Isolation and analysis of high quality nuclear DNA with reduced organellar DNA for plant genome sequencing and resequencing

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Zdepski Anna

2011-05-01

Full Text Available Abstract Background High throughput sequencing (HTS technologies have revolutionized the field of genomics by drastically reducing the cost of sequencing, making it feasible for individual labs to sequence or resequence plant genomes. Obtaining high quality, high molecular weight DNA from plants poses significant challenges due to the high copy number of chloroplast and mitochondrial DNA, as well as high levels of phenolic compounds and polysaccharides. Multiple methods have been used to isolate DNA from plants; the CTAB method is commonly used to isolate total cellular DNA from plants that contain nuclear DNA, as well as chloroplast and mitochondrial DNA. Alternatively, DNA can be isolated from nuclei to minimize chloroplast and mitochondrial DNA contamination. Results We describe optimized protocols for isolation of nuclear DNA from eight different plant species encompassing both monocot and eudicot species. These protocols use nuclei isolation to minimize chloroplast and mitochondrial DNA contamination. We also developed a protocol to determine the number of chloroplast and mitochondrial DNA copies relative to the nuclear DNA using quantitative real time PCR (qPCR. We compared DNA isolated from nuclei to total cellular DNA isolated with the CTAB method. As expected, DNA isolated from nuclei consistently yielded nuclear DNA with fewer chloroplast and mitochondrial DNA copies, as compared to the total cellular DNA prepared with the CTAB method. This protocol will allow for analysis of the quality and quantity of nuclear DNA before starting a plant whole genome sequencing or resequencing experiment. Conclusions Extracting high quality, high molecular weight nuclear DNA in plants has the potential to be a bottleneck in the era of whole genome sequencing and resequencing. The methods that are described here provide a framework for researchers to extract and quantify nuclear DNA in multiple types of plants.

Whole genome resequencing of black Angus and Holstein cattle for SNP and CNV discovery

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Stothard Paul

2011-11-01

Full Text Available Abstract Background One of the goals of livestock genomics research is to identify the genetic differences responsible for variation in phenotypic traits, particularly those of economic importance. Characterizing the genetic variation in livestock species is an important step towards linking genes or genomic regions with phenotypes. The completion of the bovine genome sequence and recent advances in DNA sequencing technology allow for in-depth characterization of the genetic variations present in cattle. Here we describe the whole-genome resequencing of two Bos taurus bulls from distinct breeds for the purpose of identifying and annotating novel forms of genetic variation in cattle. Results The genomes of a Black Angus bull and a Holstein bull were sequenced to 22-fold and 19-fold coverage, respectively, using the ABI SOLiD system. Comparisons of the sequences with the Btau4.0 reference assembly yielded 7 million single nucleotide polymorphisms (SNPs, 24% of which were identified in both animals. Of the total SNPs found in Holstein, Black Angus, and in both animals, 81%, 81%, and 75% respectively are novel. In-depth annotations of the data identified more than 16 thousand distinct non-synonymous SNPs (85% novel between the two datasets. Alignments between the SNP-altered proteins and orthologues from numerous species indicate that many of the SNPs alter well-conserved amino acids. Several SNPs predicted to create or remove stop codons were also found. A comparison between the sequencing SNPs and genotyping results from the BovineHD high-density genotyping chip indicates a detection rate of 91% for homozygous SNPs and 81% for heterozygous SNPs. The false positive rate is estimated to be about 2% for both the Black Angus and Holstein SNP sets, based on follow-up genotyping of 422 and 427 SNPs, respectively. Comparisons of read depth between the two bulls along the reference assembly identified 790 putative copy-number variations (CNVs. Ten

Investigating Drought Tolerance in Chickpea Using Genome-Wide Association Mapping and Genomic Selection Based on Whole-Genome Resequencing Data.

Science.gov (United States)

Li, Yongle; Ruperao, Pradeep; Batley, Jacqueline; Edwards, David; Khan, Tanveer; Colmer, Timothy D; Pang, Jiayin; Siddique, Kadambot H M; Sutton, Tim

2018-01-01

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.

Prediction of Genes Related to Positive Selection Using Whole-Genome Resequencing in Three Commercial Pig Breeds

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HyoYoung Kim

2015-12-01

Full Text Available Selective sweep can cause genetic differentiation across populations, which allows for the identification of possible causative regions/genes underlying important traits. The pig has experienced a long history of allele frequency changes through artificial selection in the domestication process. We obtained