertise and testing, lack of standards, and diffficulties in integrating genomic results into electronic medical records. The six research and dissemination initiatives comprising NHGRI’s genomic research portfolio are designed to speed the evaluation and incorporation, where appropriate, of genomic technologies and findings into routine clinical care. Actual adoption of successful approaches in clinical care will depend upon the willingness, interest, and energy of professional societies, practitioners, patients, and payers to promote their responsible use and share their experiences in doing so. PMID:27612677
Full Text Available For many decades karyotype was the only source of overall genomic information obtained from species of mammal. However, approaches have been developed in recent years to obtain molecular and ultimately genomic information directly from the extracted DNA of an organism. Molecular data have accumulated hugely for mammalian taxa. The growing volume of studies should motivate field researchers to collect suitable samples for molecular analysis from various species across all their ranges. This is the reason why we here include a molecular sampling procedure within a field work protocol, which also includes more traditional (including cytogenetic techniques. In this way we hope to foster the development of molecular and genomic studies in non-standard wild mammals.
Moin, Mazahar; Bakshi, Achala; Saha, Anusree; Dutta, Mouboni; Kirti, P B
The epitome of any genome research is to identify all the existing genes in a genome and investigate their roles. Various techniques have been applied to unveil the functions either by silencing or over-expressing the genes by targeted expression or random mutagenesis. Rice is the most appropriate model crop for generating a mutant resource for functional genomic studies because of the availability of high-quality genome sequence and relatively smaller genome size. Rice has syntenic relationships with members of other cereals. Hence, characterization of functionally unknown genes in rice will possibly provide key genetic insights and can lead to comparative genomics involving other cereals. The current review attempts to discuss the available gain-of-function mutagenesis techniques for functional genomics, emphasizing the contemporary approach, activation tagging and alterations to this method for the enhancement of yield and productivity of rice. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please email: email@example.com.
Mousavi-Derazmahalleh, Mahsa; Bayer, Philipp E; Hane, James K; Babu, Valliyodan; Nguyen, Henry T; Nelson, Matthew N; Erskine, William; Varshney, Rajeev K; Papa, Roberto; Edwards, David
Our agricultural system and hence food security is threatened by combination of events, such as increasing population, the impacts of climate change and the need to a more sustainable development. Evolutionary adaptation may help some species to overcome environmental changes through new selection pressures driven by climate change. However, success of evolutionary adaptation is dependent on various factors, one of which is the extent of genetic variation available within species. Genomic approaches provide an exceptional opportunity to identify genetic variation that can be employed in crop improvement programs. In this review, we illustrate some of the routinely used genomics-based methods as well as recent breakthroughs, which facilitate assessment of genetic variation and discovery of adaptive genes in legumes. While additional information is needed, the current utility of selection tools indicate a robust ability to utilize existing variation among legumes to address the challenges of climate uncertainty. This article is protected by copyright. All rights reserved.
Christensen Ole F
Full Text Available Abstract Background Genomic data are used in animal breeding to assist genetic evaluation. Several models to estimate genomic breeding values have been studied. In general, two approaches have been used. One approach estimates the marker effects first and then, genomic breeding values are obtained by summing marker effects. In the second approach, genomic breeding values are estimated directly using an equivalent model with a genomic relationship matrix. Allele coding is the method chosen to assign values to the regression coefficients in the statistical model. A common allele coding is zero for the homozygous genotype of the first allele, one for the heterozygote, and two for the homozygous genotype for the other allele. Another common allele coding changes these regression coefficients by subtracting a value from each marker such that the mean of regression coefficients is zero within each marker. We call this centered allele coding. This study considered effects of different allele coding methods on inference. Both marker-based and equivalent models were considered, and restricted maximum likelihood and Bayesian methods were used in inference. Results Theoretical derivations showed that parameter estimates and estimated marker effects in marker-based models are the same irrespective of the allele coding, provided that the model has a fixed general mean. For the equivalent models, the same results hold, even though different allele coding methods lead to different genomic relationship matrices. Calculated genomic breeding values are independent of allele coding when the estimate of the general mean is included into the values. Reliabilities of estimated genomic breeding values calculated using elements of the inverse of the coefficient matrix depend on the allele coding because different allele coding methods imply different models. Finally, allele coding affects the mixing of Markov chain Monte Carlo algorithms, with the centered coding being
Wang, Anqi; Wang, Zhanyu; Li, Zheng; Li, Lei M
It is highly desirable to assemble genomes of high continuity and consistency at low cost. The current bottleneck of draft genome continuity using the Second Generation Sequencing (SGS) reads is primarily caused by uncertainty among repetitive sequences. Even though the Single-Molecule Real-Time sequencing technology is very promising to overcome the uncertainty issue, its relatively high cost and error rate add burden on budget or computation. Many long-read assemblers take the overlap-layout-consensus (OLC) paradigm, which is less sensitive to sequencing errors, heterozygosity and variability of coverage. However, current assemblers of SGS data do not sufficiently take advantage of the OLC approach. Aiming at minimizing uncertainty, the proposed method BAUM, breaks the whole genome into regions by adaptive unique mapping; then the local OLC is used to assemble each region in parallel. BAUM can: (1) perform reference-assisted assembly based on the genome of a close species; (2) or improve the results of existing assemblies that are obtained based on short or long sequencing reads. The tests on two eukaryote genomes, a wild rice Oryza longistaminata and a parrot Melopsittacus undulatus, show that BAUM achieved substantial improvement on genome size and continuity. Besides, BAUM reconstructed a considerable amount of repetitive regions that failed to be assembled by existing short read assemblers. We also propose statistical approaches to control the uncertainty in different steps of BAUM. http://www.zhanyuwang.xin/wordpress/index.php/2017/07/21/baum. firstname.lastname@example.org. Supplementary data are available at Bioinformatics online. © The Author (2018). Published by Oxford University Press. All rights reserved. For Permissions, please email: email@example.com
Full Text Available Abstract Background DNA microarray technology is widely used to determine the expression levels of thousands of genes in a single experiment, for a broad range of organisms. Optimal design of immobilized nucleic acids has a direct impact on the reliability of microarray results. However, despite small genome size and complexity, prokaryotic organisms are not frequently studied to validate selected bioinformatics approaches. Relying on parameters shown to affect the hybridization of nucleic acids, we designed freely available software and validated experimentally its performance on the bacterial pathogen Staphylococcus aureus. Results We describe an efficient procedure for selecting 40–60 mer oligonucleotide probes combining optimal thermodynamic properties with high target specificity, suitable for genomic studies of microbial species. The algorithm for filtering probes from extensive oligonucleotides libraries fitting standard thermodynamic criteria includes positional information of predicted target-probe binding regions. This algorithm efficiently selected probes recognizing homologous gene targets across three different sequenced genomes of Staphylococcus aureus. BLAST analysis of the final selection of 5,427 probes yielded >97%, 93%, and 81% of Staphylococcus aureus genome coverage in strains N315, Mu50, and COL, respectively. A manufactured oligoarray including a subset of control Escherichia coli probes was validated for applications in the fields of comparative genomics and molecular epidemiology, mapping of deletion mutations and transcription profiling. Conclusion This generic chip-design process merging sequence information from several related genomes improves genome coverage even in conserved regions.
Over 95% of all metazoan (animal) species comprise the invertebrates, but very few genomes from these organisms have been sequenced. We have, therefore, formed a Global Invertebrate Genomics Alliance (GIGA). Our intent is to build a collaborative network of diverse scientists to tackle major challenges (e.g., species selection, sample collection and storage, sequence assembly, annotation, analytical tools) associated with genome/transcriptome sequencing across a large taxonomic spectrum. We aim to promote standards that will facilitate comparative approaches to invertebrate genomics and collaborations across the international scientific community. Candidate study taxa include species from Porifera, Ctenophora, Cnidaria, Placozoa, Mollusca, Arthropoda, Echinodermata, Annelida, Bryozoa, and Platyhelminthes, among others. GIGA will target 7000 noninsect/nonnematode species, with an emphasis on marine taxa because of the unrivaled phyletic diversity in the oceans. Priorities for selecting invertebrates for sequencing will include, but are not restricted to, their phylogenetic placement; relevance to organismal, ecological, and conservation research; and their importance to fisheries and human health. We highlight benefits of sequencing both whole genomes (DNA) and transcriptomes and also suggest policies for genomic-level data access and sharing based on transparency and inclusiveness. The GIGA Web site () has been launched to facilitate this collaborative venture.
Full Text Available For genome-wide association studies in family-based designs, we propose a new, universally applicable approach. The new test statistic exploits all available information about the association, while, by virtue of its design, it maintains the same robustness against population admixture as traditional family-based approaches that are based exclusively on the within-family information. The approach is suitable for the analysis of almost any trait type, e.g. binary, continuous, time-to-onset, multivariate, etc., and combinations of those. We use simulation studies to verify all theoretically derived properties of the approach, estimate its power, and compare it with other standard approaches. We illustrate the practical implications of the new analysis method by an application to a lung-function phenotype, forced expiratory volume in one second (FEV1 in 4 genome-wide association studies.
O’Brien, Edward J.; Monk, Jonathan M.; Palsson, Bernhard O.
Constraint-based reconstruction and analysis (COBRA) methods at the genome scale have been under development since the first whole-genome sequences appeared in the mid-1990s. A few years ago, this approach began to demonstrate the ability to predict a range of cellular functions, including cellul...
Kersey, Paul Julian; Allen, James E; Armean, Irina; Boddu, Sanjay; Bolt, Bruce J; Carvalho-Silva, Denise; Christensen, Mikkel; Davis, Paul; Falin, Lee J; Grabmueller, Christoph; Humphrey, Jay; Kerhornou, Arnaud; Khobova, Julia; Aranganathan, Naveen K; Langridge, Nicholas; Lowy, Ernesto; McDowall, Mark D; Maheswari, Uma; Nuhn, Michael; Ong, Chuang Kee; Overduin, Bert; Paulini, Michael; Pedro, Helder; Perry, Emily; Spudich, Giulietta; Tapanari, Electra; Walts, Brandon; Williams, Gareth; Tello-Ruiz, Marcela; Stein, Joshua; Wei, Sharon; Ware, Doreen; Bolser, Daniel M; Howe, Kevin L; Kulesha, Eugene; Lawson, Daniel; Maslen, Gareth; Staines, Daniel M
Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of programmatic and interactive interfaces to a rich range of data including reference sequence, gene models, transcriptional data, genetic variation and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments. These include the development of new analyses and views to represent polyploid genomes (of which bread wheat is the primary exemplar); and the continued up-scaling of the resource, which now includes over 23 000 bacterial genomes, 400 fungal genomes and 100 protist genomes, in addition to 55 genomes from invertebrate metazoa and 39 genomes from plants. This dramatic increase in the number of included genomes is one part of a broader effort to automate the integration of archival data (genome sequence, but also associated RNA sequence data and variant calls) within the context of reference genomes and make it available through the Ensembl user interfaces. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
Jenkinson, Garrett; Abante, Jordi; Feinberg, Andrew P; Goutsias, John
DNA methylation is a stable form of epigenetic memory used by cells to control gene expression. Whole genome bisulfite sequencing (WGBS) has emerged as a gold-standard experimental technique for studying DNA methylation by producing high resolution genome-wide methylation profiles. Statistical modeling and analysis is employed to computationally extract and quantify information from these profiles in an effort to identify regions of the genome that demonstrate crucial or aberrant epigenetic behavior. However, the performance of most currently available methods for methylation analysis is hampered by their inability to directly account for statistical dependencies between neighboring methylation sites, thus ignoring significant information available in WGBS reads. We present a powerful information-theoretic approach for genome-wide modeling and analysis of WGBS data based on the 1D Ising model of statistical physics. This approach takes into account correlations in methylation by utilizing a joint probability model that encapsulates all information available in WGBS methylation reads and produces accurate results even when applied on single WGBS samples with low coverage. Using the Shannon entropy, our approach provides a rigorous quantification of methylation stochasticity in individual WGBS samples genome-wide. Furthermore, it utilizes the Jensen-Shannon distance to evaluate differences in methylation distributions between a test and a reference sample. Differential performance assessment using simulated and real human lung normal/cancer data demonstrate a clear superiority of our approach over DSS, a recently proposed method for WGBS data analysis. Critically, these results demonstrate that marginal methods become statistically invalid when correlations are present in the data. This contribution demonstrates clear benefits and the necessity of modeling joint probability distributions of methylation using the 1D Ising model of statistical physics and of
For the first time in history, genetics will enable science to completely identify each human as genetically unique. Will this knowledge reinforce the trend for more individual liberties or will it create a 'brave new world'? A law policy approach to the problems raised by the human genome project shows how far our democratic institutions are from being the proper forum to discuss such issues. Because of the fears and anxiety raised in the population, and also because of its wide implications on the everyday life, the human genome analysis more than any other project needs to succeed in setting up such a social assessment.
Hotta, Akitsu; Yamanaka, Shinya
The advent of induced pluripotent stem (iPS) cells has opened up numerous avenues of opportunity for cell therapy, including the initiation in September 2014 of the first human clinical trial to treat dry age-related macular degeneration. In parallel, advances in genome-editing technologies by site-specific nucleases have dramatically improved our ability to edit endogenous genomic sequences at targeted sites of interest. In fact, clinical trials have already begun to implement this technology to control HIV infection. Genome editing in iPS cells is a powerful tool and enables researchers to investigate the intricacies of the human genome in a dish. In the near future, the groundwork laid by such an approach may expand the possibilities of gene therapy for treating congenital disorders. In this review, we summarize the exciting progress being made in the utilization of genomic editing technologies in pluripotent stem cells and discuss remaining challenges toward gene therapy applications.
Treangen, Todd J; Ondov, Brian D; Koren, Sergey; Phillippy, Adam M
Whole-genome sequences are now available for many microbial species and clades, however existing whole-genome alignment methods are limited in their ability to perform sequence comparisons of multiple sequences simultaneously. Here we present the Harvest suite of core-genome alignment and visualization tools for the rapid and simultaneous analysis of thousands of intraspecific microbial strains. Harvest includes Parsnp, a fast core-genome multi-aligner, and Gingr, a dynamic visual platform. Together they provide interactive core-genome alignments, variant calls, recombination detection, and phylogenetic trees. Using simulated and real data we demonstrate that our approach exhibits unrivaled speed while maintaining the accuracy of existing methods. The Harvest suite is open-source and freely available from: http://github.com/marbl/harvest.
Pennacchio, Len A.
Large-scale public genomic sequencing efforts have provided a wealth of vertebrate sequence data poised to provide insights into mammalian biology. These include deep genomic sequence coverage of human, mouse, rat, zebrafish, and two pufferfish (Fugu rubripes and Tetraodon nigroviridis) (Aparicio et al. 2002; Lander et al. 2001; Venter et al. 2001; Waterston et al. 2002). In addition, a high-priority has been placed on determining the genomic sequence of chimpanzee, dog, cow, frog, and chicken (Boguski 2002). While only recently available, whole genome sequence data have provided the unique opportunity to globally compare complete genome contents. Furthermore, the shared evolutionary ancestry of vertebrate species has allowed the development of comparative genomic approaches to identify ancient conserved sequences with functionality. Accordingly, this review focuses on the initial comparison of available mammalian genomes and describes various insights derived from such analysis.
Novichkov, Pavel S.; Rodionov, Dmitry A.; Stavrovskaya, Elena D.; Novichkova, Elena S.; Kazakov, Alexey E.; Gelfand, Mikhail S.; Arkin, Adam P.; Mironov, Andrey A.; Dubchak, Inna
RegPredict web server is designed to provide comparative genomics tools for reconstruction and analysis of microbial regulons using comparative genomics approach. The server allows the user to rapidly generate reference sets of regulons and regulatory motif profiles in a group of prokaryotic genomes. The new concept of a cluster of co-regulated orthologous operons allows the user to distribute the analysis of large regulons and to perform the comparative analysis of multiple clusters independently. Two major workflows currently implemented in RegPredict are: (i) regulon reconstruction for a known regulatory motif and (ii) ab initio inference of a novel regulon using several scenarios for the generation of starting gene sets. RegPredict provides a comprehensive collection of manually curated positional weight matrices of regulatory motifs. It is based on genomic sequences, ortholog and operon predictions from the MicrobesOnline. An interactive web interface of RegPredict integrates and presents diverse genomic and functional information about the candidate regulon members from several web resources. RegPredict is freely accessible at http://regpredict.lbl.gov.
Willnow, TE; Antignac, C; Brändli, AW; Christensen, EI; Cox, RD; Davidson, D; Davies, JA; Devuyst, O; Eichele, G; Hastie, ND; Verroust, PJ; Schedl, A; Meij, IC
Rapid progress in genome research creates a wealth of information on the functional annotation of mammalian genome sequences. However, as we accumulate large amounts of scientific information we are facing problems of how to integrate and relate the data produced by various genomic approaches. Here, we propose the novel concept of an organ atlas where diverse data from expression maps to histological findings to mutant phenotypes can be queried, compared and visualized in the context of a thr...
Valach, Matus; Burger, Gertraud; Gray, Michael W; Lang, B Franz
5S Ribosomal RNA (5S rRNA) is a universal component of ribosomes, and the corresponding gene is easily identified in archaeal, bacterial and nuclear genome sequences. However, organelle gene homologs (rrn5) appear to be absent from most mitochondrial and several chloroplast genomes. Here, we re-examine the distribution of organelle rrn5 by building mitochondrion- and plastid-specific covariance models (CMs) with which we screened organelle genome sequences. We not only recover all organelle rrn5 genes annotated in GenBank records, but also identify more than 50 previously unrecognized homologs in mitochondrial genomes of various stramenopiles, red algae, cryptomonads, malawimonads and apusozoans, and surprisingly, in the apicoplast (highly derived plastid) genomes of the coccidian pathogens Toxoplasma gondii and Eimeria tenella. Comparative modeling of RNA secondary structure reveals that mitochondrial 5S rRNAs from brown algae adopt a permuted triskelion shape that has not been seen elsewhere. Expression of the newly predicted rrn5 genes is confirmed experimentally in 10 instances, based on our own and published RNA-Seq data. This study establishes that particularly mitochondrial 5S rRNA has a much broader taxonomic distribution and a much larger structural variability than previously thought. The newly developed CMs will be made available via the Rfam database and the MFannot organelle genome annotator. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
Booth, Austin; Mariscal, Carlos; Doolittle, W Ford
We review the theoretical implications of findings in genomics for evolutionary biology since the Modern Synthesis. We examine the ways in which microbial genomics has influenced our understanding of the last universal common ancestor, the tree of life, species, lineages, and evolutionary transitions. We conclude by advocating a piecemeal toolkit approach to evolutionary biology, in lieu of any grand unified theory updated to include microbial genomics.
Full Text Available Abstract Background Public databases now contain multitude of complete bacterial genomes, including several genomes of the same species. The available data offers new opportunities to address questions about bacterial genome evolution, a task that requires reliable fine comparison data of closely related genomes. Recent analyses have shown, using pairwise whole genome alignments, that it is possible to segment bacterial genomes into a common conserved backbone and strain-specific sequences called loops. Results Here, we generalize this approach and propose a strategy that allows systematic and non-biased genome segmentation based on multiple genome alignments. Segmentation analyses, as applied to 13 different bacterial species, confirmed the feasibility of our approach to discern the 'mosaic' organization of bacterial genomes. Segmentation results are available through a Web interface permitting functional analysis, extraction and visualization of the backbone/loops structure of documented genomes. To illustrate the potential of this approach, we performed a precise analysis of the mosaic organization of three E. coli strains and functional characterization of the loops. Conclusion The segmentation results including the backbone/loops structure of 13 bacterial species genomes are new and available for use by the scientific community at the URL: http://genome.jouy.inra.fr/mosaic.
Alexander G. Elcheninov
Full Text Available Xanthan gum, a complex polysaccharide comprising glucose, mannose and glucuronic acid residues, is involved in numerous biotechnological applications in cosmetics, agriculture, pharmaceuticals, food and petroleum industries. Additionally, its oligosaccharides were shown to possess antimicrobial, antioxidant, and few other properties. Yet, despite its extensive usage, little is known about xanthan gum degradation pathways and mechanisms. Thermogutta terrifontis, isolated from a sample of microbial mat developed in a terrestrial hot spring of Kunashir island (Far-East of Russia, was described as the first thermophilic representative of the Planctomycetes phylum. It grows well on xanthan gum either at aerobic or anaerobic conditions. Genomic analysis unraveled the pathways of oligo- and polysaccharides utilization, as well as the mechanisms of aerobic and anaerobic respiration. The combination of genomic and transcriptomic approaches suggested a novel xanthan gum degradation pathway which involves novel glycosidase(s of DUF1080 family, hydrolyzing xanthan gum backbone beta-glucosidic linkages and beta-mannosidases instead of xanthan lyases, catalyzing cleavage of terminal beta-mannosidic linkages. Surprisingly, the genes coding DUF1080 proteins were abundant in T. terrifontis and in many other Planctomycetes genomes, which, together with our observation that xanthan gum being a selective substrate for many planctomycetes, suggest crucial role of DUF1080 in xanthan gum degradation. Our findings shed light on the metabolism of the first thermophilic planctomycete, capable to degrade a number of polysaccharides, either aerobically or anaerobically, including the biotechnologically important bacterial polysaccharide xanthan gum.
Elcheninov, Alexander G.; Menzel, Peter; Gudbergsdottir, Soley R.; Slesarev, Alexei I.; Kadnikov, Vitaly V.; Krogh, Anders; Bonch-Osmolovskaya, Elizaveta A.; Peng, Xu; Kublanov, Ilya V.
Xanthan gum, a complex polysaccharide comprising glucose, mannose and glucuronic acid residues, is involved in numerous biotechnological applications in cosmetics, agriculture, pharmaceuticals, food and petroleum industries. Additionally, its oligosaccharides were shown to possess antimicrobial, antioxidant, and few other properties. Yet, despite its extensive usage, little is known about xanthan gum degradation pathways and mechanisms. Thermogutta terrifontis, isolated from a sample of microbial mat developed in a terrestrial hot spring of Kunashir island (Far-East of Russia), was described as the first thermophilic representative of the Planctomycetes phylum. It grows well on xanthan gum either at aerobic or anaerobic conditions. Genomic analysis unraveled the pathways of oligo- and polysaccharides utilization, as well as the mechanisms of aerobic and anaerobic respiration. The combination of genomic and transcriptomic approaches suggested a novel xanthan gum degradation pathway which involves novel glycosidase(s) of DUF1080 family, hydrolyzing xanthan gum backbone beta-glucosidic linkages and beta-mannosidases instead of xanthan lyases, catalyzing cleavage of terminal beta-mannosidic linkages. Surprisingly, the genes coding DUF1080 proteins were abundant in T. terrifontis and in many other Planctomycetes genomes, which, together with our observation that xanthan gum being a selective substrate for many planctomycetes, suggest crucial role of DUF1080 in xanthan gum degradation. Our findings shed light on the metabolism of the first thermophilic planctomycete, capable to degrade a number of polysaccharides, either aerobically or anaerobically, including the biotechnologically important bacterial polysaccharide xanthan gum. PMID:29163426
Palle Duun Rohde
Full Text Available The ability of natural populations to withstand environmental stresses relies partly on their adaptive ability. In this study, we used a subset of the Drosophila Genetic Reference Panel, a population of inbred, genome-sequenced lines derived from a natural population of Drosophila melanogaster, to investigate whether this population harbors genetic variation for a set of stress resistance and life history traits. Using a genomic approach, we found substantial genetic variation for metabolic rate, heat stress resistance, expression of a major heat shock protein, and egg-to-adult viability investigated at a benign and a higher stressful temperature. This suggests that these traits will be able to evolve. In addition, we outline an approach to conduct pathway associations based on genomic linear models, which has potential to identify adaptive genes and pathways, and therefore can be a valuable tool in conservation genomics.
Smith, Stephen A; Brown, Joseph W; Walker, Joseph F
Phylogenomic datasets have been successfully used to address questions involving evolutionary relationships, patterns of genome structure, signatures of selection, and gene and genome duplications. However, despite the recent explosion in genomic and transcriptomic data, the utility of these data sources for efficient divergence-time inference remains unexamined. Phylogenomic datasets pose two distinct problems for divergence-time estimation: (i) the volume of data makes inference of the entire dataset intractable, and (ii) the extent of underlying topological and rate heterogeneity across genes makes model mis-specification a real concern. "Gene shopping", wherein a phylogenomic dataset is winnowed to a set of genes with desirable properties, represents an alternative approach that holds promise in alleviating these issues. We implemented an approach for phylogenomic datasets (available in SortaDate) that filters genes by three criteria: (i) clock-likeness, (ii) reasonable tree length (i.e., discernible information content), and (iii) least topological conflict with a focal species tree (presumed to have already been inferred). Such a winnowing procedure ensures that errors associated with model (both clock and topology) mis-specification are minimized, therefore reducing error in divergence-time estimation. We demonstrated the efficacy of this approach through simulation and applied it to published animal (Aves, Diplopoda, and Hymenoptera) and plant (carnivorous Caryophyllales, broad Caryophyllales, and Vitales) phylogenomic datasets. By quantifying rate heterogeneity across both genes and lineages we found that every empirical dataset examined included genes with clock-like, or nearly clock-like, behavior. Moreover, many datasets had genes that were clock-like, exhibited reasonable evolutionary rates, and were mostly compatible with the species tree. We identified overlap in age estimates when analyzing these filtered genes under strict clock and uncorrelated
Doerr, Daniel; Chauve, Cedric
Yersinia pestis is the causative agent of the bubonic plague, a disease responsible for several dramatic historical pandemics. Progress in ancient DNA (aDNA) sequencing rendered possible the sequencing of whole genomes of important human pathogens, including the ancient Y. pestis strains responsible for outbreaks of the bubonic plague in London in the 14th century and in Marseille in the 18th century, among others. However, aDNA sequencing data are still characterized by short reads and non-uniform coverage, so assembling ancient pathogen genomes remains challenging and often prevents a detailed study of genome rearrangements. It has recently been shown that comparative scaffolding approaches can improve the assembly of ancient Y. pestis genomes at a chromosome level. In the present work, we address the last step of genome assembly, the gap-filling stage. We describe an optimization-based method AGapEs (ancestral gap estimation) to fill in inter-contig gaps using a combination of a template obtained from related extant genomes and aDNA reads. We show how this approach can be used to refine comparative scaffolding by selecting contig adjacencies supported by a mix of unassembled aDNA reads and comparative signal. We applied our method to two Y. pestis data sets from the London and Marseilles outbreaks, for which we obtained highly improved genome assemblies for both genomes, comprised of, respectively, five and six scaffolds with 95 % of the assemblies supported by ancient reads. We analysed the genome evolution between both ancient genomes in terms of genome rearrangements, and observed a high level of synteny conservation between these strains. PMID:29114402
Full Text Available A large number of highly pathogenic bacteria utilize secretion systems to translocate effector proteins into host cells. Using these effectors, the bacteria subvert host cell processes during infection. Legionella pneumophila translocates effectors via the Icm/Dot type-IV secretion system and to date, approximately 100 effectors have been identified by various experimental and computational techniques. Effector identification is a critical first step towards the understanding of the pathogenesis system in L. pneumophila as well as in other bacterial pathogens. Here, we formulate the task of effector identification as a classification problem: each L. pneumophila open reading frame (ORF was classified as either effector or not. We computationally defined a set of features that best distinguish effectors from non-effectors. These features cover a wide range of characteristics including taxonomical dispersion, regulatory data, genomic organization, similarity to eukaryotic proteomes and more. Machine learning algorithms utilizing these features were then applied to classify all the ORFs within the L. pneumophila genome. Using this approach we were able to predict and experimentally validate 40 new effectors, reaching a success rate of above 90%. Increasing the number of validated effectors to around 140, we were able to gain novel insights into their characteristics. Effectors were found to have low G+C content, supporting the hypothesis that a large number of effectors originate via horizontal gene transfer, probably from their protozoan host. In addition, effectors were found to cluster in specific genomic regions. Finally, we were able to provide a novel description of the C-terminal translocation signal required for effector translocation by the Icm/Dot secretion system. To conclude, we have discovered 40 novel L. pneumophila effectors, predicted over a hundred additional highly probable effectors, and shown the applicability of machine
Jones, L.M.; Migneron, R.; Narayanan, K.S.S.
We show how integrodifferential equations typical of jet calculus can be combined with an averaging procedure to obtain jet-calculus-based results including the Mueller interference graphs. Results in longitudinal-momentum fraction x for physical quantities are higher at intermediate x and lower at large x than with the conventional ''incoherent'' jet calculus. These results resemble those of Marchesini and Webber, who used a Monte Carlo approach based on the same dynamics
Canals, Rocio; McClelland, Michael; Santiviago, Carlos A.; Andrews-Polymenis, Helene
Progress in the study of Salmonella survival, colonization, and virulence has increased rapidly with the advent of complete genome sequencing and higher capacity assays for transcriptomic and proteomic analysis. Although many of these techniques have yet to be used to directly assay Salmonella growth on foods, these assays are currently in use to determine Salmonella factors necessary for growth in animal models including livestock animals and in in vitro conditions that mimic many different environments. As sequencing of the Salmonella genome and microarray analysis have revolutionized genomics and transcriptomics of salmonellae over the last decade, so are new high-throughput sequencing technologies currently accelerating the pace of our studies and allowing us to approach complex problems that were not previously experimentally tractable.
Simon E Tröder
Full Text Available Electroporation of zygotes represents a rapid alternative to the elaborate pronuclear injection procedure for CRISPR/Cas9-mediated genome editing in mice. However, current protocols for electroporation either require the investment in specialized electroporators or corrosive pre-treatment of zygotes which compromises embryo viability. Here, we describe an easily adaptable approach for the introduction of specific mutations in C57BL/6 mice by electroporation of intact zygotes using a common electroporator with synthetic CRISPR/Cas9 components and minimal technical requirement. Direct comparison to conventional pronuclear injection demonstrates significantly reduced physical damage and thus improved embryo development with successful genome editing in up to 100% of living offspring. Hence, our novel approach for Easy Electroporation of Zygotes (EEZy allows highly efficient generation of CRISPR/Cas9 transgenic mice while reducing the numbers of animals required.
Entamoeba histolytica is the intestinal protozoan parasite responsible for amebic colitis and liver abscesses, which cause mortality in many developing countries. The sequencing of the parasite genome provides new insights into the cellular workings and genome evolution of this major human pathogen. Here, we reviewed ...
Zhang, Bin; Wolynes, Peter
The genome, the blueprint of life, contains nearly all the information needed to build and maintain an entire organism. A comprehensive understanding of the genome is of paramount interest to human health and will advance progress in many areas, including life sciences, medicine, and biotechnology. The overarching goal of my research is to understand the structure-dynamics-function relationships of the human genome. In this talk, I will be presenting our efforts in moving towards that goal, with a particular emphasis on studying the three-dimensional organization, the structure of the genome with multi-scale approaches. Specifically, I will discuss the reconstruction of genome structures at both interphase and metaphase by making use of data from chromosome conformation capture experiments. Computationally modeling of chromatin fiber at atomistic level from first principles will also be presented as our effort for studying the genome structure from bottom up.
Ellrott, Kyle; Bailey, Matthew H.; Saksena, Gordon; Covington, Kyle R.; Kandoth, Cyriac; Stewart, Chip; Hess, Julian; Ma, Singer; Chiotti, Kami E.; McLellan, Michael; Sofia, Heidi J.; Hutter, Carolyn M.; Getz, Gad; Wheeler, David A.; Ding, Li; Caesar-Johnson, Samantha J.; Demchok, John A.; Felau, Ina; Kasapi, Melpomeni; Ferguson, Martin L.; Hutter, Carolyn M.; Sofia, Heidi J.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean C.; Zhang, Jiashan (Julia); Chudamani, Sudha; Liu, Jia; Lolla, Laxmi; Naresh, Rashi; Pihl, Todd; Sun, Qiang; Wan, Yunhu; Wu, Ye; Cho, Juok; DeFreitas, Timothy; Frazer, Scott; Gehlenborg, Nils; Getz, Gad; Heiman, David I.; Kim, Jaegil; Lawrence, Michael S.; Lin, Pei; Meier, Sam; Noble, Michael S.; Saksena, Gordon; Voet, Doug; Zhang, Hailei; Bernard, Brady; Chambwe, Nyasha; Dhankani, Varsha; Knijnenburg, Theo; Kramer, Roger; Leinonen, Kalle; Liu, Yuexin; Miller, Michael; Reynolds, Sheila; Shmulevich, Ilya; Thorsson, Vesteinn; Zhang, Wei; Akbani, Rehan; Broom, Bradley M.; Hegde, Apurva M.; Ju, Zhenlin; Kanchi, Rupa S.; Korkut, Anil; Li, Jun; Liang, Han; Ling, Shiyun; Liu, Wenbin; Lu, Yiling; Mills, Gordon B.; Ng, Kwok Shing; Rao, Arvind; Ryan, Michael; Wang, Jing; Weinstein, John N.; Zhang, Jiexin; Abeshouse, Adam; Armenia, Joshua; Chakravarty, Debyani; Chatila, Walid K.; de Bruijn, Ino; Gao, Jianjiong; Gross, Benjamin E.; Heins, Zachary J.; Kundra, Ritika; La, Konnor; Ladanyi, Marc; Luna, Augustin; Nissan, Moriah G.; Ochoa, Angelica; Phillips, Sarah M.; Reznik, Ed; Sanchez-Vega, Francisco; Sander, Chris; Schultz, Nikolaus; Sheridan, Robert; Sumer, S. Onur; Sun, Yichao; Taylor, Barry S.; Wang, Jioajiao; Zhang, Hongxin; Anur, Pavana; Peto, Myron; Spellman, Paul; Benz, Christopher; Stuart, Joshua M.; Wong, Christopher K.; Yau, Christina; Hayes, D. Neil; Wilkerson, Matthew D.; Ally, Adrian; Balasundaram, Miruna; Bowlby, Reanne; Brooks, Denise; Carlsen, Rebecca; Chuah, Eric; Dhalla, Noreen; Holt, Robert; Jones, Steven J.M.; Kasaian, Katayoon; Lee, Darlene; Ma, Yussanne; Marra, Marco A.; Mayo, Michael; Moore, Richard A.; Mungall, Andrew J.; Mungall, Karen; Robertson, A. Gordon; Sadeghi, Sara; Schein, Jacqueline E.; Sipahimalani, Payal; Tam, Angela; Thiessen, Nina; Tse, Kane; Wong, Tina; Berger, Ashton C.; Beroukhim, Rameen; Cherniack, Andrew D.; Cibulskis, Carrie; Gabriel, Stacey B.; Gao, Galen F.; Ha, Gavin; Meyerson, Matthew; Schumacher, Steven E.; Shih, Juliann; Kucherlapati, Melanie H.; Kucherlapati, Raju S.; Baylin, Stephen; Cope, Leslie; Danilova, Ludmila; Bootwalla, Moiz S.; Lai, Phillip H.; Maglinte, Dennis T.; Van Den Berg, David J.; Weisenberger, Daniel J.; Auman, J. Todd; Balu, Saianand; Bodenheimer, Tom; Fan, Cheng; Hoadley, Katherine A.; Hoyle, Alan P.; Jefferys, Stuart R.; Jones, Corbin D.; Meng, Shaowu; Mieczkowski, Piotr A.; Mose, Lisle E.; Perou, Amy H.; Perou, Charles M.; Roach, Jeffrey; Shi, Yan; Simons, Janae V.; Skelly, Tara; Soloway, Matthew G.; Tan, Donghui; Veluvolu, Umadevi; Fan, Huihui; Hinoue, Toshinori; Laird, Peter W.; Shen, Hui; Zhou, Wanding; Bellair, Michelle; Chang, Kyle; Covington, Kyle; Creighton, Chad J.; Dinh, Huyen; Doddapaneni, Harsha Vardhan; Donehower, Lawrence A.; Drummond, Jennifer; Gibbs, Richard A.; Glenn, Robert; Hale, Walker; Han, Yi; Hu, Jianhong; Korchina, Viktoriya; Lee, Sandra; Lewis, Lora; Li, Wei; Liu, Xiuping; Morgan, Margaret; Morton, Donna; Muzny, Donna; Santibanez, Jireh; Sheth, Margi; Shinbrot, Eve; Wang, Linghua; Wang, Min; Wheeler, David A.; Xi, Liu; Zhao, Fengmei; Hess, Julian; Appelbaum, Elizabeth L.; Bailey, Matthew; Cordes, Matthew G.; Ding, Li; Fronick, Catrina C.; Fulton, Lucinda A.; Fulton, Robert S.; Kandoth, Cyriac; Mardis, Elaine R.; McLellan, Michael D.; Miller, Christopher A.; Schmidt, Heather K.; Wilson, Richard K.; Crain, Daniel; Curley, Erin; Gardner, Johanna; Lau, Kevin; Mallery, David; Morris, Scott; Paulauskis, Joseph; Penny, Robert; Shelton, Candace; Shelton, Troy; Sherman, Mark; Thompson, Eric; Yena, Peggy; Bowen, Jay; Gastier-Foster, Julie M.; Gerken, Mark; Leraas, Kristen M.; Lichtenberg, Tara M.; Ramirez, Nilsa C.; Wise, Lisa; Zmuda, Erik; Corcoran, Niall; Costello, Tony; Hovens, Christopher; Carvalho, Andre L.; de Carvalho, Ana C.; Fregnani, José H.; Longatto-Filho, Adhemar; Reis, Rui M.; Scapulatempo-Neto, Cristovam; Silveira, Henrique C.S.; Vidal, Daniel O.; Burnette, Andrew; Eschbacher, Jennifer; Hermes, Beth; Noss, Ardene; Singh, Rosy; Anderson, Matthew L.; Castro, Patricia D.; Ittmann, Michael; Huntsman, David; Kohl, Bernard; Le, Xuan; Thorp, Richard; Andry, Chris; Duffy, Elizabeth R.; Lyadov, Vladimir; Paklina, Oxana; Setdikova, Galiya; Shabunin, Alexey; Tavobilov, Mikhail; McPherson, Christopher; Warnick, Ronald; Berkowitz, Ross; Cramer, Daniel; Feltmate, Colleen; Horowitz, Neil; Kibel, Adam; Muto, Michael; Raut, Chandrajit P.; Malykh, Andrei; Barnholtz-Sloan, Jill S.; Barrett, Wendi; Devine, Karen; Fulop, Jordonna; Ostrom, Quinn T.; Shimmel, Kristen; Wolinsky, Yingli; Sloan, Andrew E.; De Rose, Agostino; Giuliante, Felice; Goodman, Marc; Karlan, Beth Y.; Hagedorn, Curt H.; Eckman, John; Harr, Jodi; Myers, Jerome; Tucker, Kelinda; Zach, Leigh Anne; Deyarmin, Brenda; Hu, Hai; Kvecher, Leonid; Larson, Caroline; Mural, Richard J.; Somiari, Stella; Vicha, Ales; Zelinka, Tomas; Bennett, Joseph; Iacocca, Mary; Rabeno, Brenda; Swanson, Patricia; Latour, Mathieu; Lacombe, Louis; Têtu, Bernard; Bergeron, Alain; McGraw, Mary; Staugaitis, Susan M.; Chabot, John; Hibshoosh, Hanina; Sepulveda, Antonia; Su, Tao; Wang, Timothy; Potapova, Olga; Voronina, Olga; Desjardins, Laurence; Mariani, Odette; Roman-Roman, Sergio; Sastre, Xavier; Stern, Marc Henri; Cheng, Feixiong; Signoretti, Sabina; Berchuck, Andrew; Bigner, Darell; Lipp, Eric; Marks, Jeffrey; McCall, Shannon; McLendon, Roger; Secord, Angeles; Sharp, Alexis; Behera, Madhusmita; Brat, Daniel J.; Chen, Amy; Delman, Keith; Force, Seth; Khuri, Fadlo; Magliocca, Kelly; Maithel, Shishir; Olson, Jeffrey J.; Owonikoko, Taofeek; Pickens, Alan; Ramalingam, Suresh; Shin, Dong M.; Sica, Gabriel; Van Meir, Erwin G.; Zhang, Hongzheng; Eijckenboom, Wil; Gillis, Ad; Korpershoek, Esther; Looijenga, Leendert; Oosterhuis, Wolter; Stoop, Hans; van Kessel, Kim E.; Zwarthoff, Ellen C.; Calatozzolo, Chiara; Cuppini, Lucia; Cuzzubbo, Stefania; DiMeco, Francesco; Finocchiaro, Gaetano; Mattei, Luca; Perin, Alessandro; Pollo, Bianca; Chen, Chu; Houck, John; Lohavanichbutr, Pawadee; Hartmann, Arndt; Stoehr, Christine; Stoehr, Robert; Taubert, Helge; Wach, Sven; Wullich, Bernd; Kycler, Witold; Murawa, Dawid; Wiznerowicz, Maciej; Chung, Ki; Edenfield, W. Jeffrey; Martin, Julie; Baudin, Eric; Bubley, Glenn; Bueno, Raphael; De Rienzo, Assunta; Richards, William G.; Kalkanis, Steven; Mikkelsen, Tom; Noushmehr, Houtan; Scarpace, Lisa; Girard, Nicolas; Aymerich, Marta; Campo, Elias; Giné, Eva; Guillermo, Armando López; Van Bang, Nguyen; Hanh, Phan Thi; Phu, Bui Duc; Tang, Yufang; Colman, Howard; Evason, Kimberley; Dottino, Peter R.; Martignetti, John A.; Gabra, Hani; Juhl, Hartmut; Akeredolu, Teniola; Stepa, Serghei; Hoon, Dave; Ahn, Keunsoo; Kang, Koo Jeong; Beuschlein, Felix; Breggia, Anne; Birrer, Michael; Bell, Debra; Borad, Mitesh; Bryce, Alan H.; Castle, Erik; Chandan, Vishal; Cheville, John; Copland, John A.; Farnell, Michael; Flotte, Thomas; Giama, Nasra; Ho, Thai; Kendrick, Michael; Kocher, Jean Pierre; Kopp, Karla; Moser, Catherine; Nagorney, David; O'Brien, Daniel; O'Neill, Brian Patrick; Patel, Tushar; Petersen, Gloria; Que, Florencia; Rivera, Michael; Roberts, Lewis; Smallridge, Robert; Smyrk, Thomas; Stanton, Melissa; Thompson, R. Houston; Torbenson, Michael; Yang, Ju Dong; Zhang, Lizhi; Brimo, Fadi; Ajani, Jaffer A.; Angulo Gonzalez, Ana Maria; Behrens, Carmen; Bondaruk, Jolanta; Broaddus, Russell; Czerniak, Bogdan; Esmaeli, Bita; Fujimoto, Junya; Gershenwald, Jeffrey; Guo, Charles; Lazar, Alexander J.; Logothetis, Christopher; Meric-Bernstam, Funda; Moran, Cesar; Ramondetta, Lois; Rice, David; Sood, Anil; Tamboli, Pheroze; Thompson, Timothy; Troncoso, Patricia; Tsao, Anne; Wistuba, Ignacio; Carter, Candace; Haydu, Lauren; Hersey, Peter; Jakrot, Valerie; Kakavand, Hojabr; Kefford, Richard; Lee, Kenneth; Long, Georgina; Mann, Graham; Quinn, Michael; Saw, Robyn; Scolyer, Richard; Shannon, Kerwin; Spillane, Andrew; Stretch, Jonathan; Synott, Maria; Thompson, John; Wilmott, James; Al-Ahmadie, Hikmat; Chan, Timothy A.; Ghossein, Ronald; Gopalan, Anuradha; Levine, Douglas A.; Reuter, Victor; Singer, Samuel; Singh, Bhuvanesh; Tien, Nguyen Viet; Broudy, Thomas; Mirsaidi, Cyrus; Nair, Praveen; Drwiega, Paul; Miller, Judy; Smith, Jennifer; Zaren, Howard; Park, Joong Won; Hung, Nguyen Phi; Kebebew, Electron; Linehan, W. Marston; Metwalli, Adam R.; Pacak, Karel; Pinto, Peter A.; Schiffman, Mark; Schmidt, Laura S.; Vocke, Cathy D.; Wentzensen, Nicolas; Worrell, Robert; Yang, Hannah; Moncrieff, Marc; Goparaju, Chandra; Melamed, Jonathan; Pass, Harvey; Botnariuc, Natalia; Caraman, Irina; Cernat, Mircea; Chemencedji, Inga; Clipca, Adrian; Doruc, Serghei; Gorincioi, Ghenadie; Mura, Sergiu; Pirtac, Maria; Stancul, Irina; Tcaciuc, Diana; Albert, Monique; Alexopoulou, Iakovina; Arnaout, Angel; Bartlett, John; Engel, Jay; Gilbert, Sebastien; Parfitt, Jeremy; Sekhon, Harman; Thomas, George; Rassl, Doris M.; Rintoul, Robert C.; Bifulco, Carlo; Tamakawa, Raina; Urba, Walter; Hayward, Nicholas; Timmers, Henri; Antenucci, Anna; Facciolo, Francesco; Grazi, Gianluca; Marino, Mirella; Merola, Roberta; de Krijger, Ronald; Gimenez-Roqueplo, Anne Paule; Piché, Alain; Chevalier, Simone; McKercher, Ginette; Birsoy, Kivanc; Barnett, Gene; Brewer, Cathy; Farver, Carol; Naska, Theresa; Pennell, Nathan A.; Raymond, Daniel; Schilero, Cathy; Smolenski, Kathy; Williams, Felicia; Morrison, Carl; Borgia, Jeffrey A.; Liptay, Michael J.; Pool, Mark; Seder, Christopher W.; Junker, Kerstin; Omberg, Larsson; Dinkin, Mikhail; Manikhas, George; Alvaro, Domenico; Bragazzi, Maria Consiglia; Cardinale, Vincenzo; Carpino, Guido; Gaudio, Eugenio; Chesla, David; Cottingham, Sandra; Dubina, Michael; Moiseenko, Fedor; Dhanasekaran, Renumathy; Becker, Karl Friedrich; Janssen, Klaus Peter; Slotta-Huspenina, Julia; Abdel-Rahman, Mohamed H.; Aziz, Dina; Bell, Sue; Cebulla, Colleen M.; Davis, Amy; Duell, Rebecca; Elder, J. Bradley; Hilty, Joe; Kumar, Bahavna; Lang, James; Lehman, Norman L.; Mandt, Randy; Nguyen, Phuong; Pilarski, Robert; Rai, Karan; Schoenfield, Lynn; Senecal, Kelly; Wakely, Paul; Hansen, Paul; Lechan, Ronald; Powers, James; Tischler, Arthur; Grizzle, William E.; Sexton, Katherine C.; Kastl, Alison; Henderson, Joel; Porten, Sima; Waldmann, Jens; Fassnacht, Martin; Asa, Sylvia L.; Schadendorf, Dirk; Couce, Marta; Graefen, Markus; Huland, Hartwig; Sauter, Guido; Schlomm, Thorsten; Simon, Ronald; Tennstedt, Pierre; Olabode, Oluwole; Nelson, Mark; Bathe, Oliver; Carroll, Peter R.; Chan, June M.; Disaia, Philip; Glenn, Pat; Kelley, Robin K.; Landen, Charles N.; Phillips, Joanna; Prados, Michael; Simko, Jeffry; Smith-McCune, Karen; VandenBerg, Scott; Roggin, Kevin; Fehrenbach, Ashley; Kendler, Ady; Sifri, Suzanne; Steele, Ruth; Jimeno, Antonio; Carey, Francis; Forgie, Ian; Mannelli, Massimo; Carney, Michael; Hernandez, Brenda; Campos, Benito; Herold-Mende, Christel; Jungk, Christin; Unterberg, Andreas; von Deimling, Andreas; Bossler, Aaron; Galbraith, Joseph; Jacobus, Laura; Knudson, Michael; Knutson, Tina; Ma, Deqin; Milhem, Mohammed; Sigmund, Rita; Godwin, Andrew K.; Madan, Rashna; Rosenthal, Howard G.; Adebamowo, Clement; Adebamowo, Sally N.; Boussioutas, Alex; Beer, David; Giordano, Thomas; Mes-Masson, Anne Marie; Saad, Fred; Bocklage, Therese; Landrum, Lisa; Mannel, Robert; Moore, Kathleen; Moxley, Katherine; Postier, Russel; Walker, Joan; Zuna, Rosemary; Feldman, Michael; Valdivieso, Federico; Dhir, Rajiv; Luketich, James; Mora Pinero, Edna M.; Quintero-Aguilo, Mario; Carlotti, Carlos Gilberto; Dos Santos, Jose Sebastião; Kemp, Rafael; Sankarankuty, Ajith; Tirapelli, Daniela; Catto, James; Agnew, Kathy; Swisher, Elizabeth; Creaney, Jenette; Robinson, Bruce; Shelley, Carl Simon; Godwin, Eryn M.; Kendall, Sara; Shipman, Cassaundra; Bradford, Carol; Carey, Thomas; Haddad, Andrea; Moyer, Jeffey; Peterson, Lisa; Prince, Mark; Rozek, Laura; Wolf, Gregory; Bowman, Rayleen; Fong, Kwun M.; Yang, Ian; Korst, Robert; Rathmell, W. Kimryn; Fantacone-Campbell, J. Leigh; Hooke, Jeffrey A.; Kovatich, Albert J.; Shriver, Craig D.; DiPersio, John; Drake, Bettina; Govindan, Ramaswamy; Heath, Sharon; Ley, Timothy; Van Tine, Brian; Westervelt, Peter; Rubin, Mark A.; Lee, Jung Il; Aredes, Natália D.; Mariamidze, Armaz
The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers project, our effort to generate a
Full Text Available Abstract Background Vibrio taxonomy has been based on a polyphasic approach. In this study, we retrieve useful taxonomic information (i.e. data that can be used to distinguish different taxonomic levels, such as species and genera from 32 genome sequences of different vibrio species. We use a variety of tools to explore the taxonomic relationship between the sequenced genomes, including Multilocus Sequence Analysis (MLSA, supertrees, Average Amino Acid Identity (AAI, genomic signatures, and Genome BLAST atlases. Our aim is to analyse the usefulness of these tools for species identification in vibrios. Results We have generated four new genome sequences of three Vibrio species, i.e., V. alginolyticus 40B, V. harveyi-like 1DA3, and V. mimicus strains VM573 and VM603, and present a broad analyses of these genomes along with other sequenced Vibrio species. The genome atlas and pangenome plots provide a tantalizing image of the genomic differences that occur between closely related sister species, e.g. V. cholerae and V. mimicus. The vibrio pangenome contains around 26504 genes. The V. cholerae core genome and pangenome consist of 1520 and 6923 genes, respectively. Pangenomes might allow different strains of V. cholerae to occupy different niches. MLSA and supertree analyses resulted in a similar phylogenetic picture, with a clear distinction of four groups (Vibrio core group, V. cholerae-V. mimicus, Aliivibrio spp., and Photobacterium spp.. A Vibrio species is defined as a group of strains that share > 95% DNA identity in MLSA and supertree analysis, > 96% AAI, ≤ 10 genome signature dissimilarity, and > 61% proteome identity. Strains of the same species and species of the same genus will form monophyletic groups on the basis of MLSA and supertree. Conclusion The combination of different analytical and bioinformatics tools will enable the most accurate species identification through genomic computational analysis. This endeavour will culminate in
Cai, Binghuang; Li, Biao; Kiga, Nikki; Thusberg, Janita; Bergquist, Timothy; Chen, Yun-Ching; Niknafs, Noushin; Carter, Hannah; Tokheim, Collin; Beleva-Guthrie, Violeta; Douville, Christopher; Bhattacharya, Rohit; Yeo, Hui Ting Grace; Fan, Jean; Sengupta, Sohini; Kim, Dewey; Cline, Melissa; Turner, Tychele; Diekhans, Mark; Zaucha, Jan; Pal, Lipika R; Cao, Chen; Yu, Chen-Hsin; Yin, Yizhou; Carraro, Marco; Giollo, Manuel; Ferrari, Carlo; Leonardi, Emanuela; Tosatto, Silvio C E; Bobe, Jason; Ball, Madeleine; Hoskins, Roger A; Repo, Susanna; Church, George; Brenner, Steven E; Moult, John; Gough, Julian; Stanke, Mario; Karchin, Rachel; Mooney, Sean D
The advent of next-generation sequencing has dramatically decreased the cost for whole-genome sequencing and increased the viability for its application in research and clinical care. The Personal Genome Project (PGP) provides unrestricted access to genomes of individuals and their associated phenotypes. This resource enabled the Critical Assessment of Genome Interpretation (CAGI) to create a community challenge to assess the bioinformatics community's ability to predict traits from whole genomes. In the CAGI PGP challenge, researchers were asked to predict whether an individual had a particular trait or profile based on their whole genome. Several approaches were used to assess submissions, including ROC AUC (area under receiver operating characteristic curve), probability rankings, the number of correct predictions, and statistical significance simulations. Overall, we found that prediction of individual traits is difficult, relying on a strong knowledge of trait frequency within the general population, whereas matching genomes to trait profiles relies heavily upon a small number of common traits including ancestry, blood type, and eye color. When a rare genetic disorder is present, profiles can be matched when one or more pathogenic variants are identified. Prediction accuracy has improved substantially over the last 6 years due to improved methodology and a better understanding of features. © 2017 Wiley Periodicals, Inc.
Full Text Available As more and more prokaryotic sequencing takes place, a method to quickly and accurately analyze this data is needed. Previous tools are mainly designed for metagenomic analysis and have limitations; such as long runtimes and significant false positive error rates. The online tool GenomePeek (edwards.sdsu.edu/GenomePeek was developed to analyze both single genome and metagenome sequencing files, quickly and with low error rates. GenomePeek uses a sequence assembly approach where reads to a set of conserved genes are extracted, assembled and then aligned against the highly specific reference database. GenomePeek was found to be faster than traditional approaches while still keeping error rates low, as well as offering unique data visualization options.
Lin, Yu; Hu, Fei; Tang, Jijun; Moret, Bernard M E
The rapid accumulation of whole-genome data has renewed interest in the study of the evolution of genomic architecture, under such events as rearrangements, duplications, losses. Comparative genomics, evolutionary biology, and cancer research all require tools to elucidate the mechanisms, history, and consequences of those evolutionary events, while phylogenetics could use whole-genome data to enhance its picture of the Tree of Life. Current approaches in the area of phylogenetic analysis are limited to very small collections of closely related genomes using low-resolution data (typically a few hundred syntenic blocks); moreover, these approaches typically do not include duplication and loss events. We describe a maximum likelihood (ML) approach for phylogenetic analysis that takes into account genome rearrangements as well as duplications, insertions, and losses. Our approach can handle high-resolution genomes (with 40,000 or more markers) and can use in the same analysis genomes with very different numbers of markers. Because our approach uses a standard ML reconstruction program (RAxML), it scales up to large trees. We present the results of extensive testing on both simulated and real data showing that our approach returns very accurate results very quickly. In particular, we analyze a dataset of 68 high-resolution eukaryotic genomes, with from 3,000 to 42,000 genes, from the eGOB database; the analysis, including bootstrapping, takes just 3 hours on a desktop system and returns a tree in agreement with all well supported branches, while also suggesting resolutions for some disputed placements.
Xu, Min; Wang, Yemin; Zhao, Zhilong; Gao, Guixi; Huang, Sheng-Xiong; Kang, Qianjin; He, Xinyi; Lin, Shuangjun; Pang, Xiuhua; Deng, Zixin
ABSTRACT Genome sequencing projects in the last decade revealed numerous cryptic biosynthetic pathways for unknown secondary metabolites in microbes, revitalizing drug discovery from microbial metabolites by approaches called genome mining. In this work, we developed a heterologous expression and functional screening approach for genome mining from genomic bacterial artificial chromosome (BAC) libraries in Streptomyces spp. We demonstrate mining from a strain of Streptomyces rochei, which is known to produce streptothricins and borrelidin, by expressing its BAC library in the surrogate host Streptomyces lividans SBT5, and screening for antimicrobial activity. In addition to the successful capture of the streptothricin and borrelidin biosynthetic gene clusters, we discovered two novel linear lipopeptides and their corresponding biosynthetic gene cluster, as well as a novel cryptic gene cluster for an unknown antibiotic from S. rochei. This high-throughput functional genome mining approach can be easily applied to other streptomycetes, and it is very suitable for the large-scale screening of genomic BAC libraries for bioactive natural products and the corresponding biosynthetic pathways. IMPORTANCE Microbial genomes encode numerous cryptic biosynthetic gene clusters for unknown small metabolites with potential biological activities. Several genome mining approaches have been developed to activate and bring these cryptic metabolites to biological tests for future drug discovery. Previous sequence-guided procedures relied on bioinformatic analysis to predict potentially interesting biosynthetic gene clusters. In this study, we describe an efficient approach based on heterologous expression and functional screening of a whole-genome library for the mining of bioactive metabolites from Streptomyces. The usefulness of this function-driven approach was demonstrated by the capture of four large biosynthetic gene clusters for metabolites of various chemical types, including
Full Text Available Identification of genetic polymorphisms and subsequent development of molecular markers is important for marker assisted breeding of superior cultivars of economically important species. Sweet cherry (Prunus avium L. is an economically important non-climacteric tree fruit crop in the Rosaceae family and has undergone a genetic bottleneck due to breeding, resulting in limited genetic diversity in the germplasm that is utilized for breeding new cultivars. Therefore, it is critical to recognize the best platforms for identifying genome-wide polymorphisms that can help identify, and consequently preserve, the diversity in a genetically constrained species. For the identification of polymorphisms in five closely related genotypes of sweet cherry, a gel-based approach (TRAP, reduced representation sequencing (TRAPseq, a 6k cherry SNParray, and whole genome sequencing (WGS approaches were evaluated in the identification of genome-wide polymorphisms in sweet cherry cultivars. All platforms facilitated detection of polymorphisms among the genotypes with variable efficiency. In assessing multiple SNP detection platforms, this study has demonstrated that a combination of appropriate approaches is necessary for efficient polymorphism identification, especially between closely related cultivars of a species. The information generated in this study provides a valuable resource for future genetic and genomic studies in sweet cherry, and the insights gained from the evaluation of multiple approaches can be utilized for other closely related species with limited genetic diversity in the breeding germplasm. Keywords: Polymorphisms, Prunus avium, Next-generation sequencing, Target region amplification polymorphism (TRAP, Genetic diversity, SNParray, Reduced representation sequencing, Whole genome sequencing (WGS
Ray, F Andrew; Zimmerman, Erin; Robinson, Bruce; Cornforth, Michael N; Bedford, Joel S; Goodwin, Edwin H; Bailey, Susan M
Chromosomal rearrangements are a source of structural variation within the genome that figure prominently in human disease, where the importance of translocations and deletions is well recognized. In principle, inversions-reversals in the orientation of DNA sequences within a chromosome-should have similar detrimental potential. However, the study of inversions has been hampered by traditional approaches used for their detection, which are not particularly robust. Even with significant advances in whole genome approaches, changes in the absolute orientation of DNA remain difficult to detect routinely. Consequently, our understanding of inversions is still surprisingly limited, as is our appreciation for their frequency and involvement in human disease. Here, we introduce the directional genomic hybridization methodology of chromatid painting-a whole new way of looking at structural features of the genome-that can be employed with high resolution on a cell-by-cell basis, and demonstrate its basic capabilities for genome-wide discovery and targeted detection of inversions. Bioinformatics enabled development of sequence- and strand-specific directional probe sets, which when coupled with single-stranded hybridization, greatly improved the resolution and ease of inversion detection. We highlight examples of the far-ranging applicability of this cytogenomics-based approach, which include confirmation of the alignment of the human genome database and evidence that individuals themselves share similar sequence directionality, as well as use in comparative and evolutionary studies for any species whose genome has been sequenced. In addition to applications related to basic mechanistic studies, the information obtainable with strand-specific hybridization strategies may ultimately enable novel gene discovery, thereby benefitting the diagnosis and treatment of a variety of human disease states and disorders including cancer, autism, and idiopathic infertility.
Full Text Available Satsuma (Citrus unshiu Marc. is one of the most abundantly produced mandarin varieties of citrus, known for its seedless fruit production and as a breeding parent of citrus. De novo assembly of the heterozygous diploid genome of Satsuma (“Miyagawa Wase” was conducted by a hybrid assembly approach using short-read sequences, three mate-pair libraries, and a long-read sequence of PacBio by the PLATANUS assembler. The assembled sequence, with a total size of 359.7 Mb at the N50 length of 386,404 bp, consisted of 20,876 scaffolds. Pseudomolecules of Satsuma constructed by aligning the scaffolds to three genetic maps showed genome-wide synteny to the genomes of Clementine, pummelo, and sweet orange. Gene prediction by modeling with MAKER-P proposed 29,024 genes and 37,970 mRNA; additionally, gene prediction analysis found candidates for novel genes in several biosynthesis pathways for gibberellin and violaxanthin catabolism. BUSCO scores for the assembled scaffold and predicted transcripts, and another analysis by BAC end sequence mapping indicated the assembled genome consistency was close to those of the haploid Clementine, pummel, and sweet orange genomes. The number of repeat elements and long terminal repeat retrotransposon were comparable to those of the seven citrus genomes; this suggested no significant failure in the assembly at the repeat region. A resequencing application using the assembled sequence confirmed that both kunenbo-A and Satsuma are offsprings of Kishu, and Satsuma is a back-crossed offspring of Kishu. These results illustrated the performance of the hybrid assembly approach and its ability to construct an accurate heterozygous diploid genome.
Jex, Aaron R; Littlewood, D Timothy; Gasser, Robin B
Mitochondrial (mt) genomics has significant implications in a range of fundamental areas of parasitology, including evolution, systematics, and population genetics as well as explorations of mt biochemistry, physiology, and function. Mt genomes also provide a rich source of markers to aid molecular epidemiological and ecological studies of key parasites. However, there is still a paucity of information on mt genomes for many metazoan organisms, particularly parasitic helminths, which has often related to challenges linked to sequencing from tiny amounts of material. The advent of next-generation sequencing (NGS) technologies has paved the way for low cost, high-throughput mt genomic research, but there have been obstacles, particularly in relation to post-sequencing assembly and analyses of large datasets. In this chapter, we describe protocols for the efficient amplification and sequencing of mt genomes from small portions of individual helminths, and highlight the utility of NGS platforms to expedite mt genomics. In addition, we recommend approaches for manual or semi-automated bioinformatic annotation and analyses to overcome the bioinformatic "bottleneck" to research in this area. Taken together, these approaches have demonstrated applicability to a range of parasites and provide prospects for using complete mt genomic sequence datasets for large-scale molecular systematic and epidemiological studies. In addition, these methods have broader utility and might be readily adapted to a range of other medium-sized molecular regions (i.e., 10-100 kb), including large genomic operons, and other organellar (e.g., plastid) and viral genomes.
Full Text Available The genome of influenza A viruses (IAV consists of eight single-stranded negative sense viral RNAs (vRNAs encapsidated into viral ribonucleoproteins (vRNPs. It is now well established that genome packaging (i.e., the incorporation of a set of eight distinct vRNPs into budding viral particles, follows a specific pathway guided by segment-specific cis-acting packaging signals on each vRNA. However, the precise nature and function of the packaging signals, and the mechanisms underlying the assembly of vRNPs into sub-bundles in the cytoplasm and their selective packaging at the viral budding site, remain largely unknown. Here, we review the diverse and complementary methods currently being used to elucidate these aspects of the viral cycle. They range from conventional and competitive reverse genetics, single molecule imaging of vRNPs by fluorescence in situ hybridization (FISH and high-resolution electron microscopy and tomography of budding viral particles, to solely in vitro approaches to investigate vRNA-vRNA interactions at the molecular level.
Chen, Gary K; Zheng, Tian; Witte, John S; Goode, Ellen L; Gao, Lei; Hu, Pingzhao; Suh, Young Ju; Suktitipat, Bhoom; Szymczak, Silke; Woo, Jung Hoon; Zhang, Wei
A number of issues arise when analyzing the large amount of data from high-throughput genotype and expression microarray experiments, including design and interpretation of genome-wide association studies of expression phenotypes. These issues were considered by contributions submitted to Group 1 of the Genetic Analysis Workshop 15 (GAW15), which focused on the association of quantitative expression data. These contributions evaluated diverse hypotheses, including those relevant to cancer and obesity research, and used various analytic techniques, many of which were derived from information theory. Several observations from these reports stand out. First, one needs to consider the genetic model of the trait of interest and carefully select which single nucleotide polymorphisms and individuals are included early in the design stage of a study. Second, by targeting specific pathways when analyzing genome-wide data, one can generate more interpretable results than agnostic approaches. Finally, for datasets with small sample sizes but a large number of features like the Genetic Analysis Workshop 15 dataset, machine learning approaches may be more practical than traditional parametric approaches. (c) 2007 Wiley-Liss, Inc.
Jeukens, J; Freschi, L; Vincent, A T; Emond-Rheault, J G; Kukavica-Ibrulj, I; Charette, S J; Levesque, R C
Over the past decade, there has been a rising interest in Achromobacter sp., an emerging opportunistic pathogen responsible for nosocomial and cystic fibrosis (CF) lung infections. Species of this genus are ubiquitous in the environment, can outcompete resident microbiota, and are resistant to commonly used disinfectants as well as antibiotics. Nevertheless, the Achromobacter genus suffers from difficulties in diagnosis, unresolved taxonomy and limited understanding of how it adapts to the CF lung, not to mention other host environments. The goals of this first genus-wide comparative genomics study were to clarify the taxonomy of this genus and identify genomic features associated with pathogenicity and host adaptation. This was done with a widely applicable approach based on pan-genome analysis. First, using all publicly available genomes, a combination of phylogenetic analysis based on 1,780 conserved genes with average nucleotide identity and accessory genome composition allowed the identification of a largely clinical lineage composed of A. xylosoxidans A insuavis A. dolens and A. ruhlandii. Within this lineage, we identified 35 positively selected genes involved in metabolism, regulation and efflux-mediated antibiotic resistance. Second, resistome analysis showed that this clinical lineage carried additional antibiotic resistance genes compared to other isolates. Finally, we identified putative mobile elements that contribute 53% of the genus's resistome and support horizontal gene transfer between Achromobacter and other ecologically similar genera. This study provides strong phylogenetic and pan-genomic bases to motivate further research on Achromobacter, and contributes to the understanding of opportunistic pathogen evolution. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
Baptista, Rodrigo P; Reis-Cunha, Joao Luis; DeBarry, Jeremy D; Chiari, Egler; Kissinger, Jessica C; Bartholomeu, Daniella C; Macedo, Andrea M
Next-generation sequencing (NGS) methods are low-cost high-throughput technologies that produce thousands to millions of sequence reads. Despite the high number of raw sequence reads, their short length, relative to Sanger, PacBio or Nanopore reads, complicates the assembly of genomic repeats. Many genome tools are available, but the assembly of highly repetitive genome sequences using only NGS short reads remains challenging. Genome assembly of organisms responsible for important neglected diseases such as Trypanosoma cruzi, the aetiological agent of Chagas disease, is known to be challenging because of their repetitive nature. Only three of six recognized discrete typing units (DTUs) of the parasite have their draft genomes published and therefore genome evolution analyses in the taxon are limited. In this study, we developed a computational workflow to assemble highly repetitive genomes via a combination of de novo and reference-based assembly strategies to better overcome the intrinsic limitations of each, based on Illumina reads. The highly repetitive genome of the human-infecting parasite T. cruzi 231 strain was used as a test subject. The combined-assembly approach shown in this study benefits from the reference-based assembly ability to resolve highly repetitive sequences and from the de novo capacity to assemble genome-specific regions, improving the quality of the assembly. The acceptable confidence obtained by analyzing our results showed that our combined approach is an attractive option to assemble highly repetitive genomes with NGS short reads. Phylogenomic analysis including the 231 strain, the first representative of DTU III whose genome was sequenced, was also performed and provides new insights into T. cruzi genome evolution.
Rohde, Palle Duun; Krag, Kristian; Loeschcke, Volker
, to investigate whether this population harbors genetic variation for a set of stress resistance and life history traits. Using a genomic approach, we found substantial genetic variation for metabolic rate, heat stress resistance, expression of a major heat shock protein, and egg-to-adult viability investigated......The ability of natural populations to withstand environmental stresses relies partly on their adaptive ability. In this study, we used a subset of the Drosophila Genetic Reference Panel, a population of inbred, genome-sequenced lines derived from a natural population of Drosophila melanogaster...... at a benign and a higher stressful temperature. This suggests that these traits will be able to evolve. In addition, we outline an approach to conduct pathway associations based on genomic linear models, which has potential to identify adaptive genes and pathways, and therefore can be a valuable tool...
Full Text Available Olga VasievaInstitute of Integrative Biology, University of Liverpool, Liverpool, United Kingdom; Fellowship for the Interpretation of Genomes, Burr Ridge, IL, USAAbstract: Shwachman-Bodian-Diamond syndrome (SBDS is linked to a mutation in a single gene. The SBDS proinvolved in RNA metabolism and ribosome-associated functions, but SBDS mutation is primarily linked to a defect in polymorphonuclear leukocytes unable to orient correctly in a spatial gradient of chemoattractants. Results of data mining and comparative genomic approaches undertaken in this study suggest that SBDS protein is also linked to tRNA metabolism and translation initiation. Analysis of crosstalk between translation machinery and cytoskeletal dynamics provides new insights into the cellular chemotactic defects caused by SBDS protein malfunction. The proposed functional interactions provide a new approach to exploit potential targets in the treatment and monitoring of this disease.Keywords: Shwachman-Bodian-Diamond syndrome, wybutosine, tRNA, chemotaxis, translation, genomics, gene proximity
Zhang, Wei; Zhang, Mingyi; Zhu, Xianwen; Cao, Yaping; Sun, Qing; Ma, Guojia; Chao, Shiaoman; Yan, Changhui; Xu, Steven S; Cai, Xiwen
This work pinpointed the goatgrass chromosomal segment in the wheat B genome using modern cytogenetic and genomic technologies, and provided novel insights into the origin of the wheat B genome. Wheat is a typical allopolyploid with three homoeologous subgenomes (A, B, and D). The donors of the subgenomes A and D had been identified, but not for the subgenome B. The goatgrass Aegilops speltoides (genome SS) has been controversially considered a possible candidate for the donor of the wheat B genome. However, the relationship of the Ae. speltoides S genome with the wheat B genome remains largely obscure. The present study assessed the homology of the B and S genomes using an integrative cytogenetic and genomic approach, and revealed the contribution of Ae. speltoides to the origin of the wheat B genome. We discovered noticeable homology between wheat chromosome 1B and Ae. speltoides chromosome 1S, but not between other chromosomes in the B and S genomes. An Ae. speltoides-originated segment spanning a genomic region of approximately 10.46 Mb was detected on the long arm of wheat chromosome 1B (1BL). The Ae. speltoides-originated segment on 1BL was found to co-evolve with the rest of the B genome. Evidently, Ae. speltoides had been involved in the origin of the wheat B genome, but should not be considered an exclusive donor of this genome. The wheat B genome might have a polyphyletic origin with multiple ancestors involved, including Ae. speltoides. These novel findings will facilitate genome studies in wheat and other polyploids.
Zhan, Bujie; Fadista, João; Thomsen, Bo
Background Integration of genomic variation with phenotypic information is an effective approach for uncovering genotype-phenotype associations. This requires an accurate identification of the different types of variation in individual genomes. Results We report the integration of the whole genome...... of split-read and read-pair approaches proved to be complementary in finding different signatures. CNVs were identified on the basis of the depth of sequenced reads, and by using SNP and CGH arrays. Conclusions Our results provide high resolution mapping of diverse classes of genomic variation...
Wang, Dapeng; Xu, Jiayue; Yu, Jun
The K-mer approach, treating genomic sequences as simple characters and counting the relative abundance of each string upon a fixed K, has been extensively applied to phylogeny inference for genome assembly, annotation, and comparison. To meet increasing demands for comparing large genome sequences and to promote the use of the K-mer approach, we develop a versatile database, KGCAK ( http://kgcak.big.ac.cn/KGCAK/ ), containing ~8,000 genomes that include genome sequences of diverse life forms (viruses, prokaryotes, protists, animals, and plants) and cellular organelles of eukaryotic lineages. It builds phylogeny based on genomic elements in an alignment-free fashion and provides in-depth data processing enabling users to compare the complexity of genome sequences based on K-mer distribution. We hope that KGCAK becomes a powerful tool for exploring relationship within and among groups of species in a tree of life based on genomic data.
Hogan, Andrew J
This paper explores evolving conceptions and depictions of the human genome among human and medical geneticists during the postwar period. Historians of science and medicine have shown significant interest in the use of informational approaches in postwar genetics, which treat the genome as an expansive digital data set composed of three billion DNA nucleotides. Since the 1950s, however, geneticists have largely interacted with the human genome at the microscopically visible level of chromosomes. Mindful of this, I examine the observational and representational approaches of postwar human and medical genetics. During the 1970s and 1980s, the genome increasingly came to be understood as, at once, a discrete part of the human anatomy and a standardised scientific object. This paper explores the role of influential medical geneticists in recasting the human genome as being a visible, tangible, and legible entity, which was highly relevant to traditional medical thinking and practice. I demonstrate how the human genome was established as an object amenable to laboratory and clinical research, and argue that the observational and representational approaches of postwar medical genetics reflect, more broadly, the interdisciplinary efforts underlying the development of contemporary biomedicine.
Kaneko-Ishino, Tomoko; Ishino, Fumitoshi
Mammals, including human beings, have evolved a unique viviparous reproductive system and a highly developed central nervous system. How did these unique characteristics emerge in mammalian evolution, and what kinds of changes did occur in the mammalian genomes as evolution proceeded? A key conceptual term in approaching these issues is "mammalian-specific genomic functions", a concept covering both mammalian-specific epigenetics and genetics. Genomic imprinting and LTR retrotransposon-derived genes are reviewed as the representative, mammalian-specific genomic functions that are essential not only for the current mammalian developmental system, but also mammalian evolution itself. First, the essential roles of genomic imprinting in mammalian development, especially related to viviparous reproduction via placental function, as well as the emergence of genomic imprinting in mammalian evolution, are discussed. Second, we introduce the novel concept of "mammalian-specific traits generated by mammalian-specific genes from LTR retrotransposons", based on the finding that LTR retrotransposons served as a critical driving force in the mammalian evolution via generating mammalian-specific genes.
Blondel, Mathieu; Onogi, Akio; Iwata, Hiroyoshi; Ueda, Naonori
Genomic selection (GS) is a recent selective breeding method which uses predictive models based on whole-genome molecular markers. Until now, existing studies formulated GS as the problem of modeling an individual's breeding value for a particular trait of interest, i.e., as a regression problem. To assess predictive accuracy of the model, the Pearson correlation between observed and predicted trait values was used. In this paper, we propose to formulate GS as the problem of ranking individuals according to their breeding value. Our proposed framework allows us to employ machine learning methods for ranking which had previously not been considered in the GS literature. To assess ranking accuracy of a model, we introduce a new measure originating from the information retrieval literature called normalized discounted cumulative gain (NDCG). NDCG rewards more strongly models which assign a high rank to individuals with high breeding value. Therefore, NDCG reflects a prerequisite objective in selective breeding: accurate selection of individuals with high breeding value. We conducted a comparison of 10 existing regression methods and 3 new ranking methods on 6 datasets, consisting of 4 plant species and 25 traits. Our experimental results suggest that tree-based ensemble methods including McRank, Random Forests and Gradient Boosting Regression Trees achieve excellent ranking accuracy. RKHS regression and RankSVM also achieve good accuracy when used with an RBF kernel. Traditional regression methods such as Bayesian lasso, wBSR and BayesC were found less suitable for ranking. Pearson correlation was found to correlate poorly with NDCG. Our study suggests two important messages. First, ranking methods are a promising research direction in GS. Second, NDCG can be a useful evaluation measure for GS.
Brankovics, Balázs; Zhang, Hao; van Diepeningen, Anne D; van der Lee, Theo A J; Waalwijk, Cees; de Hoog, G Sybren
GRAbB (Genomic Region Assembly by Baiting) is a new program that is dedicated to assemble specific genomic regions from NGS data. This approach is especially useful when dealing with multi copy regions, such as mitochondrial genome and the rDNA repeat region, parts of the genome that are often
She, Qunxin; Confalonieri, F.; Zivanovic, Y.
The original strategy used in the Sulfolobus solfatnricus genome project was to sequence non overlapping, or minimally overlapping, cosmid or lambda inserts without constructing a physical map. However, after only about two thirds of the genome sequence was completed, this approach became counter......-productive because there was a high sequence bias in the cosmid and lambda libraries. Therefore, a new approach was devised for linking the sequenced regions which may be generally applicable. BAC libraries were constructed and terminal sequences of the clones were determined and used for both end mapping and PCR...
Full Text Available Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey, PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.
Cao, Hongzhi; Wu, Honglong; Luo, Ruibang; Huang, Shujia; Sun, Yuhui; Tong, Xin; Xie, Yinlong; Liu, Binghang; Yang, Hailong; Zheng, Hancheng; Li, Jian; Li, Bo; Wang, Yu; Yang, Fang; Sun, Peng; Liu, Siyang; Gao, Peng; Huang, Haodong; Sun, Jing; Chen, Dan; He, Guangzhu; Huang, Weihua; Huang, Zheng; Li, Yue; Tellier, Laurent C A M; Liu, Xiao; Feng, Qiang; Xu, Xun; Zhang, Xiuqing; Bolund, Lars; Krogh, Anders; Kristiansen, Karsten; Drmanac, Radoje; Drmanac, Snezana; Nielsen, Rasmus; Li, Songgang; Wang, Jian; Yang, Huanming; Li, Yingrui; Wong, Gane Ka-Shu; Wang, Jun
The human genome is diploid, and knowledge of the variants on each chromosome is important for the interpretation of genomic information. Here we report the assembly of a haplotype-resolved diploid genome without using a reference genome. Our pipeline relies on fosmid pooling together with whole-genome shotgun strategies, based solely on next-generation sequencing and hierarchical assembly methods. We applied our sequencing method to the genome of an Asian individual and generated a 5.15-Gb assembled genome with a haplotype N50 of 484 kb. Our analysis identified previously undetected indels and 7.49 Mb of novel coding sequences that could not be aligned to the human reference genome, which include at least six predicted genes. This haplotype-resolved genome represents the most complete de novo human genome assembly to date. Application of our approach to identify individual haplotype differences should aid in translating genotypes to phenotypes for the development of personalized medicine.
Pérez-de-Castro, A M; Vilanova, S; Cañizares, J; Pascual, L; Blanca, J M; Díez, M J; Prohens, J; Picó, B
Plant breeding has been very successful in developing improved varieties using conventional tools and methodologies. Nowadays, the availability of genomic tools and resources is leading to a new revolution of plant breeding, as they facilitate the study of the genotype and its relationship with the phenotype, in particular for complex traits. Next Generation Sequencing (NGS) technologies are allowing the mass sequencing of genomes and transcriptomes, which is producing a vast array of genomic information. The analysis of NGS data by means of bioinformatics developments allows discovering new genes and regulatory sequences and their positions, and makes available large collections of molecular markers. Genome-wide expression studies provide breeders with an understanding of the molecular basis of complex traits. Genomic approaches include TILLING and EcoTILLING, which make possible to screen mutant and germplasm collections for allelic variants in target genes. Re-sequencing of genomes is very useful for the genome-wide discovery of markers amenable for high-throughput genotyping platforms, like SSRs and SNPs, or the construction of high density genetic maps. All these tools and resources facilitate studying the genetic diversity, which is important for germplasm management, enhancement and use. Also, they allow the identification of markers linked to genes and QTLs, using a diversity of techniques like bulked segregant analysis (BSA), fine genetic mapping, or association mapping. These new markers are used for marker assisted selection, including marker assisted backcross selection, 'breeding by design', or new strategies, like genomic selection. In conclusion, advances in genomics are providing breeders with new tools and methodologies that allow a great leap forward in plant breeding, including the 'superdomestication' of crops and the genetic dissection and breeding for complex traits.
Genome sequencing efforts in the past decade were aimed at generating draft sequences of many prokaryotic and eukaryotic model organisms. Successful completion of unicellular eukaryotes, worm, fly and human genome have opened up the new field of molecular biology and function...
Taylor, Alison M.; Shih, Juliann; Ha, Gavin; Gao, Galen F.; Zhang, Xiaoyang; Berger, Ashton C.; Schumacher, Steven E.; Wang, Chen; Hu, Hai; Liu, Jianfang; Lazar, Alexander J.; Caesar-Johnson, Samantha J.; Demchok, John A.; Felau, Ina; Kasapi, Melpomeni; Ferguson, Martin L.; Hutter, Carolyn M.; Sofia, Heidi J.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean C.; Zhang, Jiashan (Julia); Chudamani, Sudha; Liu, Jia; Lolla, Laxmi; Naresh, Rashi; Pihl, Todd; Sun, Qiang; Wan, Yunhu; Wu, Ye; Cho, Juok; DeFreitas, Timothy; Frazer, Scott; Gehlenborg, Nils; Getz, Gad; Heiman, David I.; Kim, Jaegil; Lawrence, Michael S.; Lin, Pei; Meier, Sam; Noble, Michael S.; Saksena, Gordon; Voet, Doug; Zhang, Hailei; Bernard, Brady; Chambwe, Nyasha; Dhankani, Varsha; Knijnenburg, Theo; Kramer, Roger; Leinonen, Kalle; Liu, Yuexin; Miller, Michael; Reynolds, Sheila; Shmulevich, Ilya; Thorsson, Vesteinn; Zhang, Wei; Akbani, Rehan; Broom, Bradley M.; Hegde, Apurva M.; Ju, Zhenlin; Kanchi, Rupa S.; Korkut, Anil; Li, Jun; Liang, Han; Ling, Shiyun; Liu, Wenbin; Lu, Yiling; Mills, Gordon B.; Ng, Kwok Shing; Rao, Arvind; Ryan, Michael; Wang, Jing; Weinstein, John N.; Zhang, Jiexin; Abeshouse, Adam; Armenia, Joshua; Chakravarty, Debyani; Chatila, Walid K.; de Bruijn, Ino; Gao, Jianjiong; Gross, Benjamin E.; Heins, Zachary J.; Kundra, Ritika; La, Konnor; Ladanyi, Marc; Luna, Augustin; Nissan, Moriah G.; Ochoa, Angelica; Phillips, Sarah M.; Reznik, Ed; Sanchez-Vega, Francisco; Sander, Chris; Schultz, Nikolaus; Sheridan, Robert; Sumer, S. Onur; Sun, Yichao; Taylor, Barry S.; Wang, Jioajiao; Zhang, Hongxin; Anur, Pavana; Peto, Myron; Spellman, Paul; Benz, Christopher; Stuart, Joshua M.; Wong, Christopher K.; Yau, Christina; Hayes, D. Neil; Parker, Joel S.; Wilkerson, Matthew D.; Ally, Adrian; Balasundaram, Miruna; Bowlby, Reanne; Brooks, Denise; Carlsen, Rebecca; Chuah, Eric; Dhalla, Noreen; Holt, Robert; Jones, Steven J.M.; Kasaian, Katayoon; Lee, Darlene; Ma, Yussanne; Marra, Marco A.; Mayo, Michael; Moore, Richard A.; Mungall, Andrew J.; Mungall, Karen; Robertson, A. Gordon; Sadeghi, Sara; Schein, Jacqueline E.; Sipahimalani, Payal; Tam, Angela; Thiessen, Nina; Tse, Kane; Wong, Tina; Berger, Ashton C.; Beroukhim, Rameen; Cherniack, Andrew D.; Cibulskis, Carrie; Gabriel, Stacey B.; Gao, Galen F.; Ha, Gavin; Meyerson, Matthew; Schumacher, Steven E.; Shih, Juliann; Kucherlapati, Melanie H.; Kucherlapati, Raju S.; Baylin, Stephen; Cope, Leslie; Danilova, Ludmila; Bootwalla, Moiz S.; Lai, Phillip H.; Maglinte, Dennis T.; Van Den Berg, David J.; Weisenberger, Daniel J.; Auman, J. Todd; Balu, Saianand; Bodenheimer, Tom; Fan, Cheng; Hoadley, Katherine A.; Hoyle, Alan P.; Jefferys, Stuart R.; Jones, Corbin D.; Meng, Shaowu; Mieczkowski, Piotr A.; Mose, Lisle E.; Perou, Amy H.; Perou, Charles M.; Roach, Jeffrey; Shi, Yan; Simons, Janae V.; Skelly, Tara; Soloway, Matthew G.; Tan, Donghui; Veluvolu, Umadevi; Fan, Huihui; Hinoue, Toshinori; Laird, Peter W.; Shen, Hui; Zhou, Wanding; Bellair, Michelle; Chang, Kyle; Covington, Kyle; Creighton, Chad J.; Dinh, Huyen; Doddapaneni, Harsha Vardhan; Donehower, Lawrence A.; Drummond, Jennifer; Gibbs, Richard A.; Glenn, Robert; Hale, Walker; Han, Yi; Hu, Jianhong; Korchina, Viktoriya; Lee, Sandra; Lewis, Lora; Li, Wei; Liu, Xiuping; Morgan, Margaret; Morton, Donna; Muzny, Donna; Santibanez, Jireh; Sheth, Margi; Shinbrot, Eve; Wang, Linghua; Wang, Min; Wheeler, David A.; Xi, Liu; Zhao, Fengmei; Hess, Julian; Appelbaum, Elizabeth L.; Bailey, Matthew; Cordes, Matthew G.; Ding, Li; Fronick, Catrina C.; Fulton, Lucinda A.; Fulton, Robert S.; Kandoth, Cyriac; Mardis, Elaine R.; McLellan, Michael D.; Miller, Christopher A.; Schmidt, Heather K.; Wilson, Richard K.; Crain, Daniel; Curley, Erin; Gardner, Johanna; Lau, Kevin; Mallery, David; Morris, Scott; Paulauskis, Joseph; Penny, Robert; Shelton, Candace; Shelton, Troy; Sherman, Mark; Thompson, Eric; Yena, Peggy; Bowen, Jay; Gastier-Foster, Julie M.; Gerken, Mark; Leraas, Kristen M.; Lichtenberg, Tara M.; Ramirez, Nilsa C.; Wise, Lisa; Zmuda, Erik; Corcoran, Niall; Costello, Tony; Hovens, Christopher; Carvalho, Andre L.; de Carvalho, Ana C.; Fregnani, José H.; Longatto-Filho, Adhemar; Reis, Rui M.; Scapulatempo-Neto, Cristovam; Silveira, Henrique C.S.; Vidal, Daniel O.; Burnette, Andrew; Eschbacher, Jennifer; Hermes, Beth; Noss, Ardene; Singh, Rosy; Anderson, Matthew L.; Castro, Patricia D.; Ittmann, Michael; Huntsman, David; Kohl, Bernard; Le, Xuan; Thorp, Richard; Andry, Chris; Duffy, Elizabeth R.; Lyadov, Vladimir; Paklina, Oxana; Setdikova, Galiya; Shabunin, Alexey; Tavobilov, Mikhail; McPherson, Christopher; Warnick, Ronald; Berkowitz, Ross; Cramer, Daniel; Feltmate, Colleen; Horowitz, Neil; Kibel, Adam; Muto, Michael; Raut, Chandrajit P.; Malykh, Andrei; Barnholtz-Sloan, Jill S.; Barrett, Wendi; Devine, Karen; Fulop, Jordonna; Ostrom, Quinn T.; Shimmel, Kristen; Wolinsky, Yingli; Sloan, Andrew E.; De Rose, Agostino; Giuliante, Felice; Goodman, Marc; Karlan, Beth Y.; Hagedorn, Curt H.; Eckman, John; Harr, Jodi; Myers, Jerome; Tucker, Kelinda; Zach, Leigh Anne; Deyarmin, Brenda; Hu, Hai; Kvecher, Leonid; Larson, Caroline; Mural, Richard J.; Somiari, Stella; Vicha, Ales; Zelinka, Tomas; Bennett, Joseph; Iacocca, Mary; Rabeno, Brenda; Swanson, Patricia; Latour, Mathieu; Lacombe, Louis; Têtu, Bernard; Bergeron, Alain; McGraw, Mary; Staugaitis, Susan M.; Chabot, John; Hibshoosh, Hanina; Sepulveda, Antonia; Su, Tao; Wang, Timothy; Potapova, Olga; Voronina, Olga; Desjardins, Laurence; Mariani, Odette; Roman-Roman, Sergio; Sastre, Xavier; Stern, Marc Henri; Cheng, Feixiong; Signoretti, Sabina; Berchuck, Andrew; Bigner, Darell; Lipp, Eric; Marks, Jeffrey; McCall, Shannon; McLendon, Roger; Secord, Angeles; Sharp, Alexis; Behera, Madhusmita; Brat, Daniel J.; Chen, Amy; Delman, Keith; Force, Seth; Khuri, Fadlo; Magliocca, Kelly; Maithel, Shishir; Olson, Jeffrey J.; Owonikoko, Taofeek; Pickens, Alan; Ramalingam, Suresh; Shin, Dong M.; Sica, Gabriel; Van Meir, Erwin G.; Zhang, Hongzheng; Eijckenboom, Wil; Gillis, Ad; Korpershoek, Esther; Looijenga, Leendert; Oosterhuis, Wolter; Stoop, Hans; van Kessel, Kim E.; Zwarthoff, Ellen C.; Calatozzolo, Chiara; Cuppini, Lucia; Cuzzubbo, Stefania; DiMeco, Francesco; Finocchiaro, Gaetano; Mattei, Luca; Perin, Alessandro; Pollo, Bianca; Chen, Chu; Houck, John; Lohavanichbutr, Pawadee; Hartmann, Arndt; Stoehr, Christine; Stoehr, Robert; Taubert, Helge; Wach, Sven; Wullich, Bernd; Kycler, Witold; Murawa, Dawid; Wiznerowicz, Maciej; Chung, Ki; Edenfield, W. Jeffrey; Martin, Julie; Baudin, Eric; Bubley, Glenn; Bueno, Raphael; De Rienzo, Assunta; Richards, William G.; Kalkanis, Steven; Mikkelsen, Tom; Noushmehr, Houtan; Scarpace, Lisa; Girard, Nicolas; Aymerich, Marta; Campo, Elias; Giné, Eva; Guillermo, Armando López; Van Bang, Nguyen; Hanh, Phan Thi; Phu, Bui Duc; Tang, Yufang; Colman, Howard; Evason, Kimberley; Dottino, Peter R.; Martignetti, John A.; Gabra, Hani; Juhl, Hartmut; Akeredolu, Teniola; Stepa, Serghei; Hoon, Dave; Ahn, Keunsoo; Kang, Koo Jeong; Beuschlein, Felix; Breggia, Anne; Birrer, Michael; Bell, Debra; Borad, Mitesh; Bryce, Alan H.; Castle, Erik; Chandan, Vishal; Cheville, John; Copland, John A.; Farnell, Michael; Flotte, Thomas; Giama, Nasra; Ho, Thai; Kendrick, Michael; Kocher, Jean Pierre; Kopp, Karla; Moser, Catherine; Nagorney, David; O'Brien, Daniel; O'Neill, Brian Patrick; Patel, Tushar; Petersen, Gloria; Que, Florencia; Rivera, Michael; Roberts, Lewis; Smallridge, Robert; Smyrk, Thomas; Stanton, Melissa; Thompson, R. Houston; Torbenson, Michael; Yang, Ju Dong; Zhang, Lizhi; Brimo, Fadi; Ajani, Jaffer A.; Angulo Gonzalez, Ana Maria; Behrens, Carmen; Bondaruk, Jolanta; Broaddus, Russell; Czerniak, Bogdan; Esmaeli, Bita; Fujimoto, Junya; Gershenwald, Jeffrey; Guo, Charles; Lazar, Alexander J.; Logothetis, Christopher; Meric-Bernstam, Funda; Moran, Cesar; Ramondetta, Lois; Rice, David; Sood, Anil; Tamboli, Pheroze; Thompson, Timothy; Troncoso, Patricia; Tsao, Anne; Wistuba, Ignacio; Carter, Candace; Haydu, Lauren; Hersey, Peter; Jakrot, Valerie; Kakavand, Hojabr; Kefford, Richard; Lee, Kenneth; Long, Georgina; Mann, Graham; Quinn, Michael; Saw, Robyn; Scolyer, Richard; Shannon, Kerwin; Spillane, Andrew; Stretch, Jonathan; Synott, Maria; Thompson, John; Wilmott, James; Al-Ahmadie, Hikmat; Chan, Timothy A.; Ghossein, Ronald; Gopalan, Anuradha; Levine, Douglas A.; Reuter, Victor; Singer, Samuel; Singh, Bhuvanesh; Tien, Nguyen Viet; Broudy, Thomas; Mirsaidi, Cyrus; Nair, Praveen; Drwiega, Paul; Miller, Judy; Smith, Jennifer; Zaren, Howard; Park, Joong Won; Hung, Nguyen Phi; Kebebew, Electron; Linehan, W. Marston; Metwalli, Adam R.; Pacak, Karel; Pinto, Peter A.; Schiffman, Mark; Schmidt, Laura S.; Vocke, Cathy D.; Wentzensen, Nicolas; Worrell, Robert; Yang, Hannah; Moncrieff, Marc; Goparaju, Chandra; Melamed, Jonathan; Pass, Harvey; Botnariuc, Natalia; Caraman, Irina; Cernat, Mircea; Chemencedji, Inga; Clipca, Adrian; Doruc, Serghei; Gorincioi, Ghenadie; Mura, Sergiu; Pirtac, Maria; Stancul, Irina; Tcaciuc, Diana; Albert, Monique; Alexopoulou, Iakovina; Arnaout, Angel; Bartlett, John; Engel, Jay; Gilbert, Sebastien; Parfitt, Jeremy; Sekhon, Harman; Thomas, George; Rassl, Doris M.; Rintoul, Robert C.; Bifulco, Carlo; Tamakawa, Raina; Urba, Walter; Hayward, Nicholas; Timmers, Henri; Antenucci, Anna; Facciolo, Francesco; Grazi, Gianluca; Marino, Mirella; Merola, Roberta; de Krijger, Ronald; Gimenez-Roqueplo, Anne Paule; Piché, Alain; Chevalier, Simone; McKercher, Ginette; Birsoy, Kivanc; Barnett, Gene; Brewer, Cathy; Farver, Carol; Naska, Theresa; Pennell, Nathan A.; Raymond, Daniel; Schilero, Cathy; Smolenski, Kathy; Williams, Felicia; Morrison, Carl; Borgia, Jeffrey A.; Liptay, Michael J.; Pool, Mark; Seder, Christopher W.; Junker, Kerstin; Omberg, Larsson; Dinkin, Mikhail; Manikhas, George; Alvaro, Domenico; Bragazzi, Maria Consiglia; Cardinale, Vincenzo; Carpino, Guido; Gaudio, Eugenio; Chesla, David; Cottingham, Sandra; Dubina, Michael; Moiseenko, Fedor; Dhanasekaran, Renumathy; Becker, Karl Friedrich; Janssen, Klaus Peter; Slotta-Huspenina, Julia; Abdel-Rahman, Mohamed H.; Aziz, Dina; Bell, Sue; Cebulla, Colleen M.; Davis, Amy; Duell, Rebecca; Elder, J. Bradley; Hilty, Joe; Kumar, Bahavna; Lang, James; Lehman, Norman L.; Mandt, Randy; Nguyen, Phuong; Pilarski, Robert; Rai, Karan; Schoenfield, Lynn; Senecal, Kelly; Wakely, Paul; Hansen, Paul; Lechan, Ronald; Powers, James; Tischler, Arthur; Grizzle, William E.; Sexton, Katherine C.; Kastl, Alison; Henderson, Joel; Porten, Sima; Waldmann, Jens; Fassnacht, Martin; Asa, Sylvia L.; Schadendorf, Dirk; Couce, Marta; Graefen, Markus; Huland, Hartwig; Sauter, Guido; Schlomm, Thorsten; Simon, Ronald; Tennstedt, Pierre; Olabode, Oluwole; Nelson, Mark; Bathe, Oliver; Carroll, Peter R.; Chan, June M.; Disaia, Philip; Glenn, Pat; Kelley, Robin K.; Landen, Charles N.; Phillips, Joanna; Prados, Michael; Simko, Jeffry; Smith-McCune, Karen; VandenBerg, Scott; Roggin, Kevin; Fehrenbach, Ashley; Kendler, Ady; Sifri, Suzanne; Steele, Ruth; Jimeno, Antonio; Carey, Francis; Forgie, Ian; Mannelli, Massimo; Carney, Michael; Hernandez, Brenda; Campos, Benito; Herold-Mende, Christel; Jungk, Christin; Unterberg, Andreas; von Deimling, Andreas; Bossler, Aaron; Galbraith, Joseph; Jacobus, Laura; Knudson, Michael; Knutson, Tina; Ma, Deqin; Milhem, Mohammed; Sigmund, Rita; Godwin, Andrew K.; Madan, Rashna; Rosenthal, Howard G.; Adebamowo, Clement; Adebamowo, Sally N.; Boussioutas, Alex; Beer, David; Giordano, Thomas; Mes-Masson, Anne Marie; Saad, Fred; Bocklage, Therese; Landrum, Lisa; Mannel, Robert; Moore, Kathleen; Moxley, Katherine; Postier, Russel; Walker, Joan; Zuna, Rosemary; Feldman, Michael; Valdivieso, Federico; Dhir, Rajiv; Luketich, James; Mora Pinero, Edna M.; Quintero-Aguilo, Mario; Carlotti, Carlos Gilberto; Dos Santos, Jose Sebastião; Kemp, Rafael; Sankarankuty, Ajith; Tirapelli, Daniela; Catto, James; Agnew, Kathy; Swisher, Elizabeth; Creaney, Jenette; Robinson, Bruce; Shelley, Carl Simon; Godwin, Eryn M.; Kendall, Sara; Shipman, Cassaundra; Bradford, Carol; Carey, Thomas; Haddad, Andrea; Moyer, Jeffey; Peterson, Lisa; Prince, Mark; Rozek, Laura; Wolf, Gregory; Bowman, Rayleen; Fong, Kwun M.; Yang, Ian; Korst, Robert; Rathmell, W. Kimryn; Fantacone-Campbell, J. Leigh; Hooke, Jeffrey A.; Kovatich, Albert J.; Shriver, Craig D.; DiPersio, John; Drake, Bettina; Govindan, Ramaswamy; Heath, Sharon; Ley, Timothy; Van Tine, Brian; Westervelt, Peter; Rubin, Mark A.; Lee, Jung Il; Aredes, Natália D.; Mariamidze, Armaz; Cherniack, Andrew D.; Beroukhim, Rameen; Meyerson, Matthew
Aneuploidy, whole chromosome or chromosome arm imbalance, is a near-universal characteristic of human cancers. In 10,522 cancer genomes from The Cancer Genome Atlas, aneuploidy was correlated with TP53 mutation, somatic mutation rate, and expression of proliferation genes. Aneuploidy was
Mills, Ryan E.; Walter, Klaudia; Stewart, Chip
Genomic structural variants (SVs) are abundant in humans, differing from other forms of variation in extent, origin and functional impact. Despite progress in SV characterization, the nucleotide resolution architecture of most SVs remains unknown. We constructed a map of unbalanced SVs (that is......, copy number variants) based on whole genome DNA sequencing data from 185 human genomes, integrating evidence from complementary SV discovery approaches with extensive experimental validations. Our map encompassed 22,025 deletions and 6,000 additional SVs, including insertions and tandem duplications...
Aurora A Cain
Full Text Available Many important questions in biology are, fundamentally, comparative, and this extends to our analysis of a growing number of sequenced genomes. Existing genomic analysis tools are often organized around literal views of genomes as linear strings. Even when information is highly condensed, these views grow cumbersome as larger numbers of genomes are added. Data aggregation and summarization methods from the field of visual analytics can provide abstracted comparative views, suitable for sifting large multi-genome datasets to identify critical similarities and differences. We introduce a software system for visual analysis of comparative genomics data. The system automates the process of data integration, and provides the analysis platform to identify and explore features of interest within these large datasets. GenoSets borrows techniques from business intelligence and visual analytics to provide a rich interface of interactive visualizations supported by a multi-dimensional data warehouse. In GenoSets, visual analytic approaches are used to enable querying based on orthology, functional assignment, and taxonomic or user-defined groupings of genomes. GenoSets links this information together with coordinated, interactive visualizations for both detailed and high-level categorical analysis of summarized data. GenoSets has been designed to simplify the exploration of multiple genome datasets and to facilitate reasoning about genomic comparisons. Case examples are included showing the use of this system in the analysis of 12 Brucella genomes. GenoSets software and the case study dataset are freely available at http://genosets.uncc.edu. We demonstrate that the integration of genomic data using a coordinated multiple view approach can simplify the exploration of large comparative genomic data sets, and facilitate reasoning about comparisons and features of interest.
Vincze, Éva; Bowra, Steve
) is the ‘umbrella' term used to describe a suite of tools now being applied to plant breeding. In the context of genomic-assisted breeding, we will briefly discuss in the second section of this chapter the molecular genetic-based tools underpinning GAB (understanding gene expression, candidate gene selection......In the struggle to achieve global food security, crop breeding retains an important role in crop production. A current trend is the diversification of the aims of crop production, to include an increased awareness of aspects and consequences of food quality. The added emphasis on food and feed...... quality made crop breeding more challenging and required a combination of new tools. We illustrate these concepts by taking examples from barley, one of the most ancient of domesticated grains with a diverse profile of utilisation (feed, brewing, new nutritional uses). Genomic-assisted breeding (GAB...
David W. Severson
Full Text Available Dengue (DENV, yellow fever, chikungunya, and Zika virus transmission to humans by a mosquito host is confounded by both intrinsic and extrinsic variables. Besides virulence factors of the individual arboviruses, likelihood of virus transmission is subject to variability in the genome of the primary mosquito vector, Aedes aegypti. The “vectorial capacity” of A. aegypti varies depending upon its density, biting rate, and survival rate, as well as its intrinsic ability to acquire, host and transmit a given arbovirus. This intrinsic ability is known as “vector competence”. Based on whole transcriptome analysis, several genes and pathways have been predicated to have an association with a susceptible or refractory response in A. aegypti to DENV infection. However, the functional genomics of vector competence of A. aegypti is not well understood, primarily due to lack of integrative approaches in genomic or transcriptomic studies. In this review, we focus on the present status of genomics studies of DENV vector competence in A. aegypti as limited information is available relative to the other arboviruses. We propose future areas of research needed to facilitate the integration of vector and virus genomics and environmental factors to work towards better understanding of vector competence and vectorial capacity in natural conditions.
Standen, Ismo; Christensen, Ole Fredslund
Genomic data are used in animal breeding to assist genetic evaluation. Several models to estimate genomic breeding values have been studied. In general, two approaches have been used. One approach estimates the marker effects first and then, genomic breeding values are obtained by summing marker...... effects. In the second approach, genomic breeding values are estimated directly using an equivalent model with a genomic relationship matrix. Allele coding is the method chosen to assign values to the regression coefficients in the statistical model. A common allele coding is zero for the homozygous...... genotype of the first allele, one for the heterozygote, and two for the homozygous genotype for the other allele. Another common allele coding changes these regression coefficients by subtracting a value from each marker such that the mean of regression coefficients is zero within each marker. We call...
Pareja-Tobes, Pablo; Manrique, Marina; Pareja-Tobes, Eduardo; Pareja, Eduardo; Tobes, Raquel
BG7 is a new system for de novo bacterial, archaeal and viral genome annotation based on a new approach specifically designed for annotating genomes sequenced with next generation sequencing technologies. The system is versatile and able to annotate genes even in the step of preliminary assembly of the genome. It is especially efficient detecting unexpected genes horizontally acquired from bacterial or archaeal distant genomes, phages, plasmids, and mobile elements. From the initial phases of the gene annotation process, BG7 exploits the massive availability of annotated protein sequences in databases. BG7 predicts ORFs and infers their function based on protein similarity with a wide set of reference proteins, integrating ORF prediction and functional annotation phases in just one step. BG7 is especially tolerant to sequencing errors in start and stop codons, to frameshifts, and to assembly or scaffolding errors. The system is also tolerant to the high level of gene fragmentation which is frequently found in not fully assembled genomes. BG7 current version – which is developed in Java, takes advantage of Amazon Web Services (AWS) cloud computing features, but it can also be run locally in any operating system. BG7 is a fast, automated and scalable system that can cope with the challenge of analyzing the huge amount of genomes that are being sequenced with NGS technologies. Its capabilities and efficiency were demonstrated in the 2011 EHEC Germany outbreak in which BG7 was used to get the first annotations right the next day after the first entero-hemorrhagic E. coli genome sequences were made publicly available. The suitability of BG7 for genome annotation has been proved for Illumina, 454, Ion Torrent, and PacBio sequencing technologies. Besides, thanks to its plasticity, our system could be very easily adapted to work with new technologies in the future. PMID:23185310
Full Text Available BG7 is a new system for de novo bacterial, archaeal and viral genome annotation based on a new approach specifically designed for annotating genomes sequenced with next generation sequencing technologies. The system is versatile and able to annotate genes even in the step of preliminary assembly of the genome. It is especially efficient detecting unexpected genes horizontally acquired from bacterial or archaeal distant genomes, phages, plasmids, and mobile elements. From the initial phases of the gene annotation process, BG7 exploits the massive availability of annotated protein sequences in databases. BG7 predicts ORFs and infers their function based on protein similarity with a wide set of reference proteins, integrating ORF prediction and functional annotation phases in just one step. BG7 is especially tolerant to sequencing errors in start and stop codons, to frameshifts, and to assembly or scaffolding errors. The system is also tolerant to the high level of gene fragmentation which is frequently found in not fully assembled genomes. BG7 current version - which is developed in Java, takes advantage of Amazon Web Services (AWS cloud computing features, but it can also be run locally in any operating system. BG7 is a fast, automated and scalable system that can cope with the challenge of analyzing the huge amount of genomes that are being sequenced with NGS technologies. Its capabilities and efficiency were demonstrated in the 2011 EHEC Germany outbreak in which BG7 was used to get the first annotations right the next day after the first entero-hemorrhagic E. coli genome sequences were made publicly available. The suitability of BG7 for genome annotation has been proved for Illumina, 454, Ion Torrent, and PacBio sequencing technologies. Besides, thanks to its plasticity, our system could be very easily adapted to work with new technologies in the future.
Medina, Ignacio; Salavert, Francisco; Sanchez, Rubén; de Maria, Alejandro; Alonso, Roberto; Escobar, Pablo; Bleda, Marta; Dopazo, Joaquín
Genome browsers have gained importance as more genomes and related genomic information become available. However, the increase of information brought about by new generation sequencing technologies is, at the same time, causing a subtle but continuous decrease in the efficiency of conventional genome browsers. Here, we present Genome Maps, a genome browser that implements an innovative model of data transfer and management. The program uses highly efficient technologies from the new HTML5 standard, such as scalable vector graphics, that optimize workloads at both server and client sides and ensure future scalability. Thus, data management and representation are entirely carried out by the browser, without the need of any Java Applet, Flash or other plug-in technology installation. Relevant biological data on genes, transcripts, exons, regulatory features, single-nucleotide polymorphisms, karyotype and so forth, are imported from web services and are available as tracks. In addition, several DAS servers are already included in Genome Maps. As a novelty, this web-based genome browser allows the local upload of huge genomic data files (e.g. VCF or BAM) that can be dynamically visualized in real time at the client side, thus facilitating the management of medical data affected by privacy restrictions. Finally, Genome Maps can easily be integrated in any web application by including only a few lines of code. Genome Maps is an open source collaborative initiative available in the GitHub repository (https://github.com/compbio-bigdata-viz/genome-maps). Genome Maps is available at: http://www.genomemaps.org.
Anderson, Matthew Z.
Candida species are the most prevalent human fungal pathogens, with Candida albicans being the most clinically relevant species. Candida albicans resides as a commensal of the human gastrointestinal tract but is a frequent cause of opportunistic mucosal and systemic infections. Investigation of C. albicans virulence has traditionally relied on candidate gene approaches, but recent advances in functional genomics have now facilitated global, unbiased studies of gene function. Such studies include comparative genomics (both between and within Candida species), analysis of total RNA expression, and regulation and delineation of protein–DNA interactions. Additionally, large collections of mutant strains have begun to aid systematic screening of clinically relevant phenotypes. Here, we will highlight the development of functional genomics in C. albicans and discuss the use of these approaches to addressing both commensalism and pathogenesis in this species. PMID:26424829
Shaik, Sabiha; Kumar, Narender; Lankapalli, Aditya K; Tiwari, Sumeet K; Baddam, Ramani; Ahmed, Niyaz
A wide variety of genome sequencing platforms have emerged in the recent past. High-throughput platforms like Illumina and 454 are essentially adaptations of the shotgun approach generating millions of fragmented single or paired sequencing reads. To reconstruct whole genomes, the reads have to be assembled into contigs, which often require further downstream processing. The contigs can be directly ordered according to a reference, scaffolded based on paired read information, or assembled using a combination of the two approaches. While the reference-based approach appears to mask strain-specific information, scaffolding based on paired-end information suffers when repetitive elements longer than the size of the sequencing reads are present in the genome. Sequencing technologies that produce long reads can solve the problems associated with repetitive elements but are not necessarily easily available to researchers. The most common high-throughput technology currently used is the Illumina short read platform. To improve upon the shortcomings associated with the construction of draft genomes with Illumina paired-end sequencing, we developed Contig-Layout-Authenticator (CLA). The CLA pipeline can scaffold reference-sorted contigs based on paired reads, resulting in better assembled genomes. Moreover, CLA also hints at probable misassemblies and contaminations, for the users to cross-check before constructing the consensus draft. The CLA pipeline was designed and trained extensively on various bacterial genome datasets for the ordering and scaffolding of large repetitive contigs. The tool has been validated and compared favorably with other widely-used scaffolding and ordering tools using both simulated and real sequence datasets. CLA is a user friendly tool that requires a single command line input to generate ordered scaffolds.
Hogan, Andrew J.
This paper explores evolving conceptions and depictions of the human genome among human and medical geneticists during the postwar period. Historians of science and medicine have shown significant interest in the use of informational approaches in postwar genetics, which treat the genome as an expansive digital data set composed of three billion DNA nucleotides. Since the 1950s, however, geneticists have largely interacted with the human genome at the microscopically visible level of chromosomes. Mindful of this, I examine the observational and representational approaches of postwar human and medical genetics. During the 1970s and 1980s, the genome increasingly came to be understood as, at once, a discrete part of the human anatomy and a standardised scientific object. This paper explores the role of influential medical geneticists in recasting the human genome as being a visible, tangible, and legible entity, which was highly relevant to traditional medical thinking and practice. I demonstrate how the human genome was established as an object amenable to laboratory and clinical research, and argue that the observational and representational approaches of postwar medical genetics reflect, more broadly, the interdisciplinary efforts underlying the development of contemporary biomedicine. PMID:25045177
Full Text Available People increasingly have their genomes sequenced and some of them share their genomic data online. They do so for various purposes, including to find relatives and to help advance genomic research. An individual’s genome carries very sensitive, private information such as its owner’s susceptibility to diseases, which could be used for discrimination. Therefore, genomic databases are often anonymized. However, an individual’s genotype is also linked to visible phenotypic traits, such as eye or hair color, which can be used to re-identify users in anonymized public genomic databases, thus raising severe privacy issues. For instance, an adversary can identify a target’s genome using known her phenotypic traits and subsequently infer her susceptibility to Alzheimer’s disease. In this paper, we quantify, based on various phenotypic traits, the extent of this threat in several scenarios by implementing de-anonymization attacks on a genomic database of OpenSNP users sequenced by 23andMe. Our experimental results show that the proportion of correct matches reaches 23% with a supervised approach in a database of 50 participants. Our approach outperforms the baseline by a factor of four, in terms of the proportion of correct matches, in most scenarios. We also evaluate the adversary’s ability to predict individuals’ predisposition to Alzheimer’s disease, and we observe that the inference error can be halved compared to the baseline. We also analyze the effect of the number of known phenotypic traits on the success rate of the attack. As progress is made in genomic research, especially for genotype-phenotype associations, the threat presented in this paper will become more serious.
Full Text Available Computational methods to identify functional genomic elements using genetic information have been very successful in determining gene structure and in identifying a handful of cis-regulatory elements. But the vast majority of regulatory elements have yet to be discovered, and it has become increasingly apparent that their discovery will not come from using genetic information alone. Recently, high-throughput technologies have enabled the creation of information-rich epigenetic maps, most notably for histone modifications. However, tools that search for functional elements using this epigenetic information have been lacking. Here, we describe an unsupervised learning method called ChromaSig to find, in an unbiased fashion, commonly occurring chromatin signatures in both tiling microarray and sequencing data. Applying this algorithm to nine chromatin marks across a 1% sampling of the human genome in HeLa cells, we recover eight clusters of distinct chromatin signatures, five of which correspond to known patterns associated with transcriptional promoters and enhancers. Interestingly, we observe that the distinct chromatin signatures found at enhancers mark distinct functional classes of enhancers in terms of transcription factor and coactivator binding. In addition, we identify three clusters of novel chromatin signatures that contain evolutionarily conserved sequences and potential cis-regulatory elements. Applying ChromaSig to a panel of 21 chromatin marks mapped genomewide by ChIP-Seq reveals 16 classes of genomic elements marked by distinct chromatin signatures. Interestingly, four classes containing enrichment for repressive histone modifications appear to be locally heterochromatic sites and are enriched in quickly evolving regions of the genome. The utility of this approach in uncovering novel, functionally significant genomic elements will aid future efforts of genome annotation via chromatin modifications.
Gonzalez-Perez, Abel; Mustonen, Ville; Reva, Boris
The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor but only a minority of these drive tumor progression. We present the result of discu......The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor but only a minority of these drive tumor progression. We present the result...... of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype....
Full Text Available Abstract Background Genomic tiling micro arrays have great potential for identifying previously undiscovered coding as well as non-coding transcription. To-date, however, analyses of these data have been performed in an ad hoc fashion. Results We present a probabilistic procedure, ExpressHMM, that adaptively models tiling data prior to predicting expression on genomic sequence. A hidden Markov model (HMM is used to model the distributions of tiling array probe scores in expressed and non-expressed regions. The HMM is trained on sets of probes mapped to regions of annotated expression and non-expression. Subsequently, prediction of transcribed fragments is made on tiled genomic sequence. The prediction is accompanied by an expression probability curve for visual inspection of the supporting evidence. We test ExpressHMM on data from the Cheng et al. (2005 tiling array experiments on ten Human chromosomes 1. Results can be downloaded and viewed from our web site 2. Conclusion The value of adaptive modelling of fluorescence scores prior to categorisation into expressed and non-expressed probes is demonstrated. Our results indicate that our adaptive approach is superior to the previous analysis in terms of nucleotide sensitivity and transfrag specificity.
Lobzin, Vasilii V; Chechetkin, Vladimir R
The structural analysis of genomic DNA sequences is discussed in the framework of the spectral approach, which is sufficiently universal due to the reciprocal correspondence and mutual complementarity of Fourier transform length scales. The spectral characteristics of random sequences of the same nucleotide composition possess the property of self-averaging for relatively short sequences of length M≥100-300. Comparison with the characteristics of random sequences determines the statistical significance of the structural features observed. Apart from traditional applications to the search for hidden periodicities, spectral methods are also efficient in studying mutual correlations in DNA sequences. By combining spectra for structure factors and correlation functions, not only integral correlations can be estimated but also their origin identified. Using the structural spectral entropy approach, the regularity of a sequence can be quantitatively assessed. A brief introduction to the problem is also presented and other major methods of DNA sequence analysis described. (reviews of topical problems)
Dubchak, Inna; Poliakov, Alexander; Kislyuk, Andrey; Brudno, Michael
Multiple sequence alignments have become one of the most commonly used resources in genomics research. Most algorithms for multiple alignment of whole genomes rely either on a reference genome, against which all of the other sequences are laid out, or require a one-to-one mapping between the nucleotides of the genomes, preventing the alignment of recently duplicated regions. Both approaches have drawbacks for whole-genome comparisons. In this paper we present a novel symmetric alignment algorithm. The resulting alignments not only represent all of the genomes equally well, but also include all relevant duplications that occurred since the divergence from the last common ancestor. Our algorithm, implemented as a part of the VISTA Genome Pipeline (VGP), was used to align seven vertebrate and sixDrosophila genomes. The resulting whole-genome alignments demonstrate a higher sensitivity and specificity than the pairwise alignments previously available through the VGP and have higher exon alignment accuracy than comparable public whole-genome alignments. Of the multiple alignment methods tested, ours performed the best at aligning genes from multigene families?perhaps the most challenging test for whole-genome alignments. Our whole-genome multiple alignments are available through the VISTA Browser at http://genome.lbl.gov/vista/index.shtml.
Gasc, Cyrielle; Ribière, Céline; Parisot, Nicolas; Beugnot, Réjane; Defois, Clémence; Petit-Biderre, Corinne; Boucher, Delphine; Peyretaillade, Eric; Peyret, Pierre
Prokaryotes are the most diverse and abundant cellular life forms on Earth. Most of them, identified by indirect molecular approaches, belong to microbial dark matter. The advent of metagenomic and single-cell genomic approaches has highlighted the metabolic capabilities of numerous members of this dark matter through genome reconstruction. Thus, linking functions back to the species has revolutionized our understanding of how ecosystem function is sustained by the microbial world. This review will present discoveries acquired through the illumination of prokaryotic dark matter genomes by these innovative approaches. Copyright © 2015 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.
John C. Meeks
Nostoc punctiforme is a filamentous cyanobacterium with extensive phenotypic characteristics and a relatively large genome, approaching 10 Mb. The phenotypic characteristics include a photoautotrophic, diazotrophic mode of growth, but N. punctiforme is also facultatively heterotrophic; its vegetative cells have multiple development alternatives, including terminal differentiation into nitrogen-fixing heterocysts and transient differentiation into spore-like akinetes or motile filaments called hormogonia; and N. punctiforme has broad symbiotic competence with fungi and terrestrial plants, including bryophytes, gymnosperms and an angiosperm. The shotgun-sequencing phase of the N. punctiforme strain ATCC 29133 genome has been completed by the Joint Genome Institute. Annotation of an 8.9 Mb database yielded 7432 open reading frames, 45% of which encode proteins with known or probable known function and 29% of which are unique to N. punctiforme. Comparative analysis of the sequence indicates a genome that is highly plastic and in a state of flux, with numerous insertion sequences and multilocus repeats, as well as genes encoding transposases and DNA modification enzymes. The sequence also reveals the presence of genes encoding putative proteins that collectively define almost all characteristics of cyanobacteria as a group. N. punctiforme has an extensive potential to sense and respond to environmental signals as reflected by the presence of more than 400 genes encoding sensor protein kinases, response regulators and other transcriptional factors. The signal transduction systems and any of the large number of unique genes may play essential roles in the cell differentiation and symbiotic interaction properties of N. punctiforme.
Full Text Available DNA methylation is one of the most studied epigenetic marks in the human genome, with the result that the desire to map the human methylome has driven the development of several methods to map DNA methylation on a genomic scale. Our study presents the first comparison of two of these techniques - the targeted approach of the Infinium HumanMethylation450 BeadChip® with the immunoprecipitation and sequencing-based method, MeDIP-seq. Both methods were initially validated with respect to bisulfite sequencing as the gold standard and then assessed in terms of coverage, resolution and accuracy. The regions of the methylome that can be assayed by both methods and those that can only be assayed by one method were determined and the discovery of differentially methylated regions (DMRs by both techniques was examined. Our results show that the Infinium HumanMethylation450 BeadChip® and MeDIP-seq show a good positive correlation (Spearman correlation of 0.68 on a genome-wide scale and can both be used successfully to determine differentially methylated loci in RefSeq genes, CpG islands, shores and shelves. MeDIP-seq however, allows a wider interrogation of methylated regions of the human genome, including thousands of non-RefSeq genes and repetitive elements, all of which may be of importance in disease. In our study MeDIP-seq allowed the detection of 15,709 differentially methylated regions, nearly twice as many as the array-based method (8070, which may result in a more comprehensive study of the methylome.
Araújo, Luciano V; Malkowski, Simon; Braghetto, Kelly R; Passos-Bueno, Maria R; Zatz, Mayana; Pu, Calton; Ferreira, João E
Recent medical and biological technology advances have stimulated the development of new testing systems that have been providing huge, varied amounts of molecular and clinical data. Growing data volumes pose significant challenges for information processing systems in research centers. Additionally, the routines of genomics laboratory are typically characterized by high parallelism in testing and constant procedure changes. This paper describes a formal approach to address this challenge through the implementation of a genetic testing management system applied to human genome laboratory. We introduced the Human Genome Research Center Information System (CEGH) in Brazil, a system that is able to support constant changes in human genome testing and can provide patients updated results based on the most recent and validated genetic knowledge. Our approach uses a common repository for process planning to ensure reusability, specification, instantiation, monitoring, and execution of processes, which are defined using a relational database and rigorous control flow specifications based on process algebra (ACP). The main difference between our approach and related works is that we were able to join two important aspects: 1) process scalability achieved through relational database implementation, and 2) correctness of processes using process algebra. Furthermore, the software allows end users to define genetic testing without requiring any knowledge about business process notation or process algebra. This paper presents the CEGH information system that is a Laboratory Information Management System (LIMS) based on a formal framework to support genetic testing management for Mendelian disorder studies. We have proved the feasibility and showed usability benefits of a rigorous approach that is able to specify, validate, and perform genetic testing using easy end user interfaces.
Argout, X; Martin, G; Droc, G; Fouet, O; Labadie, K; Rivals, E; Aury, J M; Lanaud, C
Theobroma cacao L., native to the Amazonian basin of South America, is an economically important fruit tree crop for tropical countries as a source of chocolate. The first draft genome of the species, from a Criollo cultivar, was published in 2011. Although a useful resource, some improvements are possible, including identifying misassemblies, reducing the number of scaffolds and gaps, and anchoring un-anchored sequences to the 10 chromosomes. We used a NGS-based approach to significantly improve the assembly of the Belizian Criollo B97-61/B2 genome. We combined four Illumina large insert size mate paired libraries with 52x of Pacific Biosciences long reads to correct misassembled regions and reduced the number of scaffolds. We then used genotyping by sequencing (GBS) methods to increase the proportion of the assembly anchored to chromosomes. The scaffold number decreased from 4,792 in assembly V1 to 554 in V2 while the scaffold N50 size has increased from 0.47 Mb in V1 to 6.5 Mb in V2. A total of 96.7% of the assembly was anchored to the 10 chromosomes compared to 66.8% in the previous version. Unknown sites (Ns) were reduced from 10.8% to 5.7%. In addition, we updated the functional annotations and performed a new RefSeq structural annotation based on RNAseq evidence. Theobroma cacao Criollo genome version 2 will be a valuable resource for the investigation of complex traits at the genomic level and for future comparative genomics and genetics studies in cacao tree. New functional tools and annotations are available on the Cocoa Genome Hub ( http://cocoa-genome-hub.southgreen.fr ).
Hayes, Benjamin J; MacLeod, Iona M; Daetwyler, Hans D
Advantages of using whole genome sequence data to predict genomic estimated breeding values (GEBV) include better persistence of accuracy of GEBV across generations and more accurate GEBV across breeds. The 1000 Bull Genomes Project provides a database of whole genome sequenced key ancestor bulls....... In a dairy data set, predictions using BayesRC and imputed sequence data from 1000 Bull Genomes were 2% more accurate than with 800k data. We could demonstrate the method identified causal mutations in some cases. Further improvements will come from more accurate imputation of sequence variant genotypes...
Department of Energy/Joint Genome Institute (DOE/JGI) collaborates with DOE national laboratories and community users, to advance genome science in support of the DOE missions of clean bio-energy, carbon cycling, and bioremediation.
Hood, Leroy; Rowen, Lee
The Human Genome Project has transformed biology through its integrated big science approach to deciphering a reference human genome sequence along with the complete sequences of key model organisms. The project exemplifies the power, necessity and success of large, integrated, cross-disciplinary efforts - so-called 'big science' - directed towards complex major objectives. In this article, we discuss the ways in which this ambitious endeavor led to the development of novel technologies and analytical tools, and how it brought the expertise of engineers, computer scientists and mathematicians together with biologists. It established an open approach to data sharing and open-source software, thereby making the data resulting from the project accessible to all. The genome sequences of microbes, plants and animals have revolutionized many fields of science, including microbiology, virology, infectious disease and plant biology. Moreover, deeper knowledge of human sequence variation has begun to alter the practice of medicine. The Human Genome Project has inspired subsequent large-scale data acquisition initiatives such as the International HapMap Project, 1000 Genomes, and The Cancer Genome Atlas, as well as the recently announced Human Brain Project and the emerging Human Proteome Project.
Ravet, Karl; Patterson, Eric L; Krähmer, Hansjörg; Hamouzová, Kateřina; Fan, Longjiang; Jasieniuk, Marie; Lawton-Rauh, Amy; Malone, Jenna M; Scott McElroy, J; Merotto, Aldo; Westra, Philip; Preston, Christopher; Vila-Aiub, Martin M; Busi, Roberto; Tranel, Patrick J; Reinhardt, Carl; Saski, Christopher; Beffa, Roland; Neve, Paul; Gaines, Todd A
There have been previous calls for, and efforts focused on, realizing the power and potential of weed genomics for better understanding of weeds. Sustained advances in genome sequencing and assembly technologies now make it possible for individual research groups to generate reference genomes for multiple weed species at reasonable costs. Here, we present the outcomes from several meetings, discussions, and workshops focused on establishing an International Weed Genomics Consortium (IWGC) for a coordinated international effort in weed genomics. We review the 'state of the art' in genomics and weed genomics, including technologies, applications, and on-going weed genome projects. We also report the outcomes from a workshop and a global survey of the weed science community to identify priority species, key biological questions, and weed management applications that can be addressed through greater availability of, and access to, genomic resources. Major focus areas include the evolution of herbicide resistance and weedy traits, the development of molecular diagnostics, and the identification of novel targets and approaches for weed management. There is increasing interest in, and need for, weed genomics, and the establishment of the IWGC will provide the necessary global platform for communication and coordination of weed genomics research. This article is protected by copyright. All rights reserved.
Shengkui ZHANG,Ping'an MA,Haiyan WANG,Cheng LU,Xin CHEN,Zhiqiang XIA,Meiling ZOU,Xinchen ZHOU,Wenquan WANG
Full Text Available Cassava, a tropical food, feed and biofuel crop, has great capacity for biomass accumulation and an extraordinary efficiency in water use and mineral nutrition, which makes it highly suitable as a model plant for tropical crops. However, the understanding of the metabolism and genomics of this important crop is limited. The recent breakthroughs in the genomics of cassava, including whole-genome sequencing and transcriptome analysis, as well as advances in the biology of photosynthesis, starch biosynthesis, adaptation to drought and high temperature, and resistance to virus and bacterial diseases, are reviewed here. Many of the new developments have come from comparative analyses between a wild ancestor and existing cultivars. Finally, the current challenges and future potential of cassava as a model plant are discussed.
Full Text Available Anaplastic oligodendrogliomas (AOD are rare glial tumors in adults with relative homogeneous clinical, radiological and histological features at the time of diagnosis but dramatically various clinical courses. Studies have identified several molecular abnormalities with clinical or biological relevance to AOD (e.g. t(1;19(q10;p10, IDH1, IDH2, CIC and FUBP1 mutations.To better characterize the clinical and biological behavior of this tumor type, the creation of a national multicentric network, named "Prise en charge des OLigodendrogliomes Anaplasiques (POLA," has been supported by the Institut National du Cancer (InCA. Newly diagnosed and centrally validated AOD patients and their related biological material (tumor and blood samples were prospectively included in the POLA clinical database and tissue bank, respectively.At the molecular level, we have conducted a high-resolution single nucleotide polymorphism array analysis, which included 83 patients. Despite a careful central pathological review, AOD have been found to exhibit heterogeneous genomic features. A total of 82% of the tumors exhibited a 1p/19q-co-deletion, while 18% harbor a distinct chromosome pattern. Novel focal abnormalities, including homozygously deleted, amplified and disrupted regions, have been identified. Recurring copy neutral losses of heterozygosity (CNLOH inducing the modulation of gene expression have also been discovered. CNLOH in the CDKN2A locus was associated with protein silencing in 1/3 of the cases. In addition, FUBP1 homozygous deletion was detected in one case suggesting a putative tumor suppressor role of FUBP1 in AOD.Our study showed that the genomic and pathological analyses of AOD are synergistic in detecting relevant clinical and biological subgroups of AOD.
Cabrera-Bosquet, Llorenç; Crossa, José; von Zitzewitz, Jarislav; Serret, María Dolors; Araus, José Luis
Genomic selection (GS) and high-throughput phenotyping have recently been captivating the interest of the crop breeding community from both the public and private sectors world-wide. Both approaches promise to revolutionize the prediction of complex traits, including growth, yield and adaptation to stress. Whereas high-throughput phenotyping may help to improve understanding of crop physiology, most powerful techniques for high-throughput field phenotyping are empirical rather than analytical and comparable to genomic selection. Despite the fact that the two methodological approaches represent the extremes of what is understood as the breeding process (phenotype versus genome), they both consider the targeted traits (e.g. grain yield, growth, phenology, plant adaptation to stress) as a black box instead of dissecting them as a set of secondary traits (i.e. physiological) putatively related to the target trait. Both GS and high-throughput phenotyping have in common their empirical approach enabling breeders to use genome profile or phenotype without understanding the underlying biology. This short review discusses the main aspects of both approaches and focuses on the case of genomic selection of maize flowering traits and near-infrared spectroscopy (NIRS) and plant spectral reflectance as high-throughput field phenotyping methods for complex traits such as crop growth and yield. © 2012 Institute of Botany, Chinese Academy of Sciences.
Beverly E. Flood
Full Text Available The genus Thiomargarita includes the world’s largest bacteria. But as uncultured organisms, their physiology, metabolism, and basis for their gigantism are not well understood. Thus a genomics approach, applied to a single Candidatus Thiomargarita nelsonii cell was employed to explore the genetic potential of one of these enigmatic giant bacteria. The Thiomargarita cell was obtained from an assemblage of budding Ca. T. nelsonii attached to a provannid gastropod shell from Hydrate Ridge, a methane seep offshore of Oregon, USA. Here we present a manually curated genome of Bud S10 resulting from a hybrid assembly of long Pacific Biosciences and short Illumina sequencing reads. With respect to inorganic carbon fixation and sulfur oxidation pathways, the Ca. T. nelsonii Hydrate Ridge Bud S10 genome was similar to marine sister taxa within the family Beggiatoaceae. However, the Bud S10 genome contains genes suggestive of the genetic potential for lithotrophic growth on arsenite and perhaps hydrogen. The genome also revealed that Bud S10 likely respires nitrate via two pathways: a complete denitrification pathway and a dissimilatory nitrate reduction to ammonia pathway. Both pathways have been predicted, but not previously fully elucidated, in the genomes of other large, vacuolated, sulfur-oxidizing bacteria.Surprisingly, the genome also had a high number of unusual features for a bacterium to include the largest number of metacaspases and introns ever reported in a bacterium. Also present, are a large number of other mobile genetic elements, such as insertion sequence transposable elements and miniature inverted-repeat transposable elements (MITEs. In some cases, mobile genetic elements disrupted key genes in metabolic pathways. For example, a MITE interrupts hupL, which encodes the large subunit of the hydrogenase in hydrogen oxidation. Moreover, we detected a group I intron in one of the most critical genes in the sulfur oxidation pathway, dsr
Rusconi, Brigida; Sanjar, Fatemeh; Koenig, Sara S K; Mammel, Mark K; Tarr, Phillip I; Eppinger, Mark
Multi isolate whole genome sequencing (WGS) and typing for outbreak investigations has become a reality in the post-genomics era. We applied this technology to strains from Escherichia coli O157:H7 outbreaks. These include isolates from seven North America outbreaks, as well as multiple isolates from the same patient and from different infected individuals in the same household. Customized high-resolution bioinformatics sequence typing strategies were developed to assess the core genome and mobilome plasticity. Sequence typing was performed using an in-house single nucleotide polymorphism (SNP) discovery and validation pipeline. Discriminatory power becomes of particular importance for the investigation of isolates from outbreaks in which macrogenomic techniques such as pulse-field gel electrophoresis or multiple locus variable number tandem repeat analysis do not differentiate closely related organisms. We also characterized differences in the phage inventory, allowing us to identify plasticity among outbreak strains that is not detectable at the core genome level. Our comprehensive analysis of the mobilome identified multiple plasmids that have not previously been associated with this lineage. Applied phylogenomics approaches provide strong molecular evidence for exceptionally little heterogeneity of strains within outbreaks and demonstrate the value of intra-cluster comparisons, rather than basing the analysis on archetypal reference strains. Next generation sequencing and whole genome typing strategies provide the technological foundation for genomic epidemiology outbreak investigation utilizing its significantly higher sample throughput, cost efficiency, and phylogenetic relatedness accuracy. These phylogenomics approaches have major public health relevance in translating information from the sequence-based survey to support timely and informed countermeasures. Polymorphisms identified in this work offer robust phylogenetic signals that index both short- and
Timothy G Lesnick
Full Text Available While major inroads have been made in identifying the genetic causes of rare Mendelian disorders, little progress has been made in the discovery of common gene variations that predispose to complex diseases. The single gene variants that have been shown to associate reproducibly with complex diseases typically have small effect sizes or attributable risks. However, the joint actions of common gene variants within pathways may play a major role in predisposing to complex diseases (the paradigm of complex genetics. The goal of this study was to determine whether polymorphism in a candidate pathway (axon guidance predisposed to a complex disease (Parkinson disease [PD]. We mined a whole-genome association dataset and identified single nucleotide polymorphisms (SNPs that were within axon-guidance pathway genes. We then constructed models of axon-guidance pathway SNPs that predicted three outcomes: PD susceptibility (odds ratio = 90.8, p = 4.64 x 10(-38, survival free of PD (hazards ratio = 19.0, p = 5.43 x 10(-48, and PD age at onset (R(2 = 0.68, p = 1.68 x 10(-51. By contrast, models constructed from thousands of random selections of genomic SNPs predicted the three PD outcomes poorly. Mining of a second whole-genome association dataset and mining of an expression profiling dataset also supported a role for many axon-guidance pathway genes in PD. These findings could have important implications regarding the pathogenesis of PD. This genomic pathway approach may also offer insights into other complex diseases such as Alzheimer disease, diabetes mellitus, nicotine and alcohol dependence, and several cancers.
Guldbrandtsen, Bernt; Cai, Zexi; Sahana, Goutam
The American Mink’s (Neovison vison) genome has recently been sequenced. This opens numerous avenues of research both for studying the basic genetics and physiology of the mink as well as genetic improvement in mink. Using genotyping-by-sequencing (GBS) generated marker data for 2,352 Danish farm...... mink runs of homozygosity (ROH) were detect in mink genomes. Detectable ROH made up on average 1.7% of the genome indicating the presence of at most a moderate level of genomic inbreeding. The fraction of genome regions found in ROH varied. Ten percent of the included regions were never found in ROH....... The ability to detect ROH in the mink genome also demonstrates the general reliability of the new mink genome assembly. Keywords: american mink, run of homozygosity, genome, selection, genomic inbreeding...
Rasmussen, Jane Lind Nybo; Theobald, Sebastian; Brandl, Julian
and applicable for many types of studies. In this chapter, we provide an overview of the state-of-the-art of comparative genomics in these fungi, along with recommended methods. The chapter describes databases for fungal comparative genomics. Based on experience, we suggest strategies for multiple types...... of comparative genomics, ranging from analysis of single genes, over gene clusters and CaZymes to genome-scale comparative genomics. Furthermore, we have examined published comparative genomics papers to summarize the preferred bioinformatic methods and parameters for a given type of analysis, highly useful...... comparative genomics to the development in bacterial genomics, where the comparison of hundreds of genomes has been performed for a while....
Arun Prabhu Dhanapal
Full Text Available The number of sequenced crop genomes and associated genomic resources is growing rapidly with the advent of inexpensive next generation sequencing methods. Databases have become an integral part of all aspects of science research, including basic and applied plant and animal sciences. The importance of databases keeps increasing as the volume of datasets from direct and indirect genomics, as well as other omics approaches, keeps expanding in recent years. The databases and associated web portals provide at a minimum a uniform set of tools and automated analysis across a wide range of crop plant genomes. This paper reviews some basic terms and considerations in dealing with crop plant databases utilization in advancing genomic era. The utilization of databases for variation analysis with other comparative genomics tools, and data interpretation platforms are well described. The major focus of this review is to provide knowledge on platforms and databases for genome-based investigations of agriculturally important crop plants. The utilization of these databases in applied crop improvement program is still being achieved widely; otherwise, the end for sequencing is not far away.
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
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.
Moraes, Fernanda; Góes, Andréa
The Human Genome Project (HGP) was initiated in 1990 and completed in 2003. It aimed to sequence the whole human genome. Although it represented an advance in understanding the human genome and its complexity, many questions remained unanswered. Other projects were launched in order to unravel the mysteries of our genome, including the ENCyclopedia of DNA Elements (ENCODE). This review aims to analyze the evolution of scientific knowledge related to both the HGP and ENCODE projects. Data were retrieved from scientific articles published in 1990-2014, a period comprising the development and the 10 years following the HGP completion. The fact that only 20,000 genes are protein and RNA-coding is one of the most striking HGP results. A new concept about the organization of genome arose. The ENCODE project was initiated in 2003 and targeted to map the functional elements of the human genome. This project revealed that the human genome is pervasively transcribed. Therefore, it was determined that a large part of the non-protein coding regions are functional. Finally, a more sophisticated view of chromatin structure emerged. The mechanistic functioning of the genome has been redrafted, revealing a much more complex picture. Besides, a gene-centric conception of the organism has to be reviewed. A number of criticisms have emerged against the ENCODE project approaches, raising the question of whether non-conserved but biochemically active regions are truly functional. Thus, HGP and ENCODE projects accomplished a great map of the human genome, but the data generated still requires further in depth analysis. © 2016 by The International Union of Biochemistry and Molecular Biology, 44:215-223, 2016. © 2016 The International Union of Biochemistry and Molecular Biology.
Albertsen, Mads; Hugenholtz, Philip; Tyson, Gene W.
of the community. The assembled genomes include many of the process-critical bacteria involved in wastewater treatment, such as Competibacter, Tetrasphaera and TM7. The approach is not limited to different extraction methods, but can be applied to any treatment that results in different relative abundance......Bacteria play a pivotal role in engineered systems such as wastewater treatment plants. Obtaining genomes of the bacteria provides the genetic potential of the system and also allows studies of in situ functions through transcriptomics and proteomics. Hence, it enables correlations of operational......, the sequencing of bulk genomic DNA from environmental samples, has the potential to provide genomes of this uncultured majority. However, so far only few bacterial genomes have been obtained from metagenomic data. In this study we present a new approach to obtain individual genomes from metagenomes. We deeply...
Coller, Hilary A
Emerging technologies for the analysis of genome-wide information in single cells have the potential to transform many fields of biology, including our understanding of cell states, the response of cells to external stimuli, mosaicism, and intratumor heterogeneity. At Experimental Biology 2017 in Chicago, Physiological Genomics hosted a symposium in which five leaders in the field of single cell genomics presented their recent research. The speakers discussed emerging methodologies in single cell analysis and critical issues for the analysis of single cell data. Also discussed were applications of single cell genomics to understanding the different types of cells within an organism or tissue and the basis for cell-to-cell variability in response to stimuli. Copyright © 2017 the American Physiological Society.
Lingli HE; Jing ZHAO; Man ZHAO; Chaoying HE
Soybean (Glycine max),an important domesticated species originated in China,constitutes a major source of edible oils and high-quality plant proteins worldwide.In spite of its complex genome as a consequence of an ancient tetraploidilization,platforms for map-based genomics,sequence-based genomics,comparative genomics and functional genomics have been well developed in the last decade,thus rich repertoires of genomic tools and resources are available,which have been influencing the soybean genetic improvement.Here we mainly review the progresses of soybean (including its wild relative Glycine soja) genomics and its impetus for soybean breeding,and raise the major biological questions needing to be addressed.Genetic maps,physical maps,QTL and EST mapping have been so well achieved that the marker assisted selection and positional cloning in soybean is feasible and even routine.Whole genome sequencing and transcriptomic analyses provide a large collection of molecular markers and predicted genes,which are instrumental to comparative genomics and functional genomics.Comparative genomics has started to reveal the evolution of soybean genome and the molecular basis of soybean domestication process.Microarrays resources,mutagenesis and efficient transformation systems become essential components of soybean functional genomics.Furthermore,phenotypic functional genomics via both forward and reverse genetic approaches has inferred functions of many genes involved in plant and seed development,in response to abiotic stresses,functioning in plant-pathogenic microbe interactions,and controlling the oil and protein content of seed.These achievements have paved the way for generation of transgenic or genetically modified (GM) soybean crops.
Chakravarti, Deboki; Cho, Jang Hwan; Weinberg, Benjamin H; Wong, Nicole M; Wong, Wilson W
Investigations into cells and their contents have provided evolving insight into the emergence of complex biological behaviors. Capitalizing on this knowledge, synthetic biology seeks to manipulate the cellular machinery towards novel purposes, extending discoveries from basic science to new applications. While these developments have demonstrated the potential of building with biological parts, the complexity of cells can pose numerous challenges. In this review, we will highlight the broad and vital role that the synthetic biology approach has played in applying fundamental biological discoveries in receptors, genetic circuits, and genome-editing systems towards translation in the fields of immunotherapy, biosensors, disease models and gene therapy. These examples are evidence of the strength of synthetic approaches, while also illustrating considerations that must be addressed when developing systems around living cells.
Full Text Available Abstract Background Array comparative genomic hybridization is a fast and cost-effective method for detecting, genotyping, and comparing the genomic sequence of unknown bacterial isolates. This method, as with all microarray applications, requires adequate coverage of probes targeting the regions of interest. An unbiased tiling of probes across the entire length of the genome is the most flexible design approach. However, such a whole-genome tiling requires that the genome sequence is known in advance. For the accurate analysis of uncharacterized bacteria, an array must query a fully representative set of sequences from the species' pan-genome. Prior microarrays have included only a single strain per array or the conserved sequences of gene families. These arrays omit potentially important genes and sequence variants from the pan-genome. Results This paper presents a new probe selection algorithm (PanArray that can tile multiple whole genomes using a minimal number of probes. Unlike arrays built on clustered gene families, PanArray uses an unbiased, probe-centric approach that does not rely on annotations, gene clustering, or multi-alignments. Instead, probes are evenly tiled across all sequences of the pan-genome at a consistent level of coverage. To minimize the required number of probes, probes conserved across multiple strains in the pan-genome are selected first, and additional probes are used only where necessary to span polymorphic regions of the genome. The viability of the algorithm is demonstrated by array designs for seven different bacterial pan-genomes and, in particular, the design of a 385,000 probe array that fully tiles the genomes of 20 different Listeria monocytogenes strains with overlapping probes at greater than twofold coverage. Conclusion PanArray is an oligonucleotide probe selection algorithm for tiling multiple genome sequences using a minimal number of probes. It is capable of fully tiling all genomes of a species on
Smith, Silvia E; Showers-Corneli, Patrice; Dardenne, Caitlin N; Harpending, Henry H; Martin, Darren P; Beiko, Robert G
The genus Mycobacterium encompasses over one hundred named species of environmental and pathogenic organisms, including the causative agents of devastating human diseases such as tuberculosis and leprosy. The success of these human pathogens is due in part to their ability to rapidly adapt to their changing environment and host. Recombination is the fastest way for bacterial genomes to acquire genetic material, but conflicting results about the extent of recombination in the genus Mycobacterium have been reported. We examined a data set comprising 18 distinct strains from 13 named species for evidence of recombination. Genomic regions common to all strains (accounting for 10% to 22% of the full genomes of all examined species) were aligned and concatenated in the chromosomal order of one mycobacterial reference species. The concatenated sequence was screened for evidence of recombination using a variety of statistical methods, with each proposed event evaluated by comparing maximum-likelihood phylogenies of the recombinant section with the non-recombinant portion of the dataset. Incongruent phylogenies were identified by comparing the site-wise log-likelihoods of each tree using multiple tests. We also used a phylogenomic approach to identify genes that may have been acquired through horizontal transfer from non-mycobacterial sources. The most frequent associated lineages (and potential gene transfer partners) in the Mycobacterium lineage-restricted gene trees are other members of suborder Corynebacterinae, but more-distant partners were identified as well. In two examined cases of potentially frequent and habitat-directed transfer (M. abscessus to Segniliparus and M. smegmatis to Streptomyces), observed sequence distances were small and consistent with a hypothesis of transfer, while in a third case (M. vanbaalenii to Streptomyces) distances were larger. The analyses described here indicate that whereas evidence of recombination in core regions within the genus is
Gregory W. Stull
Full Text Available Premise of the study: We explored a targeted enrichment strategy to facilitate rapid and low-cost next-generation sequencing (NGS of numerous complete plastid genomes from across the phylogenetic breadth of angiosperms. Methods and Results: A custom RNA probe set including the complete sequences of 22 previously sequenced eudicot plastomes was designed to facilitate hybridization-based targeted enrichment of eudicot plastid genomes. Using this probe set and an Agilent SureSelect targeted enrichment kit, we conducted an enrichment experiment including 24 angiosperms (22 eudicots, two monocots, which were subsequently sequenced on a single lane of the Illumina GAIIx with single-end, 100-bp reads. This approach yielded nearly complete to complete plastid genomes with exceptionally high coverage (mean coverage: 717×, even for the two monocots. Conclusions: Our enrichment experiment was highly successful even though many aspects of the capture process employed were suboptimal. Hence, significant improvements to this methodology are feasible. With this general approach and probe set, it should be possible to sequence more than 300 essentially complete plastid genomes in a single Illumina GAIIx lane (achieving 50× mean coverage. However, given the complications of pooling numerous samples for multiplex sequencing and the limited number of barcodes (e.g., 96 available in commercial kits, we recommend 96 samples as a current practical maximum for multiplex plastome sequencing. This high-throughput approach should facilitate large-scale plastid genome sequencing at any level of phylogenetic diversity in angiosperms.
Discriminating the causative disease variant(s) for individuals with inherited or de novo mutations presents one of the main challenges faced by the clinical genetics community today. Computational approaches for variant prioritization include machine learning methods utilizing a large number of features, including molecular information, interaction networks, or phenotypes. Here, we demonstrate the PhenomeNET Variant Predictor (PVP) system that exploits semantic technologies and automated reasoning over genotype-phenotype relations to filter and prioritize variants in whole exome and whole genome sequencing datasets. We demonstrate the performance of PVP in identifying causative variants on a large number of synthetic whole exome and whole genome sequences, covering a wide range of diseases and syndromes. In a retrospective study, we further illustrate the application of PVP for the interpretation of whole exome sequencing data in patients suffering from congenital hypothyroidism. We find that PVP accurately identifies causative variants in whole exome and whole genome sequencing datasets and provides a powerful resource for the discovery of causal variants.
Boudellioua, Imene; Mohamad Razali, Rozaimi; Kulmanov, Maxat; Hashish, Yasmeen; Bajic, Vladimir B.; Goncalves-Serra, Eva; Schoenmakers, Nadia; Gkoutos, Georgios V.; Schofield, Paul N.; Hoehndorf, Robert
Discriminating the causative disease variant(s) for individuals with inherited or de novo mutations presents one of the main challenges faced by the clinical genetics community today. Computational approaches for variant prioritization include machine learning methods utilizing a large number of features, including molecular information, interaction networks, or phenotypes. Here, we demonstrate the PhenomeNET Variant Predictor (PVP) system that exploits semantic technologies and automated reasoning over genotype-phenotype relations to filter and prioritize variants in whole exome and whole genome sequencing datasets. We demonstrate the performance of PVP in identifying causative variants on a large number of synthetic whole exome and whole genome sequences, covering a wide range of diseases and syndromes. In a retrospective study, we further illustrate the application of PVP for the interpretation of whole exome sequencing data in patients suffering from congenital hypothyroidism. We find that PVP accurately identifies causative variants in whole exome and whole genome sequencing datasets and provides a powerful resource for the discovery of causal variants.
Full Text Available Jangampalli Adi Pradeepkiran,1* Sri Bhashyam Sainath,2,3* Konidala Kranthi Kumar,1 Matcha Bhaskar1 1Division of Animal Biotechnology, Department of Zoology, Sri Venkateswara University, Tirupati, India; 2CIMAR/CIIMAR, Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Rua dos Bragas, Porto, Portugal, 3Department of Biotechnology, Vikrama Simhapuri University, Nellore, Andhra Pradesh, India *These authors contributed equally to this work Abstract: Brucella melitensis 16M is a Gram-negative coccobacillus that infects both animals and humans. It causes a disease known as brucellosis, which is characterized by acute febrile illness in humans and causes abortions in livestock. To prevent and control brucellosis, identification of putative drug targets is crucial. The present study aimed to identify drug targets in B. melitensis 16M by using a subtractive genomic approach. We used available database repositories (Database of Essential Genes, Kyoto Encyclopedia of Genes and Genomes Automatic Annotation Server, and Kyoto Encyclopedia of Genes and Genomes to identify putative genes that are nonhomologous to humans and essential for pathogen B. melitensis 16M. The results revealed that among 3 Mb genome size of pathogen, 53 putative characterized and 13 uncharacterized hypothetical genes were identified; further, from Basic Local Alignment Search Tool protein analysis, one hypothetical protein showed a close resemblance (50% to Silicibacter pomeroyi DUF1285 family protein (2RE3. A further homology model of the target was constructed using MODELLER 9.12 and optimized through variable target function method by molecular dynamics optimization with simulating annealing. The stereochemical quality of the restrained model was evaluated by PROCHECK, VERIFY-3D, ERRAT, and WHATIF servers. Furthermore, structure-based virtual screening was carried out against the predicted active site of the respective protein using the
T.A. Knoch (Tobias)
textabstractGenomes are one of the major foundations of life due to their role in information storage, process regulation and evolution. To achieve a deeper unterstanding of the human genome the three-dimensional organization of the human cell nucleus, the structural-, scaling- and dynamic
Haque, M Muksitul; Holder, Lawrence B; Skinner, Michael K
Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs). Different environmental toxicants have been shown to promote exposure (i.e., toxicant) specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm) epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT) and methoxychlor (MXC) exposure lineage F3 generation. Analysis of this positive validation data set showed a 100% prediction accuracy for all the DDT-MXC sperm epimutations. Observations further elucidate the genomic features associated with transgenerational germline epimutations and identify a genome
Tremendous progress has been made in the construction of physical and genetic maps of the human chromosomes. The next step in the solving of disease related problems, and in understanding the human genome as a whole, is the systematic isolation of transcribed sequences. Many investigators have already embarked upon comprehensive gene searches, and many more are considering the best strategies for undertaking such searches. Because these are likely to be costly and time consuming endeavors, it is important to determine the most efficient approaches. As a result, it is critical that investigators involved in the construction of transcriptional maps have the opportunity to discuss their experiences and their successes with both old and new technologies. This document contains the proceedings of the Fourth Annual Workshop on the Identification of Transcribed Sequences, held in Montreal, Quebec, October 16-18, 1994. Included are the workshop notebook, containing the agenda, abstracts presented and list of attendees. Topics included: Progress in the application of the hybridization based approaches and exon trapping; Progress in transcriptional map construction of selected genomic regions; Computer assisted analysis of genomic and protein coding sequences and additional new approaches; and, Sequencing and mapping of random cDNAs.
Full Text Available The Fungal Genome Initiative of the Broad Institute, in partnership with the Paracoccidioides research community, has recently sequenced the genome of representative isolates of this human-pathogen dimorphic fungus: Pb18 (S1, Pb03 (PS2 and Pb01. The accomplishment of future high-throughput, genome-wide, functional genomics will rely upon appropriate molecular tools and straightforward techniques to streamline the generation of stable loss-of-function phenotypes. In the past decades, RNAi has emerged as the most robust genetic technique to modulate or to suppress gene expression in diverse eukaryotes, including fungi. These molecular tools and techniques, adapted for RNAi, were up until now unavailable for P. brasiliensis.In this paper, we report Agrobacterium tumefaciens mediated transformation of yeast cells for high-throughput applications with which higher transformation frequencies of 150±24 yeast cell transformants per 1×106 viable yeast cells were obtained. Our approach is based on a bifunctional selective marker fusion protein consisted of the Streptoalloteichus hindustanus bleomycin-resistance gene (Shble and the intrinsically fluorescent monomeric protein mCherry which was codon-optimized for heterologous expression in P. brasiliensis. We also report successful GP43 gene knock-down through the expression of intron-containing hairpin RNA (ihpRNA from a Gateway-adapted cassette (cALf which was purpose-built for gene silencing in a high-throughput manner. Gp43 transcript levels were reduced by 73.1±22.9% with this approach.We have a firm conviction that the genetic transformation technique and the molecular tools herein described will have a relevant contribution in future Paracoccidioides spp. functional genomics research.
Chiu, Weihsueh A; Euling, Susan Y; Scott, Cheryl Siegel; Subramaniam, Ravi P
The contribution of genomics and associated technologies to human health risk assessment for environmental chemicals has focused largely on elucidating mechanisms of toxicity, as discussed in other articles in this issue. However, there is interest in moving beyond hazard characterization to making more direct impacts on quantitative risk assessment (QRA)--i.e., the determination of toxicity values for setting exposure standards and cleanup values. We propose that the evolution of QRA of environmental chemicals in the post-genomic era will involve three, somewhat overlapping phases in which different types of approaches begin to mature. The initial focus (in Phase I) has been and continues to be on "augmentation" of weight of evidence--using genomic and related technologies qualitatively to increase the confidence in and scientific basis of the results of QRA. Efforts aimed towards "integration" of these data with traditional animal-based approaches, in particular quantitative predictors, or surrogates, for the in vivo toxicity data to which they have been anchored are just beginning to be explored now (in Phase II). In parallel, there is a recognized need for "expansion" of the use of established biomarkers of susceptibility or risk of human diseases and disorders for QRA, particularly for addressing the issues of cumulative assessment and population risk. Ultimately (in Phase III), substantial further advances could be realized by the development of novel molecular and pathway-based biomarkers and statistical and in silico models that build on anticipated progress in understanding the pathways of human diseases and disorders. Such efforts would facilitate a gradual "reorientation" of QRA towards approaches that more directly link environmental exposures to human outcomes. Published by Elsevier Inc.
Chiu, Weihsueh A., E-mail: firstname.lastname@example.org [National Center for Environmental Assessment, U.S. Environmental Protection Agency, Washington DC, 20460 (United States); Euling, Susan Y.; Scott, Cheryl Siegel; Subramaniam, Ravi P. [National Center for Environmental Assessment, U.S. Environmental Protection Agency, Washington DC, 20460 (United States)
The contribution of genomics and associated technologies to human health risk assessment for environmental chemicals has focused largely on elucidating mechanisms of toxicity, as discussed in other articles in this issue. However, there is interest in moving beyond hazard characterization to making more direct impacts on quantitative risk assessment (QRA) — i.e., the determination of toxicity values for setting exposure standards and cleanup values. We propose that the evolution of QRA of environmental chemicals in the post-genomic era will involve three, somewhat overlapping phases in which different types of approaches begin to mature. The initial focus (in Phase I) has been and continues to be on “augmentation” of weight of evidence — using genomic and related technologies qualitatively to increase the confidence in and scientific basis of the results of QRA. Efforts aimed towards “integration” of these data with traditional animal-based approaches, in particular quantitative predictors, or surrogates, for the in vivo toxicity data to which they have been anchored are just beginning to be explored now (in Phase II). In parallel, there is a recognized need for “expansion” of the use of established biomarkers of susceptibility or risk of human diseases and disorders for QRA, particularly for addressing the issues of cumulative assessment and population risk. Ultimately (in Phase III), substantial further advances could be realized by the development of novel molecular and pathway-based biomarkers and statistical and in silico models that build on anticipated progress in understanding the pathways of human diseases and disorders. Such efforts would facilitate a gradual “reorientation” of QRA towards approaches that more directly link environmental exposures to human outcomes.
Chiu, Weihsueh A.; Euling, Susan Y.; Scott, Cheryl Siegel; Subramaniam, Ravi P.
The contribution of genomics and associated technologies to human health risk assessment for environmental chemicals has focused largely on elucidating mechanisms of toxicity, as discussed in other articles in this issue. However, there is interest in moving beyond hazard characterization to making more direct impacts on quantitative risk assessment (QRA) — i.e., the determination of toxicity values for setting exposure standards and cleanup values. We propose that the evolution of QRA of environmental chemicals in the post-genomic era will involve three, somewhat overlapping phases in which different types of approaches begin to mature. The initial focus (in Phase I) has been and continues to be on “augmentation” of weight of evidence — using genomic and related technologies qualitatively to increase the confidence in and scientific basis of the results of QRA. Efforts aimed towards “integration” of these data with traditional animal-based approaches, in particular quantitative predictors, or surrogates, for the in vivo toxicity data to which they have been anchored are just beginning to be explored now (in Phase II). In parallel, there is a recognized need for “expansion” of the use of established biomarkers of susceptibility or risk of human diseases and disorders for QRA, particularly for addressing the issues of cumulative assessment and population risk. Ultimately (in Phase III), substantial further advances could be realized by the development of novel molecular and pathway-based biomarkers and statistical and in silico models that build on anticipated progress in understanding the pathways of human diseases and disorders. Such efforts would facilitate a gradual “reorientation” of QRA towards approaches that more directly link environmental exposures to human outcomes
Reneker, Jeff; Lyons, Eric; Conant, Gavin C; Pires, J Chris; Freeling, Michael; Shyu, Chi-Ren; Korkin, Dmitry
Ultraconserved elements (UCEs) are DNA sequences that are 100% identical (no base substitutions, insertions, or deletions) and located in syntenic positions in at least two genomes. Although hundreds of UCEs have been found in animal genomes, little is known about the incidence of ultraconservation in plant genomes. Using an alignment-free information-retrieval approach, we have comprehensively identified all long identical multispecies elements (LIMEs), which include both syntenic and nonsyntenic regions, of at least 100 identical base pairs shared by at least two genomes. Among six animal genomes, we found the previously known syntenic UCEs as well as previously undescribed nonsyntenic elements. In contrast, among six plant genomes, we only found nonsyntenic LIMEs. LIMEs can also be classified as either simple (repetitive) or complex (nonrepetitive), they may occur in multiple copies in a genome, and they are often spread across multiple chromosomes. Although complex LIMEs were found in both animal and plant genomes, they differed significantly in their composition and copy number. Further analyses of plant LIMEs revealed their functional diversity, encompassing elements found near rRNA and enzyme-coding genes, as well as those found in transposons and noncoding DNA. We conclude that despite the common presence of LIMEs in both animal and plant lineages, the evolutionary processes involved in the creation and maintenance of these elements differ in the two groups and are likely attributable to several mechanisms, including transfer of genetic material from organellar to nuclear genomes, de novo sequence manufacturing, and purifying selection.
Röhl, Annika; Bockmayr, Alexander
Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.
Green, Eric D
Starting with the launch of the Human Genome Project in 1990, the past quarter-century has brought spectacular achievements in genomics that dramatically empower the study of human biology and disease. The human genomics enterprise is now in the midst of an important transition, as the growing foundation of genomic knowledge is being used by researchers and clinicians to tackle increasingly complex problems in biomedicine. Of particular prominence is the use of revolutionary new DNA sequencing technologies for generating prodigious amounts of DNA sequence data to elucidate the complexities of genome structure, function, and evolution, as well as to unravel the genomic bases of rare and common diseases. Together, these developments are ushering in the era of genomic medicine. Augmenting the advances in human genomics have been innovations in technologies for measuring environmental and lifestyle information, electronic health records, and data science; together, these provide opportunities of unprecedented scale and scope for investigating the underpinnings of health and disease. To capitalize on these opportunities, U.S. President Barack Obama recently announced a major new research endeavor - the U.S. Precision Medicine Initiative. This bold effort will be framed around several key aims, which include accelerating the use of genomically informed approaches to cancer care, making important policy and regulatory changes, and establishing a large research cohort of >1 million volunteers to facilitate precision medicine research. The latter will include making the partnership with all participants a centerpiece feature in the cohort's design and development. The Precision Medicine Initiative represents a broad-based research program that will allow new approaches for individualized medical care to be rigorously tested, so as to establish a new evidence base for advancing clinical practice and, eventually, human health.
Full Text Available Abstract Background The Order Rickettsiales includes important tick-borne pathogens, from Rickettsia rickettsii, which causes Rocky Mountain spotted fever, to Anaplasma marginale, the most prevalent vector-borne pathogen of cattle. Although most pathogens in this Order are transmitted by arthropod vectors, little is known about the microbial determinants of transmission. A. marginale provides unique tools for studying the determinants of transmission, with multiple strain sequences available that display distinct and reproducible transmission phenotypes. The closed core A. marginale genome suggests that any phenotypic differences are due to single nucleotide polymorphisms (SNPs. We combined DNA/RNA comparative genomic approaches using strains with different tick transmission phenotypes and identified genes that segregate with transmissibility. Results Comparison of seven strains with different transmission phenotypes generated a list of SNPs affecting 18 genes and nine promoters. Transcriptional analysis found two candidate genes downstream from promoter SNPs that were differentially transcribed. To corroborate the comparative genomics approach we used three RNA-seq platforms to analyze the transcriptomes from two A. marginale strains with different transmission phenotypes. RNA-seq analysis confirmed the comparative genomics data and found 10 additional genes whose transcription between strains with distinct transmission efficiencies was significantly different. Six regions of the genome that contained no annotation were found to be transcriptionally active, and two of these newly identified transcripts were differentially transcribed. Conclusions This approach identified 30 genes and two novel transcripts potentially involved in tick transmission. We describe the transcriptome of an obligate intracellular bacterium in depth, while employing massive parallel sequencing to dissect an important trait in bacterial pathogenesis.
Kadarmideen, Haja; Do, Duy Ngoc; Janss, Luc
Genomic selection is widely used in both animal and plant species, however, it is performed with no input from known genomic or biological role of genetic variants and therefore is a black box approach in a genomic era. This study investigated the role of different genomic regions and detected QTLs...... in their contribution to estimated genomic variances and in prediction of genomic breeding values by applying SNP annotation approaches to feed efficiency. Ensembl Variant Predictor (EVP) and Pig QTL database were used as the source of genomic annotation for 60K chip. Genomic prediction was performed using the Bayes...... classes. Predictive accuracy was 0.531, 0.532, 0.302, and 0.344 for DFI, RFI, ADG and BF, respectively. The contribution per SNP to total genomic variance was similar among annotated classes across different traits. Predictive performance of SNP classes did not significantly differ from randomized SNP...
Genomes of solid tumors are often highly rearranged and these rearrangements promote cancer progression through disruption of genes mediating immortality, survival, metastasis, and resistance to therapy...
Li, Qingjiao; Tjong, Harianto; Li, Xiao; Gong, Ke; Zhou, Xianghong Jasmine; Chiolo, Irene; Alber, Frank
Genome structures are dynamic and non-randomly organized in the nucleus of higher eukaryotes. To maximize the accuracy and coverage of three-dimensional genome structural models, it is important to integrate all available sources of experimental information about a genome's organization. It remains a major challenge to integrate such data from various complementary experimental methods. Here, we present an approach for data integration to determine a population of complete three-dimensional genome structures that are statistically consistent with data from both genome-wide chromosome conformation capture (Hi-C) and lamina-DamID experiments. Our structures resolve the genome at the resolution of topological domains, and reproduce simultaneously both sets of experimental data. Importantly, this data deconvolution framework allows for structural heterogeneity between cells, and hence accounts for the expected plasticity of genome structures. As a case study we choose Drosophila melanogaster embryonic cells, for which both data types are available. Our three-dimensional genome structures have strong predictive power for structural features not directly visible in the initial data sets, and reproduce experimental hallmarks of the D. melanogaster genome organization from independent and our own imaging experiments. Also they reveal a number of new insights about genome organization and its functional relevance, including the preferred locations of heterochromatic satellites of different chromosomes, and observations about homologous pairing that cannot be directly observed in the original Hi-C or lamina-DamID data. Our approach allows systematic integration of Hi-C and lamina-DamID data for complete three-dimensional genome structure calculation, while also explicitly considering genome structural variability.
the Fanconi Anemia Pathway- Regulated Nucleases in Genome Maintenance for Preventing Bone Marrow Failure and Cancer PRINCIPAL INVESTIGATOR...GRANT NUMBER 4. TITLE AND SUBTITLE A Biochemical Approach to Understanding the Fanconi Anemia Pathway-Regulated Nucleases in Genome Maintenance for...Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Fanconi anemia is the most prevalent inherited BMF syndromes, caused by mutations in
Cancela, M. Leonor; Bargelloni, Luca; Boudry, Pierre
. Improving state-of-the-art genomics research in various aquaculture systems, as well as its industrial applications, remains one of the major challenges in this area and should be the focus of well developed strategies to be implemented in the next generation of projects. This chapter will first provide...
Jimenez Infante, Francy M.
The SAR11 clade (Pelagibacterales) is a diverse group that forms a monophyletic clade within the Alphaproteobacteria, and constitutes up to one third of all prokaryotic cells in the photic zone of most oceans. Pelagibacterales are very abundant in the warm and highly saline surface waters of the Red Sea, raising the question of adaptive traits of SAR11 populations in this water body and warmer oceans through the world. In this study, two pure cultures were successfully obtained from surface waters on the Red Sea, one isolate of subgroup Ia and one of the previously uncultured SAR11 Ib lineage. The novel genomes were very similar to each other and to genomes of isolates of SAR11 subgroup Ia (Ia pan-genome), both in terms of gene content and synteny. Among the genes that were not present in the Ia pan-genome, 108 (RS39, Ia) and 151 genes (RS40, Ib) were strain-specific. Detailed analyses showed that only 51 (RS39, Ia) and 55 (RS40, Ib) of these strain-specific genes had not reported before on genome fragments of Pelagibacterales. Further analyses revealed the potential production of phosphonates by some SAR11 members and possible adaptations for oligotrophic life, including pentose sugar utilization and adhesion to marine particulate matter.
Jimenez Infante, Francy M.; Ngugi, David; Vinu, Manikandan; Blom, Jochen; Alam, Intikhab; Bajic, Vladimir B.; Stingl, Ulrich
The SAR11 clade (Pelagibacterales) is a diverse group that forms a monophyletic clade within the Alphaproteobacteria, and constitutes up to one third of all prokaryotic cells in the photic zone of most oceans. Pelagibacterales are very abundant in the warm and highly saline surface waters of the Red Sea, raising the question of adaptive traits of SAR11 populations in this water body and warmer oceans through the world. In this study, two pure cultures were successfully obtained from surface waters on the Red Sea, one isolate of subgroup Ia and one of the previously uncultured SAR11 Ib lineage. The novel genomes were very similar to each other and to genomes of isolates of SAR11 subgroup Ia (Ia pan-genome), both in terms of gene content and synteny. Among the genes that were not present in the Ia pan-genome, 108 (RS39, Ia) and 151 genes (RS40, Ib) were strain-specific. Detailed analyses showed that only 51 (RS39, Ia) and 55 (RS40, Ib) of these strain-specific genes had not reported before on genome fragments of Pelagibacterales. Further analyses revealed the potential production of phosphonates by some SAR11 members and possible adaptations for oligotrophic life, including pentose sugar utilization and adhesion to marine particulate matter.
Raghuraman, M K; Winzeler, E A; Collingwood, D; Hunt, S; Wodicka, L; Conway, A; Lockhart, D J; Davis, R W; Brewer, B J; Fangman, W L
Oligonucleotide microarrays were used to map the detailed topography of chromosome replication in the budding yeast Saccharomyces cerevisiae. The times of replication of thousands of sites across the genome were determined by hybridizing replicated and unreplicated DNAs, isolated at different times in S phase, to the microarrays. Origin activations take place continuously throughout S phase but with most firings near mid-S phase. Rates of replication fork movement vary greatly from region to region in the genome. The two ends of each of the 16 chromosomes are highly correlated in their times of replication. This microarray approach is readily applicable to other organisms, including humans.
Williams, Anna Marie; Liu, Yong; Regner, Kevin R; Jotterand, Fabrice; Liu, Pengyuan; Liang, Mingyu
Big data are a major driver in the development of precision medicine. Efficient analysis methods are needed to transform big data into clinically-actionable knowledge. To accomplish this, many researchers are turning toward machine learning (ML), an approach of artificial intelligence (AI) that utilizes modern algorithms to give computers the ability to learn. Much of the effort to advance ML for precision medicine has been focused on the development and implementation of algorithms and the generation of ever larger quantities of genomic sequence data and electronic health records. However, relevance and accuracy of the data are as important as quantity of data in the advancement of ML for precision medicine. For common diseases, physiological genomic readouts in disease-applicable tissues may be an effective surrogate to measure the effect of genetic and environmental factors and their interactions that underlie disease development and progression. Disease-applicable tissue may be difficult to obtain, but there are important exceptions such as kidney needle biopsy specimens. As AI continues to advance, new analytical approaches, including those that go beyond data correlation, need to be developed and ethical issues of AI need to be addressed. Physiological genomic readouts in disease-relevant tissues, combined with advanced AI, can be a powerful approach for precision medicine for common diseases.
Full Text Available We propose a two-stage penalized logistic regression approach to case-control genome-wide association studies. This approach consists of a screening stage and a selection stage. In the screening stage, main-effect and interaction-effect features are screened by using L1-penalized logistic like-lihoods. In the selection stage, the retained features are ranked by the logistic likelihood with the smoothly clipped absolute deviation (SCAD penalty (Fan and Li, 2001 and Jeffrey’s Prior penalty (Firth, 1993, a sequence of nested candidate models are formed, and the models are assessed by a family of extended Bayesian information criteria (J. Chen and Z. Chen, 2008. The proposed approach is applied to the analysis of the prostate cancer data of the Cancer Genetic Markers of Susceptibility (CGEMS project in the National Cancer Institute, USA. Simulation studies are carried out to compare the approach with the pair-wise multiple testing approach (Marchini et al. 2005 and the LASSO-patternsearch algorithm (Shi et al. 2007.
Feng, Bin; Nazarian, Rosalynn M.; Bosenberg, Marcus; Wu, Min; Scott, Kenneth L.; Kwong, Lawrence N.; Xiao, Yonghong; Cordon-Cardo, Carlos; Granter, Scott R.; Ramaswamy, Sridhar; Golub, Todd; Duncan, Lyn M.; Wagner, Stephan N.; Brennan, Cameron; Chin, Lynda
A cardinal feature of malignant melanoma is its metastatic propensity. An incomplete view of the genetic events driving metastatic progression has been a major barrier to rational development of effective therapeutics and prognostic diagnostics for melanoma patients. In this study, we conducted global genomic characterization of primary and metastatic melanomas to examine the genomic landscape associated with metastatic progression. In addition to uncovering three genomic subclasses of metastastic melanomas, we delineated 39 focal and recurrent regions of amplification and deletions, many of which encompassed resident genes that have not been implicated in cancer or metastasis. To identify progression-associated metastasis gene candidates, we applied a statistical approach, Integrative Genome Comparison (IGC), to define 32 genomic regions of interest that were significantly altered in metastatic relative to primary melanomas, encompassing 30 resident genes with statistically significant expression deregulation. Functional assays on a subset of these candidates, including MET, ASPM, AKAP9, IMP3, PRKCA, RPA3, and SCAP2, validated their pro-invasion activities in human melanoma cells. Validity of the IGC approach was further reinforced by tissue microarray analysis of Survivin showing significant increased protein expression in thick versus thin primary cutaneous melanomas, and a progression correlation with lymph node metastases. Together, these functional validation results and correlative analysis of human tissues support the thesis that integrated genomic and pathological analyses of staged melanomas provide a productive entry point for discovery of melanoma metastases genes. PMID:20520718
Oldfield, Lauren M; Grzesik, Peter; Voorhies, Alexander A; Alperovich, Nina; MacMath, Derek; Najera, Claudia D; Chandra, Diya Sabrina; Prasad, Sanjana; Noskov, Vladimir N; Montague, Michael G; Friedman, Robert M; Desai, Prashant J; Vashee, Sanjay
Here, we present a transformational approach to genome engineering of herpes simplex virus type 1 (HSV-1), which has a large DNA genome, using synthetic genomics tools. We believe this method will enable more rapid and complex modifications of HSV-1 and other large DNA viruses than previous technologies, facilitating many useful applications. Yeast transformation-associated recombination was used to clone 11 fragments comprising the HSV-1 strain KOS 152 kb genome. Using overlapping sequences between the adjacent pieces, we assembled the fragments into a complete virus genome in yeast, transferred it into an Escherichia coli host, and reconstituted infectious virus following transfection into mammalian cells. The virus derived from this yeast-assembled genome, KOS YA , replicated with kinetics similar to wild-type virus. We demonstrated the utility of this modular assembly technology by making numerous modifications to a single gene, making changes to two genes at the same time and, finally, generating individual and combinatorial deletions to a set of five conserved genes that encode virion structural proteins. While the ability to perform genome-wide editing through assembly methods in large DNA virus genomes raises dual-use concerns, we believe the incremental risks are outweighed by potential benefits. These include enhanced functional studies, generation of oncolytic virus vectors, development of delivery platforms of genes for vaccines or therapy, as well as more rapid development of countermeasures against potential biothreats.
Henrik Bjørn Nielsen
Full Text Available The systematic comparison of transcriptional responses of organisms is a powerful tool in functional genomics. For example, mutants may be characterized by comparing their transcript profiles to those obtained in other experiments querying the effects on gene expression of many experimental factors including treatments, mutations and pathogen infections. Similarly, drugs may be discovered by the relationship between the transcript profiles effectuated or impacted by a candidate drug and by the target disease. The integration of such data enables systems biology to predict the interplay between experimental factors affecting a biological system. Unfortunately, direct comparisons of gene expression profiles obtained in independent, publicly available microarray experiments are typically compromised by substantial, experiment-specific biases. Here we suggest a novel yet conceptually simple approach for deriving 'Functional Association(s by Response Overlap' (FARO between microarray gene expression studies. The transcriptional response is defined by the set of differentially expressed genes independent from the magnitude or direction of the change. This approach overcomes the limited comparability between studies that is typical for methods that rely on correlation in gene expression. We apply FARO to a compendium of 242 diverse Arabidopsis microarray experimental factors, including phyto-hormones, stresses and pathogens, growth conditions/stages, tissue types and mutants. We also use FARO to confirm and further delineate the functions of Arabidopsis MAP kinase 4 in disease and stress responses. Furthermore, we find that a large, well-defined set of genes responds in opposing directions to different stress conditions and predict the effects of different stress combinations. This demonstrates the usefulness of our approach for exploiting public microarray data to derive biologically meaningful associations between experimental factors. Finally, our
Fornace, Jr, A J
Abstract for final report for project entitled A functional genomics approach using radiation-induced changes in gene expression to study low dose radiation effects in vitro and in vivo which has been supported by the DOE Low Dose Radiation Research Program for approximately 7 years. This project has encompassed two sequential awards, ER62683 and then ER63308, in the Gene Response Section in the Center for Cancer Research at the National Cancer Institute. The project was temporarily suspended during the relocation of the Principal Investigators laboratory to the Dept. of Genetics and Complex Diseases at Harvard School of Public Health at the end of 2004. Remaining support for the final year was transferred to this new site later in 2005 and was assigned the DOE Award Number ER64065. The major aims of this project have been 1) to characterize changes in gene expression in response to low-dose radiation responses; this includes responses in human cells lines, peripheral blood lymphocytes (PBL), and in vivo after human or murine exposures, as well as the effect of dose-rate on gene responses; 2) to characterize changes in gene expression that may be involved in bystander effects, such as may be mediated by cytokines and other intercellular signaling proteins; and 3) to characterize responses in transgenic mouse models with relevance to genomic stability. A variety of approaches have been used to study transcriptional events including microarray hybridization, quantitative single-probe hybridization which was developed in this laboratory, quantitative RT-PCR, and promoter microarray analysis using genomic regulatory motifs. Considering the frequent responsiveness of genes encoding cytokines and related signaling proteins that can affect cellular metabolism, initial efforts were initiated to study radiation responses at the metabolomic level and to correlate with radiation-responsive gene expression. Productivity includes twenty-four published and in press manuscripts
Sun, Chen; Hu, Zhiqiang; Zheng, Tianqing; Lu, Kuangchen; Zhao, Yue; Wang, Wensheng; Shi, Jianxin; Wang, Chunchao; Lu, Jinyuan; Zhang, Dabing; Li, Zhikang; Wei, Chaochun
A pan-genome is the union of the gene sets of all the individuals of a clade or a species and it provides a new dimension of genome complexity with the presence/absence variations (PAVs) of genes among these genomes. With the progress of sequencing technologies, pan-genome study is becoming affordable for eukaryotes with large-sized genomes. The Asian cultivated rice, Oryza sativa L., is one of the major food sources for the world and a model organism in plant biology. Recently, the 3000 Rice Genome Project (3K RGP) sequenced more than 3000 rice genomes with a mean sequencing depth of 14.3×, which provided a tremendous resource for rice research. In this paper, we present a genome browser, Rice Pan-genome Browser (RPAN), as a tool to search and visualize the rice pan-genome derived from 3K RGP. RPAN contains a database of the basic information of 3010 rice accessions, including genomic sequences, gene annotations, PAV information and gene expression data of the rice pan-genome. At least 12 000 novel genes absent in the reference genome were included. RPAN also provides multiple search and visualization functions. RPAN can be a rich resource for rice biology and rice breeding. It is available at http://cgm.sjtu.edu.cn/3kricedb/ or http://www.rmbreeding.cn/pan3k. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
Evans, Teri; Johnson, Andrew D; Loose, Matthew
Large repeat rich genomes present challenges for assembly using short read technologies. The 32 Gb axolotl genome is estimated to contain ~19 Gb of repetitive DNA making an assembly from short reads alone effectively impossible. Indeed, this model species has been sequenced to 20× coverage but the reads could not be conventionally assembled. Using an alternative strategy, we have assembled subsets of these reads into scaffolds describing over 19,000 gene models. We call this method Virtual Genome Walking as it locally assembles whole genome reads based on a reference transcriptome, identifying exons and iteratively extending them into surrounding genomic sequence. These assemblies are then linked and refined to generate gene models including upstream and downstream genomic, and intronic, sequence. Our assemblies are validated by comparison with previously published axolotl bacterial artificial chromosome (BAC) sequences. Our analyses of axolotl intron length, intron-exon structure, repeat content and synteny provide novel insights into the genic structure of this model species. This resource will enable new experimental approaches in axolotl, such as ChIP-Seq and CRISPR and aid in future whole genome sequencing efforts. The assembled sequences and annotations presented here are freely available for download from https://tinyurl.com/y8gydc6n . The software pipeline is available from https://github.com/LooseLab/iterassemble .
Background The ability to transport and store DNA at room temperature in low volumes has the advantage of optimising cost, time and storage space. Blood spots on adapted filter papers are popular for this, with FTA (Flinders Technology Associates) Whatman™TM technology being one of the most recent. Plant material, plasmids, viral particles, bacteria and animal blood have been stored and transported successfully using this technology, however the method of porcine DNA extraction from FTA Whatman™TM cards is a relatively new approach, allowing nucleic acids to be ready for downstream applications such as PCR, whole genome amplification, sequencing and subsequent application to single nucleotide polymorphism microarrays has hitherto been under-explored. Findings DNA was extracted from FTA Whatman™TM cards (following adaptations of the manufacturer’s instructions), whole genome amplified and subsequently analysed to validate the integrity of the DNA for downstream SNP analysis. DNA was successfully extracted from 288/288 samples and amplified by WGA. Allele dropout post WGA, was observed in less than 2% of samples and there was no clear evidence of amplification bias nor contamination. Acceptable call rates on porcine SNP chips were also achieved using DNA extracted and amplified in this way. Conclusions DNA extracted from FTA Whatman cards is of a high enough quality and quantity following whole genomic amplification to perform meaningful SNP chip studies. PMID:22974252
M Muksitul Haque
Full Text Available Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs. Different environmental toxicants have been shown to promote exposure (i.e., toxicant specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (<3 CpG / 100bp termed CpG deserts and a number of unique DNA sequence motifs. The rat genome was annotated for these and additional relevant features. The objective of the current study was to use a machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT and methoxychlor (MXC exposure lineage F3 generation. Analysis of this positive validation
Douglas L. Brutlag Nancy Ryan Gray
This Gordon conference will cover the areas of structural, functional and evolutionary genomics. It will take a systematic approach to genomics, examining the evolution of proteins, protein functional sites, protein-protein interactions, regulatory networks, and metabolic networks. Emphasis will be placed on what we can learn from comparative genomics and entire genomes and proteomes.
Full Text Available Cotton is one of the most important economic crops and the primary source of natural fiber and is an important protein source for animal feed. The complete nuclear and chloroplast (cp genome sequences of G. raimondii are already available but not mitochondria. Here, we assembled the complete mitochondrial (mt DNA sequence of G. raimondii into a circular genome of length of 676,078 bp and performed comparative analyses with other higher plants. The genome contains 39 protein-coding genes, 6 rRNA genes, and 25 tRNA genes. We also identified four larger repeats (63.9 kb, 10.6 kb, 9.1 kb, and 2.5 kb in this mt genome, which may be active in intramolecular recombination in the evolution of cotton. Strikingly, nearly all of the G. raimondii mt genome has been transferred to nucleus on Chr1, and the transfer event must be very recent. Phylogenetic analysis reveals that G. raimondii, as a member of Malvaceae, is much closer to another cotton (G. barbadense than other rosids, and the clade formed by two Gossypium species is sister to Brassicales. The G. raimondii mt genome may provide a crucial foundation for evolutionary analysis, molecular biology, and cytoplasmic male sterility in cotton and other higher plants.
Sverdlov Alexander V
Full Text Available Abstract Background The availability of multiple, essentially complete genome sequences of prokaryotes and eukaryotes spurred both the demand and the opportunity for the construction of an evolutionary classification of genes from these genomes. Such a classification system based on orthologous relationships between genes appears to be a natural framework for comparative genomics and should facilitate both functional annotation of genomes and large-scale evolutionary studies. Results We describe here a major update of the previously developed system for delineation of Clusters of Orthologous Groups of proteins (COGs from the sequenced genomes of prokaryotes and unicellular eukaryotes and the construction of clusters of predicted orthologs for 7 eukaryotic genomes, which we named KOGs after eukaryotic orthologous groups. The COG collection currently consists of 138,458 proteins, which form 4873 COGs and comprise 75% of the 185,505 (predicted proteins encoded in 66 genomes of unicellular organisms. The eukaryotic orthologous groups (KOGs include proteins from 7 eukaryotic genomes: three animals (the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster and Homo sapiens, one plant, Arabidopsis thaliana, two fungi (Saccharomyces cerevisiae and Schizosaccharomyces pombe, and the intracellular microsporidian parasite Encephalitozoon cuniculi. The current KOG set consists of 4852 clusters of orthologs, which include 59,838 proteins, or ~54% of the analyzed eukaryotic 110,655 gene products. Compared to the coverage of the prokaryotic genomes with COGs, a considerably smaller fraction of eukaryotic genes could be included into the KOGs; addition of new eukaryotic genomes is expected to result in substantial increase in the coverage of eukaryotic genomes with KOGs. Examination of the phyletic patterns of KOGs reveals a conserved core represented in all analyzed species and consisting of ~20% of the KOG set. This conserved portion of the
Adebamowo, Sally N; Francis, Veronica; Tambo, Ernest; Diallo, Seybou H; Landouré, Guida; Nembaware, Victoria; Dareng, Eileen; Muhamed, Babu; Odutola, Michael; Akeredolu, Teniola; Nerima, Barbara; Ozumba, Petronilla J; Mbhele, Slee; Ghanash, Anita; Wachinou, Ablo P; Ngomi, Nicholas
There is exponential growth in the interest and implementation of genomics research in Africa. This growth has been facilitated by the Human Hereditary and Health in Africa (H3Africa) initiative, which aims to promote a contemporary research approach to the study of genomics and environmental determinants of common diseases in African populations. The purpose of this article is to describe important challenges affecting genomics research implementation in Africa. The observations, challenges and recommendations presented in this article were obtained through discussions by African scientists at teleconferences and face-to-face meetings, seminars at consortium conferences and in-depth individual discussions. Challenges affecting genomics research implementation in Africa, which are related to limited resources include ill-equipped facilities, poor accessibility to research centers, lack of expertise and an enabling environment for research activities in local hospitals. Challenges related to the research study include delayed funding, extensive procedures and interventions requiring multiple visits, delays setting up research teams and insufficient staff training, language barriers and an underappreciation of cultural norms. While many African countries are struggling to initiate genomics projects, others have set up genomics research facilities that meet international standards. The lessons learned in implementing successful genomics projects in Africa are recommended as strategies to overcome these challenges. These recommendations may guide the development and application of new research programs in low-resource settings.
Full Text Available Similar to other malignancies, urothelial carcinoma (UC is characterized by specific recurrent chromosomal aberrations and gene mutations. However, the interconnection between specific genomic alterations, and how patterns of chromosomal alterations adhere to different molecular subgroups of UC, is less clear. We applied tiling resolution array CGH to 146 cases of UC and identified a number of regions harboring recurrent focal genomic amplifications and deletions. Several potential oncogenes were included in the amplified regions, including known oncogenes like E2F3, CCND1, and CCNE1, as well as new candidate genes, such as SETDB1 (1q21, and BCL2L1 (20q11. We next combined genome profiling with global gene expression, gene mutation, and protein expression data and identified two major genomic circuits operating in urothelial carcinoma. The first circuit was characterized by FGFR3 alterations, overexpression of CCND1, and 9q and CDKN2A deletions. The second circuit was defined by E3F3 amplifications and RB1 deletions, as well as gains of 5p, deletions at PTEN and 2q36, 16q, 20q, and elevated CDKN2A levels. TP53/MDM2 alterations were common for advanced tumors within the two circuits. Our data also suggest a possible RAS/RAF circuit. The tumors with worst prognosis showed a gene expression profile that indicated a keratinized phenotype. Taken together, our integrative approach revealed at least two separate networks of genomic alterations linked to the molecular diversity seen in UC, and that these circuits may reflect distinct pathways of tumor development.
Eng, G; Chen, A; Vess, T; Ginsburg, G S
The addition of genomic information to our understanding of oral disease is driving important changes in oral health care. It is anticipated that genome-derived information will promote a deeper understanding of disease etiology and permit earlier diagnosis, allowing for preventative measures prior to disease onset rather than treatment that attempts to repair the diseased state. Advances in genome technologies have fueled expectations for this proactive healthcare approach. Application of genomic testing is expanding and has already begun to find its way into the practice of clinical dentistry. To take full advantage of the information and technologies currently available, it is vital that dental care providers, consumers, and policymakers be aware of genomic approaches to understanding of oral diseases and the application of genomic testing to disease diagnosis and treatment. Ethical, legal, clinical, and educational initiatives are also required to responsibly incorporate genomic information into the practice of dentistry. This article provides an overview of the application of genomic technologies to oral health care and introduces issues that require consideration if we are to realize the full potential of genomics to enable the practice of personalized dental medicine. © 2011 John Wiley & Sons A/S.
Staats, Martijn; Erkens, Roy H J; van de Vossenberg, Bart; Wieringa, Jan J; Kraaijeveld, Ken; Stielow, Benjamin; Geml, József; Richardson, James E; Bakker, Freek T
Unlocking the vast genomic diversity stored in natural history collections would create unprecedented opportunities for genome-scale evolutionary, phylogenetic, domestication and population genomic studies. Many researchers have been discouraged from using historical specimens in molecular studies because of both generally limited success of DNA extraction and the challenges associated with PCR-amplifying highly degraded DNA. In today's next-generation sequencing (NGS) world, opportunities and prospects for historical DNA have changed dramatically, as most NGS methods are actually designed for taking short fragmented DNA molecules as templates. Here we show that using a standard multiplex and paired-end Illumina sequencing approach, genome-scale sequence data can be generated reliably from dry-preserved plant, fungal and insect specimens collected up to 115 years ago, and with minimal destructive sampling. Using a reference-based assembly approach, we were able to produce the entire nuclear genome of a 43-year-old Arabidopsis thaliana (Brassicaceae) herbarium specimen with high and uniform sequence coverage. Nuclear genome sequences of three fungal specimens of 22-82 years of age (Agaricus bisporus, Laccaria bicolor, Pleurotus ostreatus) were generated with 81.4-97.9% exome coverage. Complete organellar genome sequences were assembled for all specimens. Using de novo assembly we retrieved between 16.2-71.0% of coding sequence regions, and hence remain somewhat cautious about prospects for de novo genome assembly from historical specimens. Non-target sequence contaminations were observed in 2 of our insect museum specimens. We anticipate that future museum genomics projects will perhaps not generate entire genome sequences in all cases (our specimens contained relatively small and low-complexity genomes), but at least generating vital comparative genomic data for testing (phylo)genetic, demographic and genetic hypotheses, that become increasingly more horizontal
Li, Yongle; Ruperao, Pradeep; Batley, Jacqueline; Edwards, David; Khan, Tanveer; Colmer, Timothy D; Pang, Jiayin; Siddique, Kadambot H M; Sutton, Tim
Drought tolerance is a complex trait that involves numerous genes. Identifying key causal genes or linked molecular markers can facilitate the fast development of drought tolerant varieties. Using a whole-genome resequencing approach, we sequenced 132 chickpea varieties and advanced breeding lines and found more than 144,000 single nucleotide polymorphisms (SNPs). We measured 13 yield and yield-related traits in three drought-prone environments of Western Australia. The genotypic effects were significant for all traits, and many traits showed highly significant correlations, ranging from 0.83 between grain yield and biomass to -0.67 between seed weight and seed emergence rate. To identify candidate genes, the SNP and trait data were incorporated into the SUPER genome-wide association study (GWAS) model, a modified version of the linear mixed model. We found that several SNPs from auxin-related genes, including auxin efflux carrier protein (PIN3), p-glycoprotein, and nodulin MtN21/EamA-like transporter, were significantly associated with yield and yield-related traits under drought-prone environments. We identified four genetic regions containing SNPs significantly associated with several different traits, which was an indication of pleiotropic effects. We also investigated the possibility of incorporating the GWAS results into a genomic selection (GS) model, which is another approach to deal with complex traits. Compared to using all SNPs, application of the GS model using subsets of SNPs significantly associated with the traits under investigation increased the prediction accuracies of three yield and yield-related traits by more than twofold. This has important implication for implementing GS in plant breeding programs.
Ma, Peng-Fei; Guo, Zhen-Hua; Li, De-Zhu
Compared to their counterparts in animals, the mitochondrial (mt) genomes of angiosperms exhibit a number of unique features. However, unravelling their evolution is hindered by the few completed genomes, of which are essentially Sanger sequenced. While next-generation sequencing technologies have revolutionized chloroplast genome sequencing, they are just beginning to be applied to angiosperm mt genomes. Chloroplast genomes of grasses (Poaceae) have undergone episodic evolution and the evolutionary rate was suggested to be correlated between chloroplast and mt genomes in Poaceae. It is interesting to investigate whether correlated rate change also occurred in grass mt genomes as expected under lineage effects. A time-calibrated phylogenetic tree is needed to examine rate change. We determined a largely completed mt genome from a bamboo, Ferrocalamus rimosivaginus (Poaceae), through Illumina sequencing of total DNA. With combination of de novo and reference-guided assembly, 39.5-fold coverage Illumina reads were finally assembled into scaffolds totalling 432,839 bp. The assembled genome contains nearly the same genes as the completed mt genomes in Poaceae. For examining evolutionary rate in grass mt genomes, we reconstructed a phylogenetic tree including 22 taxa based on 31 mt genes. The topology of the well-resolved tree was almost identical to that inferred from chloroplast genome with only minor difference. The inconsistency possibly derived from long branch attraction in mtDNA tree. By calculating absolute substitution rates, we found significant rate change (∼4-fold) in mt genome before and after the diversification of Poaceae both in synonymous and nonsynonymous terms. Furthermore, the rate change was correlated with that of chloroplast genomes in grasses. Our result demonstrates that it is a rapid and efficient approach to obtain angiosperm mt genome sequences using Illumina sequencing technology. The parallel episodic evolution of mt and chloroplast
Okamoto, Nobuhiko; Watanabe, Miki; Naruto, Takuya; Matsuda, Keiko; Kohmoto, Tomohiro; Saito, Masako; Masuda, Kiyoshi; Imoto, Issei
Cabezas syndrome is a syndromic form of X-linked intellectual disability primarily characterized by a short stature, hypogonadism and abnormal gait, with other variable features resulting from mutations in the CUL4B gene. Here, we report a clinically undiagnosed 5-year-old male with severe intellectual disability. A genome-first approach using targeted exome sequencing identified a novel nonsense mutation [NM_003588.3:c.2698G>T, p.(Glu900*)] in the last coding exon of CUL4B , thus diagnosing this patient with Cabezas syndrome.
Algorithmic methods for gene prediction have been developed and successfully applied to many different prokaryotic genome sequences. As the set of genes in a particular genome is not homogeneous with respect to DNA sequence composition features, the GeneMark.hmm program utilizes two Markov models representing distinct classes of protein coding genes denoted "typical" and "atypical". Atypical genes are those whose DNA features deviate significantly from those classified as typical and they represent approximately 10% of any given genome. In addition to the inherent interest of more accurately predicting genes, the atypical status of these genes may also reflect their separate evolutionary ancestry from other genes in that genome. We hypothesize that atypical genes are largely comprised of those genes that have been relatively recently acquired through lateral gene transfer (LGT). If so, what fraction of atypical genes are such bona fide LGTs? We have made atypical gene predictions for all fully completed prokaryotic genomes; we have been able to compare these results to other "surrogate" methods of LGT prediction.
Jimenez-Infante, Francy; Ngugi, David Kamanda; Vinu, Manikandan; Blom, Jochen; Alam, Intikhab; Bajic, Vladimir B; Stingl, Ulrich
The SAR11 clade (Pelagibacterales) is a diverse group that forms a monophyletic clade within the Alphaproteobacteria, and constitutes up to one third of all prokaryotic cells in the photic zone of most oceans. Pelagibacterales are very abundant in the warm and highly saline surface waters of the Red Sea, raising the question of adaptive traits of SAR11 populations in this water body and warmer oceans through the world. In this study, two pure cultures were successfully obtained from surface waters on the Red Sea: one isolate of subgroup Ia and one of the previously uncultured SAR11 Ib lineage. The novel genomes were very similar to each other and to genomes of isolates of SAR11 subgroup Ia (Ia pan-genome), both in terms of gene content and synteny. Among the genes that were not present in the Ia pan-genome, 108 (RS39, Ia) and 151 genes (RS40, Ib) were strain specific. Detailed analyses showed that only 51 (RS39, Ia) and 55 (RS40, Ib) of these strain-specific genes had not reported before on genome fragments of Pelagibacterales. Further analyses revealed the potential production of phosphonates by some SAR11 members and possible adaptations for oligotrophic life, including pentose sugar utilization and adhesion to marine particulate matter. © FEMS 2017. All rights reserved. For permissions, please e-mail: email@example.com.
König, Stefanie; Romoth, Lars W; Gerischer, Lizzy; Stanke, Mario
As the tree of life is populated with sequenced genomes ever more densely, the new challenge is the accurate and consistent annotation of entire clades of genomes. We address this problem with a new approach to comparative gene finding that takes a multiple genome alignment of closely related species and simultaneously predicts the location and structure of protein-coding genes in all input genomes, thereby exploiting negative selection and sequence conservation. The model prefers potential gene structures in the different genomes that are in agreement with each other, or-if not-where the exon gains and losses are plausible given the species tree. We formulate the multi-species gene finding problem as a binary labeling problem on a graph. The resulting optimization problem is NP hard, but can be efficiently approximated using a subgradient-based dual decomposition approach. The proposed method was tested on whole-genome alignments of 12 vertebrate and 12 Drosophila species. The accuracy was evaluated for human, mouse and Drosophila melanogaster and compared to competing methods. Results suggest that our method is well-suited for annotation of (a large number of) genomes of closely related species within a clade, in particular, when RNA-Seq data are available for many of the genomes. The transfer of existing annotations from one genome to another via the genome alignment is more accurate than previous approaches that are based on protein-spliced alignments, when the genomes are at close to medium distances. The method is implemented in C ++ as part of Augustus and available open source at http://bioinf.uni-greifswald.de/augustus/ CONTACT: firstname.lastname@example.org or email@example.comSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: firstname.lastname@example.org.
Pfeifer, Bastian; Wittelsbürger, Ulrich; Ramos-Onsins, Sebastian E.; Lercher, Martin J.
Although many computer programs can perform population genetics calculations, they are typically limited in the analyses and data input formats they offer; few applications can process the large data sets produced by whole-genome resequencing projects. Furthermore, there is no coherent framework for the easy integration of new statistics into existing pipelines, hindering the development and application of new population genetics and genomics approaches. Here, we present PopGenome, a populati...
Lee, Myoungsook; Kwon, Dae Young; Kim, Myung-Sunny; Choi, Chong Ran; Park, Mi-Young; Kim, Ae-Jung
This is the first study to identify common genetic factors associated with the basal metabolic rate (BMR) and body mass index (BMI) in obese Korean women including overweight. This will be a basic study for future research of obese gene-BMR interaction. The experimental design was 2 by 2 with variables of BMR and BMI. A genome-wide association study (GWAS) of single nucleotide polymorphisms (SNPs) was conducted in the overweight and obesity (BMI > 23 kg/m(2)) compared to the normality, and in women with low BMR (BMR. A total of 140 SNPs reached formal genome-wide statistical significance in this study (P BMR (rs10786764; P = 8.0 × 10(-7), rs1040675; 2.3 × 10(-6)) and BMI (rs10786764; P = 2.5 × 10(-5), rs10786764; 6.57 × 10(-5)). The other genes related to BMI (HSD52, TMA16, MARCH1, NRG1, NRXN3, and STK4) yielded P BMR and BMI, including NRG3, OR8U8, BCL2L2-PABPN1, PABPN1, and SLC22A17 were identified in obese Korean women (P BMR- and BMI-related genes using GWAS. Although most of these newly established loci were not previously associated with obesity, they may provide new insights into body weight regulation. Our findings of five common genes associated with BMR and BMI in Koreans will serve as a reference for replication and validation of future studies on the metabolic rate.
Burgess-Herbert, Sarah L.; Euling, Susan Y.
A critical challenge for environmental chemical risk assessment is the characterization and reduction of uncertainties introduced when extrapolating inferences from one species to another. The purpose of this article is to explore the challenges, opportunities, and research needs surrounding the issue of how genomics data and computational and systems level approaches can be applied to inform differences in response to environmental chemical exposure across species. We propose that the data, tools, and evolutionary framework of comparative genomics be adapted to inform interspecies differences in chemical mechanisms of action. We compare and contrast existing approaches, from disciplines as varied as evolutionary biology, systems biology, mathematics, and computer science, that can be used, modified, and combined in new ways to discover and characterize interspecies differences in chemical mechanism of action which, in turn, can be explored for application to risk assessment. We consider how genetic, protein, pathway, and network information can be interrogated from an evolutionary biology perspective to effectively characterize variations in biological processes of toxicological relevance among organisms. We conclude that comparative genomics approaches show promise for characterizing interspecies differences in mechanisms of action, and further, for improving our understanding of the uncertainties inherent in extrapolating inferences across species in both ecological and human health risk assessment. To achieve long-term relevance and consistent use in environmental chemical risk assessment, improved bioinformatics tools, computational methods robust to data gaps, and quantitative approaches for conducting extrapolations across species are critically needed. Specific areas ripe for research to address these needs are recommended
Palacios-Flores, Kim; García-Sotelo, Jair; Castillo, Alejandra; Uribe, Carina; Aguilar, Luis; Morales, Lucía; Gómez-Romero, Laura; Reyes, José; Garciarubio, Alejandro; Boege, Margareta; Dávila, Guillermo
We present a conceptually simple, sensitive, precise, and essentially nonstatistical solution for the analysis of genome variation in haploid organisms. The generation of a Perfect Match Genomic Landscape (PMGL), which computes intergenome identity with single nucleotide resolution, reveals signatures of variation wherever a query genome differs from a reference genome. Such signatures encode the precise location of different types of variants, including single nucleotide variants, deletions, insertions, and amplifications, effectively introducing the concept of a general signature of variation. The precise nature of variants is then resolved through the generation of targeted alignments between specific sets of sequence reads and known regions of the reference genome. Thus, the perfect match logic decouples the identification of the location of variants from the characterization of their nature, providing a unified framework for the detection of genome variation. We assessed the performance of the PMGL strategy via simulation experiments. We determined the variation profiles of natural genomes and of a synthetic chromosome, both in the context of haploid yeast strains. Our approach uncovered variants that have previously escaped detection. Moreover, our strategy is ideally suited for further refining high-quality reference genomes. The source codes for the automated PMGL pipeline have been deposited in a public repository. Copyright © 2018 by the Genetics Society of America.
Lee, Jun-Yeong; Han, Geon Goo; Choi, Jaeyun; Jin, Gwi-Deuk; Kang, Sang-Kee; Chae, Byung Jo; Kim, Eun Bae; Choi, Yun-Jaie
After the introduction of a ban on the use of antibiotic growth promoters (AGPs) for livestock, reuterin-producing Lactobacillus reuteri is getting attention as an alternative to AGPs. In this study, we investigated genetic features of L. reuteri associated with host specificity and antipathogenic effect. We isolated 104 L. reuteri strains from porcine feces, and 16 strains, composed of eight strains exhibiting the higher antipathogenic effect (group HS) and eight strains exhibiting the lower effect (group LS), were selected for genomic comparison. We generated draft genomes of the 16 isolates and investigated their pan-genome together with the 26 National Center for Biotechnology Information-registered genomes. L. reuteri genomes organized six clades with multi-locus sequence analysis, and the clade IV includes the 16 isolates. First, we identified six L. reuteri clade IV-specific genes including three hypothetical protein-coding genes. The three annotated genes encode transposases and cell surface proteins, indicating that these genes are the result of adaptation to the host gastrointestinal epithelia and that these host-specific traits were acquired by horizontal gene transfer. We also identified differences between groups HS and LS in the pdu-cbi-cob-hem gene cluster, which is essential for reuterin and cobalamin synthesis, and six genes specific to group HS are revealed. While the strains of group HS possessed all genes of this cluster, LS strains have lost many genes of the cluster. This study provides a deeper understanding of the relationship between probiotic properties and genomic features of L. reuteri.
Vilella Albert J
Full Text Available Abstract Background DNA sequence polymorphisms analysis can provide valuable information on the evolutionary forces shaping nucleotide variation, and provides an insight into the functional significance of genomic regions. The recent ongoing genome projects will radically improve our capabilities to detect specific genomic regions shaped by natural selection. Current available methods and software, however, are unsatisfactory for such genome-wide analysis. Results We have developed methods for the analysis of DNA sequence polymorphisms at the genome-wide scale. These methods, which have been tested on a coalescent-simulated and actual data files from mouse and human, have been implemented in the VariScan software package version 2.0. Additionally, we have also incorporated a graphical-user interface. The main features of this software are: i exhaustive population-genetic analyses including those based on the coalescent theory; ii analysis adapted to the shallow data generated by the high-throughput genome projects; iii use of genome annotations to conduct a comprehensive analyses separately for different functional regions; iv identification of relevant genomic regions by the sliding-window and wavelet-multiresolution approaches; v visualization of the results integrated with current genome annotations in commonly available genome browsers. Conclusion VariScan is a powerful and flexible suite of software for the analysis of DNA polymorphisms. The current version implements new algorithms, methods, and capabilities, providing an important tool for an exhaustive exploratory analysis of genome-wide DNA polymorphism data.
Wang, Jiawei; Zhai, Ying; Zhu, Dongzi; Liu, Weizhen; Pappu, Hanu R; Liu, Qingzhong
Prunus necrotic ringspot virus (PNRSV) causes yield loss in most cultivated stone fruits, including sweet cherry. Using a small RNA deep-sequencing approach combined with end-genome sequence cloning, we identified the complete genomes of all three PNRSV strands from PNRSV-infected sweet cherry trees and compared them with those of two previously reported isolates. Copyright © 2018 Wang et al.
Jolly Emmitt R
Full Text Available Abstract Background A major challenge in computational genomics is the development of methodologies that allow accurate genome-wide prediction of the regulatory targets of a transcription factor. We present a method for target identification that combines experimental characterization of binding requirements with computational genomic analysis. Results Our method identified potential target genes of the transcription factor Ndt80, a key transcriptional regulator involved in yeast sporulation, using the combined information of binding affinity, positional distribution, and conservation of the binding sites across multiple species. We have also developed a mathematical approach to compute the false positive rate and the total number of targets in the genome based on the multiple selection criteria. Conclusion We have shown that combining biochemical characterization and computational genomic analysis leads to accurate identification of the genome-wide targets of a transcription factor. The method can be extended to other transcription factors and can complement other genomic approaches to transcriptional regulation.
Nielsen, H Bjørn; Almeida, Mathieu; Juncker, Agnieszka Sierakowska; Rasmussen, Simon; Li, Junhua; Sunagawa, Shinichi; Plichta, Damian R; Gautier, Laurent; Pedersen, Anders G; Le Chatelier, Emmanuelle; Pelletier, Eric; Bonde, Ida; Nielsen, Trine; Manichanh, Chaysavanh; Arumugam, Manimozhiyan; Batto, Jean-Michel; Quintanilha Dos Santos, Marcelo B; Blom, Nikolaj; Borruel, Natalia; Burgdorf, Kristoffer S; Boumezbeur, Fouad; Casellas, Francesc; Doré, Joël; Dworzynski, Piotr; Guarner, Francisco; Hansen, Torben; Hildebrand, Falk; Kaas, Rolf S; Kennedy, Sean; Kristiansen, Karsten; Kultima, Jens Roat; Léonard, Pierre; Levenez, Florence; Lund, Ole; Moumen, Bouziane; Le Paslier, Denis; Pons, Nicolas; Pedersen, Oluf; Prifti, Edi; Qin, Junjie; Raes, Jeroen; Sørensen, Søren; Tap, Julien; Tims, Sebastian; Ussery, David W; Yamada, Takuji; Renault, Pierre; Sicheritz-Ponten, Thomas; Bork, Peer; Wang, Jun; Brunak, Søren; Ehrlich, S Dusko
Most current approaches for analyzing metagenomic data rely on comparisons to reference genomes, but the microbial diversity of many environments extends far beyond what is covered by reference databases. De novo segregation of complex metagenomic data into specific biological entities, such as particular bacterial strains or viruses, remains a largely unsolved problem. Here we present a method, based on binning co-abundant genes across a series of metagenomic samples, that enables comprehensive discovery of new microbial organisms, viruses and co-inherited genetic entities and aids assembly of microbial genomes without the need for reference sequences. We demonstrate the method on data from 396 human gut microbiome samples and identify 7,381 co-abundance gene groups (CAGs), including 741 metagenomic species (MGS). We use these to assemble 238 high-quality microbial genomes and identify affiliations between MGS and hundreds of viruses or genetic entities. Our method provides the means for comprehensive profiling of the diversity within complex metagenomic samples.
Barrett Daniel R
Full Text Available Abstract Background Accurate evaluation of the quality of genomic or proteomic data and computational methods is vital to our ability to use them for formulating novel biological hypotheses and directing further experiments. There is currently no standard approach to evaluation in functional genomics. Our analysis of existing approaches shows that they are inconsistent and contain substantial functional biases that render the resulting evaluations misleading both quantitatively and qualitatively. These problems make it essentially impossible to compare computational methods or large-scale experimental datasets and also result in conclusions that generalize poorly in most biological applications. Results We reveal issues with current evaluation methods here and suggest new approaches to evaluation that facilitate accurate and representative characterization of genomic methods and data. Specifically, we describe a functional genomics gold standard based on curation by expert biologists and demonstrate its use as an effective means of evaluation of genomic approaches. Our evaluation framework and gold standard are freely available to the community through our website. Conclusion Proper methods for evaluating genomic data and computational approaches will determine how much we, as a community, are able to learn from the wealth of available data. We propose one possible solution to this problem here but emphasize that this topic warrants broader community discussion.
Facey, Paul D; Méric, Guillaume; Hitchings, Matthew D; Pachebat, Justin A; Hegarty, Matt J; Chen, Xiaorui; Morgan, Laura V A; Hoeppner, James E; Whitten, Miranda M A; Kirk, William D J; Dyson, Paul J; Sheppard, Sam K; Del Sol, Ricardo
Obligate bacterial symbionts are widespread in many invertebrates, where they are often confined to specialized host cells and are transmitted directly from mother to progeny. Increasing numbers of these bacteria are being characterized but questions remain about their population structure and evolution. Here we take a comparative genomics approach to investigate two prominent bacterial symbionts (BFo1 and BFo2) isolated from geographically separated populations of western flower thrips, Frankliniella occidentalis. Our multifaceted approach to classifying these symbionts includes concatenated multilocus sequence analysis (MLSA) phylogenies, ribosomal multilocus sequence typing (rMLST), construction of whole-genome phylogenies, and in-depth genomic comparisons. We showed that the BFo1 genome clusters more closely to species in the genus Erwinia, and is a putative close relative to Erwinia aphidicola. BFo1 is also likely to have shared a common ancestor with Erwinia pyrifoliae/Erwinia amylovora and the nonpathogenic Erwinia tasmaniensis and genetic traits similar to Erwinia billingiae. The BFo1 genome contained virulence factors found in the genus Erwinia but represented a divergent lineage. In contrast, we showed that BFo2 belongs within the Enterobacteriales but does not group closely with any currently known bacterial species. Concatenated MLSA phylogenies indicate that it may have shared a common ancestor to the Erwinia and Pantoea genera, and based on the clustering of rMLST genes, it was most closely related to Pantoea ananatis but represented a divergent lineage. We reconstructed a core genome of a putative common ancestor of Erwinia and Pantoea and compared this with the genomes of BFo bacteria. BFo2 possessed none of the virulence determinants that were omnipresent in the Erwinia and Pantoea genera. Taken together, these data are consistent with BFo2 representing a highly novel species that maybe related to known Pantoea. © The Author(s) 2015. Published by
Full Text Available Abstract Background Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology. Results We developed the Genome-based Modeling (GEM System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model. Conclusion The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.
West, Patrick T; Probst, Alexander J; Grigoriev, Igor V; Thomas, Brian C; Banfield, Jillian F
Microbial eukaryotes are integral components of natural microbial communities, and their inclusion is critical for many ecosystem studies, yet the majority of published metagenome analyses ignore eukaryotes. In order to include eukaryotes in environmental studies, we propose a method to recover eukaryotic genomes from complex metagenomic samples. A key step for genome recovery is separation of eukaryotic and prokaryotic fragments. We developed a k -mer-based strategy, EukRep, for eukaryotic sequence identification and applied it to environmental samples to show that it enables genome recovery, genome completeness evaluation, and prediction of metabolic potential. We used this approach to test the effect of addition of organic carbon on a geyser-associated microbial community and detected a substantial change of the community metabolism, with selection against almost all candidate phyla bacteria and archaea and for eukaryotes. Near complete genomes were reconstructed for three fungi placed within the Eurotiomycetes and an arthropod. While carbon fixation and sulfur oxidation were important functions in the geyser community prior to carbon addition, the organic carbon-impacted community showed enrichment for secreted proteases, secreted lipases, cellulose targeting CAZymes, and methanol oxidation. We demonstrate the broader utility of EukRep by reconstructing and evaluating relatively high-quality fungal, protist, and rotifer genomes from complex environmental samples. This approach opens the way for cultivation-independent analyses of whole microbial communities. © 2018 West et al.; Published by Cold Spring Harbor Laboratory Press.
Li, Cheng-Lin Frank; Santhanam, Balaji; Webb, Amanda Nicole; Zupan, Blaž; Shaulsky, Gad
Whole-genome sequencing is a useful approach for identification of chemical-induced lesions, but previous applications involved tedious genetic mapping to pinpoint the causative mutations. We propose that saturation mutagenesis under low mutagenic loads, followed by whole-genome sequencing, should allow direct implication of genes by identifying multiple independent alleles of each relevant gene. We tested the hypothesis by performing three genetic screens with chemical mutagenesis in the social soil amoeba Dictyostelium discoideum Through genome sequencing, we successfully identified mutant genes with multiple alleles in near-saturation screens, including resistance to intense illumination and strong suppressors of defects in an allorecognition pathway. We tested the causality of the mutations by comparison to published data and by direct complementation tests, finding both dominant and recessive causative mutations. Therefore, our strategy provides a cost- and time-efficient approach to gene discovery by integrating chemical mutagenesis and whole-genome sequencing. The method should be applicable to many microbial systems, and it is expected to revolutionize the field of functional genomics in Dictyostelium by greatly expanding the mutation spectrum relative to other common mutagenesis methods. © 2016 Li et al.; Published by Cold Spring Harbor Laboratory Press.
Iwata, Hiroyoshi; Minamikawa, Mai F; Kajiya-Kanegae, Hiromi; Ishimori, Motoyuki; Hayashi, Takeshi
Recent advancements in genomic analysis technologies have opened up new avenues to promote the efficiency of plant breeding. Novel genomics-based approaches for plant breeding and genetics research, such as genome-wide association studies (GWAS) and genomic selection (GS), are useful, especially in fruit tree breeding. The breeding of fruit trees is hindered by their long generation time, large plant size, long juvenile phase, and the necessity to wait for the physiological maturity of the plant to assess the marketable product (fruit). In this article, we describe the potential of genomics-assisted breeding, which uses these novel genomics-based approaches, to break through these barriers in conventional fruit tree breeding. We first introduce the molecular marker systems and whole-genome sequence data that are available for fruit tree breeding. Next we introduce the statistical methods for biparental linkage and quantitative trait locus (QTL) mapping as well as GWAS and GS. We then review QTL mapping, GWAS, and GS studies conducted on fruit trees. We also review novel technologies for rapid generation advancement. Finally, we note the future prospects of genomics-assisted fruit tree breeding and problems that need to be overcome in the breeding.
Ferlaino, Michael; Rogers, Mark F; Shihab, Hashem A; Mort, Matthew; Cooper, David N; Gaunt, Tom R; Campbell, Colin
Small insertions and deletions (indels) have a significant influence in human disease and, in terms of frequency, they are second only to single nucleotide variants as pathogenic mutations. As the majority of mutations associated with complex traits are located outside the exome, it is crucial to investigate the potential pathogenic impact of indels in non-coding regions of the human genome. We present FATHMM-indel, an integrative approach to predict the functional effect, pathogenic or neutral, of indels in non-coding regions of the human genome. Our method exploits various genomic annotations in addition to sequence data. When validated on benchmark data, FATHMM-indel significantly outperforms CADD and GAVIN, state of the art models in assessing the pathogenic impact of non-coding variants. FATHMM-indel is available via a web server at indels.biocompute.org.uk. FATHMM-indel can accurately predict the functional impact and prioritise small indels throughout the whole non-coding genome.
María A. Morel
Full Text Available Delftia sp. JD2 is a chromium-resistant bacterium that reduces Cr(VI to Cr(III, accumulates Pb(II, produces the phytohormone indole-3-acetic acid and siderophores, and increases the plant growth performance of rhizobia in co-inoculation experiments. We aimed to analyze the biotechnological potential of JD2 using a genomic approach. JD2 has a genome of 6.76Mb, with 6,051 predicted protein coding sequences and 93 RNA genes (tRNA and rRNA. The indole-acetamide pathway was identified as responsible for the synthesis of indole-3-acetic acid. The genetic information involved in chromium resistance (the gene cluster, chrBACF, was found. At least 40 putative genes encoding for TonB-dependent receptors, probably involved in the utilization of siderophores and biopolymers, and genes for the synthesis, maturation, exportation and uptake of pyoverdine, and acquisition of Fe-pyochelin and Fe-enterobactin were also identified. The information also suggests that JD2 produce polyhydroxybutyrate, a carbon reserve polymer commonly used for manufacturing petrochemical free bioplastics. In addition, JD2 may degrade lignin-derived aromatic compounds to 2-pyrone-4,6-dicarboxylate, a molecule used in the bio-based polymer industry. Finally, a comparative genomic analysis of JD2, Delftia sp. Cs1-4 and Delftia acidovorans SPH-1 is also discussed. The present work provides insights into the physiology and genetics of a microorganism with many potential uses in biotechnology.
Full Text Available This meeting report summarizes the proceedings of the “eGenomics: Cataloguing our Complete Genome Collection III” workshop held September 11–13, 2006, at the National Institute for Environmental eScience (NIEeS, Cambridge, United Kingdom. This 3rd workshop of the Genomic Standards Consortium was divided into two parts. The first half of the three-day workshop was dedicated to reviewing the genomic diversity of our current and future genome and metagenome collection, and exploring linkages to a series of existing projects through formal presentations. The second half was dedicated to strategic discussions. Outcomes of the workshop include a revised “Minimum Information about a Genome Sequence” (MIGS specification (v1.1, consensus on a variety of features to be added to the Genome Catalogue (GCat, agreement by several researchers to adopt MIGS for imminent genome publications, and an agreement by the EBI and NCBI to input their genome collections into GCat for the purpose of quantifying the amount of optional data already available (e.g., for geographic location coordinates and working towards a single, global list of all public genomes and metagenomes.
Nawrocki, Eric P
Many different types of functional non-coding RNAs participate in a wide range of important cellular functions but the large majority of these RNAs are not routinely annotated in published genomes. Several programs have been developed for identifying RNAs, including specific tools tailored to a particular RNA family as well as more general ones designed to work for any family. Many of these tools utilize covariance models (CMs), statistical models of the conserved sequence, and structure of an RNA family. In this chapter, as an illustrative example, the Infernal software package and CMs from the Rfam database are used to identify RNAs in the genome of the archaeon Methanobrevibacter ruminantium, uncovering some additional RNAs not present in the genome's initial annotation. Analysis of the results and comparison with family-specific methods demonstrate some important strengths and weaknesses of this general approach.
Onogi, Akio; Watanabe, Maya; Mochizuki, Toshihiro; Hayashi, Takeshi; Nakagawa, Hiroshi; Hasegawa, Toshihiro; Iwata, Hiroyoshi
It is suggested that accuracy in predicting plant phenotypes can be improved by integrating genomic prediction with crop modelling in a single hierarchical model. Accurate prediction of phenotypes is important for plant breeding and management. Although genomic prediction/selection aims to predict phenotypes on the basis of whole-genome marker information, it is often difficult to predict phenotypes of complex traits in diverse environments, because plant phenotypes are often influenced by genotype-environment interaction. A possible remedy is to integrate genomic prediction with crop/ecophysiological modelling, which enables us to predict plant phenotypes using environmental and management information. To this end, in the present study, we developed a novel method for integrating genomic prediction with phenological modelling of Asian rice (Oryza sativa, L.), allowing the heading date of untested genotypes in untested environments to be predicted. The method simultaneously infers the phenological model parameters and whole-genome marker effects on the parameters in a Bayesian framework. By cultivating backcross inbred lines of Koshihikari × Kasalath in nine environments, we evaluated the potential of the proposed method in comparison with conventional genomic prediction, phenological modelling, and two-step methods that applied genomic prediction to phenological model parameters inferred from Nelder-Mead or Markov chain Monte Carlo algorithms. In predicting heading dates of untested lines in untested environments, the proposed and two-step methods tended to provide more accurate predictions than the conventional genomic prediction methods, particularly in environments where phenotypes from environments similar to the target environment were unavailable for training genomic prediction. The proposed method showed greater accuracy in prediction than the two-step methods in all cross-validation schemes tested, suggesting the potential of the integrated approach in
Full Text Available The largest gaps in the human genome assembly correspond to multi-megabase heterochromatic regions composed primarily of two related families of tandem repeats, Human Satellites 2 and 3 (HSat2,3. The abundance of repetitive DNA in these regions challenges standard mapping and assembly algorithms, and as a result, the sequence composition and potential biological functions of these regions remain largely unexplored. Furthermore, existing genomic tools designed to predict consensus-based descriptions of repeat families cannot be readily applied to complex satellite repeats such as HSat2,3, which lack a consistent repeat unit reference sequence. Here we present an alignment-free method to characterize complex satellites using whole-genome shotgun read datasets. Utilizing this approach, we classify HSat2,3 sequences into fourteen subfamilies and predict their chromosomal distributions, resulting in a comprehensive satellite reference database to further enable genomic studies of heterochromatic regions. We also identify 1.3 Mb of non-repetitive sequence interspersed with HSat2,3 across 17 unmapped assembly scaffolds, including eight annotated gene predictions. Finally, we apply our satellite reference database to high-throughput sequence data from 396 males to estimate array size variation of the predominant HSat3 array on the Y chromosome, confirming that satellite array sizes can vary between individuals over an order of magnitude (7 to 98 Mb and further demonstrating that array sizes are distributed differently within distinct Y haplogroups. In summary, we present a novel framework for generating initial reference databases for unassembled genomic regions enriched with complex satellite DNA, and we further demonstrate the utility of these reference databases for studying patterns of sequence variation within human populations.
Edifizi, Diletta; Schumacher, Björn
DNA damage causally contributes to aging and age-related diseases. The declining functioning of tissues and organs during aging can lead to the increased risk of succumbing to aging-associated diseases. Congenital syndromes that are caused by heritable mutations in DNA repair pathways lead to cancer susceptibility and accelerated aging, thus underlining the importance of genome maintenance for withstanding aging. High-throughput mass-spectrometry-based approaches have recently contributed to identifying signalling response networks and gaining a more comprehensive understanding of the physiological adaptations occurring upon unrepaired DNA damage. The insulin-like signalling pathway has been implicated in a DNA damage response (DDR) network that includes epidermal growth factor (EGF)-, AMP-activated protein kinases (AMPK)- and the target of rapamycin (TOR)-like signalling pathways, which are known regulators of growth, metabolism, and stress responses. The same pathways, together with the autophagy-mediated proteostatic response and the decline in energy metabolism have also been found to be similarly regulated during natural aging, suggesting striking parallels in the physiological adaptation upon persistent DNA damage due to DNA repair defects and long-term low-level DNA damage accumulation occurring during natural aging. These insights will be an important starting point to study the interplay between signalling networks involved in progeroid syndromes that are caused by DNA repair deficiencies and to gain new understanding of the consequences of DNA damage in the aging process.
Adebamowo, Sally N.; Francis, Veronica; Tambo, Ernest; Diallo, Seybou H.; Landouré, Guida; Nembaware, Victoria; Dareng, Eileen; Muhamed, Babu; Odutola, Michael; Akeredolu, Teniola; Nerima, Barbara; Ozumba, Petronilla J.; Mbhele, Slee; Ghanash, Anita; Wachinou, Ablo P.; Ngomi, Nicholas
ABSTRACT Background: There is exponential growth in the interest and implementation of genomics research in Africa. This growth has been facilitated by the Human Hereditary and Health in Africa (H3Africa) initiative, which aims to promote a contemporary research approach to the study of genomics and environmental determinants of common diseases in African populations. Objective: The purpose of this article is to describe important challenges affecting genomics research implementation in Africa. Methods: The observations, challenges and recommendations presented in this article were obtained through discussions by African scientists at teleconferences and face-to-face meetings, seminars at consortium conferences and in-depth individual discussions. Results: Challenges affecting genomics research implementation in Africa, which are related to limited resources include ill-equipped facilities, poor accessibility to research centers, lack of expertise and an enabling environment for research activities in local hospitals. Challenges related to the research study include delayed funding, extensive procedures and interventions requiring multiple visits, delays setting up research teams and insufficient staff training, language barriers and an underappreciation of cultural norms. While many African countries are struggling to initiate genomics projects, others have set up genomics research facilities that meet international standards. Conclusions: The lessons learned in implementing successful genomics projects in Africa are recommended as strategies to overcome these challenges. These recommendations may guide the development and application of new research programs in low-resource settings. PMID:29336236
Kohl, Thomas A; Diel, Roland; Harmsen, Dag; Rothgänger, Jörg; Walter, Karen Meywald; Merker, Matthias; Weniger, Thomas; Niemann, Stefan
Whole-genome sequencing (WGS) allows for effective tracing of Mycobacterium tuberculosis complex (MTBC) (tuberculosis pathogens) transmission. However, it is difficult to standardize and, therefore, is not yet employed for interlaboratory prospective surveillance. To allow its widespread application, solutions for data standardization and storage in an easily expandable database are urgently needed. To address this question, we developed a core genome multilocus sequence typing (cgMLST) scheme for clinical MTBC isolates using the Ridom SeqSphere(+) software, which transfers the genome-wide single nucleotide polymorphism (SNP) diversity into an allele numbering system that is standardized, portable, and not computationally intensive. To test its performance, we performed WGS analysis of 26 isolates with identical IS6110 DNA fingerprints and spoligotyping patterns from a longitudinal outbreak in the federal state of Hamburg, Germany (notified between 2001 and 2010). The cgMLST approach (3,041 genes) discriminated the 26 strains with a resolution comparable to that of SNP-based WGS typing (one major cluster of 22 identical or closely related and four outlier isolates with at least 97 distinct SNPs or 63 allelic variants). Resulting tree topologies are highly congruent and grouped the isolates in both cases analogously. Our data show that SNP- and cgMLST-based WGS analyses facilitate high-resolution discrimination of longitudinal MTBC outbreaks. cgMLST allows for a meaningful epidemiological interpretation of the WGS genotyping data. It enables standardized WGS genotyping for epidemiological investigations, e.g., on the regional public health office level, and the creation of web-accessible databases for global TB surveillance with an integrated early warning system. Copyright © 2014, American Society for Microbiology. All Rights Reserved.
Excoffier, Laurent; Dupanloup, Isabelle; Huerta-Sánchez, Emilia; Sousa, Vitor C.; Foll, Matthieu
We introduce a flexible and robust simulation-based framework to infer demographic parameters from the site frequency spectrum (SFS) computed on large genomic datasets. We show that our composite-likelihood approach allows one to study evolutionary models of arbitrary complexity, which cannot be tackled by other current likelihood-based methods. For simple scenarios, our approach compares favorably in terms of accuracy and speed with , the current reference in the field, while showing better convergence properties for complex models. We first apply our methodology to non-coding genomic SNP data from four human populations. To infer their demographic history, we compare neutral evolutionary models of increasing complexity, including unsampled populations. We further show the versatility of our framework by extending it to the inference of demographic parameters from SNP chips with known ascertainment, such as that recently released by Affymetrix to study human origins. Whereas previous ways of handling ascertained SNPs were either restricted to a single population or only allowed the inference of divergence time between a pair of populations, our framework can correctly infer parameters of more complex models including the divergence of several populations, bottlenecks and migration. We apply this approach to the reconstruction of African demography using two distinct ascertained human SNP panels studied under two evolutionary models. The two SNP panels lead to globally very similar estimates and confidence intervals, and suggest an ancient divergence (>110 Ky) between Yoruba and San populations. Our methodology appears well suited to the study of complex scenarios from large genomic data sets. PMID:24204310
Wang, Lu; Jordan, I King
A convergence of novel genome analysis technologies is enabling population genomic studies of human transposable elements (TEs). Population surveys of human genome sequences have uncovered thousands of individual TE insertions that segregate as common genetic variants, i.e. TE polymorphisms. These recent TE insertions provide an important source of naturally occurring human genetic variation. Investigators are beginning to leverage population genomic data sets to execute genome-scale association studies for assessing the phenotypic impact of human TE polymorphisms. For example, the expression quantitative trait loci (eQTL) analytical paradigm has recently been used to uncover hundreds of associations between human TE insertion variants and gene expression levels. These include population-specific gene regulatory effects as well as coordinated changes to gene regulatory networks. In addition, analyses of linkage disequilibrium patterns with previously characterized genome-wide association study (GWAS) trait variants have uncovered TE insertion polymorphisms that are likely causal variants for a variety of common complex diseases. Gene regulatory mechanisms that underlie specific disease phenotypes have been proposed for a number of these trait associated TE polymorphisms. These new population genomic approaches hold great promise for understanding how ongoing TE activity contributes to functionally relevant genetic variation within and between human populations. Copyright © 2018 Elsevier Ltd. All rights reserved.
Tavares, Sílvia; Ramos, Ana Paula; Pires, Ana Sofia; Azinheira, Helena G; Caldeirinha, Patrícia; Link, Tobias; Abranches, Rita; Silva, Maria do Céu; Voegele, Ralf T; Loureiro, João; Talhinhas, Pedro
Rust fungi (Basidiomycota, Pucciniales) are biotrophic plant pathogens which exhibit diverse complexities in their life cycles and host ranges. The completion of genome sequencing of a few rust fungi has revealed the occurrence of large genomes. Sequencing efforts for other rust fungi have been hampered by uncertainty concerning their genome sizes. Flow cytometry was recently applied to estimate the genome size of a few rust fungi, and confirmed the occurrence of large genomes in this order (averaging 225.3 Mbp, while the average for Basidiomycota was 49.9 Mbp and was 37.7 Mbp for all fungi). In this work, we have used an innovative and simple approach to simultaneously isolate nuclei from the rust and its host plant in order to estimate the genome size of 30 rust species by flow cytometry. Genome sizes varied over 10-fold, from 70 to 893 Mbp, with an average genome size value of 380.2 Mbp. Compared to the genome sizes of over 1800 fungi, Gymnosporangium confusum possesses the largest fungal genome ever reported (893.2 Mbp). Moreover, even the smallest rust genome determined in this study is larger than the vast majority of fungal genomes (94%). The average genome size of the Pucciniales is now of 305.5 Mbp, while the average Basidiomycota genome size has shifted to 70.4 Mbp and the average for all fungi reached 44.2 Mbp. Despite the fact that no correlation could be drawn between the genome sizes, the phylogenomics or the life cycle of rust fungi, it is interesting to note that rusts with Fabaceae hosts present genomes clearly larger than those with Poaceae hosts. Although this study comprises only a small fraction of the more than 7000 rust species described, it seems already evident that the Pucciniales represent a group where genome size expansion could be a common characteristic. This is in sharp contrast to sister taxa, placing this order in a relevant position in fungal genomics research.
Arkhipova, Irina R; Batzer, Mark A; Brosius, Juergen; Feschotte, Cédric; Moran, John V; Schmitz, Jürgen; Jurka, Jerzy
The third international conference on the genomic impact of eukaryotic transposable elements (TEs) was held 24 to 28 February 2012 at the Asilomar Conference Center, Pacific Grove, CA, USA. Sponsored in part by the National Institutes of Health grant 5 P41 LM006252, the goal of the conference was to bring together researchers from around the world who study the impact and mechanisms of TEs using multiple computational and experimental approaches. The meeting drew close to 170 attendees and included invited floor presentations on the biology of TEs and their genomic impact, as well as numerous talks contributed by young scientists. The workshop talks were devoted to computational analysis of TEs with additional time for discussion of unresolved issues. Also, there was ample opportunity for poster presentations and informal evening discussions. The success of the meeting reflects the important role of Repbase in comparative genomic studies, and emphasizes the need for close interactions between experimental and computational biologists in the years to come.
Genome editing technology can alter the genomic sequence at will, contributing the creation of cellular and animal models of human diseases including hereditary disorders and cancers, and the generation of the mutation-corrected human induced pluripotent stem cells for ex vivo regenerative medicine. In addition, novel approaches such as drug development using genome-wide CRISPR screening and cancer suppression using epigenome editing technology, which can change the epigenetic modifications in a site-specific manner, have also been conducted. In this article, I summarize the current advances and future prospects of genome editing technology in the field of biomedicine.
Gao, Xiao-Yang; Zhi, Xiao-Yang; Li, Hong-Wei; Klenk, Hans-Peter; Li, Wen-Jun
Members of the genus Streptococcus within the phylum Firmicutes are among the most diverse and significant zoonotic pathogens. This genus has gone through considerable taxonomic revision due to increasing improvements of chemotaxonomic approaches, DNA hybridization and 16S rRNA gene sequencing. It is proposed to place the majority of streptococci into “species groups”. However, the evolutionary implications of species groups are not clear presently. We use comparative genomic approaches to yield a better understanding of the evolution of Streptococcus through genome dynamics, population structure, phylogenies and virulence factor distribution of species groups. Genome dynamics analyses indicate that the pan-genome size increases with the addition of newly sequenced strains, while the core genome size decreases with sequential addition at the genus level and species group level. Population structure analysis reveals two distinct lineages, one including Pyogenic, Bovis, Mutans and Salivarius groups, and the other including Mitis, Anginosus and Unknown groups. Phylogenetic dendrograms show that species within the same species group cluster together, and infer two main clades in accordance with population structure analysis. Distribution of streptococcal virulence factors has no obvious patterns among the species groups; however, the evolution of some common virulence factors is congruous with the evolution of species groups, according to phylogenetic inference. We suggest that the proposed streptococcal species groups are reasonable from the viewpoints of comparative genomics; evolution of the genus is congruent with the individual evolutionary trajectories of different species groups. PMID:24977706
Zomer, Albertus Lambert
This thesis describes a number of strategies of Lactococcus lactis to adapt to its ever-changing environment. Although the complete genome sequence of L. lactis subspecies lactis IL1403, became available when this research was started, the genome sequence of the lactic acid bacterial paradigm, L.
Full Text Available While the bulk of the finished microbial genomes sequenced to date are derived from cultured bacterial and archaeal representatives, the vast majority of microorganisms elude current culturing attempts, severely limiting the ability to recover complete or even partial genomes from these environmental species. Single cell genomics is a novel culture-independent approach, which enables access to the genetic material of an individual cell. No single cell genome has to our knowledge been closed and finished to date. Here we report the completed genome from an uncultured single cell of Candidatus Sulcia muelleri DMIN. Digital PCR on single symbiont cells isolated from the bacteriome of the green sharpshooter Draeculacephala minerva bacteriome allowed us to assess that this bacteria is polyploid with genome copies ranging from approximately 200-900 per cell, making it a most suitable target for single cell finishing efforts. For single cell shotgun sequencing, an individual Sulcia cell was isolated and whole genome amplified by multiple displacement amplification (MDA. Sanger-based finishing methods allowed us to close the genome. To verify the correctness of our single cell genome and exclude MDA-derived artifacts, we independently shotgun sequenced and assembled the Sulcia genome from pooled bacteriomes using a metagenomic approach, yielding a nearly identical genome. Four variations we detected appear to be genuine biological differences between the two samples. Comparison of the single cell genome with bacteriome metagenomic sequence data detected two single nucleotide polymorphisms (SNPs, indicating extremely low genetic diversity within a Sulcia population. This study demonstrates the power of single cell genomics to generate a complete, high quality, non-composite reference genome within an environmental sample, which can be used for population genetic analyzes.
Woyke, Tanja; Tighe, Damon; Mavrommatis, Konstantinos; Clum, Alicia; Copeland, Alex; Schackwitz, Wendy; Lapidus, Alla; Wu, Dongying; McCutcheon, John P.; McDonald, Bradon R.; Moran, Nancy A.; Bristow, James; Cheng, Jan-Fang
While the bulk of the finished microbial genomes sequenced to date are derived from cultured bacterial and archaeal representatives, the vast majority of microorganisms elude current culturing attempts, severely limiting the ability to recover complete or even partial genomes from these environmental species. Single cell genomics is a novel culture-independent approach, which enables access to the genetic material of an individual cell. No single cell genome has to our knowledge been closed and finished to date. Here we report the completed genome from an uncultured single cell of Candidatus Sulcia muelleri DMIN. Digital PCR on single symbiont cells isolated from the bacteriome of the green sharpshooter Draeculacephala minerva bacteriome allowed us to assess that this bacteria is polyploid with genome copies ranging from approximately 200?900 per cell, making it a most suitable target for single cell finishing efforts. For single cell shotgun sequencing, an individual Sulcia cell was isolated and whole genome amplified by multiple displacement amplification (MDA). Sanger-based finishing methods allowed us to close the genome. To verify the correctness of our single cell genome and exclude MDA-derived artifacts, we independently shotgun sequenced and assembled the Sulcia genome from pooled bacteriomes using a metagenomic approach, yielding a nearly identical genome. Four variations we detected appear to be genuine biological differences between the two samples. Comparison of the single cell genome with bacteriome metagenomic sequence data detected two single nucleotide polymorphisms (SNPs), indicating extremely low genetic diversity within a Sulcia population. This study demonstrates the power of single cell genomics to generate a complete, high quality, non-composite reference genome within an environmental sample, which can be used for population genetic analyzes.
Oakey, Helena; Cullis, Brian; Thompson, Robin; Comadran, Jordi; Halpin, Claire; Waugh, Robbie
Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and nonmarker residual genetic variation (i.e., additive and nonadditive effects). This results in a more precise estimate of marker genetic effects. Using barley height data from trials, in 2 different years, of up to 477 cultivars, we demonstrate that our new genomic selection model improves predictions compared to current models. Analyzing single trials revealed improvements in predictive ability of up to 5.7%. For the multiple environment trial (MET) model, combining both year trials improved predictive ability up to 11.4% compared to a single environment analysis. Benefits were significant even when fewer markers were used. Compared to a single-year standard model run with 3490 markers, our partitioned MET model achieved the same predictive ability using between 500 and 1000 markers depending on the trial. Our approach can be used to increase accuracy and confidence in the selection of the best lines for breeding and/or, to reduce costs by using fewer markers. Copyright © 2016 Oakey et al.
Full Text Available Drought tolerance is a complex trait that involves numerous genes. Identifying key causal genes or linked molecular markers can facilitate the fast development of drought tolerant varieties. Using a whole-genome resequencing approach, we sequenced 132 chickpea varieties and advanced breeding lines and found more than 144,000 single nucleotide polymorphisms (SNPs. We measured 13 yield and yield-related traits in three drought-prone environments of Western Australia. The genotypic effects were significant for all traits, and many traits showed highly significant correlations, ranging from 0.83 between grain yield and biomass to -0.67 between seed weight and seed emergence rate. To identify candidate genes, the SNP and trait data were incorporated into the SUPER genome-wide association study (GWAS model, a modified version of the linear mixed model. We found that several SNPs from auxin-related genes, including auxin efflux carrier protein (PIN3, p-glycoprotein, and nodulin MtN21/EamA-like transporter, were significantly associated with yield and yield-related traits under drought-prone environments. We identified four genetic regions containing SNPs significantly associated with several different traits, which was an indication of pleiotropic effects. We also investigated the possibility of incorporating the GWAS results into a genomic selection (GS model, which is another approach to deal with complex traits. Compared to using all SNPs, application of the GS model using subsets of SNPs significantly associated with the traits under investigation increased the prediction accuracies of three yield and yield-related traits by more than twofold. This has important implication for implementing GS in plant breeding programs.
Lack, Justin B; Lange, Jeremy D; Tang, Alison D; Corbett-Detig, Russell B; Pool, John E
The Drosophila Genome Nexus is a population genomic resource that provides D. melanogaster genomes from multiple sources. To facilitate comparisons across data sets, genomes are aligned using a common reference alignment pipeline which involves two rounds of mapping. Regions of residual heterozygosity, identity-by-descent, and recent population admixture are annotated to enable data filtering based on the user's needs. Here, we present a significant expansion of the Drosophila Genome Nexus, which brings the current data object to a total of 1,121 wild-derived genomes. New additions include 305 previously unpublished genomes from inbred lines representing six population samples in Egypt, Ethiopia, France, and South Africa, along with another 193 genomes added from recently-published data sets. We also provide an aligned D. simulans genome to facilitate divergence comparisons. This improved resource will broaden the range of population genomic questions that can addressed from multi-population allele frequencies and haplotypes in this model species. The larger set of genomes will also enhance the discovery of functionally relevant natural variation that exists within and between populations. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
Fage-Butler, Antoinette Mary
Existing research reveals that patients’ perspectives are missing from mandatory patient information leaflets (PILs). At the same time, there is overwhelming consensus that they should be included in this genre, and a corresponding need for potential approaches to tackle this problem. This paper ...
Mun, Seyoung; Kim, Yun-Ji; Markkandan, Kesavan; Shin, Wonseok; Oh, Sumin; Woo, Jiyoung; Yoo, Jongsu; An, Hyesuck; Han, Kyudong
The manila clam, Ruditapes philippinarum, is an important bivalve species in worldwide aquaculture including Korea. The aquaculture production of R. philippinarum is under threat from diverse environmental factors including viruses, microorganisms, parasites, and water conditions with subsequently declining production. In spite of its importance as a marine resource, the reference genome of R. philippinarum for comprehensive genetic studies is largely unexplored. Here, we report the de novo whole-genome and transcriptome assembly of R. philippinarum across three different tissues (foot, gill, and adductor muscle), and provide the basic data for advanced studies in selective breeding and disease control in order to obtain successful aquaculture systems. An approximately 2.56 Gb high quality whole-genome was assembled with various library construction methods. A total of 108,034 protein coding gene models were predicted and repetitive elements including simple sequence repeats and noncoding RNAs were identified to further understanding of the genetic background of R. philippinarum for genomics-assisted breeding. Comparative analysis with the bivalve marine invertebrates uncover that the gene family related to complement C1q was enriched. Furthermore, we performed transcriptome analysis with three different tissues in order to support genome annotation and then identified 41,275 transcripts which were annotated. The R. philippinarum genome resource will markedly advance a wide range of potential genetic studies, a reference genome for comparative analysis of bivalve species and unraveling mechanisms of biological processes in molluscs. We believe that the R. philippinarum genome will serve as an initial platform for breeding better-quality clams using a genomic approach. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
Leekitcharoenphon, Pimlapas; Nielsen, Eva M.; Kaas, Rolf Sommer
Salmonella enterica is a common cause of minor and large food borne outbreaks. To achieve successful and nearly ‘real-time’ monitoring and identification of outbreaks, reliable sub-typing is essential. Whole genome sequencing (WGS) shows great promises for using as a routine epidemiological typing....... Enteritidis and 5 S. Derby were also sequenced and used for comparison. A number of different bioinformatics approaches were applied on the data; including pan-genome tree, k-mer tree, nucleotide difference tree and SNP tree. The outcome of each approach was evaluated in relation to the association...... of the isolates to specific outbreaks. The pan-genome tree clustered 65% of the S. Typhimurium isolates according to the pre-defined epidemiology, the k-mer tree 88%, the nucleotide difference tree 100% and the SNP tree 100% of the strains within S. Typhimurium. The resulting outcome of the four phylogenetic...
Vaez Barzani, Ahmad
In this thesis we present an overview of bioinformatics-based approaches for genomic association mapping, with emphasis on human quantitative traits and their contribution to complex diseases. We aim to provide a comprehensive walk-through of the classic steps of genomic association mapping
Abad, P.; Gouzy, J.; Aury, J.M.; Tytgat, T.O.G.; Smant, G.
Plant-parasitic nematodes are major agricultural pests worldwide and novel approaches to control them are sorely needed. We report the draft genome sequence of the root-knot nematode Meloidogyne incognita, a biotrophic parasite of many crops, including tomato, cotton and coffee. Most of the
Kellis, Manolis; Wold, Barbara; Snyder, Michael P.; Bernstein, Bradley E.; Kundaje, Anshul; Marinov, Georgi K.; Ward, Lucas D.; Birney, Ewan; Crawford, Gregory E.; Dekker, Job; Dunham, Ian; Elnitski, Laura L.; Farnham, Peggy J.; Feingold, Elise A.; Gerstein, Mark; Giddings, Morgan C.; Gilbert, David M.; Gingeras, Thomas R.; Green, Eric D.; Guigo, Roderic; Hubbard, Tim; Kent, Jim; Lieb, Jason D.; Myers, Richard M.; Pazin, Michael J.; Ren, Bing; Stamatoyannopoulos, John A.; Weng, Zhiping; White, Kevin P.; Hardison, Ross C.
With the completion of the human genome sequence, attention turned to identifying and annotating its functional DNA elements. As a complement to genetic and comparative genomics approaches, the Encyclopedia of DNA Elements Project was launched to contribute maps of RNA transcripts, transcriptional regulator binding sites, and chromatin states in many cell types. The resulting genome-wide data reveal sites of biochemical activity with high positional resolution and cell type specificity that facilitate studies of gene regulation and interpretation of noncoding variants associated with human disease. However, the biochemically active regions cover a much larger fraction of the genome than do evolutionarily conserved regions, raising the question of whether nonconserved but biochemically active regions are truly functional. Here, we review the strengths and limitations of biochemical, evolutionary, and genetic approaches for defining functional DNA segments, potential sources for the observed differences in estimated genomic coverage, and the biological implications of these discrepancies. We also analyze the relationship between signal intensity, genomic coverage, and evolutionary conservation. Our results reinforce the principle that each approach provides complementary information and that we need to use combinations of all three to elucidate genome function in human biology and disease. PMID:24753594
Join us for a live, moderated discussion about two NCI efforts to expand access to cancer genomics data: the Genomic Data Commons and Genomic Cloud Pilots. NCI subject matters experts will include Louis M. Staudt, M.D., Ph.D., Director Center for Cancer Genomics, Warren Kibbe, Ph.D., Director, NCI Center for Biomedical Informatics and Information Technology, and moderated by Anthony Kerlavage, Ph.D., Chief, Cancer Informatics Branch, Center for Biomedical Informatics and Information Technology. We welcome your questions before and during the Hangout on Twitter using the hashtag #AskNCI.
Wurtzel, Omri; Dori-Bachash, Mally; Pietrokovski, Shmuel; Jurkevitch, Edouard; Sorek, Rotem; Ben-Jacob, Eshel
The affordability of next generation sequencing (NGS) is transforming the field of mutation analysis in bacteria. The genetic basis for phenotype alteration can be identified directly by sequencing the entire genome of the mutant and comparing it to the wild-type (WT) genome, thus identifying acquired mutations. A major limitation for this approach is the need for an a-priori sequenced reference genome for the WT organism, as the short reads of most current NGS approaches usually prohibit de-novo genome assembly. To overcome this limitation we propose a general framework that utilizes the genome of relative organisms as mediators for comparing WT and mutant bacteria. Under this framework, both mutant and WT genomes are sequenced with NGS, and the short sequencing reads are mapped to the mediator genome. Variations between the mutant and the mediator that recur in the WT are ignored, thus pinpointing the differences between the mutant and the WT. To validate this approach we sequenced the genome of Bdellovibrio bacteriovorus 109J, an obligatory bacterial predator, and its prey-independent mutant, and compared both to the mediator species Bdellovibrio bacteriovorus HD100. Although the mutant and the mediator sequences differed in more than 28,000 nucleotide positions, our approach enabled pinpointing the single causative mutation. Experimental validation in 53 additional mutants further established the implicated gene. Our approach extends the applicability of NGS-based mutant analyses beyond the domain of available reference genomes.
Lukas A. Mueller
Full Text Available The genome of tomato ( L. is being sequenced by an international consortium of 10 countries (Korea, China, the United Kingdom, India, the Netherlands, France, Japan, Spain, Italy, and the United States as part of the larger “International Solanaceae Genome Project (SOL: Systems Approach to Diversity and Adaptation” initiative. The tomato genome sequencing project uses an ordered bacterial artificial chromosome (BAC approach to generate a high-quality tomato euchromatic genome sequence for use as a reference genome for the Solanaceae and euasterids. Sequence is deposited at GenBank and at the SOL Genomics Network (SGN. Currently, there are around 1000 BACs finished or in progress, representing more than a third of the projected euchromatic portion of the genome. An annotation effort is also underway by the International Tomato Annotation Group. The expected number of genes in the euchromatin is ∼40,000, based on an estimate from a preliminary annotation of 11% of finished sequence. Here, we present this first snapshot of the emerging tomato genome and its annotation, a short comparison with potato ( L. sequence data, and the tools available for the researchers to exploit this new resource are also presented. In the future, whole-genome shotgun techniques will be combined with the BAC-by-BAC approach to cover the entire tomato genome. The high-quality reference euchromatic tomato sequence is expected to be near completion by 2010.
Vesth, Tammi Camilla
of this class have very little homology to other known genomes making functional annotation based on sequence similarity very difficult. Inspired in part by this analysis, an approach for comparative functional annotation was created based public sequenced genomes, CMGfunc. Functionally related groups......In November 2013, there was around 21.000 different prokaryotic genomes sequenced and publicly available, and the number is growing daily with another 20.000 or more genomes expected to be sequenced and deposited by the end of 2014. An important part of the analysis of this data is the functional...... annotation of genes – the descriptions assigned to genes that describe the likely function of the encoded proteins. This process is limited by several factors, including the definition of a function which can be more or less specific as well as how many genes can actually be assigned a function based...
Elbrecht, Vasco; Poettker, Lisa; John, Uwe; Leese, Florian
The complete mitochondrial genome of the perlid stonefly Dinocras cephalotes (Curtis, 1827) was sequenced using a combined 454 and Sanger sequencing approach using the known sequence of Pteronarcys princeps Banks, 1907 (Pteronarcyidae), to identify homologous 454 reads. The genome is 15,666 bp in length and includes 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes and a control region. Gene order resembles that of basal arthropods. The base composition of the genome is A (33.5%), T (29.0%), C (24.4%) and G (13.1%). This is the second published mitogenome for the order Plecoptera and will be useful in future phylogenetic analysis.
Margrethe H. Serres
-throughput expression analyses, and functional genomics approaches to uncover key genes as well as metabolic and regulatory networks. The "bottom-up" component employs more traditional approaches including genetics, physiology and biochemistry to test or verify predictions. This information will ultimately be linked to analyses of signal transduction and transcriptional regulatory systems and used to develop a linked model that will contribute to understanding the ecophysiology of Shewanella in redox stratified environments. A central component of this effort is the development of a data and knowledge integration environment that will allow investigators to query across the individual research domains, link to analysis applications, visualize data in a cell systems context, and produce new knowledge, while minimizing the effort, time and complexity to participating institutions.
Mishra, Bagdevi; Gupta, Deepak K; Pfenninger, Markus; Hickler, Thomas; Langer, Ewald; Nam, Bora; Paule, Juraj; Sharma, Rahul; Ulaszewski, Bartosz; Warmbier, Joanna; Burczyk, Jaroslaw; Thines, Marco
The European beech is arguably the most important climax broad-leaved tree species in Central Europe, widely planted for its valuable wood. Here, we report the 542 Mb draft genome sequence of an up to 300-year-old individual (Bhaga) from an undisturbed stand in the Kellerwald-Edersee National Park in central Germany. Using a hybrid assembly approach, Illumina reads with short- and long-insert libraries, coupled with long Pacific Biosciences reads, we obtained an assembled genome size of 542 Mb, in line with flow cytometric genome size estimation. The largest scaffold was of 1.15 Mb, the N50 length was 145 kb, and the L50 count was 983. The assembly contained 0.12% of Ns. A Benchmarking with Universal Single-Copy Orthologs (BUSCO) analysis retrieved 94% complete BUSCO genes, well in the range of other high-quality draft genomes of trees. A total of 62,012 protein-coding genes were predicted, assisted by transcriptome sequencing. In addition, we are reporting an efficient method for extracting high-molecular-weight DNA from dormant buds, by which contamination by environmental bacteria and fungi was kept at a minimum. The assembled genome will be a valuable resource and reference for future population genomics studies on the evolution and past climate change adaptation of beech and will be helpful for identifying genes, e.g., involved in drought tolerance, in order to select and breed individuals to adapt forestry to climate change in Europe. A continuously updated genome browser and download page can be accessed from beechgenome.net, which will include future genome versions of the reference individual Bhaga, as new sequencing approaches develop.
King, E.; Brodie, E.; Anantharaman, K.; Karaoz, U.; Bouskill, N.; Banfield, J. F.; Steefel, C. I.; Molins, S.
Characterizing and predicting the microbial and chemical compositions of subsurface aquatic systems necessitates an understanding of the metabolism and physiology of organisms that are often uncultured or studied under conditions not relevant for one's environment of interest. Cultivation-independent approaches are therefore important and have greatly enhanced our ability to characterize functional microbial diversity. The capability to reconstruct genomes representing thousands of populations from microbial communities using metagenomic techniques provides a foundation for development of predictive models for community structure and function. Here, we discuss a genome-informed stochastic trait-based model incorporated into a reactive transport framework to represent the activities of coupled guilds of hypothetical microorganisms. Metabolic pathways for each microbe within a functional guild are parameterized from metagenomic data with a unique combination of traits governing organism fitness under dynamic environmental conditions. We simulate the thermodynamics of coupled electron donor and acceptor reactions to predict the energy available for cellular maintenance, respiration, biomass development, and enzyme production. While `omics analyses can now characterize the metabolic potential of microbial communities, it is functionally redundant as well as computationally prohibitive to explicitly include the thousands of recovered organisms into biogeochemical models. However, one can derive potential metabolic pathways from genomes along with trait-linkages to build probability distributions of traits. These distributions are used to assemble groups of microbes that couple one or more of these pathways. From the initial ensemble of microbes, only a subset will persist based on the interaction of their physiological and metabolic traits with environmental conditions, competing organisms, etc. Here, we analyze the predicted niches of these hypothetical microbes and
Chen, Fei; Dong, Wei; Zhang, Jiawei; Guo, Xinyue; Chen, Junhao; Wang, Zhengjia; Lin, Zhenguo; Tang, Haibao; Zhang, Liangsheng
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.
Kristopher J. L. Irizarry
Full Text Available Comparative genomics approaches provide a means of leveraging functional genomics information from a highly annotated model organism’s genome (such as the mouse genome in order to make physiological inferences about the role of genes and proteins in a less characterized organism’s genome (such as the Burmese python. We employed a comparative genomics approach to produce the functional annotation of Python bivittatus genes encoding proteins associated with sperm phenotypes. We identify 129 gene-phenotype relationships in the python which are implicated in 10 specific sperm phenotypes. Results obtained through our systematic analysis identified subsets of python genes exhibiting associations with gene ontology annotation terms. Functional annotation data was represented in a semantic scatter plot. Together, these newly annotated Python bivittatus genome resources provide a high resolution framework from which the biology relating to reptile spermatogenesis, fertility, and reproduction can be further investigated. Applications of our research include (1 production of genetic diagnostics for assessing fertility in domestic and wild reptiles; (2 enhanced assisted reproduction technology for endangered and captive reptiles; and (3 novel molecular targets for biotechnology-based approaches aimed at reducing fertility and reproduction of invasive reptiles. Additional enhancements to reptile genomic resources will further enhance their value.
Sharp, N C Craig
Hugh Montgomery's discovery of the first of more than 239 fitness genes together with rapid advances in human gene therapy have created a prospect of using genes, genetic elements, and cells that have the capacity to enhance athletic performance (to paraphrase the World Anti-Doping Agency's definition of gene doping). This brief overview covers the main areas of interface between genetics and sport, attempts to provide a context against which gene doping may be viewed, and predicts a futuristic legitimate use of genomic (and possibly epigenetic) information in sport. Copyright 2010 Elsevier Inc. All rights reserved.
Lisa Zeigler Allen
Full Text Available Whole genome amplification and sequencing of single microbial cells has significantly influenced genomics and microbial ecology by facilitating direct recovery of reference genome data. However, viral genomics continues to suffer due to difficulties related to the isolation and characterization of uncultivated viruses. We report here on a new approach called 'Single Virus Genomics', which enabled the isolation and complete genome sequencing of the first single virus particle. A mixed assemblage comprised of two known viruses; E. coli bacteriophages lambda and T4, were sorted using flow cytometric methods and subsequently immobilized in an agarose matrix. Genome amplification was then achieved in situ via multiple displacement amplification (MDA. The complete lambda phage genome was recovered with an average depth of coverage of approximately 437X. The isolation and genome sequencing of uncultivated viruses using Single Virus Genomics approaches will enable researchers to address questions about viral diversity, evolution, adaptation and ecology that were previously unattainable.
Kumar, Shiva; Mudeppa, Devaraja G; Sharma, Ambika; Mascarenhas, Anjali; Dash, Rashmi; Pereira, Ligia; Shaik, Riaz Basha; Maki, Jennifer N; White, John; Zuo, Wenyun; Tuljapurkar, Shripad; Duraisingh, Manoj T; Gomes, Edwin; Chery, Laura; Rathod, Pradipsinh K
Previous whole genome comparisons of Plasmodium falciparum populations have not included collections from the Indian subcontinent, even though two million Indians contract malaria and about 50,000 die from the disease every year. Stratification of global parasites has revealed spatial relatedness of parasite genotypes on different continents. Here, genomic analysis was further improved to obtain country-level resolution by removing var genes and intergenic regions from distance calculations. P. falciparum genomes from India were found to be most closely related to each other. Their nearest neighbors were from Bangladesh and Myanmar, followed by Thailand. Samples from the rest of Southeast Asia, Africa and South America were increasingly more distant, demonstrating a high-resolution genomic-geographic continuum. Such genome stratification approaches will help monitor variations of malaria parasites within South Asia and future changes in parasite populations that may arise from in-country and cross-border migrations. Copyright Â© 2016 The Author(s). Published by Elsevier B.V. All rights reserved.
Juan, Liran; Liu, Yongzhuang; Wang, Yongtian; Teng, Mingxiang; Zang, Tianyi; Wang, Yadong
Families with inherited diseases are widely used in Mendelian/complex disease studies. Owing to the advances in high-throughput sequencing technologies, family genome sequencing becomes more and more prevalent. Visualizing family genomes can greatly facilitate human genetics studies and personalized medicine. However, due to the complex genetic relationships and high similarities among genomes of consanguineous family members, family genomes are difficult to be visualized in traditional genome visualization framework. How to visualize the family genome variants and their functions with integrated pedigree information remains a critical challenge. We developed the Family Genome Browser (FGB) to provide comprehensive analysis and visualization for family genomes. The FGB can visualize family genomes in both individual level and variant level effectively, through integrating genome data with pedigree information. Family genome analysis, including determination of parental origin of the variants, detection of de novo mutations, identification of potential recombination events and identical-by-decent segments, etc., can be performed flexibly. Diverse annotations for the family genome variants, such as dbSNP memberships, linkage disequilibriums, genes, variant effects, potential phenotypes, etc., are illustrated as well. Moreover, the FGB can automatically search de novo mutations and compound heterozygous variants for a selected individual, and guide investigators to find high-risk genes with flexible navigation options. These features enable users to investigate and understand family genomes intuitively and systematically. The FGB is available at http://mlg.hit.edu.cn/FGB/. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: email@example.com.
Andrés, Aida M; Hubisz, Melissa J; Indap, Amit
Balancing selection is potentially an important biological force for maintaining advantageous genetic diversity in populations, including variation that is responsible for long-term adaptation to the environment. By serving as a means to maintain genetic variation, it may be particularly relevant...... to maintaining phenotypic variation in natural populations. Nevertheless, its prevalence and specific targets in the human genome remain largely unknown. We have analyzed the patterns of diversity and divergence of 13,400 genes in two human populations using an unbiased single-nucleotide polymorphism data set......, a genome-wide approach, and a method that incorporates demography in neutrality tests. We identified an unbiased catalog of genes with signatures of long-term balancing selection, which includes immunity genes as well as genes encoding keratins and membrane channels; the catalog also shows enrichment...
Libbrecht, Maxwell W; Noble, William Stafford
The field of machine learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in the analysis of large, complex data sets. Here, we provide an overview of machine learning applications for the analysis of genome sequencing data sets, including the annotation of sequence elements and epigenetic, proteomic or metabolomic data. We present considerations and recurrent challenges in the application of supervised, semi-supervised and unsupervised machine learning methods, as well as of generative and discriminative modelling approaches. We provide general guidelines to assist in the selection of these machine learning methods and their practical application for the analysis of genetic and genomic data sets.
Full Text Available Abstract Background Since the full genome sequences of Saccharomyces cerevisiae were released in 1996, genome sequences of over 90 fungal species have become publicly available. The heterogeneous formats of genome sequences archived in different sequencing centers hampered the integration of the data for efficient and comprehensive comparative analyses. The Comparative Fungal Genomics Platform (CFGP was developed to archive these data via a single standardized format that can support multifaceted and integrated analyses of the data. To facilitate efficient data visualization and utilization within and across species based on the architecture of CFGP and associated databases, a new genome browser was needed. Results The Seoul National University Genome Browser (SNUGB integrates various types of genomic information derived from 98 fungal/oomycete (137 datasets and 34 plant and animal (38 datasets species, graphically presents germane features and properties of each genome, and supports comparison between genomes. The SNUGB provides three different forms of the data presentation interface, including diagram, table, and text, and six different display options to support visualization and utilization of the stored information. Information for individual species can be quickly accessed via a new tool named the taxonomy browser. In addition, SNUGB offers four useful data annotation/analysis functions, including 'BLAST annotation.' The modular design of SNUGB makes its adoption to support other comparative genomic platforms easy and facilitates continuous expansion. Conclusion The SNUGB serves as a powerful platform supporting comparative and functional genomics within the fungal kingdom and also across other kingdoms. All data and functions are available at the web site http://genomebrowser.snu.ac.kr/.
Iwata, Hiroyoshi; Minamikawa, Mai F.; Kajiya-Kanegae, Hiromi; Ishimori, Motoyuki; Hayashi, Takeshi
Recent advancements in genomic analysis technologies have opened up new avenues to promote the efficiency of plant breeding. Novel genomics-based approaches for plant breeding and genetics research, such as genome-wide association studies (GWAS) and genomic selection (GS), are useful, especially in fruit tree breeding. The breeding of fruit trees is hindered by their long generation time, large plant size, long juvenile phase, and the necessity to wait for the physiological maturity of the pl...
Tong, Yaojun; Robertsen, Helene Lunde; Blin, Kai
engineering approaches for boosting known and discovering novel natural products. In order to facilitate the genome editing for actinomycetes, we developed a CRISPR-Cas9 toolkit with high efficiency for actinomyces genome editing. This basic toolkit includes a software for spacer (sgRNA) identification......, a system for in-frame gene/gene cluster knockout, a system for gene loss-of-function study, a system for generating a random size deletion library, and a system for gene knockdown. For the latter, a uracil-specific excision reagent (USER) cloning technology was adapted to simplify the CRISPR vector...... construction process. The application of this toolkit was successfully demonstrated by perturbation of genomes of Streptomyces coelicolor A3(2) and Streptomyces collinus Tü 365. The CRISPR-Cas9 toolkit and related protocol described here can be widely used for metabolic engineering of actinomycetes....
Morrison, M.; Nelson, K.E.
Improving microbial degradation of plant cell wall polysaccharides remains one of the highest priority goals for all livestock enterprises, including the cattle herds and draught animals of developing countries. The North American Consortium for Genomics of Fibrolytic Ruminal Bacteria was created to promote the sequencing and comparative analysis of rumen microbial genomes, offering the potential to fully assess the genetic potential in a functional and comparative fashion. It has been found that the Fibrobacter succinogenes genome encodes many more endoglucanases and cellodextrinases than previously isolated, and several new processive endoglucanases have been identified by genome and proteomic analysis of Ruminococcus albus, in addition to a variety of strategies for its adhesion to fibre. The ramifications of acquiring genome sequence data for rumen microorganisms are profound, including the potential to elucidate and overcome the biochemical, ecological or physiological processes that are rate limiting for ruminal fibre degradation. (author)
Full Text Available Whole genome sequencing (WGS, using high throughput sequencing technology, reveals the complete sequence of the bacterial genome in a few days. WGS is increasingly being used for source tracking, pathogen surveillance and outbreak investigation due to its high discriminatory power. In the food industry, WGS used for source tracking is beneficial to support contamination investigations. Despite its increased use, no standards or guidelines are available today for the use of WGS in outbreak and/or trace-back investigations. Here we present a validation of our complete (end-to-end WGS workflow for Listeria monocytogenes and Salmonella enterica including: subculture of isolates, DNA extraction, sequencing and bioinformatics analysis. This end-to-end WGS workflow was evaluated according to the following performance criteria: stability, repeatability, reproducibility, discriminatory power, and epidemiological concordance. The current study showed that few single nucleotide polymorphism (SNPs were observed for L. monocytogenes and S. enterica when comparing genome sequences from five independent colonies from the first subculture and five independent colonies after the tenth subculture. Consequently, the stability of the WGS workflow for L. monocytogenes and S. enterica was demonstrated despite the few genomic variations that can occur during subculturing steps. Repeatability and reproducibility were also demonstrated. The WGS workflow was shown to have a high discriminatory power and has the ability to show genetic relatedness. Additionally, the WGS workflow was able to reproduce published outbreak investigation results, illustrating its capability of showing epidemiological concordance. The current study proposes a validation approach comprising all steps of a WGS workflow and demonstrates that the workflow can be applied to L. monocytogenes or S. enterica.
Yi, Guoqiang; Qu, Lujiang; Liu, Jianfeng; Yan, Yiyuan; Xu, Guiyun; Yang, Ning
Copy number variation (CNV) is important and widespread in the genome, and is a major cause of disease and phenotypic diversity. Herein, we performed a genome-wide CNV analysis in 12 diversified chicken genomes based on whole genome sequencing. A total of 8,840 CNV regions (CNVRs) covering 98.2 Mb and representing 9.4% of the chicken genome were identified, ranging in size from 1.1 to 268.8 kb with an average of 11.1 kb. Sequencing-based predictions were confirmed at a high validation rate by two independent approaches, including array comparative genomic hybridization (aCGH) and quantitative PCR (qPCR). The Pearson's correlation coefficients between sequencing and aCGH results ranged from 0.435 to 0.755, and qPCR experiments revealed a positive validation rate of 91.71% and a false negative rate of 22.43%. In total, 2,214 (25.0%) predicted CNVRs span 2,216 (36.4%) RefSeq genes associated with specific biological functions. Besides two previously reported copy number variable genes EDN3 and PRLR, we also found some promising genes with potential in phenotypic variation. Two genes, FZD6 and LIMS1, related to disease susceptibility/resistance are covered by CNVRs. The highly duplicated SOCS2 may lead to higher bone mineral density. Entire or partial duplication of some genes like POPDC3 may have great economic importance in poultry breeding. Our results based on extensive genetic diversity provide a more refined chicken CNV map and genome-wide gene copy number estimates, and warrant future CNV association studies for important traits in chickens.
Full Text Available Manganese efficiency is a quantitative abiotic stress trait controlled by several genes each with a small effect. Manganese deficiency leads to yield reduction in winter barley ( L.. Breeding new cultivars for this trait remains difficult because of the lack of visual symptoms and the polygenic features of the trait. Hence, Mn efficiency is a potential suitable trait for a genomic selection (GS approach. A collection of 248 winter barley varieties was screened for Mn efficiency using Chlorophyll (Chl fluorescence in six environments prone to induce Mn deficiency. Two models for genomic prediction were implemented to predict future performance and breeding value of untested varieties. Predictions were obtained using multivariate mixed models: best linear unbiased predictor (BLUP and genomic best linear unbiased predictor (G-BLUP. In the first model, predictions were based on the phenotypic evaluation, whereas both phenotypic and genomic marker data were included in the second model. Accuracy of predicting future phenotype, , and accuracy of predicting true breeding values, , were calculated and compared for both models using six cross-validation (CV schemes; these were designed to mimic plant breeding programs. Overall, the CVs showed that prediction accuracies increased when using the G-BLUP model compared with the prediction accuracies using the BLUP model. Furthermore, the accuracies  of predicting breeding values were more accurate than accuracy of predicting future phenotypes . The study confirms that genomic data may enhance the prediction accuracy. Moreover it indicates that GS is a suitable breeding approach for quantitative abiotic stress traits.
Doran, Anthony G; Berry, Donagh P; Creevey, Christopher J
Four traits related to carcass performance have been identified as economically important in beef production: carcass weight, carcass fat, carcass conformation of progeny and cull cow carcass weight. Although Holstein-Friesian cattle are primarily utilized for milk production, they are also an important source of meat for beef production and export. Because of this, there is great interest in understanding the underlying genomic structure influencing these traits. Several genome-wide association studies have identified regions of the bovine genome associated with growth or carcass traits, however, little is known about the mechanisms or underlying biological pathways involved. This study aims to detect regions of the bovine genome associated with carcass performance traits (employing a panel of 54,001 SNPs) using measures of genetic merit (as predicted transmitting abilities) for 5,705 Irish Holstein-Friesian animals. Candidate genes and biological pathways were then identified for each trait under investigation. Following adjustment for false discovery (q-value carcass traits using a single SNP regression approach. Using a Bayesian approach, 46 QTL were associated (posterior probability > 0.5) with at least one of the four traits. In total, 557 unique bovine genes, which mapped to 426 human orthologs, were within 500kbs of QTL found associated with a trait using the Bayesian approach. Using this information, 24 significantly over-represented pathways were identified across all traits. The most significantly over-represented biological pathway was the peroxisome proliferator-activated receptor (PPAR) signaling pathway. A large number of genomic regions putatively associated with bovine carcass traits were detected using two different statistical approaches. Notably, several significant associations were detected in close proximity to genes with a known role in animal growth such as glucagon and leptin. Several biological pathways, including PPAR signaling, were
Lagesen, Karin; Ussery, David; Wassenaar, Gertrude Maria
conclusions for example about the largest bacterial genome sequenced. Biological diversity is far greater than many have thought. For example, analysis of multiple Escherichia coli genomes has led to an estimate of around 45 000 gene families more genes than are recognized in the human genome. Moreover......There are now more than 1000 sequenced prokaryotic genomes deposited in public databases and available for analysis. Currently, although the sequence databases GenBank, DNA Database of Japan and EMBL are synchronized continually, there are slight differences in content at the genomes level...... for a variety of logistical reasons, including differences in format and loading errors, such as those caused by file transfer protocol interruptions. This means that the 1000th genome will be different in the various databases. Some of the data on the highly accessed web pages are inaccurate, leading to false...
Disz, Terry; Akhter, Sajia; Cuevas, Daniel; Olson, Robert; Overbeek, Ross; Vonstein, Veronika; Stevens, Rick; Edwards, Robert A
The SEED integrates many publicly available genome sequences into a single resource. The database contains accurate and up-to-date annotations based on the subsystems concept that leverages clustering between genomes and other clues to accurately and efficiently annotate microbial genomes. The backend is used as the foundation for many genome annotation tools, such as the Rapid Annotation using Subsystems Technology (RAST) server for whole genome annotation, the metagenomics RAST server for random community genome annotations, and the annotation clearinghouse for exchanging annotations from different resources. In addition to a web user interface, the SEED also provides Web services based API for programmatic access to the data in the SEED, allowing the development of third-party tools and mash-ups. The currently exposed Web services encompass over forty different methods for accessing data related to microbial genome annotations. The Web services provide comprehensive access to the database back end, allowing any programmer access to the most consistent and accurate genome annotations available. The Web services are deployed using a platform independent service-oriented approach that allows the user to choose the most suitable programming platform for their application. Example code demonstrate that Web services can be used to access the SEED using common bioinformatics programming languages such as Perl, Python, and Java. We present a novel approach to access the SEED database. Using Web services, a robust API for access to genomics data is provided, without requiring large volume downloads all at once. The API ensures timely access to the most current datasets available, including the new genomes as soon as they come online.
Gordo, D G M; Espigolan, R; Tonussi, R L; Júnior, G A F; Bresolin, T; Magalhães, A F Braga; Feitosa, F L; Baldi, F; Carvalheiro, R; Tonhati, H; de Oliveira, H N; Chardulo, L A L; de Albuquerque, L G
The objective of this study was to determine whether visual scores used as selection criteria in Nellore breeding programs are effective indicators of carcass traits measured after slaughter. Additionally, this study evaluated the effect of different structures of the relationship matrix ( and ) on the estimation of genetic parameters and on the prediction accuracy of breeding values. There were 13,524 animals for visual scores of conformation (CS), finishing precocity (FP), and muscling (MS) and 1,753, 1,747, and 1,564 for LM area (LMA), backfat thickness (BF), and HCW, respectively. Of these, 1,566 animals were genotyped using a high-density panel containing 777,962 SNP. Six analyses were performed using multitrait animal models, each including the 3 visual scores and 1 carcass trait. For the visual scores, the model included direct additive genetic and residual random effects and the fixed effects of contemporary group (defined by year of birth, management group at yearling, and farm) and the linear effect of age of animal at yearling. The same model was used for the carcass traits, replacing the effect of age of animal at yearling with the linear effect of age of animal at slaughter. The variance and covariance components were estimated by the REML method in analyses using the numerator relationship matrix () or combining the genomic and the numerator relationship matrices (). The heritability estimates for the visual scores obtained with the 2 methods were similar and of moderate magnitude (0.23-0.34), indicating that these traits should response to direct selection. The heritabilities for LMA, BF, and HCW were 0.13, 0.07, and 0.17, respectively, using matrix and 0.29, 0.16, and 0.23, respectively, using matrix . The genetic correlations between the visual scores and carcass traits were positive, and higher correlations were generally obtained when matrix was used. Considering the difficulties and cost of measuring carcass traits postmortem, visual scores of
Full Text Available DNA damage causally contributes to aging and age-related diseases. The declining functioning of tissues and organs during aging can lead to the increased risk of succumbing to aging-associated diseases. Congenital syndromes that are caused by heritable mutations in DNA repair pathways lead to cancer susceptibility and accelerated aging, thus underlining the importance of genome maintenance for withstanding aging. High-throughput mass-spectrometry-based approaches have recently contributed to identifying signalling response networks and gaining a more comprehensive understanding of the physiological adaptations occurring upon unrepaired DNA damage. The insulin-like signalling pathway has been implicated in a DNA damage response (DDR network that includes epidermal growth factor (EGF-, AMP-activated protein kinases (AMPK- and the target of rapamycin (TOR-like signalling pathways, which are known regulators of growth, metabolism, and stress responses. The same pathways, together with the autophagy-mediated proteostatic response and the decline in energy metabolism have also been found to be similarly regulated during natural aging, suggesting striking parallels in the physiological adaptation upon persistent DNA damage due to DNA repair defects and long-term low-level DNA damage accumulation occurring during natural aging. These insights will be an important starting point to study the interplay between signalling networks involved in progeroid syndromes that are caused by DNA repair deficiencies and to gain new understanding of the consequences of DNA damage in the aging process.
Tom Gilbert of the Natural History Museum of Denmark on "Biodiversity monitoring using NGS approaches on unusual substrates" at the 8th Annual Genomics of Energy & Environment Meeting in Walnut Creek, Calif.
Full Text Available Abstract We present here the first use of DNA barcoding in a new approach to ethnobotany we coined "ethnobotany genomics". This new approach is founded on the concept of 'assemblage' of biodiversity knowledge, which includes a coming together of different ways of knowing and valorizing species variation in a novel approach seeking to add value to both traditional knowledge (TK and scientific knowledge (SK. We employed contemporary genomic technology, DNA barcoding, as an important tool for identifying cryptic species, which were already recognized ethnotaxa using the TK classification systems of local cultures in the Velliangiri Hills of India. This research is based on several case studies in our lab, which define an approach to that is poised to evolve quickly with the advent of new ideas and technology. Our results show that DNA barcoding validated several new cryptic plant species to science that were previously recognized by TK classifications of the Irulas and Malasars, and were lumped using SK classification. The contribution of the local aboriginal knowledge concerning plant diversity and utility in India is considerable; our study presents new ethnomedicine to science. Ethnobotany genomics can also be used to determine the distribution of rare species and their ecological requirements, including traditional ecological knowledge so that conservation strategies can be implemented. This is aligned with the Convention on Biological Diversity that was signed by over 150 nations, and thus the world's complex array of human-natural-technological relationships has effectively been re-organized.
Newmaster, Steven G; Ragupathy, Subramanyam
We present here the first use of DNA barcoding in a new approach to ethnobotany we coined "ethnobotany genomics". This new approach is founded on the concept of 'assemblage' of biodiversity knowledge, which includes a coming together of different ways of knowing and valorizing species variation in a novel approach seeking to add value to both traditional knowledge (TK) and scientific knowledge (SK). We employed contemporary genomic technology, DNA barcoding, as an important tool for identifying cryptic species, which were already recognized ethnotaxa using the TK classification systems of local cultures in the Velliangiri Hills of India. This research is based on several case studies in our lab, which define an approach to that is poised to evolve quickly with the advent of new ideas and technology. Our results show that DNA barcoding validated several new cryptic plant species to science that were previously recognized by TK classifications of the Irulas and Malasars, and were lumped using SK classification. The contribution of the local aboriginal knowledge concerning plant diversity and utility in India is considerable; our study presents new ethnomedicine to science. Ethnobotany genomics can also be used to determine the distribution of rare species and their ecological requirements, including traditional ecological knowledge so that conservation strategies can be implemented. This is aligned with the Convention on Biological Diversity that was signed by over 150 nations, and thus the world's complex array of human-natural-technological relationships has effectively been re-organized.
Full Text Available Features such as mutations or structural characteristics can be non-randomly or non-uniformly distributed within a genome. So far, computer simulations were required for statistical inferences on the distribution of sequence motifs. Here, we show that these analyses are possible using an analytical, mathematical approach. For the assessment of non-randomness, our calculations only require information including genome size, number of (sampled sequence motifs and distance parameters. We have developed computer programs evaluating our analytical formulas for the real-time determination of expected values and p-values. This approach permits a flexible cluster definition that can be applied to most effectively identify non-random or non-uniform sequence motif distribution. As an example, we show the effectivity and reliability of our mathematical approach in clinical retroviral vector integration site distribution.
Jiang, Likun; You, Weiwei; Zhang, Xiaojun; Xu, Jian; Jiang, Yanliang; Wang, Kai; Zhao, Zixia; Chen, Baohua; Zhao, Yunfeng; Mahboob, Shahid; Al-Ghanim, Khalid A; Ke, Caihuan; Xu, Peng
The small abalone (Haliotis diversicolor) is one of the most important aquaculture species in East Asia. To facilitate gene cloning and characterization, genome analysis, and genetic breeding of it, we constructed a large-insert bacterial artificial chromosome (BAC) library, which is an important genetic tool for advanced genetics and genomics research. The small abalone BAC library includes 92,610 clones with an average insert size of 120 Kb, equivalent to approximately 7.6× of the small abalone genome. We set up three-dimensional pools and super pools of 18,432 BAC clones for target gene screening using PCR method. To assess the approach, we screened 12 target genes in these 18,432 BAC clones and identified 16 positive BAC clones. Eight positive BAC clones were then sequenced and assembled with the next generation sequencing platform. The assembled contigs representing these 8 BAC clones spanned 928 Kb of the small abalone genome, providing the first batch of genome sequences for genome evaluation and characterization. The average GC content of small abalone genome was estimated as 40.33%. A total of 21 protein-coding genes, including 7 target genes, were annotated into the 8 BACs, which proved the feasibility of PCR screening approach with three-dimensional pools in small abalone BAC library. One hundred fifty microsatellite loci were also identified from the sequences for marker development in the future. The BAC library and clone pools provided valuable resources and tools for genetic breeding and conservation of H. diversicolor.
Vesth, Tammi; Lagesen, Karin; Acar, Öncel; Ussery, David
Today, there are more than a hundred times as many sequenced prokaryotic genomes than were present in the year 2000. The economical sequencing of genomic DNA has facilitated a whole new approach to microbial genomics. The real power of genomics is manifested through comparative genomics that can reveal strain specific characteristics, diversity within species and many other aspects. However, comparative genomics is a field not easily entered into by scientists with few computational skills. The CMG-biotools package is designed for microbiologists with limited knowledge of computational analysis and can be used to perform a number of analyses and comparisons of genomic data. The CMG-biotools system presents a stand-alone interface for comparative microbial genomics. The package is a customized operating system, based on Xubuntu 10.10, available through the open source Ubuntu project. The system can be installed on a virtual computer, allowing the user to run the system alongside any other operating system. Source codes for all programs are provided under GNU license, which makes it possible to transfer the programs to other systems if so desired. We here demonstrate the package by comparing and analyzing the diversity within the class Negativicutes, represented by 31 genomes including 10 genera. The analyses include 16S rRNA phylogeny, basic DNA and codon statistics, proteome comparisons using BLAST and graphical analyses of DNA structures. This paper shows the strength and diverse use of the CMG-biotools system. The system can be installed on a vide range of host operating systems and utilizes as much of the host computer as desired. It allows the user to compare multiple genomes, from various sources using standardized data formats and intuitive visualizations of results. The examples presented here clearly shows that users with limited computational experience can perform complicated analysis without much training.
Wingfield, Brenda D.; Barnes, Irene; Wilhelm de Beer, Z.; De Vos, Lieschen; Duong, Tuan A.; Kanzi, Aquillah M.; Naidoo, Kershney; Nguyen, Hai D.T.; Santana, Quentin C.; Sayari, Mohammad; Seifert, Keith A.; Steenkamp, Emma T.; Trollip, Conrad; van der Merwe, Nicolaas A.; van der Nest, Magriet A.
The genomes of Ceratocystis eucalypticola, Chrysoporthe cubensis, Chrysoporthe deuterocubensis, Davidsoniella virescens, Fusarium temperatum, Graphilbum fragrans, Penicillium nordicum and Thielaviopsis musarum are presented in this genome announcement. These seven genomes are from plant pathogens and otherwise economically important fungal species. The genome sizes range from 28 Mb in the case of T. musarum to 45 Mb for Fusarium temperatum. These genomes include the first reports of genomes f...
Wang, M.J.; Lamberth, K.; Harndahl, M.
are present in the emerging bird flu isolates. Our study demonstrates that present technology enables a fast global screening for T cell immune epitopes of potential diagnostics and vaccine interest. This technology includes immuno-bioinformatics predictors with the capacity to perform fast genome-, pathogen......-, and HLA-wide searches for immune targets. To exploit this new potential, a coordinated international effort to analyze the precious source of information represented by rare patients, such as the current victims of bird flu, would be essential....
Babu, B Kalyana; Dinesh, Pandey; Agrawal, Pawan K; Sood, S; Chandrashekara, C; Bhatt, Jagadish C; Kumar, Anil
The major limiting factor for production and productivity of finger millet crop is blast disease caused by Magnaporthe grisea. Since, the genome sequence information available in finger millet crop is scarce, comparative genomics plays a very important role in identification of genes/QTLs linked to the blast resistance genes using SSR markers. In the present study, a total of 58 genic SSRs were developed for use in genetic analysis of a global collection of 190 finger millet genotypes. The 58 SSRs yielded ninety five scorable alleles and the polymorphism information content varied from 0.186 to 0.677 at an average of 0.385. The gene diversity was in the range of 0.208 to 0.726 with an average of 0.487. Association mapping for blast resistance was done using 104 SSR markers which identified four QTLs for finger blast and one QTL for neck blast resistance. The genomic marker RM262 and genic marker FMBLEST32 were linked to finger blast disease at a P value of 0.007 and explained phenotypic variance (R²) of 10% and 8% respectively. The genomic marker UGEP81 was associated to finger blast at a P value of 0.009 and explained 7.5% of R². The QTLs for neck blast was associated with the genomic SSR marker UGEP18 at a P value of 0.01, which explained 11% of R². Three QTLs for blast resistance were found common by using both GLM and MLM approaches. The resistant alleles were found to be present mostly in the exotic genotypes. Among the genotypes of NW Himalayan region of India, VHC3997, VHC3996 and VHC3930 were found highly resistant, which may be effectively used as parents for developing blast resistant cultivars in the NW Himalayan region of India. The markers linked to the QTLs for blast resistance in the present study can be further used for cloning of the full length gene, fine mapping and their further use in the marker assisted breeding programmes for introgression of blast resistant alleles into locally adapted cultivars.
Burkart-Waco, Diana; Kuppu, Sundaram; Britt, Anne; Chetelat, Roger
Genetic markers are essential when developing or working with genetically variable populations. Indel Group in Genomes (IGG) markers are primer pairs that amplify single-locus sequences that differ in size for two or more alleles. They are attractive for their ease of use for rapid genotyping and their codominant nature. Here, we describe a heuristic algorithm that uses a k-mer-based approach to search two or more genome sequences to locate polymorphic regions suitable for designing candidate IGG marker primers. As input to the IGG pipeline software, the user provides genome sequences and the desired amplicon sizes and size differences. Primer sequences flanking polymorphic insertions/deletions are produced as output. IGG marker files for three sets of genomes, Solanum lycopersicum/Solanum pennellii, Arabidopsis (Arabidopsis thaliana) Columbia-0/Landsberg erecta-0 accessions, and S. lycopersicum/S. pennellii/Solanum tuberosum (three-way polymorphic) are included. PMID:27436831
Arkhipova Irina R
Full Text Available Abstract The third international conference on the genomic impact of eukaryotic transposable elements (TEs was held 24 to 28 February 2012 at the Asilomar Conference Center, Pacific Grove, CA, USA. Sponsored in part by the National Institutes of Health grant 5 P41 LM006252, the goal of the conference was to bring together researchers from around the world who study the impact and mechanisms of TEs using multiple computational and experimental approaches. The meeting drew close to 170 attendees and included invited floor presentations on the biology of TEs and their genomic impact, as well as numerous talks contributed by young scientists. The workshop talks were devoted to computational analysis of TEs with additional time for discussion of unresolved issues. Also, there was ample opportunity for poster presentations and informal evening discussions. The success of the meeting reflects the important role of Repbase in comparative genomic studies, and emphasizes the need for close interactions between experimental and computational biologists in the years to come.
Visel, Axel; Bristow, James; Pennacchio, Len A.
With the availability of genomic sequence from numerousvertebrates, a paradigm shift has occurred in the identification ofdistant-acting gene regulatory elements. In contrast to traditionalgene-centric studies in which investigators randomly scanned genomicfragments that flank genes of interest in functional assays, the modernapproach begins electronically with publicly available comparativesequence datasets that provide investigators with prioritized lists ofputative functional sequences based on their evolutionary conservation.However, although a large number of tools and resources are nowavailable, application of comparative genomic approaches remains far fromtrivial. In particular, it requires users to dynamically consider thespecies and methods for comparison depending on the specific biologicalquestion under investigation. While there is currently no single generalrule to this end, it is clear that when applied appropriately,comparative genomic approaches exponentially increase our power ingenerating biological hypotheses for subsequent experimentaltesting.
Li, Kai; Wang, Gang; Andersen, Troels
Designer nucleases such as TALENS and Cas9 have opened new opportunities to scarlessly edit the mammalian genome. Here we explored several parameters that influence Cas9-mediated scarless genome editing efficiency in murine embryonic stem cells. Optimization of transfection conditions and enrichi...
Lipka, Alexander E.; Lu, Fei; Cherney, Jerome H.; Buckler, Edward S.; Casler, Michael D.; Costich, Denise E.
Switchgrass (Panicum virgatum L.) is a perennial grass undergoing development as a biofuel feedstock. One of the most important factors hindering breeding efforts in this species is the need for accurate measurement of biomass yield on a per-hectare basis. Genomic selection on simple-to-measure traits that approximate biomass yield has the potential to significantly speed up the breeding cycle. Recent advances in switchgrass genomic and phenotypic resources are now making it possible to evaluate the potential of genomic selection of such traits. We leveraged these resources to study the ability of three widely-used genomic selection models to predict phenotypic values of morphological and biomass quality traits in an association panel consisting of predominantly northern adapted upland germplasm. High prediction accuracies were obtained for most of the traits, with standability having the highest ten-fold cross validation prediction accuracy (0.52). Moreover, the morphological traits generally had higher prediction accuracies than the biomass quality traits. Nevertheless, our results suggest that the quality of current genomic and phenotypic resources available for switchgrass is sufficiently high for genomic selection to significantly impact breeding efforts for biomass yield. PMID:25390940
Trevisan, Marta; Palù, Giorgio; Barzon, Luisa
Genome editing by programmable nucleases represents a promising tool that could be exploited to develop new therapeutic strategies to fight infectious diseases. These nucleases, such as zinc-finger nucleases, transcription activator-like effector nucleases, clustered regularly interspaced short palindromic repeat (CRISPR)-CRISPR-associated protein 9 (Cas9) and homing endonucleases, are molecular scissors that can be targeted at predetermined loci in order to modify the genome sequence of an organism. Areas covered: By perturbing genomic DNA at predetermined loci, programmable nucleases can be used as antiviral and antimicrobial treatment. This approach includes targeting of essential viral genes or viral sequences able, once mutated, to inhibit viral replication; repurposing of CRISPR-Cas9 system for lethal self-targeting of bacteria; targeting antibiotic-resistance and virulence genes in bacteria, fungi, and parasites; engineering arthropod vectors to prevent vector-borne infections. Expert commentary: While progress has been done in demonstrating the feasibility of using genome editing as antimicrobial strategy, there are still many hurdles to overcome, such as the risk of off-target mutations, the raising of escape mutants, and the inefficiency of delivery methods, before translating results from preclinical studies into clinical applications.
Iwakawa, Mayumi; Imai, Takashi; Harada, Yoshinobu [National Inst. of Radiological Sciences, Chiba (Japan). Frontier Research Center] [and others
Human health is determined by a complex interplay of factors, predominantly between genetic susceptibility, environmental conditions and aging. The ultimate aim of the RadGenomics (Radiation Genomics) project is to understand the implications of heterogeneity in responses to ionizing radiation arising from genetic variation between individuals in the human population. The rapid progression of the human genome sequencing and the recent development of new technologies in molecular genetics are providing us with new opportunities to understand the genetic basis of individual differences in susceptibility to natural and/or artificial environmental factors, including radiation exposure. The RadGenomics project will inevitably lead to improved protocols for personalized radiotherapy and reductions in the potential side effects of such treatment. The project will contribute to future research into the molecular mechanisms of radiation sensitivity in humans and will stimulate the development of new high-throughput technologies for a broader application of biological and medical sciences. The staff members are specialists in a variety of fields, including genome science, radiation biology, medical science, molecular biology, and informatics, and have joined the RadGenomics project from various universities, companies, and research institutes. The project started in April 2001. (author)
Iwakawa, Mayumi; Imai, Takashi; Harada, Yoshinobu
Human health is determined by a complex interplay of factors, predominantly between genetic susceptibility, environmental conditions and aging. The ultimate aim of the RadGenomics (Radiation Genomics) project is to understand the implications of heterogeneity in responses to ionizing radiation arising from genetic variation between individuals in the human population. The rapid progression of the human genome sequencing and the recent development of new technologies in molecular genetics are providing us with new opportunities to understand the genetic basis of individual differences in susceptibility to natural and/or artificial environmental factors, including radiation exposure. The RadGenomics project will inevitably lead to improved protocols for personalized radiotherapy and reductions in the potential side effects of such treatment. The project will contribute to future research into the molecular mechanisms of radiation sensitivity in humans and will stimulate the development of new high-throughput technologies for a broader application of biological and medical sciences. The staff members are specialists in a variety of fields, including genome science, radiation biology, medical science, molecular biology, and informatics, and have joined the RadGenomics project from various universities, companies, and research institutes. The project started in April 2001. (author)
Genomes with their complexity and size present what appears to be an impossible challenge. Scientists speak in terms of decades or even centuries before we will understand how genomes and their hosts the cell and the city of cells that make up the multicellular context function. We believe that there will be surprisingly quick progress made in our understanding of genomes. The key is to stop taking the Central Dogma as the only direction in which genome research can scale the semantics of genomes. Instead a top-down approach coupled with a bottom-up approach may snare the unwieldy beast and make sense of genomes. The method we propose is to take in silico biology seriously. By developing in silico models of genomes cells and multicellular systems, we position ourselves to develop a theory of meaning for artificial genomes. Then using that develop a natural semantics of genomes.
Cuomo, Christina A
Comparative genome sequencing studies of human fungal pathogens enable identification of genes and variants associated with virulence and drug resistance. This review describes current approaches, resources, and advances in applying whole genome sequencing to study clinically important fungal pathogens. Genomes for some important fungal pathogens were only recently assembled, revealing gene family expansions in many species and extreme gene loss in one obligate species. The scale and scope of species sequenced is rapidly expanding, leveraging technological advances to assemble and annotate genomes with higher precision. By using iteratively improved reference assemblies or those generated de novo for new species, recent studies have compared the sequence of isolates representing populations or clinical cohorts. Whole genome approaches provide the resolution necessary for comparison of closely related isolates, for example, in the analysis of outbreaks or sampled across time within a single host. Genomic analysis of fungal pathogens has enabled both basic research and diagnostic studies. The increased scale of sequencing can be applied across populations, and new metagenomic methods allow direct analysis of complex samples.
Manivannan, Abinaya; Kim, Jin-Hee; Yang, Eun-Young; Ahn, Yul-Kyun; Lee, Eun-Su; Choi, Sena; Kim, Do-Sun
Pepper is an economically important horticultural plant that has been widely used for its pungency and spicy taste in worldwide cuisines. Therefore, the domestication of pepper has been carried out since antiquity. Owing to meet the growing demand for pepper with high quality, organoleptic property, nutraceutical contents, and disease tolerance, genomics assisted breeding techniques can be incorporated to develop novel pepper varieties with desired traits. The application of next-generation sequencing (NGS) approaches has reformed the plant breeding technology especially in the area of molecular marker assisted breeding. The availability of genomic information aids in the deeper understanding of several molecular mechanisms behind the vital physiological processes. In addition, the NGS methods facilitate the genome-wide discovery of DNA based markers linked to key genes involved in important biological phenomenon. Among the molecular markers, single nucleotide polymorphism (SNP) indulges various benefits in comparison with other existing DNA based markers. The present review concentrates on the impact of NGS approaches in the discovery of useful SNP markers associated with pungency and disease resistance in pepper. The information provided in the current endeavor can be utilized for the betterment of pepper breeding in future.
Full Text Available Pepper is an economically important horticultural plant that has been widely used for its pungency and spicy taste in worldwide cuisines. Therefore, the domestication of pepper has been carried out since antiquity. Owing to meet the growing demand for pepper with high quality, organoleptic property, nutraceutical contents, and disease tolerance, genomics assisted breeding techniques can be incorporated to develop novel pepper varieties with desired traits. The application of next-generation sequencing (NGS approaches has reformed the plant breeding technology especially in the area of molecular marker assisted breeding. The availability of genomic information aids in the deeper understanding of several molecular mechanisms behind the vital physiological processes. In addition, the NGS methods facilitate the genome-wide discovery of DNA based markers linked to key genes involved in important biological phenomenon. Among the molecular markers, single nucleotide polymorphism (SNP indulges various benefits in comparison with other existing DNA based markers. The present review concentrates on the impact of NGS approaches in the discovery of useful SNP markers associated with pungency and disease resistance in pepper. The information provided in the current endeavor can be utilized for the betterment of pepper breeding in future.
S.L. Smits (Saskia); R. Bodewes (Rogier); A. Ruiz-Gonzalez (Aritz); V. Baumgärtner (Volkmar); M.P.G. Koopmans D.V.M. (Marion); A.D.M.E. Osterhaus (Albert); A. Schürch (Anita)
textabstractViral infections remain a serious global health issue. Metagenomic approaches are increasingly used in the detection of novel viral pathogens but also to generate complete genomes of uncultivated viruses. In silico identification of complete viral genomes from sequence data would allow
Robert J. Redden
Full Text Available Pea (Pisum sativum L. was the original model organism used in Mendel’s discovery (1866 of the laws of inheritance, making it the foundation of modern plant genetics. However, subsequent progress in pea genomics has lagged behind many other plant species. Although the size and repetitive nature of the pea genome has so far restricted its sequencing, comprehensive genomic and post genomic resources already exist. These include BAC libraries, several types of molecular marker sets, both transcriptome and proteome datasets and mutant populations for reverse genetics. The availability of the full genome sequences of three legume species has offered significant opportunities for genome wide comparison revealing synteny and co-linearity to pea. A combination of a candidate gene and colinearity approach has successfully led to the identification of genes underlying agronomically important traits including virus resistances and plant architecture. Some of this knowledge has already been applied to marker assisted selection (MAS programs, increasing precision and shortening the breeding cycle. Yet, complete translation of marker discovery to pea breeding is still to be achieved. Molecular analysis of pea collections has shown that although substantial variation is present within the cultivated genepool, wild material offers the possibility to incorporate novel traits that may have been inadvertently eliminated. Association mapping analysis of diverse pea germplasm promises to identify genetic variation related to desirable agronomic traits, which are historically difficult to breed for in a traditional manner. The availability of high throughput ‘omics’ methodologies offers great promise for the development of novel, highly accurate selective breeding tools for improved pea genotypes that are sustainable under current and future climates and farming systems.
Nair, Nidhi; Shoaib, Muhammad; Sørensen, Claus Storgaard
Genomic DNA is compacted into chromatin through packaging with histone and non-histone proteins. Importantly, DNA accessibility is dynamically regulated to ensure genome stability. This is exemplified in the response to DNA damage where chromatin relaxation near genomic lesions serves to promote...... access of relevant enzymes to specific DNA regions for signaling and repair. Furthermore, recent data highlight genome maintenance roles of chromatin through the regulation of endogenous DNA-templated processes including transcription and replication. Here, we review research that shows the importance...... of chromatin structure regulation in maintaining genome integrity by multiple mechanisms including facilitating DNA repair and directly suppressing endogenous DNA damage....
Nivard, Michel G.; Middeldorp, Christel M.; Lubke, Gitta; Hottenga, Jouke-Jan; Abdellaoui, Abdel; Boomsma, Dorret I.; Dolan, Conor V.
Heritability may be estimated using phenotypic data collected in relatives or in distantly related individuals using genome-wide single nucleotide polymorphism (SNP) data. We combined these approaches by re-parameterizing the model proposed by Zaitlen et al and extended this model to include
Stella, Stefano; Montoya, Guillermo
-Cas system has become the main tool for genome editing in many laboratories. Currently the targeted genome editing technology has been used in many fields and may be a possible approach for human gene therapy. Furthermore, it can also be used to modifying the genomes of model organisms for studying human......In the last 10 years, we have witnessed a blooming of targeted genome editing systems and applications. The area was revolutionized by the discovery and characterization of the transcription activator-like effector proteins, which are easier to engineer to target new DNA sequences than...... sequence). This ribonucleoprotein complex protects bacteria from invading DNAs, and it was adapted to be used in genome editing. The CRISPR ribonucleic acid (RNA) molecule guides to the specific DNA site the Cas9 nuclease to cleave the DNA target. Two years and more than 1000 publications later, the CRISPR...
Throughout the human genome millions of places exist where humans differ gentically. The aim of this PhD thesis was to systematically assess this genetic variation and its biological consequences in a genome-wide way, through the utilization of DNA oligonucleotide arrays that assess hundres of
Full Text Available BACKGROUND: Metaviriomes, the viral genomes present in an environment, have been studied by direct sequencing of the viral DNA or by cloning in small insert libraries. The short reads generated by both approaches make it very difficult to assemble and annotate such flexible genomic entities. Many environmental viruses belong to unknown groups or prey on uncultured and little known cellular lineages, and hence might not be present in databases. METHODOLOGY AND PRINCIPAL FINDINGS: Here we have used a different approach, the cloning of viral DNA into fosmids before sequencing, to obtain natural contigs that are close to the size of a viral genome. We have studied a relatively low diversity extreme environment: saturated NaCl brines, which simplifies the analysis and interpretation of the data. Forty-two different viral genomes were retrieved, and some of these were almost complete, and could be tentatively identified as head-tail phages (Caudovirales. CONCLUSIONS AND SIGNIFICANCE: We found a cluster of phage genomes that most likely infect Haloquadratum walsbyi, the square archaeon and major component of the community in these hypersaline habitats. The identity of the prey could be confirmed by the presence of CRISPR spacer sequences shared by the virus and one of the available strain genomes. Other viral clusters detected appeared to prey on the Nanohaloarchaea and on the bacterium Salinibacter ruber, covering most of the diversity of microbes found in this type of environment. This approach appears then as a viable alternative to describe metaviriomes in a much more detailed and reliable way than by the more common approaches based on direct sequencing. An example of transfer of a CRISPR cluster including repeats and spacers was accidentally found supporting the dynamic nature and frequent transfer of this peculiar prokaryotic mechanism of cell protection.
Badouin, Hélène; Gouzy, Jérôme; Grassa, Christopher J; Murat, Florent; Staton, S Evan; Cottret, Ludovic; Lelandais-Brière, Christine; Owens, Gregory L; Carrère, Sébastien; Mayjonade, Baptiste; Legrand, Ludovic; Gill, Navdeep; Kane, Nolan C; Bowers, John E; Hubner, Sariel; Bellec, Arnaud; Bérard, Aurélie; Bergès, Hélène; Blanchet, Nicolas; Boniface, Marie-Claude; Brunel, Dominique; Catrice, Olivier; Chaidir, Nadia; Claudel, Clotilde; Donnadieu, Cécile; Faraut, Thomas; Fievet, Ghislain; Helmstetter, Nicolas; King, Matthew; Knapp, Steven J; Lai, Zhao; Le Paslier, Marie-Christine; Lippi, Yannick; Lorenzon, Lolita; Mandel, Jennifer R; Marage, Gwenola; Marchand, Gwenaëlle; Marquand, Elodie; Bret-Mestries, Emmanuelle; Morien, Evan; Nambeesan, Savithri; Nguyen, Thuy; Pegot-Espagnet, Prune; Pouilly, Nicolas; Raftis, Frances; Sallet, Erika; Schiex, Thomas; Thomas, Justine; Vandecasteele, Céline; Varès, Didier; Vear, Felicity; Vautrin, Sonia; Crespi, Martin; Mangin, Brigitte; Burke, John M; Salse, Jérôme; Muños, Stéphane; Vincourt, Patrick; Rieseberg, Loren H; Langlade, Nicolas B
The domesticated sunflower, Helianthus annuus L., is a global oil crop that has promise for climate change adaptation, because it can maintain stable yields across a wide variety of environmental conditions, including drought. Even greater resilience is achievable through the mining of resistance alleles from compatible wild sunflower relatives, including numerous extremophile species. Here we report a high-quality reference for the sunflower genome (3.6 gigabases), together with extensive transcriptomic data from vegetative and floral organs. The genome mostly consists of highly similar, related sequences and required single-molecule real-time sequencing technologies for successful assembly. Genome analyses enabled the reconstruction of the evolutionary history of the Asterids, further establishing the existence of a whole-genome triplication at the base of the Asterids II clade and a sunflower-specific whole-genome duplication around 29 million years ago. An integrative approach combining quantitative genetics, expression and diversity data permitted development of comprehensive gene networks for two major breeding traits, flowering time and oil metabolism, and revealed new candidate genes in these networks. We found that the genomic architecture of flowering time has been shaped by the most recent whole-genome duplication, which suggests that ancient paralogues can remain in the same regulatory networks for dozens of millions of years. This genome represents a cornerstone for future research programs aiming to exploit genetic diversity to improve biotic and abiotic stress resistance and oil production, while also considering agricultural constraints and human nutritional needs.
Spencer, Amy V; Cox, Angela; Lin, Wei-Yu; Easton, Douglas F; Michailidou, Kyriaki; Walters, Kevin
There is a large amount of functional genetic data available, which can be used to inform fine-mapping association studies (in diseases with well-characterised disease pathways). Single nucleotide polymorphism (SNP) prioritization via Bayes factors is attractive because prior information can inform the effect size or the prior probability of causal association. This approach requires the specification of the effect size. If the information needed to estimate a priori the probability density for the effect sizes for causal SNPs in a genomic region isn't consistent or isn't available, then specifying a prior variance for the effect sizes is challenging. We propose both an empirical method to estimate this prior variance, and a coherent approach to using SNP-level functional data, to inform the prior probability of causal association. Through simulation we show that when ranking SNPs by our empirical Bayes factor in a fine-mapping study, the causal SNP rank is generally as high or higher than the rank using Bayes factors with other plausible values of the prior variance. Importantly, we also show that assigning SNP-specific prior probabilities of association based on expert prior functional knowledge of the disease mechanism can lead to improved causal SNPs ranks compared to ranking with identical prior probabilities of association. We demonstrate the use of our methods by applying the methods to the fine mapping of the CASP8 region of chromosome 2 using genotype data from the Collaborative Oncological Gene-Environment Study (COGS) Consortium. The data we analysed included approximately 46,000 breast cancer case and 43,000 healthy control samples. © 2016 The Authors. *Genetic Epidemiology published by Wiley Periodicals, Inc.
The JGI Fungal Genomics Program aims to scale up sequencing and analysis of fungal genomes to explore the diversity of fungi important for energy and the environment, and to promote functional studies on a system level. Combining new sequencing technologies and comparative genomics tools, JGI is now leading the world in fungal genome sequencing and analysis. Over 120 sequenced fungal genomes with analytical tools are available via MycoCosm (www.jgi.doe.gov/fungi), a web-portal for fungal biologists. Our model of interacting with user communities, unique among other sequencing centers, helps organize these communities, improves genome annotation and analysis work, and facilitates new larger-scale genomic projects. This resulted in 20 high-profile papers published in 2011 alone and contributing to the Genomics Encyclopedia of Fungi, which targets fungi related to plant health (symbionts, pathogens, and biocontrol agents) and biorefinery processes (cellulose degradation, sugar fermentation, industrial hosts). Our next grand challenges include larger scale exploration of fungal diversity (1000 fungal genomes), developing molecular tools for DOE-relevant model organisms, and analysis of complex systems and metagenomes.
Kersey, Paul J; Staines, Daniel M; Lawson, Daniel; Kulesha, Eugene; Derwent, Paul; Humphrey, Jay C; Hughes, Daniel S T; Keenan, Stephan; Kerhornou, Arnaud; Koscielny, Gautier; Langridge, Nicholas; McDowall, Mark D; Megy, Karine; Maheswari, Uma; Nuhn, Michael; Paulini, Michael; Pedro, Helder; Toneva, Iliana; Wilson, Derek; Yates, Andrew; Birney, Ewan
Ensembl Genomes (http://www.ensemblgenomes.org) is an integrative resource for genome-scale data from non-vertebrate species. The project exploits and extends technology (for genome annotation, analysis and dissemination) developed in the context of the (vertebrate-focused) Ensembl project and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. Since its launch in 2009, Ensembl Genomes has undergone rapid expansion, with the goal of providing coverage of all major experimental organisms, and additionally including taxonomic reference points to provide the evolutionary context in which genes can be understood. Against the backdrop of a continuing increase in genome sequencing activities in all parts of the tree of life, we seek to work, wherever possible, with the communities actively generating and using data, and are participants in a growing range of collaborations involved in the annotation and analysis of genomes.
Lilje, Berit; Rasmussen, Rasmus Vedby; Dahl, Anders
Most Staphylococcus aureus isolates can cause invasive disease given the right circumstances, but it is unknown if some isolates are more likely to cause severe infections than others. S. aureus bloodstream isolates from 120 patients with definite infective endocarditis and 121 with S. aureus...... bacteraemia without infective endocarditis underwent whole-genome sequencing. Genome-wide association analysis was performed using a variety of bioinformatics approaches including SNP analysis, accessory genome analysis and k-mer based analysis. Core and accessory genome analyses found no association...... with either of the two clinical groups. In this study, the genome sequences of S. aureus bloodstream isolates did not discriminate between bacteraemia and infective endocarditis. Based on our study and the current literature, it is not convincing that a specific S. aureus genotype is clearly associated...
Organ, Chris L; Brusatte, Stephen L; Stein, Koen
Sauropodomorph dinosaurs include the largest land animals to have ever lived, some reaching up to 10 times the mass of an African elephant. Despite their status defining the upper range for body size in land animals, it remains unknown whether sauropodomorphs evolved larger-sized genomes than non-avian theropods, their sister taxon, or whether a relationship exists between genome size and body size in dinosaurs, two questions critical for understanding broad patterns of genome evolution in dinosaurs. Here we report inferences of genome size for 10 sauropodomorph taxa. The estimates are derived from a Bayesian phylogenetic generalized least squares approach that generates posterior distributions of regression models relating genome size to osteocyte lacunae volume in extant tetrapods. We estimate that the average genome size of sauropodomorphs was 2.02 pg (range of species means: 1.77-2.21 pg), a value in the upper range of extant birds (mean = 1.42 pg, range: 0.97-2.16 pg) and near the average for extant non-avian reptiles (mean = 2.24 pg, range: 1.05-5.44 pg). The results suggest that the variation in size and architecture of genomes in extinct dinosaurs was lower than the variation found in mammals. A substantial difference in genome size separates the two major clades within dinosaurs, Ornithischia (large genomes) and Saurischia (moderate to small genomes). We find no relationship between body size and estimated genome size in extinct dinosaurs, which suggests that neutral forces did not dominate the evolution of genome size in this group.
Genome resource banking is the systematic collection, storage, and redistribution of biomaterials in an organized, logistical, and secure manner. Genome cryobanks usually contain biomaterials and associated genomic information essential for progression of biomedicine, human health, and research. In that regard, appropriate genome cryobanks could provide essential biomaterials for both current and future research projects in the form of various cell types and tissues, including sperm, oocytes, embryos, embryonic or adult stem cells, induced pluripotent stem cells, and gonadal tissues. In addition to cryobanked germplasm, cryobanking of DNA, serum, blood products, and tissues from scientifically, economically, and ecologically important species has become a common practice. For revitalization of the whole organism, cryopreserved germplasm in conjunction with assisted reproductive technologies, offer a powerful approach for research model management, as well as assisting in animal production for agriculture, conservation, and human reproductive medicine. Recently, many developed and developing countries have allocated substantial resources to establish genome resources banks which are responsible for safeguarding scientifically, economically, and ecologically important wild type, mutant, and transgenic plants, fish, and local livestock breeds, as well as wildlife species. This review is dedicated to the memory of Dr. John K. Critser, who has made profound contributions to the science of cryobiology and establishment of genome research and resources centers for mice, rats, and swine. Emphasis will be given to application of genome resource banks to species with substantial contributions to the advancement of biomedicine and human health. Copyright © 2012 Elsevier Inc. All rights reserved.
Card, Daren C; Schield, Drew R; Reyes-Velasco, Jacobo; Fujita, Matthew K; Andrew, Audra L; Oyler-McCance, Sara J; Fike, Jennifer A; Tomback, Diana F; Ruggiero, Robert P; Castoe, Todd A
As a greater number and diversity of high-quality vertebrate reference genomes become available, it is increasingly feasible to use these references to guide new draft assemblies for related species. Reference-guided assembly approaches may substantially increase the contiguity and completeness of a new genome using only low levels of genome coverage that might otherwise be insufficient for de novo genome assembly. We used low-coverage (∼3.5-5.5x) Illumina paired-end sequencing to assemble draft genomes of two bird species (the Gunnison Sage-Grouse, Centrocercus minimus, and the Clark's Nutcracker, Nucifraga columbiana). We used these data to estimate de novo genome assemblies and reference-guided assemblies, and compared the information content and completeness of these assemblies by comparing CEGMA gene set representation, repeat element content, simple sequence repeat content, and GC isochore structure among assemblies. Our results demonstrate that even lower-coverage genome sequencing projects are capable of producing informative and useful genomic resources, particularly through the use of reference-guided assemblies.
Card, Daren C.; Schield, Drew R.; Reyes-Velasco, Jacobo; Fujita, Matthre K.; Andrew, Audra L.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Tomback, Diana F.; Ruggiero, Robert P.; Castoe, Todd A.
As a greater number and diversity of high-quality vertebrate reference genomes become available, it is increasingly feasible to use these references to guide new draft assemblies for related species. Reference-guided assembly approaches may substantially increase the contiguity and completeness of a new genome using only low levels of genome coverage that might otherwise be insufficient for de novo genome assembly. We used low-coverage (~3.5–5.5x) Illumina paired-end sequencing to assemble draft genomes of two bird species (the Gunnison Sage-Grouse, Centrocercus minimus, and the Clark's Nutcracker, Nucifraga columbiana). We used these data to estimate de novo genome assemblies and reference-guided assemblies, and compared the information content and completeness of these assemblies by comparing CEGMA gene set representation, repeat element content, simple sequence repeat content, and GC isochore structure among assemblies. Our results demonstrate that even lower-coverage genome sequencing projects are capable of producing informative and useful genomic resources, particularly through the use of reference-guided assemblies.
Huynh, H. T.
We introduce a new approach to high-order accuracy for the numerical solution of diffusion problems by solving the equations in differential form using a reconstruction technique. The approach has the advantages of simplicity and economy. It results in several new high-order methods including a simplified version of discontinuous Galerkin (DG). It also leads to new definitions of common value and common gradient quantities at each interface shared by the two adjacent cells. In addition, the new approach clarifies the relations among the various choices of new and existing common quantities. Fourier stability and accuracy analyses are carried out for the resulting schemes. Extensions to the case of quadrilateral meshes are obtained via tensor products. For the two-point boundary value problem (steady state), it is shown that these schemes, which include most popular DG methods, yield exact common interface quantities as well as exact cell average solutions for nearly all cases.
Zhu, Xiaoxiao; Xu, Yajie; Yu, Shanshan; Lu, Lu; Ding, Mingqin; Cheng, Jing; Song, Guoxu; Gao, Xing; Yao, Liangming; Fan, Dongdong; Meng, Shu; Zhang, Xuewen; Hu, Shengdi; Tian, Yong
The rapid generation of various species and strains of laboratory animals using CRISPR/Cas9 technology has dramatically accelerated the interrogation of gene function in vivo. So far, the dominant approach for genotyping of genome-modified animals has been the T7E1 endonuclease cleavage assay. Here, we present a polyacrylamide gel electrophoresis-based (PAGE) method to genotype mice harboring different types of indel mutations. We developed 6 strains of genome-modified mice using CRISPR/Cas9 system, and utilized this approach to genotype mice from F0 to F2 generation, which included single and multiplexed genome-modified mice. We also determined the maximal detection sensitivity for detecting mosaic DNA using PAGE-based assay as 0.5%. We further applied PAGE-based genotyping approach to detect CRISPR/Cas9-mediated on- and off-target effect in human 293T and induced pluripotent stem cells (iPSCs). Thus, PAGE-based genotyping approach meets the rapidly increasing demand for genotyping of the fast-growing number of genome-modified animals and human cell lines created using CRISPR/Cas9 system or other nuclease systems such as TALEN or ZFN.
Canver, Matthew C; Bauer, Daniel E; Orkin, Stuart H
Methodologies to interrogate non-coding regions have lagged behind coding regions despite comprising the vast majority of the genome. However, the rapid evolution of clustered regularly interspaced short palindromic repeats (CRISPR)-based genome editing has provided a multitude of novel techniques for laboratory investigation including significant contributions to the toolbox for studying non-coding DNA. CRISPR-mediated loss-of-function strategies rely on direct disruption of the underlying sequence or repression of transcription without modifying the targeted DNA sequence. CRISPR-mediated gain-of-function approaches similarly benefit from methods to alter the targeted sequence through integration of customized sequence into the genome as well as methods to activate transcription. Here we review CRISPR-based loss- and gain-of-function techniques for the interrogation of non-coding DNA. Copyright © 2017 Elsevier Inc. All rights reserved.
Roth, Bryan L; Kroeze, Wesley K
G-protein-coupled receptors (GPCRs) are frequent and fruitful targets for drug discovery and development, as well as being off-targets for the side effects of a variety of medications. Much of the druggable non-olfactory human GPCR-ome remains under-interrogated, and we present here various approaches that we and others have used to shine light into these previously dark corners of the human genome. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.
Boffelli, Dario; Weer, Claire V.; Weng, Li; Lewis, Keith D.; Shoukry, Malak I.; Pachter, Lior; Keys, David N.; Rubin, Edward M.
Analysis of sequence variation among members of a single species offers a potential approach to identify functional DNA elements responsible for biological features unique to that species. Due to its high rate of allelic polymorphism and ease of genetic manipulability, we chose the sea squirt, Ciona intestinalis, to explore intra-species sequence comparisons for genome annotation. A large number of C. intestinalis specimens were collected from four continents and a set of genomic intervals amplified, resequenced and analyzed to determine the mutation rates at each nucleotide in the sequence. We found that regions with low mutation rates efficiently demarcated functionally constrained sequences: these include a set of noncoding elements, which we showed in C intestinalis transgenic assays to act as tissue-specific enhancers, as well as the location of coding sequences. This illustrates that comparisons of multiple members of a species can be used for genome annotation, suggesting a path for the annotation of the sequenced genomes of organisms occupying uncharacterized phylogenetic branches of the animal kingdom and raises the possibility that the resequencing of a large number of Homo sapiens individuals might be used to annotate the human genome and identify sequences defining traits unique to our species. The sequence data from this study has been submitted to GenBank under accession nos. AY667278-AY667407.
Utturkar, Sagar M; Klingeman, Dawn M; Hurt, Richard A; Brown, Steven D
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.
Weitzel, Kristin Wiisanen; Alexander, Madeline; Bernhardt, Barbara A; Calman, Neil; Carey, David J; Cavallari, Larisa H; Field, Julie R; Hauser, Diane; Junkins, Heather A; Levin, Phillip A; Levy, Kenneth; Madden, Ebony B; Manolio, Teri A; Odgis, Jacqueline; Orlando, Lori A; Pyeritz, Reed; Wu, R Ryanne; Shuldiner, Alan R; Bottinger, Erwin P; Denny, Joshua C; Dexter, Paul R; Flockhart, David A; Horowitz, Carol R; Johnson, Julie A; Kimmel, Stephen E; Levy, Mia A; Pollin, Toni I; Ginsburg, Geoffrey S
Patients, clinicians, researchers and payers are seeking to understand the value of using genomic information (as reflected by genotyping, sequencing, family history or other data) to inform clinical decision-making. However, challenges exist to widespread clinical implementation of genomic medicine, a prerequisite for developing evidence of its real-world utility. To address these challenges, the National Institutes of Health-funded IGNITE (Implementing GeNomics In pracTicE; www.ignite-genomics.org ) Network, comprised of six projects and a coordinating center, was established in 2013 to support the development, investigation and dissemination of genomic medicine practice models that seamlessly integrate genomic data into the electronic health record and that deploy tools for point of care decision making. IGNITE site projects are aligned in their purpose of testing these models, but individual projects vary in scope and design, including exploring genetic markers for disease risk prediction and prevention, developing tools for using family history data, incorporating pharmacogenomic data into clinical care, refining disease diagnosis using sequence-based mutation discovery, and creating novel educational approaches. This paper describes the IGNITE Network and member projects, including network structure, collaborative initiatives, clinical decision support strategies, methods for return of genomic test results, and educational initiatives for patients and providers. Clinical and outcomes data from individual sites and network-wide projects are anticipated to begin being published over the next few years. The IGNITE Network is an innovative series of projects and pilot demonstrations aiming to enhance translation of validated actionable genomic information into clinical settings and develop and use measures of outcome in response to genome-based clinical interventions using a pragmatic framework to provide early data and proofs of concept on the utility of these
Ulianov, Sergey V; Tachibana-Konwalski, Kikue; Razin, Sergey V
Recent years have witnessed an explosion of the single-cell biochemical toolbox including chromosome conformation capture (3C)-based methods that provide novel insights into chromatin spatial organization in individual cells. The observations made with these techniques revealed that topologically associating domains emerge from cell population averages and do not exist as static structures in individual cells. Stochastic nature of the genome folding is likely to be biologically relevant and may reflect the ability of chromatin fibers to adopt a number of alternative configurations, some of which could be transiently stabilized and serve regulatory purposes. Single-cell Hi-C approaches provide an opportunity to analyze chromatin folding in rare cell types such as stem cells, tumor progenitors, oocytes, and totipotent cells, contributing to a deeper understanding of basic mechanisms in development and disease. Here, we review key findings of single-cell Hi-C and discuss possible biological reasons and consequences of the inferred dynamic chromatin spatial organization. © 2017 WILEY Periodicals, Inc.
Full Text Available Lactobacillae are gram positive diverse group of species and have association with nutrient rich niches like humans, animals and plants. Lactobacillus casei is considered as one of the most competent probiotic throughout the world. Its microbiological feature historically well-established but genomic analysis including comparative genomics is recent. Lactobacillus casei Lbs2 strain was isolated from the gut of a healthy north Indian individual and sequenced. We compared the genomes of Lactobacillus casei Lbs2 with 8 other complete genomes of the same species e.g.; LC2W, BL23, BDII, W56, 12A, Zhang, LOCK919, ATCC393 using BRIG (Blast Ring Image Generator, Gene enrichment analysis using Fischer Extract test in R. Lbs2 strain has a number of genes including bile tolerance, stress response re-iterating its probiotic stand. Interestingly, genes coding for transposons, co-enzyme transport and metabolisms are enriched in the Indian Genome. Presence of large number of transposons indicates this genome is undergoing expansion and under adaptive selection pressure. When we compared our genome based on Multilocus Sequence Typing (rMLST, we found this strain is closely similar to Lactobacillus fermentum rather than other L. casei strains. Comparison of Lbs2 strain with other L. casei strains indicates ATCC393 (isolated from daily product is closer than others.
Bovo, Samuele; Mazzoni, Gianluca; Ribani, Anisa
Shot-gun next generation sequencing (NGS) on whole DNA extracted from specimens collected from mammals often produces reads that are not mapped (i.e. unmapped reads) on the host reference genome and that are usually discarded as by-products of the experiments. In this study, we mined Ion Torrent...... reads obtained by sequencing DNA isolated from archived blood samples collected from 100 performance tested Italian Large White pigs. Two reduced representation libraries were prepared from two DNA pools constructed each from 50 equimolar DNA samples. Bioinformatic analyses were carried out to mine...... unmapped reads on the reference pig genome that were obtained from the two NGS datasets. In silico analyses included read mapping and sequence assembly approaches for a viral metagenomic analysis using the NCBI Viral Genome Resource. Our approach identified sequences matching several viruses...
Wang, Tao; Guan, Guiquan; Korhonen, Pasi K; Koehler, Anson V; Hall, Ross S; Young, Neil D; Yin, Hong; Gasser, Robin B
The apicoplast (ap) is a unique, non-photosynthetic organelle found in most apicomplexan parasites. Due to the essential roles that this organelle has, it has been widely considered as target for drugs against diseases caused by apicomplexans. Exploring the ap genomes of such parasites would provide a better understanding of their systematics and their basic molecular biology for therapeutics. However, there is limited information available on the ap genomes of apicomplexan parasites. In the present study, the ap genomes of two operational taxonomic units of Babesia (known as Babesia sp. Lintan [Bl] and Babesia sp. Xinjiang [Bx]) from sheep were sequenced, assembled and annotated using a massive parallel sequencing-based approach. Then, the gene content and gene order in these ap genomes (∼30.7kb in size) were defined and compared, and the genetic differences were assessed. In addition, a phylogenetic analysis of ap genomic data sets was carried out to assess the relationships of these taxonomic units with other apicomplexan parasites for which complete ap genomic data sets were publicly available. The results showed that the ap genomes of Bl and Bx encode 59 and 57 genes, respectively, including 2 ribosomal RNA genes, 25 transfer RNA genes and 30-32 protein-encoding genes, being similar in content to those of Babesia bovis and B. orientalis. Ap gene regions that might serve as markers for future epidemiological and population genetic studies of Babesia species were identified. Using sequence data for a subset of six protein-encoding genes, a close relationship of Bl and Bx with Babesia bovis from cattle and B. orientalis from water buffalo was inferred. Although the focus of the present study was on Babesia, we propose that the present sequencing-bioinformatic approach should be applicable to organellar genomes of a wide range of apicomplexans of veterinary importance. Copyright © 2016 Elsevier B.V. All rights reserved.
Dorman, Stephanie N.; Shirley, Ben C.; Knoll, Joan H. M.; Rogan, Peter K.
Diagnostic DNA hybridization relies on probes composed of single copy (sc) genomic sequences. Sc sequences in probe design ensure high specificity and avoid cross-hybridization to other regions of the genome, which could lead to ambiguous results that are difficult to interpret. We examine how the distribution and composition of repetitive sequences in the genome affects sc probe performance. A divide and conquer algorithm was implemented to design sc probes. With this approach, sc probes can include divergent repetitive elements, which hybridize to unique genomic targets under higher stringency experimental conditions. Genome-wide custom probe sets were created for fluorescent in situ hybridization (FISH) and microarray genomic hybridization. The scFISH probes were developed for detection of copy number changes within small tumour suppressor genes and oncogenes. The microarrays demonstrated increased reproducibility by eliminating cross-hybridization to repetitive sequences adjacent to probe targets. The genome-wide microarrays exhibited lower median coefficients of variation (17.8%) for two HapMap family trios. The coefficients of variations of commercial probes within 300 nt of a repetitive element were 48.3% higher than the nearest custom probe. Furthermore, the custom microarray called a chromosome 15q11.2q13 deletion more consistently. This method for sc probe design increases probe coverage for FISH and lowers variability in genomic microarrays. PMID:23376933
Mauldin, Denise; Hood, Leroy; Robinson, Max; Glusman, Gustavo
We present an ultra-fast method for comparing personal genomes. We transform the standard genome representation (lists of variants relative to a reference) into 'genome fingerprints' that can be readily compared across sequencing technologies and reference versions. Because of their reduced size, computation on the genome fingerprints is fast and requires little memory. This enables scaling up a variety of important genome analyses, including quantifying relatedness, recognizing duplicative s...
Brilli, Matteo; Liò, Pietro; Lacroix, Vincent; Sagot, Marie-France
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
Staunton, Ciara; Tindana, Paulina; Hendricks, Melany; Moodley, Keymanthri
Genomic biobanking research is undergoing exponential growth in Africa raising a host of legal, ethical and social issues. Given the scientific complexity associated with genomics, there is a growing recognition globally of the importance of science translation and community engagement (CE) for this type of research, as it creates the potential to build relationships, increase trust, improve consent processes and empower local communities. Despite this level of recognition, there is a lack of empirical evidence of the practise and processes for effective CE in genomic biobanking in Africa. To begin to address this vacuum, 17 in-depth face to face interviews were conducted with South African experts in genomic biobanking research and CE to provide insight into the process, benefits and challenges of CE in South Africa. Emerging themes were analysed using a contextualised thematic approach. Several themes emerged concerning the conduct of CE in genomic biobanking research in Africa. Although the literature tends to focus on the local community in CE, respondents in this study described three different layers of stakeholder engagement: community level, peer level and high level. Community level engagement includes potential participants, community advisory boards (CAB) and field workers; peer level engagement includes researchers, biobankers and scientists, while high level engagement includes government officials, funders and policy makers. Although education of each stakeholder layer is important, education of the community layer can be most challenging, due to the complexity of the research and educational levels of stakeholders in this layer. CE is time-consuming and often requires an interdisciplinary research team approach. However careful planning of the engagement strategy, including an understanding of the differing layers of stakeholder engagement, and the specific educational needs at each layer, can help in the development of a relationship based on trust
Santoni, Daniele; Romano-Spica, Vincenzo
Whole genome analysis provides new perspectives to determine phylogenetic relationships among microorganisms. The availability of whole nucleotide sequences allows different levels of comparison among genomes by several approaches. In this work, self-attraction rates were considered for each cluster of orthologous groups of proteins (COGs) class in order to analyse gene aggregation levels in physical maps. Phylogenetic relationships among microorganisms were obtained by comparing self-attraction coefficients. Eighteen-dimensional vectors were computed for a set of 168 completely sequenced microbial genomes (19 archea, 149 bacteria). The components of the vector represent the aggregation rate of the genes belonging to each of 18 COGs classes. Genes involved in nonessential functions or related to environmental conditions showed the highest aggregation rates. On the contrary genes involved in basic cellular tasks showed a more uniform distribution along the genome, except for translation genes. Self-attraction clustering approach allowed classification of Proteobacteria, Bacilli and other species belonging to Firmicutes. Rearrangement and Lateral Gene Transfer events may influence divergences from classical taxonomy. Each set of COG classes' aggregation values represents an intrinsic property of the microbial genome. This novel approach provides a new point of view for whole genome analysis and bacterial characterization.
Jackson, Anne U.; Monda, Keri L.; Kilpeläinen, Tuomas O.; Esko, Tõnu; Mägi, Reedik; Li, Shengxu; Workalemahu, Tsegaselassie; Feitosa, Mary F.; Croteau-Chonka, Damien C.; Day, Felix R.; Fall, Tove; Ferreira, Teresa; Gustafsson, Stefan; Locke, Adam E.; Mathieson, Iain; Scherag, Andre; Vedantam, Sailaja; Wood, Andrew R.; Liang, Liming; Steinthorsdottir, Valgerdur; Thorleifsson, Gudmar; Dermitzakis, Emmanouil T.; Dimas, Antigone S.; Karpe, Fredrik; Min, Josine L.; Nicholson, George; Clegg, Deborah J.; Person, Thomas; Krohn, Jon P.; Bauer, Sabrina; Buechler, Christa; Eisinger, Kristina; Bonnefond, Amélie; Froguel, Philippe; Hottenga, Jouke-Jan; Prokopenko, Inga; Waite, Lindsay L.; Harris, Tamara B.; Smith, Albert Vernon; Shuldiner, Alan R.; McArdle, Wendy L.; Caulfield, Mark J.; Munroe, Patricia B.; Grönberg, Henrik; Chen, Yii-Der Ida; Li, Guo; Beckmann, Jacques S.; Johnson, Toby; Thorsteinsdottir, Unnur; Teder-Laving, Maris; Khaw, Kay-Tee; Wareham, Nicholas J.; Zhao, Jing Hua; Amin, Najaf; Oostra, Ben A.; Kraja, Aldi T.; Province, Michael A.; Cupples, L. Adrienne; Heard-Costa, Nancy L.; Kaprio, Jaakko; Ripatti, Samuli; Surakka, Ida; Collins, Francis S.; Saramies, Jouko; Tuomilehto, Jaakko; Jula, Antti; Salomaa, Veikko; Erdmann, Jeanette; Hengstenberg, Christian; Loley, Christina; Schunkert, Heribert; Lamina, Claudia; Wichmann, H. Erich; Albrecht, Eva; Gieger, Christian; Hicks, Andrew A.; Johansson, Åsa; Pramstaller, Peter P.; Kathiresan, Sekar; Speliotes, Elizabeth K.; Penninx, Brenda; Hartikainen, Anna-Liisa; Jarvelin, Marjo-Riitta; Gyllensten, Ulf; Boomsma, Dorret I.; Campbell, Harry; Wilson, James F.; Chanock, Stephen J.; Farrall, Martin; Goel, Anuj; Medina-Gomez, Carolina; Rivadeneira, Fernando; Estrada, Karol; Uitterlinden, André G.; Hofman, Albert; Zillikens, M. Carola; den Heijer, Martin; Kiemeney, Lambertus A.; Maschio, Andrea; Hall, Per; Tyrer, Jonathan; Teumer, Alexander; Völzke, Henry; Kovacs, Peter; Tönjes, Anke; Mangino, Massimo; Spector, Tim D.; Hayward, Caroline; Rudan, Igor; Hall, Alistair S.; Samani, Nilesh J.; Attwood, Antony Paul; Sambrook, Jennifer G.; Hung, Joseph; Palmer, Lyle J.; Lokki, Marja-Liisa; Sinisalo, Juha; Boucher, Gabrielle; Huikuri, Heikki; Lorentzon, Mattias; Ohlsson, Claes; Eklund, Niina; Eriksson, Johan G.; Barlassina, Cristina; Rivolta, Carlo; Nolte, Ilja M.; Snieder, Harold; Van der Klauw, Melanie M.; Van Vliet-Ostaptchouk, Jana V.; Gejman, Pablo V.; Shi, Jianxin; Jacobs, Kevin B.; Wang, Zhaoming; Bakker, Stephan J. L.; Mateo Leach, Irene; Navis, Gerjan; van der Harst, Pim; Martin, Nicholas G.; Medland, Sarah E.; Montgomery, Grant W.; Yang, Jian; Chasman, Daniel I.; Ridker, Paul M.; Rose, Lynda M.; Lehtimäki, Terho; Raitakari, Olli; Absher, Devin; Iribarren, Carlos; Basart, Hanneke; Hovingh, Kees G.; Hyppönen, Elina; Power, Chris; Anderson, Denise; Beilby, John P.; Hui, Jennie; Jolley, Jennifer; Sager, Hendrik; Bornstein, Stefan R.; Schwarz, Peter E. H.; Kristiansson, Kati; Perola, Markus; Lindström, Jaana; Swift, Amy J.; Uusitupa, Matti; Atalay, Mustafa; Lakka, Timo A.; Rauramaa, Rainer; Bolton, Jennifer L.; Fowkes, Gerry; Fraser, Ross M.; Price, Jackie F.; Fischer, Krista; KrjutÅ¡kov, Kaarel; Metspalu, Andres; Mihailov, Evelin; Langenberg, Claudia; Luan, Jian'an; Ong, Ken K.; Chines, Peter S.; Keinanen-Kiukaanniemi, Sirkka M.; Saaristo, Timo E.; Edkins, Sarah; Franks, Paul W.; Hallmans, Göran; Shungin, Dmitry; Morris, Andrew David; Palmer, Colin N. A.; Erbel, Raimund; Moebus, Susanne; Nöthen, Markus M.; Pechlivanis, Sonali; Hveem, Kristian; Narisu, Narisu; Hamsten, Anders; Humphries, Steve E.; Strawbridge, Rona J.; Tremoli, Elena; Grallert, Harald; Thorand, Barbara; Illig, Thomas; Koenig, Wolfgang; Müller-Nurasyid, Martina; Peters, Annette; Boehm, Bernhard O.; Kleber, Marcus E.; März, Winfried; Winkelmann, Bernhard R.; Kuusisto, Johanna; Laakso, Markku; Arveiler, Dominique; Cesana, Giancarlo; Kuulasmaa, Kari; Virtamo, Jarmo; Yarnell, John W. G.; Kuh, Diana; Wong, Andrew; Lind, Lars; de Faire, Ulf; Gigante, Bruna; Magnusson, Patrik K. E.; Pedersen, Nancy L.; Dedoussis, George; Dimitriou, Maria; Kolovou, Genovefa; Kanoni, Stavroula; Stirrups, Kathleen; Bonnycastle, Lori L.; Njølstad, Inger; Wilsgaard, Tom; Ganna, Andrea; Rehnberg, Emil; Hingorani, Aroon; Kivimaki, Mika; Kumari, Meena; Assimes, Themistocles L.; Barroso, Inês; Boehnke, Michael; Borecki, Ingrid B.; Deloukas, Panos; Fox, Caroline S.; Frayling, Timothy; Groop, Leif C.; Haritunians, Talin; Hunter, David; Ingelsson, Erik; Kaplan, Robert; Mohlke, Karen L.; O'Connell, Jeffrey R.; Schlessinger, David; Strachan, David P.; Stefansson, Kari; van Duijn, Cornelia M.; Abecasis, Gonçalo R.; McCarthy, Mark I.; Hirschhorn, Joel N.; Qi, Lu; Loos, Ruth J. F.; Lindgren, Cecilia M.; North, Kari E.; Heid, Iris M.
Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10−8), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits. PMID:23754948
Joshua C Randall
Full Text Available Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals and took forward 348 SNPs into follow-up (additional 137,052 individuals in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%, including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9 and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG, all of which were genome-wide significant in women (P<5×10(-8, but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.
Amyotte, Beatrice; Bowen, Amy J; Banks, Travis; Rajcan, Istvan; Somers, Daryl J
Breeding apples is a long-term endeavour and it is imperative that new cultivars are selected to have outstanding consumer appeal. This study has taken the approach of merging sensory science with genome wide association analyses in order to map the human perception of apple flavour and texture onto the apple genome. The goal was to identify genomic associations that could be used in breeding apples for improved fruit quality. A collection of 85 apple cultivars was examined over two years through descriptive sensory evaluation by a trained sensory panel. The trained sensory panel scored randomized sliced samples of each apple cultivar for seventeen taste, flavour and texture attributes using controlled sensory evaluation practices. In addition, the apple collection was subjected to genotyping by sequencing for marker discovery. A genome wide association analysis suggested significant genomic associations for several sensory traits including juiciness, crispness, mealiness and fresh green apple flavour. The findings include previously unreported genomic regions that could be used in apple breeding and suggest that similar sensory association mapping methods could be applied in other plants.
Amyotte, Beatrice; Bowen, Amy J.; Banks, Travis; Rajcan, Istvan; Somers, Daryl J.
Breeding apples is a long-term endeavour and it is imperative that new cultivars are selected to have outstanding consumer appeal. This study has taken the approach of merging sensory science with genome wide association analyses in order to map the human perception of apple flavour and texture onto the apple genome. The goal was to identify genomic associations that could be used in breeding apples for improved fruit quality. A collection of 85 apple cultivars was examined over two years through descriptive sensory evaluation by a trained sensory panel. The trained sensory panel scored randomized sliced samples of each apple cultivar for seventeen taste, flavour and texture attributes using controlled sensory evaluation practices. In addition, the apple collection was subjected to genotyping by sequencing for marker discovery. A genome wide association analysis suggested significant genomic associations for several sensory traits including juiciness, crispness, mealiness and fresh green apple flavour. The findings include previously unreported genomic regions that could be used in apple breeding and suggest that similar sensory association mapping methods could be applied in other plants. PMID:28231290
Chen, Hao; Wang, Xiangfeng
In plants and animals, chromosomal breakage and fusion events based on conserved syntenic genomic blocks lead to conserved patterns of karyotype evolution among species of the same family. However, karyotype information has not been well utilized in genomic comparison studies. We present CrusView, a Java-based bioinformatic application utilizing Standard Widget Toolkit/Swing graphics libraries and a SQLite database for performing visualized analyses of comparative genomics data in Brassicaceae (crucifer) plants. Compared with similar software and databases, one of the unique features of CrusView is its integration of karyotype information when comparing two genomes. This feature allows users to perform karyotype-based genome assembly and karyotype-assisted genome synteny analyses with preset karyotype patterns of the Brassicaceae genomes. Additionally, CrusView is a local program, which gives its users high flexibility when analyzing unpublished genomes and allows users to upload self-defined genomic information so that they can visually study the associations between genome structural variations and genetic elements, including chromosomal rearrangements, genomic macrosynteny, gene families, high-frequency recombination sites, and tandem and segmental duplications between related species. This tool will greatly facilitate karyotype, chromosome, and genome evolution studies using visualized comparative genomics approaches in Brassicaceae species. CrusView is freely available at http://www.cmbb.arizona.edu/CrusView/.
Sverrisdóttir, Elsa; Janss, Luc; Byrne, Stephen
Breeding for more space and resource efficient crops is important to feed the world’s increasing population. Potatoes produce approximately twice the amount of calories per hectare compared to cereals. The traditional “mate and phenotype” breeding approach is costly and time-consuming; however......, the completion of the genome sequence of potato has enabled the application of genomics-assisted breeding technologies. Genomic selection using genome-wide molecular markers is becoming increasingly applicable to crops as the genotyping costs continue to reduce and it is thus an attractive breeding alternative...... selection, can be obtained with good prediction accuracies in tetraploid potato....
Aaron B. A. Shafer; Jochen B. W. Wolf; Paulo C. Alves; Linnea Bergstrom; Michael W. Bruford; Ioana Brannstrom; Guy Colling; Love Dalen; Luc De Meester; Robert Ekblom; Katie D. Fawcett; Simone Fior; Mehrdad Hajibabaei; Jason A. Hill; A. Rus Hoezel; Jacob Hoglund; Evelyn L. Jensen; Johannes Krause; Torsten N. Kristensen; Michael Krutzen; John K. McKay; Anita J. Norman; Rob Ogden; E. Martin Osterling; N. Joop Ouborg; John Piccolo; Danijela Popovic; Craig R. Primmer; Floyd A. Reed; Marie Roumet; Jordi Salmona; Tamara Schenekar; Michael K. Schwartz; Gernot Segelbacher; Helen Senn; Jens Thaulow; Mia Valtonen; Andrew Veale; Philippine Vergeer; Nagarjun Vijay; Carles Vila; Matthias Weissensteiner; Lovisa Wennerstrom; Christopher W. Wheat; Piotr Zielinski
The global loss of biodiversity continues at an alarming rate. Genomic approaches have been suggested as a promising tool for conservation practice as scaling up to genome-wide data can improve traditional conservation genetic inferences and provide qualitatively novel insights. However, the generation of genomic data and subsequent analyses and interpretations remain...
B Kalyana Babu
Full Text Available The major limiting factor for production and productivity of finger millet crop is blast disease caused by Magnaporthe grisea. Since, the genome sequence information available in finger millet crop is scarce, comparative genomics plays a very important role in identification of genes/QTLs linked to the blast resistance genes using SSR markers. In the present study, a total of 58 genic SSRs were developed for use in genetic analysis of a global collection of 190 finger millet genotypes. The 58 SSRs yielded ninety five scorable alleles and the polymorphism information content varied from 0.186 to 0.677 at an average of 0.385. The gene diversity was in the range of 0.208 to 0.726 with an average of 0.487. Association mapping for blast resistance was done using 104 SSR markers which identified four QTLs for finger blast and one QTL for neck blast resistance. The genomic marker RM262 and genic marker FMBLEST32 were linked to finger blast disease at a P value of 0.007 and explained phenotypic variance (R² of 10% and 8% respectively. The genomic marker UGEP81 was associated to finger blast at a P value of 0.009 and explained 7.5% of R². The QTLs for neck blast was associated with the genomic SSR marker UGEP18 at a P value of 0.01, which explained 11% of R². Three QTLs for blast resistance were found common by using both GLM and MLM approaches. The resistant alleles were found to be present mostly in the exotic genotypes. Among the genotypes of NW Himalayan region of India, VHC3997, VHC3996 and VHC3930 were found highly resistant, which may be effectively used as parents for developing blast resistant cultivars in the NW Himalayan region of India. The markers linked to the QTLs for blast resistance in the present study can be further used for cloning of the full length gene, fine mapping and their further use in the marker assisted breeding programmes for introgression of blast resistant alleles into locally adapted cultivars.
Pandey, Manish K; Khan, Aamir W; Singh, Vikas K; Vishwakarma, Manish K; Shasidhar, Yaduru; Kumar, Vinay; Garg, Vanika; Bhat, Ramesh S; Chitikineni, Annapurna; Janila, Pasupuleti; Guo, Baozhu; Varshney, Rajeev K
Rust and late leaf spot (LLS) are the two major foliar fungal diseases in groundnut, and their co-occurrence leads to significant yield loss in addition to the deterioration of fodder quality. To identify candidate genomic regions controlling resistance to rust and LLS, whole-genome resequencing (WGRS)-based approach referred as 'QTL-seq' was deployed. A total of 231.67 Gb raw and 192.10 Gb of clean sequence data were generated through WGRS of resistant parent and the resistant and susceptible bulks for rust and LLS. Sequence analysis of bulks for rust and LLS with reference-guided resistant parent assembly identified 3136 single-nucleotide polymorphisms (SNPs) for rust and 66 SNPs for LLS with the read depth of ≥7 in the identified genomic region on pseudomolecule A03. Detailed analysis identified 30 nonsynonymous SNPs affecting 25 candidate genes for rust resistance, while 14 intronic and three synonymous SNPs affecting nine candidate genes for LLS resistance. Subsequently, allele-specific diagnostic markers were identified for three SNPs for rust resistance and one SNP for LLS resistance. Genotyping of one RIL population (TAG 24 × GPBD 4) with these four diagnostic markers revealed higher phenotypic variation for these two diseases. These results suggest usefulness of QTL-seq approach in precise and rapid identification of candidate genomic regions and development of diagnostic markers for breeding applications. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.
Dimitrijevic, Aleksandra; Horn, Renate
In sunflower, molecular markers for simple traits as, e.g., fertility restoration, high oleic acid content, herbicide tolerance or resistances to Plasmopara halstedii, Puccinia helianthi , or Orobanche cumana have been successfully used in marker-assisted breeding programs for years. However, agronomically important complex quantitative traits like yield, heterosis, drought tolerance, oil content or selection for disease resistance, e.g., against Sclerotinia sclerotiorum have been challenging and will require genome-wide approaches. Plant genetic resources for sunflower are being collected and conserved worldwide that represent valuable resources to study complex traits. Sunflower association panels provide the basis for genome-wide association studies, overcoming disadvantages of biparental populations. Advances in technologies and the availability of the sunflower genome sequence made novel approaches on the whole genome level possible. Genotype-by-sequencing, and whole genome sequencing based on next generation sequencing technologies facilitated the production of large amounts of SNP markers for high density maps as well as SNP arrays and allowed genome-wide association studies and genomic selection in sunflower. Genome wide or candidate gene based association studies have been performed for traits like branching, flowering time, resistance to Sclerotinia head and stalk rot. First steps in genomic selection with regard to hybrid performance and hybrid oil content have shown that genomic selection can successfully address complex quantitative traits in sunflower and will help to speed up sunflower breeding programs in the future. To make sunflower more competitive toward other oil crops higher levels of resistance against pathogens and better yield performance are required. In addition, optimizing plant architecture toward a more complex growth type for higher plant densities has the potential to considerably increase yields per hectare. Integrative approaches
Full Text Available In sunflower, molecular markers for simple traits as, e.g., fertility restoration, high oleic acid content, herbicide tolerance or resistances to Plasmopara halstedii, Puccinia helianthi, or Orobanche cumana have been successfully used in marker-assisted breeding programs for years. However, agronomically important complex quantitative traits like yield, heterosis, drought tolerance, oil content or selection for disease resistance, e.g., against Sclerotinia sclerotiorum have been challenging and will require genome-wide approaches. Plant genetic resources for sunflower are being collected and conserved worldwide that represent valuable resources to study complex traits. Sunflower association panels provide the basis for genome-wide association studies, overcoming disadvantages of biparental populations. Advances in technologies and the availability of the sunflower genome sequence made novel approaches on the whole genome level possible. Genotype-by-sequencing, and whole genome sequencing based on next generation sequencing technologies facilitated the production of large amounts of SNP markers for high density maps as well as SNP arrays and allowed genome-wide association studies and genomic selection in sunflower. Genome wide or candidate gene based association studies have been performed for traits like branching, flowering time, resistance to Sclerotinia head and stalk rot. First steps in genomic selection with regard to hybrid performance and hybrid oil content have shown that genomic selection can successfully address complex quantitative traits in sunflower and will help to speed up sunflower breeding programs in the future. To make sunflower more competitive toward other oil crops higher levels of resistance against pathogens and better yield performance are required. In addition, optimizing plant architecture toward a more complex growth type for higher plant densities has the potential to considerably increase yields per hectare
Dimitrijevic, Aleksandra; Horn, Renate
In sunflower, molecular markers for simple traits as, e.g., fertility restoration, high oleic acid content, herbicide tolerance or resistances to Plasmopara halstedii, Puccinia helianthi, or Orobanche cumana have been successfully used in marker-assisted breeding programs for years. However, agronomically important complex quantitative traits like yield, heterosis, drought tolerance, oil content or selection for disease resistance, e.g., against Sclerotinia sclerotiorum have been challenging and will require genome-wide approaches. Plant genetic resources for sunflower are being collected and conserved worldwide that represent valuable resources to study complex traits. Sunflower association panels provide the basis for genome-wide association studies, overcoming disadvantages of biparental populations. Advances in technologies and the availability of the sunflower genome sequence made novel approaches on the whole genome level possible. Genotype-by-sequencing, and whole genome sequencing based on next generation sequencing technologies facilitated the production of large amounts of SNP markers for high density maps as well as SNP arrays and allowed genome-wide association studies and genomic selection in sunflower. Genome wide or candidate gene based association studies have been performed for traits like branching, flowering time, resistance to Sclerotinia head and stalk rot. First steps in genomic selection with regard to hybrid performance and hybrid oil content have shown that genomic selection can successfully address complex quantitative traits in sunflower and will help to speed up sunflower breeding programs in the future. To make sunflower more competitive toward other oil crops higher levels of resistance against pathogens and better yield performance are required. In addition, optimizing plant architecture toward a more complex growth type for higher plant densities has the potential to considerably increase yields per hectare. Integrative approaches
Pierron, Denis; Heiske, Margit; Razafindrazaka, Harilanto; Rakoto, Ignace; Rabetokotany, Nelly; Ravololomanga, Bodo; Rakotozafy, Lucien M.-A.; Rakotomalala, Mireille Mialy; Razafiarivony, Michel; Rasoarifetra, Bako; Raharijesy, Miakabola Andriamampianina; Razafindralambo, Lolona; Ramilisonina; Fanony, Fulgence; Lejamble, Sendra; Thomas, Olivier; Mohamed Abdallah, Ahmed; Rocher, Christophe; Arachiche, Amal; Tonaso, Laure; Pereda-loth, Veronica; Schiavinato, Stéphanie; Brucato, Nicolas; Ricaut, Francois-Xavier; Kusuma, Pradiptajati; Sudoyo, Herawati; Ni, Shengyu; Boland, Anne; Deleuze, Jean-Francois; Beaujard, Philippe; Grange, Philippe; Adelaar, Sander; Stoneking, Mark; Rakotoarisoa, Jean-Aimé; Radimilahy, Chantal; Letellier, Thierry
Although situated ∼400 km from the east coast of Africa, Madagascar exhibits cultural, linguistic, and genetic traits from both Southeast Asia and Eastern Africa. The settlement history remains contentious; we therefore used a grid-based approach to sample at high resolution the genomic diversity (including maternal lineages, paternal lineages, and genome-wide data) across 257 villages and 2,704 Malagasy individuals. We find a common Bantu and Austronesian descent for all Malagasy individuals with a limited paternal contribution from Europe and the Middle East. Admixture and demographic growth happened recently, suggesting a rapid settlement of Madagascar during the last millennium. However, the distribution of African and Asian ancestry across the island reveals that the admixture was sex biased and happened heterogeneously across Madagascar, suggesting independent colonization of Madagascar from Africa and Asia rather than settlement by an already admixed population. In addition, there are geographic influences on the present genomic diversity, independent of the admixture, showing that a few centuries is sufficient to produce detectable genetic structure in human populations. PMID:28716916
Full Text Available Pigeonpea is an important pulse crop grown predominantly in the tropical and sub-tropical regions of the world. Although pigeonpea growing area has considerably increased, yield has remained stagnant for the last six decades mainly due to the exposure of the crop to various biotic and abiotic constraints. In addition, low level of genetic variability and limited genomic resources have been serious impediments to pigeonpea crop improvement through modern breeding approaches. In recent years, however, due to the availability of next generation sequencing and high-throughput genotyping technologies, the scenario has changed tremendously. The reduced sequencing costs resulting in the decoding of the pigeonpea genome has led to the development of various genomic resources including molecular markers, transcript sequences and comprehensive genetic maps. Mapping of some important traits including resistance to Fusarium wilt and sterility mosaic disease, fertility restoration, determinacy with other agronomically important traits have paved the way for applying genomics-assisted breeding (GAB through marker assisted selection as well as genomic selection. This would lead to accelerate the development and improvement of both varieties and hybrids in pigeonpea. Particularly for hybrid breeding programme, mitochondrial genomes of cytoplasmic male sterile lines, maintainers and hybrids have also been sequenced to identify genes responsible for cytoplasmic male sterility. Furthermore, several diagnostic molecular markers have been developed to assess the purity of commercial hybrids. In summary, pigeonpea has become a genomic resources-rich crop and efforts have already been initiated to integrate these resources in pigeonpea breeding.
The species in the genus Oryza, encompassing nine genome types and 23 species, are a rich genetic resource and may have applications in deeper genomic analyses aiming to understand the evolution of plant genomes. With the advancement of next-generation sequencing (NGS) technology, a flood of Oryza species reference genomes and genomic variation information has become available in recent years. This genomic information, combined with the comprehensive phenotypic information that we are accumulating in our Oryzabase, can serve as an excellent genotype-phenotype association resource for analyzing rice functional and structural evolution, and the associated diversity of the Oryza genus. Here we integrate our previous and future phenotypic/habitat information and newly determined genotype information into a united repository, named OryzaGenome, providing the variant information with hyperlinks to Oryzabase. The current version of OryzaGenome includes genotype information of 446 O. rufipogon accessions derived by imputation and of 17 accessions derived by imputation-free deep sequencing. Two variant viewers are implemented: SNP Viewer as a conventional genome browser interface and Variant Table as a textbased browser for precise inspection of each variant one by one. Portable VCF (variant call format) file or tabdelimited file download is also available. Following these SNP (single nucleotide polymorphism) data, reference pseudomolecules/ scaffolds/contigs and genome-wide variation information for almost all of the closely and distantly related wild Oryza species from the NIG Wild Rice Collection will be available in future releases. All of the resources can be accessed through http://viewer.shigen.info/oryzagenome/.
Full Text Available A tripartite comparison of Archaea phylogeny and taxonomy at and above the rank order is reported: (1 the whole-genome-based and alignment-free CVTree using 179 genomes; (2 the 16S rRNA analysis exemplified by the All-Species Living Tree with 366 archaeal sequences; and (3 the Second Edition of Bergey’s Manual of Systematic Bacteriology complemented by some current literature. A high degree of agreement is reached at these ranks. From the newly proposed archaeal phyla, Korarchaeota, Thaumarchaeota, Nanoarchaeota and Aigarchaeota, to the recent suggestion to divide the class Halobacteria into three orders, all gain substantial support from CVTree. In addition, the CVTree helped to determine the taxonomic position of some newly sequenced genomes without proper lineage information. A few discrepancies between the CVTree and the 16S rRNA approaches call for further investigation.
Maojo, V; Crespo, J; de la Calle, G; Barreiro, J; Garcia-Remesal, M
To develop a new perspective for biomedical information systems, regarding the introduction of ideas, methods and tools related to the new scenario of genomic medicine. Technological aspects related to the analysis and integration of heterogeneous clinical and genomic data include mapping clinical and genetic concepts, potential future standards or the development of integrated biomedical ontologies. In this clinicomics scenario, we describe the use of Web services technologies to improve access to and integrate different information sources. We give a concrete example of the use of Web services technologies: the OntoFusion project. Web services provide new biomedical informatics (BMI) approaches related to genomic medicine. Customized workflows will aid research tasks by linking heterogeneous Web services. Two significant examples of these European Commission-funded efforts are the INFOBIOMED Network of Excellence and the Advancing Clinico-Genomic Trials on Cancer (ACGT) integrated project. Supplying medical researchers and practitioners with omics data and biologists with clinical datasets can help to develop genomic medicine. BMI is contributing by providing the informatics methods and technological infrastructure needed for these collaborative efforts.
Chandrani, P; Kulkarni, V; Iyer, P; Upadhyay, P; Chaubal, R; Das, P; Mulherkar, R; Singh, R; Dutt, A
Human papilloma virus (HPV) accounts for the most common cause of all virus-associated human cancers. Here, we describe the first graphic user interface (GUI)-based automated tool 'HPVDetector', for non-computational biologists, exclusively for detection and annotation of the HPV genome based on next-generation sequencing data sets. We developed a custom-made reference genome that comprises of human chromosomes along with annotated genome of 143 HPV types as pseudochromosomes. The tool runs on a dual mode as defined by the user: a 'quick mode' to identify presence of HPV types and an 'integration mode' to determine genomic location for the site of integration. The input data can be a paired-end whole-exome, whole-genome or whole-transcriptome data set. The HPVDetector is available in public domain for download: http://www.actrec.gov.in/pi-webpages/AmitDutt/HPVdetector/HPVDetector.html. On the basis of our evaluation of 116 whole-exome, 23 whole-transcriptome and 2 whole-genome data, we were able to identify presence of HPV in 20 exomes and 4 transcriptomes of cervical and head and neck cancer tumour samples. Using the inbuilt annotation module of HPVDetector, we found predominant integration of viral gene E7, a known oncogene, at known 17q21, 3q27, 7q35, Xq28 and novel sites of integration in the human genome. Furthermore, co-infection with high-risk HPVs such as 16 and 31 were found to be mutually exclusive compared with low-risk HPV71. HPVDetector is a simple yet precise and robust tool for detecting HPV from tumour samples using variety of next-generation sequencing platforms including whole genome, whole exome and transcriptome. Two different modes (quick detection and integration mode) along with a GUI widen the usability of HPVDetector for biologists and clinicians with minimal computational knowledge.
Amin, Rupesh P.; Hamadeh, Hisham K.; Bushel, Pierre R.; Bennett, Lee; Afshari, Cynthia A.; Paules, Richard S.
Assessment of the impact of xenobiotic exposure on human health and disease progression is complex. Knowledge of mode(s) of action, including mechanism(s) contributing to toxicity and disease progression, is valuable for evaluating compounds. Toxicogenomics, the subdiscipline which merges genomics with toxicology, holds the promise to contributing significantly toward the goal of elucidating mechanism(s) by studying genome-wide effects of xenobiotics. Global gene expression profiling, revolutionized by microarray technology and a crucial aspect of a toxicogenomic study, allows measuring transcriptional modulation of thousands of genes following exposure to a xenobiotic. We use our results from previous studies on compounds representing two different classes of xenobiotics (barbiturate and peroxisome proliferator) to discuss the application of computational approaches for analyzing microarray data to elucidate mechanism(s) underlying cellular responses to toxicants. In particular, our laboratory demonstrated that chemical-specific patterns of gene expression can be revealed using cDNA microarrays. Transcript profiling provides discrimination between classes of toxicants, as well as, genome-wide insight into mechanism(s) of toxicity and disease progression. Ultimately, the expectation is that novel approaches for predicting xenobiotic toxicity in humans will emerge from such information
The introduction of alien genetic variation from the genus Thinopyrum through chromosome engineering into wheat is a valuable and proven technique for wheat improvement. A number of economically important traits have been transferred into wheat as single genes, chromosome arms or entire chromosomes. Successful transfers can be greatly assisted by the precise identification of alien chromatin in the recipient progenies. Chromosome identification and characterization are useful for genetic manipulation and transfer in wheat breeding following chromosome engineering. Genomic in situ hybridization (GISH) using an S genomic DNA probe from the diploid species Pseudoroegneria has proven to be a powerful diagnostic cytogenetic tool for monitoring the transfer of many promising agronomic traits from Thinopyrum. This specific S genomic probe not only allows the direct determination of the chromosome composition in wheat-Thinopyrum hybrids, but also can separate the Th. intermedium chromosomes into the J, J(S) and S genomes. The J(S) genome, which consists of a modified J genome chromosome distinguished by S genomic sequences of Pseudoroegneria near the centromere and telomere, carries many disease and mite resistance genes. Utilization of this S genomic probe leads to a better understanding of genomic affinities between Thinopyrum and wheat, and provides a molecular cytogenetic marker for monitoring the transfer of alien Thinopyrum agronomic traits into wheat recipient lines. Copyright 2005 S. Karger AG, Basel.
Full Text Available The Pseudomonas fluorescens complex includes Pseudomonas strains that have been taxonomically assigned to more than fifty different species, many of which have been described as plant growth-promoting rhizobacteria (PGPR with potential applications in biocontrol and biofertilization. So far the phylogeny of this complex has been analyzed according to phenotypic traits, 16S rDNA, MLSA and inferred by whole-genome analysis. However, since most of the type strains have not been fully sequenced and new species are frequently described, correlation between taxonomy and phylogenomic analysis is missing. In recent years, the genomes of a large number of strains have been sequenced, showing important genomic heterogeneity and providing information suitable for genomic studies that are important to understand the genomic and genetic diversity shown by strains of this complex. Based on MLSA and several whole-genome sequence-based analyses of 93 sequenced strains, we have divided the P. fluorescens complex into eight phylogenomic groups that agree with previous works based on type strains. Digital DDH (dDDH identified 69 species and 75 subspecies within the 93 genomes. The eight groups corresponded to clustering with a threshold of 31.8% dDDH, in full agreement with our MLSA. The Average Nucleotide Identity (ANI approach showed inconsistencies regarding the assignment to species and to the eight groups. The small core genome of 1,334 CDSs and the large pan-genome of 30,848 CDSs, show the large diversity and genetic heterogeneity of the P. fluorescens complex. However, a low number of strains were enough to explain most of the CDSs diversity at core and strain-specific genomic fractions. Finally, the identification and analysis of group-specific genome and the screening for distinctive characters revealed a phylogenomic distribution of traits among the groups that provided insights into biocontrol and bioremediation applications as well as their role as
Nakaya, Akihiro; Isobe, Sachiko N
Genomic selection or genome-wide selection (GS) has been highlighted as a new approach for marker-assisted selection (MAS) in recent years. GS is a form of MAS that selects favourable individuals based on genomic estimated breeding values. Previous studies have suggested the utility of GS, especially for capturing small-effect quantitative trait loci, but GS has not become a popular methodology in the field of plant breeding, possibly because there is insufficient information available on GS for practical use. In this review, GS is discussed from a practical breeding viewpoint. Statistical approaches employed in GS are briefly described, before the recent progress in GS studies is surveyed. GS practices in plant breeding are then reviewed before future prospects are discussed. Statistical concepts used in GS are discussed with genetic models and variance decomposition, heritability, breeding value and linear model. Recent progress in GS studies is reviewed with a focus on empirical studies. For the practice of GS in plant breeding, several specific points are discussed including linkage disequilibrium, feature of populations and genotyped markers and breeding scheme. Currently, GS is not perfect, but it is a potent, attractive and valuable approach for plant breeding. This method will be integrated into many practical breeding programmes in the near future with further advances and the maturing of its theory.
Muthamilarasan, Mehanathan; Prasad, Manoj
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.
Becker, Karsten; Bierbaum, Gabriele; von Eiff, Christof; Engelmann, Susanne; Götz, Friedrich; Hacker, Jörg; Hecker, Michael; Peters, Georg; Rosenstein, Ralf; Ziebuhr, Wilma
Staphylococcus aureus as well as coagulase-negative staphylococci are medically highly important pathogens characterized by an increasing resistance rate toward many antibiotics. Although normally being skin and mucosa commensals, some staphylococcal species and strains have the capacity to cause a wide range of infectious diseases. Many of these infections affect immunocompromised patients in hospitals. However, community-acquired staphylococcal infections due to resistant strains are also currently on the rise. In the light of this development, there is an urgent need for novel anti-staphylococcal therapeutic and prevention strategies for which a better understanding of the physiology of these bacteria is an essential prerequisite. Within the past years, staphylococci have been in the focus of genomic research, resulting in the determination and publication of a range of full-genome sequences of different staphylococcal species and strains which provided the basis for the design and application of DNA microarrays and other genomic tools. Here we summarize the results of the project group 'Staphylococci' within the research network 'Pathogenomics' giving new insights into the genome structure, molecular epidemiology, physiology, and genetic adaptation of both S. aureus and coagulase-negative staphylococci.
Dessimoz, Christophe; Boeckmann, Brigitte; Roth, Alexander C J; Gonnet, Gaston H
Correct orthology assignment is a critical prerequisite of numerous comparative genomics procedures, such as function prediction, construction of phylogenetic species trees and genome rearrangement analysis. We present an algorithm for the detection of non-orthologs that arise by mistake in current orthology classification methods based on genome-specific best hits, such as the COGs database. The algorithm works with pairwise distance estimates, rather than computationally expensive and error-prone tree-building methods. The accuracy of the algorithm is evaluated through verification of the distribution of predicted cases, case-by-case phylogenetic analysis and comparisons with predictions from other projects using independent methods. Our results show that a very significant fraction of the COG groups include non-orthologs: using conservative parameters, the algorithm detects non-orthology in a third of all COG groups. Consequently, sequence analysis sensitive to correct orthology assignments will greatly benefit from these findings.
Park, Doori; Park, Su-Hyun; Ban, Yong Wook; Kim, Youn Shic; Park, Kyoung-Cheul; Kim, Nam-Soo; Kim, Ju-Kon; Choi, Ik-Young
Genetically modified crops (GM crops) have been developed to improve the agricultural traits of modern crop cultivars. Safety assessments of GM crops are of paramount importance in research at developmental stages and before releasing transgenic plants into the marketplace. Sequencing technology is developing rapidly, with higher output and labor efficiencies, and will eventually replace existing methods for the molecular characterization of genetically modified organisms. To detect the transgenic insertion locations in the three GM rice gnomes, Illumina sequencing reads are mapped and classified to the rice genome and plasmid sequence. The both mapped reads are classified to characterize the junction site between plant and transgene sequence by sequence alignment. Herein, we present a next generation sequencing (NGS)-based molecular characterization method, using transgenic rice plants SNU-Bt9-5, SNU-Bt9-30, and SNU-Bt9-109. Specifically, using bioinformatics tools, we detected the precise insertion locations and copy numbers of transfer DNA, genetic rearrangements, and the absence of backbone sequences, which were equivalent to results obtained from Southern blot analyses. NGS methods have been suggested as an effective means of characterizing and detecting transgenic insertion locations in genomes. Our results demonstrate the use of a combination of NGS technology and bioinformatics approaches that offers cost- and time-effective methods for assessing the safety of transgenic plants.
Blazier, J. Chris; Ruhlman, Tracey A.; Weng, Mao-Lun; Rehman, Sumaiyah K.; Sabir, Jamal S. M.; Jansen, Robert K.
Genes for the plastid-encoded RNA polymerase (PEP) persist in the plastid genomes of all photosynthetic angiosperms. However, three unrelated lineages (Annonaceae, Passifloraceae and Geraniaceae) have been identified with unusually divergent open reading frames (ORFs) in the conserved region of rpoA, the gene encoding the PEP ? subunit. We used sequence-based approaches to evaluate whether these genes retain function. Both gene sequences and complete plastid genome sequences were assembled an...
Bowers, Robert M.; Kyrpides, Nikos C.; Stepanauskas, Ramunas; Harmon-Smith, Miranda; Doud, Devin; Reddy, T. B. K.; Schulz, Frederik; Jarett, Jessica; Rivers, Adam R.; Eloe-Fadrosh, Emiley A.; Tringe, Susannah G.; Ivanova, Natalia N.; Copeland, Alex; Clum, Alicia; Becraft, Eric D.; Malmstrom, Rex R.; Birren, Bruce; Podar, Mircea; Bork, Peer; Weinstock, George M.; Garrity, George M.; Dodsworth, Jeremy A.; Yooseph, Shibu; Sutton, Granger; Glöckner, Frank O.; Gilbert, Jack A.; Nelson, William C.; Hallam, Steven J.; Jungbluth, Sean P.; Ettema, Thijs J. G.; Tighe, Scott; Konstantinidis, Konstantinos T.; Liu, Wen-Tso; Baker, Brett J.; Rattei, Thomas; Eisen, Jonathan A.; Hedlund, Brian; McMahon, Katherine D.; Fierer, Noah; Knight, Rob; Finn, Rob; Cochrane, Guy; Karsch-Mizrachi, Ilene; Tyson, Gene W.; Rinke, Christian; Kyrpides, Nikos C.; Schriml, Lynn; Garrity, George M.; Hugenholtz, Philip; Sutton, Granger; Yilmaz, Pelin; Meyer, Folker; Glöckner, Frank O.; Gilbert, Jack A.; Knight, Rob; Finn, Rob; Cochrane, Guy; Karsch-Mizrachi, Ilene; Lapidus, Alla; Meyer, Folker; Yilmaz, Pelin; Parks, Donovan H.; Eren, A. M.; Schriml, Lynn; Banfield, Jillian F.; Hugenholtz, Philip; Woyke, Tanja
We present two standards developed by the Genomic Standards Consortium (GSC) for reporting bacterial and archaeal genome sequences. Both are extensions of the Minimum Information about Any (x) Sequence (MIxS). The standards are the Minimum Information about a Single Amplified Genome (MISAG) and the Minimum Information about a Metagenome-Assembled Genome (MIMAG), including, but not limited to, assembly quality, and estimates of genome completeness and contamination. These standards can be used in combination with other GSC checklists, including the Minimum Information about a Genome Sequence (MIGS), Minimum Information about a Metagenomic Sequence (MIMS), and Minimum Information about a Marker Gene Sequence (MIMARKS). Community-wide adoption of MISAG and MIMAG will facilitate more robust comparative genomic analyses of bacterial and archaeal diversity.
Blazier, J Chris; Ruhlman, Tracey A; Weng, Mao-Lun; Rehman, Sumaiyah K; Sabir, Jamal S M; Jansen, Robert K
Genes for the plastid-encoded RNA polymerase (PEP) persist in the plastid genomes of all photosynthetic angiosperms. However, three unrelated lineages (Annonaceae, Passifloraceae and Geraniaceae) have been identified with unusually divergent open reading frames (ORFs) in the conserved region of rpoA, the gene encoding the PEP α subunit. We used sequence-based approaches to evaluate whether these genes retain function. Both gene sequences and complete plastid genome sequences were assembled and analyzed from each of the three angiosperm families. Multiple lines of evidence indicated that the rpoA sequences are likely functional despite retaining as low as 30% nucleotide sequence identity with rpoA genes from outgroups in the same angiosperm order. The ratio of non-synonymous to synonymous substitutions indicated that these genes are under purifying selection, and bioinformatic prediction of conserved domains indicated that functional domains are preserved. One of the lineages (Pelargonium, Geraniaceae) contains species with multiple rpoA-like ORFs that show evidence of ongoing inter-paralog gene conversion. The plastid genomes containing these divergent rpoA genes have experienced extensive structural rearrangement, including large expansions of the inverted repeat. We propose that illegitimate recombination, not positive selection, has driven the divergence of rpoA.
Howe, Kevin; Davis, Paul; Paulini, Michael; Tuli, Mary Ann; Williams, Gary; Yook, Karen; Durbin, Richard; Kersey, Paul; Sternberg, Paul W
WormBase (www.wormbase.org) has been serving the scientific community for over 11 years as the central repository for genomic and genetic information for the soil nematode Caenorhabditis elegans. The resource has evolved from its beginnings as a database housing the genomic sequence and genetic and physical maps of a single species, and now represents the breadth and diversity of nematode research, currently serving genome sequence and annotation for around 20 nematodes. In this article, we focus on WormBase's role of genome sequence annotation, describing how we annotate and integrate data from a growing collection of nematode species and strains. We also review our approaches to sequence curation, and discuss the impact on annotation quality of large functional genomics projects such as modENCODE.
Full Text Available The linked read sequencing library preparation platform by 10X Genomics produces barcoded sequencing libraries, which are subsequently sequenced using the Illumina short read sequencing technology. In this new approach, long fragments of DNA are partitioned into separate micro-reactions, where the same index sequence is incorporated into each of the sequencing fragment inserts derived from a given long fragment. In this study, we exploited this property by using reads from index sequences associated with a large number of reads, to assemble the chloroplast genome of the Sitka spruce tree (Picea sitchensis. Here we report on the first Sitka spruce chloroplast genome assembled exclusively from P. sitchensis genomic libraries prepared using the 10X Genomics protocol. We show that the resulting 124,049 base pair long genome shares high sequence similarity with the related white spruce and Norway spruce chloroplast genomes, but diverges substantially from a previously published P. sitchensis- P. thunbergii chimeric genome. The use of reads from high-frequency indices enabled separation of the nuclear genome reads from that of the chloroplast, which resulted in the simplification of the de Bruijn graphs used at the various stages of assembly.
Murat, Claude; Zampieri, Elisa; Vallino, Marta; Daghino, Stefania; Perotto, Silvia; Bonfante, Paola
Characterization of genomic variation among different microbial species, or different strains of the same species, is a field of significant interest with a wide range of potential applications. We have investigated the genomic variation in mycorrhizal fungal genomes through genomic suppressive subtractive hybridization. The comparison was between phylogenetically distant and close truffle species (Tuber spp.), and between isolates of the ericoid mycorrhizal fungus Oidiodendron maius featuring different degrees of metal tolerance. In the interspecies experiment, almost all the sequences that were identified in the Tuber melanosporum genome and absent in Tuber borchii and Tuber indicum corresponded to transposable elements. In the intraspecies comparison, some specific sequences corresponded to regions coding for enzymes, among them a glutathione synthetase known to be involved in metal tolerance. This approach is a quick and rather inexpensive tool to develop molecular markers for mycorrhizal fungi tracking and barcoding, to identify functional genes and to investigate the genome plasticity, adaptation and evolution. © 2011 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.
Peng, Qian; Alekseyev, Max A.; Tesler, Glenn; Pevzner, Pavel A.
The existing synteny block reconstruction algorithms use anchors (e.g., orthologous genes) shared over all genomes to construct the synteny blocks for multiple genomes. This approach, while efficient for a few genomes, cannot be scaled to address the need to construct synteny blocks in many mammalian genomes that are currently being sequenced. The problem is that the number of anchors shared among all genomes quickly decreases with the increase in the number of genomes. Another problem is that many genomes (plant genomes in particular) had extensive duplications, which makes decoding of genomic architecture and rearrangement analysis in plants difficult. The existing synteny block generation algorithms in plants do not address the issue of generating non-overlapping synteny blocks suitable for analyzing rearrangements and evolution history of duplications. We present a new algorithm based on the A-Bruijn graph framework that overcomes these difficulties and provides a unified approach to synteny block reconstruction for multiple genomes, and for genomes with large duplications.
Clarke, Wayne E.; Parkin, Isobel A.; Gajardo, Humberto A.; Gerhardt, Daniel J.; Higgins, Erin; Sidebottom, Christine; Sharpe, Andrew G.; Snowdon, Rod J.; Federico, Maria L.; Iniguez-Luy, Federico L.
Targeted genomic selection methodologies, or sequence capture, allow for DNA enrichment and large-scale resequencing and characterization of natural genetic variation in species with complex genomes, such as rapeseed canola (Brassica napus L., AACC, 2n=38). The main goal of this project was to combine sequence capture with next generation sequencing (NGS) to discover single nucleotide polymorphisms (SNPs) in specific areas of the B. napus genome historically associated (via quantitative trait loci –QTL– analysis) to traits of agronomical and nutritional importance. A 2.1 million feature sequence capture platform was designed to interrogate DNA sequence variation across 47 specific genomic regions, representing 51.2 Mb of the Brassica A and C genomes, in ten diverse rapeseed genotypes. All ten genotypes were sequenced using the 454 Life Sciences chemistry and to assess the effect of increased sequence depth, two genotypes were also sequenced using Illumina HiSeq chemistry. As a result, 589,367 potentially useful SNPs were identified. Analysis of sequence coverage indicated a four-fold increased representation of target regions, with 57% of the filtered SNPs falling within these regions. Sixty percent of discovered SNPs corresponded to transitions while 40% were transversions. Interestingly, fifty eight percent of the SNPs were found in genic regions while 42% were found in intergenic regions. Further, a high percentage of genic SNPs was found in exons (65% and 64% for the A and C genomes, respectively). Two different genotyping assays were used to validate the discovered SNPs. Validation rates ranged from 61.5% to 84% of tested SNPs, underpinning the effectiveness of this SNP discovery approach. Most importantly, the discovered SNPs were associated with agronomically important regions of the B. napus genome generating a novel data resource for research and breeding this crop species. PMID:24312619
David José Martínez-Cano
Full Text Available As revealed by genome sequencing, the biology of prokaryotes with reduced genomes is strikingly diverse. These include free-living prokaryotes with ~800 genes as well as endosymbiotic bacteria with as few as ~140 genes. Comparative genomics is revealing the evolutionary mechanisms that led to these small genomes. In the case of free-living prokaryotes, natural selection directly favored genome reduction, while in the case of endosymbiotic prokaryotes neutral processes played a more prominent role. However, new experimental data suggest that selective processes may be at operation as well for endosymbiotic prokaryotes at least during the first stages of genome reduction. Endosymbiotic prokaryotes have evolved diverse strategies for living with reduced gene sets inside a host-defined medium. These include utilization of host-encoded functions (some of them coded by genes acquired by gene transfer from the endosymbiont and/or other bacteria; metabolic complementation between co-symbionts; and forming consortiums with other bacteria within the host. Recent genome sequencing projects of intracellular mutualistic bacteria showed that previously believed universal evolutionary trends like reduced G+C content and conservation of genome synteny are not always present in highly reduced genomes. Finally, the simplified molecular machinery of some of these organisms with small genomes may be used to aid in the design of artificial minimal cells. Here we review recent genomic discoveries of the biology of prokaryotes endowed with small gene sets and discuss the evolutionary mechanisms that have been proposed to explain their peculiar nature.
Li, Xueyan; Fan, Dingding; Zhang, Wei; Liu, Guichun; Zhang, Lu; Zhao, Li; Fang, Xiaodong; Chen, Lei; Dong, Yang; Chen, Yuan; Ding, Yun; Zhao, Ruoping; Feng, Mingji; Zhu, Yabing; Feng, Yue; Jiang, Xuanting; Zhu, Deying; Xiang, Hui; Feng, Xikan; Li, Shuaicheng; Wang, Jun; Zhang, Guojie; Kronforst, Marcus R.; Wang, Wen
Butterflies are exceptionally diverse but their potential as an experimental system has been limited by the difficulty of deciphering heterozygous genomes and a lack of genetic manipulation technology. Here we use a hybrid assembly approach to construct high-quality reference genomes for Papilio xuthus (contig and scaffold N50: 492 kb, 3.4 Mb) and Papilio machaon (contig and scaffold N50: 81 kb, 1.15 Mb), highly heterozygous species that differ in host plant affiliations, and adult and larval colour patterns. Integrating comparative genomics and analyses of gene expression yields multiple insights into butterfly evolution, including potential roles of specific genes in recent diversification. To functionally test gene function, we develop an efficient (up to 92.5%) CRISPR/Cas9 gene editing method that yields obvious phenotypes with three genes, Abdominal-B, ebony and frizzled. Our results provide valuable genomic and technological resources for butterflies and unlock their potential as a genetic model system. PMID:26354079
Song, Shuhui; Tian, Dongmei; Li, Cuiping; Tang, Bixia; Dong, Lili; Xiao, Jingfa; Bao, Yiming; Zhao, Wenming; He, Hang; Zhang, Zhang
The Genome Variation Map (GVM; http://bigd.big.ac.cn/gvm/) is a public data repository of genome variations. As a core resource in the BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, GVM dedicates to collect, integrate and visualize genome variations for a wide range of species, accepts submissions of different types of genome variations from all over the world and provides free open access to all publicly available data in support of worldwide research activities. Unlike existing related databases, GVM features integration of a large number of genome variations for a broad diversity of species including human, cultivated plants and domesticated animals. Specifically, the current implementation of GVM not only houses a total of ∼4.9 billion variants for 19 species including chicken, dog, goat, human, poplar, rice and tomato, but also incorporates 8669 individual genotypes and 13 262 manually curated high-quality genotype-to-phenotype associations for non-human species. In addition, GVM provides friendly intuitive web interfaces for data submission, browse, search and visualization. Collectively, GVM serves as an important resource for archiving genomic variation data, helpful for better understanding population genetic diversity and deciphering complex mechanisms associated with different phenotypes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
Tian, Dongmei; Li, Cuiping; Tang, Bixia; Dong, Lili; Xiao, Jingfa; Bao, Yiming; Zhao, Wenming; He, Hang
Abstract The Genome Variation Map (GVM; http://bigd.big.ac.cn/gvm/) is a public data repository of genome variations. As a core resource in the BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, GVM dedicates to collect, integrate and visualize genome variations for a wide range of species, accepts submissions of different types of genome variations from all over the world and provides free open access to all publicly available data in support of worldwide research activities. Unlike existing related databases, GVM features integration of a large number of genome variations for a broad diversity of species including human, cultivated plants and domesticated animals. Specifically, the current implementation of GVM not only houses a total of ∼4.9 billion variants for 19 species including chicken, dog, goat, human, poplar, rice and tomato, but also incorporates 8669 individual genotypes and 13 262 manually curated high-quality genotype-to-phenotype associations for non-human species. In addition, GVM provides friendly intuitive web interfaces for data submission, browse, search and visualization. Collectively, GVM serves as an important resource for archiving genomic variation data, helpful for better understanding population genetic diversity and deciphering complex mechanisms associated with different phenotypes. PMID:29069473
Norman, Kaitlyn L; Kumar, Anuj
The budding yeast has long served as a model eukaryote for the functional genomic analysis of highly conserved signaling pathways, cellular processes and mechanisms underlying human disease. The collection of reagents available for genomics in yeast is extensive, encompassing a growing diversity of mutant collections beyond gene deletion sets in the standard wild-type S288C genetic background. We review here three main types of mutant allele collections: transposon mutagen collections, essential gene collections and overexpression libraries. Each collection provides unique and identifiable alleles that can be utilized in genome-wide, high-throughput studies. These genomic reagents are particularly informative in identifying synthetic phenotypes and functions associated with essential genes, including those modeled most effectively in complex genetic backgrounds. Several examples of genomic studies in filamentous/pseudohyphal backgrounds are provided here to illustrate this point. Additionally, the limitations of each approach are examined. Collectively, these mutant allele collections in Saccharomyces cerevisiae and the related pathogenic yeast Candida albicans promise insights toward an advanced understanding of eukaryotic molecular and cellular biology. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: firstname.lastname@example.org.
The Computational Pan-Genomics Consortium; T. Marschall (Tobias); M. Marz (Manja); T. Abeel (Thomas); L.J. Dijkstra (Louis); B.E. Dutilh (Bas); A. Ghaffaari (Ali); P. Kersey (Paul); W.P. Kloosterman (Wigard); V. Mäkinen (Veli); A.M. Novak (Adam); B. Paten (Benedict); D. Porubsky (David); E. Rivals (Eric); C. Alkan (Can); J.A. Baaijens (Jasmijn); P.I.W. de Bakker (Paul); V. Boeva (Valentina); R.J.P. Bonnal (Raoul); F. Chiaromonte (Francesca); R. Chikhi (Rayan); F.D. Ciccarelli (Francesca); C.P. Cijvat (Robin); E. Datema (Erwin); C.M. van Duijn (Cornelia); E.E. Eichler (Evan); C. Ernst (Corinna); E. Eskin (Eleazar); E. Garrison (Erik); M. El-Kebir (Mohammed); G.W. Klau (Gunnar); J.O. Korbel (Jan); E.-W. Lameijer (Eric-Wubbo); B. Langmead (Benjamin); M. Martin; P. Medvedev (Paul); J.C. Mu (John); P.B.T. Neerincx (Pieter); K. Ouwens (Klaasjan); P. Peterlongo (Pierre); N. Pisanti (Nadia); S. Rahmann (Sven); B.J. Raphael (Benjamin); K. Reinert (Knut); D. de Ridder (Dick); J. de Ridder (Jeroen); M. Schlesner (Matthias); O. Schulz-Trieglaff (Ole); A.D. Sanders (Ashley); S. Sheikhizadeh (Siavash); C. Shneider (Carl); S. Smit (Sandra); D. Valenzuela (Daniel); J. Wang (Jiayin); L.F.A. Wessels (Lodewyk); Y. Zhang (Ying); V. Guryev (Victor); F. Vandin (Fabio); K. Ye (Kai); A. Schönhuth (Alexander)
textabstractMany disciplines, from human genetics and oncology to plant breeding, microbiology and virology, commonly face the challenge of analyzing rapidly increasing numbers of genomes. In case of Homo sapiens, the number of sequenced genomes will approach hundreds of thousands in the next few
Full Text Available Genotyping by sequencing (GBS is a restriction enzyme based targeted approach developed to reduce the genome complexity and discover genetic markers when a priori sequence information is unavailable. Sufficient coverage at each locus is essential to distinguish heterozygous from homozygous sites accurately. The number of GBS samples able to be pooled in one sequencing lane is limited by the number of restriction sites present in the genome and the read depth required at each site per sample for accurate calling of single-nucleotide polymorphisms. Loci bias was observed using a slight modification of the Elshire et al.some restriction enzyme sites were represented in higher proportions while others were poorly represented or absent. This bias could be due to the quality of genomic DNA, the endonuclease and ligase reaction efficiency, the distance between restriction sites, the preferential amplification of small library restriction fragments, or bias towards cluster formation of small amplicons during the sequencing process. To overcome these issues, we have developed a GBS method based on randomly tagging genomic DNA (rtGBS. By randomly landing on the genome, we can, with less bias, find restriction sites that are far apart, and undetected by the standard GBS (stdGBS method. The study comprises two types of biological replicates: six different kiwifruit plants and two independent DNA extractions per plant; and three types of technical replicates: four samples of each DNA extraction, stdGBS vs. rtGBS methods, and two independent library amplifications, each sequenced in separate lanes. A statistically significant unbiased distribution of restriction fragment size by rtGBS showed that this method targeted 49% (39,145 of BamH I sites shared with the reference genome, compared to only 14% (11,513 by stdGBS.
Zhao, Yongan; Wang, Xiaofeng; Tang, Haixu
The elastic and inexpensive computing resources such as clouds have been recognized as a useful solution to analyzing massive human genomic data (e.g., acquired by using next-generation sequencers) in biomedical researches. However, outsourcing human genome computation to public or commercial clouds was hindered due to privacy concerns: even a small number of human genome sequences contain sufficient information for identifying the donor of the genomic data. This issue cannot be directly addressed by existing security and cryptographic techniques (such as homomorphic encryption), because they are too heavyweight to carry out practical genome computation tasks on massive data. In this article, we present a secure algorithm to accomplish the read mapping, one of the most basic tasks in human genomic data analysis based on a hybrid cloud computing model. Comparing with the existing approaches, our algorithm delegates most computation to the public cloud, while only performing encryption and decryption on the private cloud, and thus makes the maximum use of the computing resource of the public cloud. Furthermore, our algorithm reports similar results as the nonsecure read mapping algorithms, including the alignment between reads and the reference genome, which can be directly used in the downstream analysis such as the inference of genomic variations. We implemented the algorithm in C++ and Python on a hybrid cloud system, in which the public cloud uses an Apache Spark system.
Ye, Christine J; Liu, Guo; Heng, Henry H
Genome chaos, or karyotype chaos, represents a powerful survival strategy for somatic cells under high levels of stress/selection. Since the genome context, not the gene content, encodes the genomic blueprint of the cell, stress-induced rapid and massive reorganization of genome topology functions as a very important mechanism for genome (karyotype) evolution. In recent years, the phenomenon of genome chaos has been confirmed by various sequencing efforts, and many different terms have been coined to describe different subtypes of the chaotic genome including "chromothripsis," "chromoplexy," and "structural mutations." To advance this exciting field, we need an effective experimental system to induce and characterize the karyotype reorganization process. In this chapter, an experimental protocol to induce chaotic genomes is described, following a brief discussion of the mechanism and implication of genome chaos in cancer evolution.
Chen, Hao; Wang, Xiangfeng
In plants and animals, chromosomal breakage and fusion events based on conserved syntenic genomic blocks lead to conserved patterns of karyotype evolution among species of the same family. However, karyotype information has not been well utilized in genomic comparison studies. We present CrusView, a Java-based bioinformatic application utilizing Standard Widget Toolkit/Swing graphics libraries and a SQLite database for performing visualized analyses of comparative genomics data in Brassicaceae (crucifer) plants. Compared with similar software and databases, one of the unique features of CrusView is its integration of karyotype information when comparing two genomes. This feature allows users to perform karyotype-based genome assembly and karyotype-assisted genome synteny analyses with preset karyotype patterns of the Brassicaceae genomes. Additionally, CrusView is a local program, which gives its users high flexibility when analyzing unpublished genomes and allows users to upload self-defined genomic information so that they can visually study the associations between genome structural variations and genetic elements, including chromosomal rearrangements, genomic macrosynteny, gene families, high-frequency recombination sites, and tandem and segmental duplications between related species. This tool will greatly facilitate karyotype, chromosome, and genome evolution studies using visualized comparative genomics approaches in Brassicaceae species. CrusView is freely available at http://www.cmbb.arizona.edu/CrusView/. PMID:23898041
Full Text Available Twenty one fully sequenced and well annotated insect genomes were used to construct genome content matrices for phylogenetic analysis and functional annotation of insect genomes. To examine the role of e-value cutoff in ortholog determination we used scaled e-value cutoffs and a single linkage clustering approach.. The present communication includes (1 a list of the genomes used to construct the genome content phylogenetic matrices, (2 a nexus file with the data matrices used in phylogenetic analysis, (3 a nexus file with the Newick trees generated by phylogenetic analysis, (4 an excel file listing the Core (CORE genes and Unique (UNI genes found in five insect groups, and (5 a figure showing a plot of consistency index (CI versus percent of unannotated genes that are apomorphies in the data set for gene losses and gains and bar plots of gains and losses for four consistency index (CI cutoffs.
Ciobanu, Doina; Clum, Alicia; Singh, Vasanth; Salamov, Asaf; Han, James; Copeland, Alex; Grigoriev, Igor; James, Timothy; Singer, Steven; Woyke, Tanja; Malmstrom, Rex; Cheng, Jan-Fang
Despite their small size, unicellular eukaryotes have complex genomes with a high degree of plasticity that allow them to adapt quickly to environmental changes. Unicellular eukaryotes live with prokaryotes and higher eukaryotes, frequently in symbiotic or parasitic niches. To this day their contribution to the dynamics of the environmental communities remains to be understood. Unfortunately, the vast majority of eukaryotic microorganisms are either uncultured or unculturable, making genome sequencing impossible using traditional approaches. We have developed an approach to isolate unicellular eukaryotes of interest from environmental samples, and to sequence and analyze their genomes and transcriptomes. We have tested our methods with six species: an uncharacterized protist from cellulose-enriched compost identified as Platyophrya, a close relative of P. vorax; the fungus Metschnikowia bicuspidate, a parasite of water flea Daphnia; the mycoparasitic fungi Piptocephalis cylindrospora, a parasite of Cokeromyces and Mucor; Caulochytrium protosteloides, a parasite of Sordaria; Rozella allomycis, a parasite of the water mold Allomyces; and the microalgae Chlamydomonas reinhardtii. Here, we present the four components of our approach: pre-sequencing methods, sequence analysis for single cell genome assembly, sequence analysis of single cell transcriptomes, and genome annotation. This technology has the potential to uncover the complexity of single cell eukaryotes and their role in the environmental samples.
Ivanov, Mark V.; Lobas, Anna A.; Levitsky, Lev I.; Moshkovskii, Sergei A.; Gorshkov, Mikhail V.
In a proteogenomic approach based on tandem mass spectrometry analysis of proteolytic peptide mixtures, customized exome or RNA-seq databases are employed for identifying protein sequence variants. However, the problem of variant peptide identification without personalized genomic data is important for a variety of applications. Following the recent proposal by Chick et al. (Nat. Biotechnol. 33, 743-749, 2015) on the feasibility of such variant peptide search, we evaluated two available approaches based on the previously suggested "open" search and the "brute-force" strategy. To improve the efficiency of these approaches, we propose an algorithm for exclusion of false variant identifications from the search results involving analysis of modifications mimicking single amino acid substitutions. Also, we propose a de novo based scoring scheme for assessment of identified point mutations. In the scheme, the search engine analyzes y-type fragment ions in MS/MS spectra to confirm the location of the mutation in the variant peptide sequence.
Bailey Timothy L
Full Text Available Abstract Background: Current methods to find significantly under- and over-represented gene ontology (GO terms in a set of genes consider the genes as equally probable "balls in a bag", as may be appropriate for transcripts in micro-array data. However, due to the varying length of genes and intergenic regions, that approach is inappropriate for deciding if any GO terms are correlated with a set of genomic positions. Results: We present an algorithm – GONOME – that can determine which GO terms are significantly associated with a set of genomic positions given a genome annotated with (at least the starts and ends of genes. We show that certain GO terms may appear to be significantly associated with a set of randomly chosen positions in the human genome if gene lengths are not considered, and that these same terms have been reported as significantly over-represented in a number of recent papers. This apparent over-representation disappears when gene lengths are considered, as GONOME does. For example, we show that, when gene length is taken into account, the term "development" is not significantly enriched in genes associated with human CpG islands, in contradiction to a previous report. We further demonstrate the efficacy of GONOME by showing that occurrences of the proteosome-associated control element (PACE upstream activating sequence in the S. cerevisiae genome associate significantly to appropriate GO terms. An extension of this approach yields a whole-genome motif discovery algorithm that allows identification of many other promoter sequences linked to different types of genes, including a large group of previously unknown motifs significantly associated with the terms 'translation' and 'translational elongation'. Conclusion: GONOME is an algorithm that correctly extracts over-represented GO terms from a set of genomic positions. By explicitly considering gene size, GONOME avoids a systematic bias toward GO terms linked to large genes
Full Text Available The aim of this study was to identify the evidence of recent selection based on estimation of the integrated Haplotype Score (iHS, population differentiation index (FST and characterize affected regions near QTL associated with traits under strong selection in Pinzgau cattle. In total 21 Austrian and 19 Slovak purebreed bulls genotyped with Illumina bovineHD and bovineSNP50 BeadChip were used to identify genomic regions under selection. Only autosomal loci with call rate higher than 90%, minor allele frequency higher than 0.01 and Hardy-Weinberg equlibrium limit of 0.001 were included in the subsequent analyses of selection sweeps presence. The final dataset was consisted from 30538 SNPs with 81.86 kb average adjacent SNPs spacing. The iHS score were averaged into non-overlapping 500 kb segments across the genome. The FST values were also plotted against genome position based on sliding windows approach and averaged over 8 consecutive SNPs. Based on integrated Haplotype Score evaluation only 7 regions with iHS score higher than 1.7 was found. The average iHS score observed for each adjacent syntenic regions indicated slight effect of recent selection in analysed group of Pinzgau bulls. The level of genetic differentiation between Austrian and Slovak bulls estimated based on FST index was low. Only 24% of FST values calculated for each SNP was greather than 0.01. By using sliding windows approach was found that 5% of analysed windows had higher value than 0.01. Our results indicated use of similar selection scheme in breeding programs of Slovak and Austrian Pinzgau bulls. The evidence for genome-wide association between signatures of selection and regions affecting complex traits such as milk production was insignificant, because the loci in segments identified as affected by selection were very distant from each other. Identification of genomic regions that may be under pressure of selection for phenotypic traits to better understanding of the
Mar 1, 2010 ... For genomic in situ hybridization, genomic DNA from O. australiensis was used as probe for the mitotic and meiotic ... Wide hybridization is one of the plant breeding approaches ..... Disease and insect resistance in rice.
The second edition of this successful book provides further and in-depth insight into theoretical models dealing with Internet addiction, as well as includes new therapeutical approaches. The editors also broach the emerging topic of smartphone addiction. This book combines a scholarly introduction with state-of-the-art research in the characterization of Internet addiction. It is intended for a broad audience including scientists, students and practitioners. The first part of the book contains an introduction to Internet addiction and their pathogenesis. The second part of the book is dedicated to an in-depth review of neuroscientific findings which cover studies using a variety of biological techniques including brain imaging and molecular genetics. The third part of the book focuses on therapeutic interventions for Internet addiction. The fourth part of the present book is an extension to the first edition and deals with a new emerging potential disorder related to Internet addiction – smartphone addicti...
S, Chandana; Russiachand, Heikham; H, Pradeep; S, Shilpa; M, Ashwini; S, Sahana; B, Jayanth; Atla, Goutham; Jain, Smita; Arunkumar, Nandini; Gowda, Malali
Next-Generation Sequencing (NGS; http://www.genome.gov/12513162) is a recent life-sciences technological revolution that allows scientists to decode genomes or transcriptomes at a much faster rate with a lower cost. Genomic-based studies are in a relatively slow pace in India due to the non-availability of genomics experts, trained personnel and dedicated service providers. Using NGS there is a lot of potential to study India's national diversity (of all kinds). We at the Centre for Cellular and Molecular Platforms (C-CAMP) have launched the Next Generation Genomics Facility (NGGF) to provide genomics service to scientists, to train researchers and also work on national and international genomic projects. We have HiSeq1000 from Illumina and GS-FLX Plus from Roche454. The long reads from GS FLX Plus, and high sequence depth from HiSeq1000, are the best and ideal hybrid approaches for de novo and re-sequencing of genomes and transcriptomes. At our facility, we have sequenced around 70 different organisms comprising of more than 388 genomes and 615 transcriptomes – prokaryotes and eukaryotes (fungi, plants and animals). In addition we have optimized other unique applications such as small RNA (miRNA, siRNA etc), long Mate-pair sequencing (2 to 20 Kb), Coding sequences (Exome), Methylome (ChIP-Seq), Restriction Mapping (RAD-Seq), Human Leukocyte Antigen (HLA) typing, mixed genomes (metagenomes) and target amplicons, etc. Translating DNA sequence data from NGS sequencer into meaningful information is an important exercise. Under NGGF, we have bioinformatics experts and high-end computing resources to dissect NGS data such as genome assembly and annotation, gene expression, target enrichment, variant calling (SSR or SNP), comparative analysis etc. Our services (sequencing and bioinformatics) have been utilized by more than 45 organizations (academia and industry) both within India and outside, resulting several publications in peer-reviewed journals and several genomic
Myelodysplastic syndromes (MDS) are characterized by clonal proliferation of hematopoietic stem/progenitor cells and their apoptosis, and show a propensity to progress to acute myelogenous leukemia (AML). Although MDS are recognized as neoplastic diseases caused by genomic aberrations of hematopoietic cells, the details of the genetic abnormalities underlying disease development have not as yet been fully elucidated due to difficulties in analyzing chromosomal abnormalities. Recent advances in comprehensive analyses of disease genomes including whole-genome sequencing technologies have revealed the genomic abnormalities in MDS. Surprisingly, gene mutations were found in approximately 80-90% of cases with MDS, and the novel mutations discovered with these technologies included previously unknown, MDS-specific, mutations such as those of the genes in the RNA-splicing machinery. It is anticipated that these recent studies will shed new light on the pathophysiology of MDS due to genomic aberrations.
Weber, Hannah; Garabedian, Michael J
Mediator is a conserved, multi-subunit macromolecular machine divided structurally into head, middle, and tail modules, along with a transiently associating kinase module. Mediator functions as an integrator of transcriptional regulatory activity by interacting with DNA-bound transcription factors and with RNA polymerase II (Pol II) to both activate and repress gene expression. Mediator has been shown to affect multiple steps in transcription, including chromatin looping between enhancers and promoters, pre-initiation complex formation, transcriptional elongation, and mRNA splicing. Individual Mediator subunits participate in regulation of gene expression by the estrogen and androgen receptors and are altered in a number of endocrine cancers, including breast and prostate cancer. In addition to its role in genomic signaling, MED12 has been implicated in non-genomic signaling by interacting with and activating TGF-beta receptor 2 in the cytoplasm. Recent structural studies have revealed extensive inter-domain interactions and complex architecture of the Mediator-Pol II complex, suggesting that Mediator is capable of reorganizing its conformation and composition to fit cellular needs. We propose that alterations in Mediator subunit expression that occur in various cancers could impact the organization and function of Mediator, resulting in changes in gene expression that promote malignancy. A better understanding of the role of Mediator in cancer could reveal new approaches to the diagnosis and treatment of Mediator-dependent endocrine cancers, especially in settings of therapy resistance. Copyright © 2017 Elsevier Inc. All rights reserved.
Pérez-Enciso, Miguel; Rincón, Juan C; Legarra, Andrés
The development of next-generation sequencing technologies (NGS) has made the use of whole-genome sequence data for routine genetic evaluations possible, which has triggered a considerable interest in animal and plant breeding fields. Here, we investigated whether complete or partial sequence data can improve upon existing SNP (single nucleotide polymorphism) array-based selection strategies by simulation using a mixed coalescence - gene-dropping approach. We simulated 20 or 100 causal mutations (quantitative trait nucleotides, QTN) within 65 predefined 'gene' regions, each 10 kb long, within a genome composed of ten 3-Mb chromosomes. We compared prediction accuracy by cross-validation using a medium-density chip (7.5 k SNPs), a high-density (HD, 17 k) and sequence data (335 k). Genetic evaluation was based on a GBLUP method. The simulations showed: (1) a law of diminishing returns with increasing number of SNPs; (2) a modest effect of SNP ascertainment bias in arrays; (3) a small advantage of using whole-genome sequence data vs. HD arrays i.e. ~4%; (4) a minor effect of NGS errors except when imputation error rates are high (≥20%); and (5) if QTN were known, prediction accuracy approached 1. Since this is obviously unrealistic, we explored milder assumptions. We showed that, if all SNPs within causal genes were included in the prediction model, accuracy could also dramatically increase by ~40%. However, this criterion was highly sensitive to either misspecification (including wrong genes) or to the use of an incomplete gene list; in these cases, accuracy fell rapidly towards that reached when all SNPs from sequence data were blindly included in the model. Our study shows that, unless an accurate prior estimate on the functionality of SNPs can be included in the predictor, there is a law of diminishing returns with increasing SNP density. As a result, use of whole-genome sequence data may not result in a highly increased selection response over high
He, Karen Y; Ge, Dongliang; He, Max M
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.
Jiang, Jianping; Gu, Jianlei; Zhang, Liang; Zhang, Chenyi; Deng, Xiao; Dou, Tonghai; Zhao, Guoping; Zhou, Yan
Over the last decade, emerging research methods, such as comparative genomic analysis and phylogenetic study, have yielded new insights into genotypes and phenotypes of closely related bacterial strains. Several findings have revealed that genomic structural variations (SVs), including gene gain/loss, gene duplication and genome rearrangement, can lead to different phenotypes among strains, and an investigation of genes affected by SVs may extend our knowledge of the relationships between SVs and phenotypes in microbes, especially in pathogenic bacteria. In this work, we introduce a 'Genome Topology Network' (GTN) method based on gene homology and gene locations to analyze genomic SVs and perform phylogenetic analysis. Furthermore, the concept of 'unfixed ortholog' has been proposed, whose members are affected by SVs in genome topology among close species. To improve the precision of 'unfixed ortholog' recognition, a strategy to detect annotation differences and complete gene annotation was applied. To assess the GTN method, a set of thirteen complete M. tuberculosis genomes was analyzed as a case study. GTNs with two different gene homology-assigning methods were built, the Clusters of Orthologous Groups (COG) method and the orthoMCL clustering method, and two phylogenetic trees were constructed accordingly, which may provide additional insights into whole genome-based phylogenetic analysis. We obtained 24 unfixable COG groups, of which most members were related to immunogenicity and drug resistance, such as PPE-repeat proteins (COG5651) and transcriptional regulator TetR gene family members (COG1309). The GTN method has been implemented in PERL and released on our website. The tool can be downloaded from http://homepage.fudan.edu.cn/zhouyan/gtn/ , and allows re-annotating the 'lost' genes among closely related genomes, analyzing genes affected by SVs, and performing phylogenetic analysis. With this tool, many immunogenic-related and drug resistance-related genes
Zamani, Neda; Sundström, Görel; Meadows, Jennifer R S; Höppner, Marc P; Dainat, Jacques; Lantz, Henrik; Haas, Brian J; Grabherr, Manfred G
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
Full Text Available The purpose of this study was to compare results obtained from various methodologies for genome-wide association studies, when applied to real data, in terms of number and commonality of regions identified and their genetic variance explained, computational speed, and possible pitfalls in interpretations of results. Methodologies include: two iteratively reweighted single-step genomic BLUP procedures (ssGWAS1 and ssGWAS2, a single-marker model (CGWAS, and BayesB. The ssGWAS methods utilize genomic breeding values (GEBVs based on combined pedigree, genomic and phenotypic information, while CGWAS and BayesB only utilize phenotypes from genotyped animals or pseudo-phenotypes. In this study, ssGWAS was performed by converting GEBVs to SNP marker effects. Unequal variances for markers were incorporated for calculating weights into a new genomic relationship matrix. SNP weights were refined iteratively. The data was body weight at 6 weeks on 274,776 broiler chickens, of which 4553 were genotyped using a 60k SNP chip. Comparison of genomic regions was based on genetic variances explained by local SNP regions (20 SNPs. After 3 iterations, the noise was greatly reduced of ssGWAS1 and results are similar to that of CGWAS, with 4 out of the top 10 regions in common. In contrast, for BayesB, the plot was dominated by a single region explaining 23.1% of the genetic variance. This same region was found by ssGWAS1 with the same rank, but the amount of genetic variation attributed to the region was only 3%. These finding emphasize the need for caution when comparing and interpreting results from various methods, and highlight that detected associations, and strength of association, strongly depends on methodologies and details of implementations. BayesB appears to overly shrink regions to zero, while overestimating the amount of genetic variation attributed to the remaining SNP effects. The real world is most likely a compromise between methods and remains to
Schürch, A C; Arredondo-Alonso, S; Willems, R J L; Goering, R V
Whole genome sequence (WGS)-based strain typing finds increasing use in the epidemiologic analysis of bacterial pathogens in both public health as well as more localized infection control settings. This minireview describes methodologic approaches that have been explored for WGS-based epidemiologic analysis and considers the challenges and pitfalls of data interpretation. Personal collection of relevant publications. When applying WGS to study the molecular epidemiology of bacterial pathogens, genomic variability between strains is translated into measures of distance by determining single nucleotide polymorphisms in core genome alignments or by indexing allelic variation in hundreds to thousands of core genes, assigning types to unique allelic profiles. Interpreting isolate relatedness from these distances is highly organism specific, and attempts to establish species-specific cutoffs are unlikely to be generally applicable. In cases where single nucleotide polymorphism or core gene typing do not provide the resolution necessary for accurate assessment of the epidemiology of bacterial pathogens, inclusion of accessory gene or plasmid sequences may provide the additional required discrimination. As with all epidemiologic analysis, realizing the full potential of the revolutionary advances in WGS-based approaches requires understanding and dealing with issues related to the fundamental steps of data generation and interpretation. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.
Chen, Xinwei; Hedley, P.E.; Morris, J.; Liu, Hui; Niks, R.E.; Waugh, R.
Positional gene isolation in unsequenced species generally requires either a reference genome sequence or an inference of gene content based on conservation of synteny with a genomic model. In the large unsequenced genomes of the Triticeae cereals the latter, i.e. conservation of synteny with the
Full Text Available Genomic selection is a promising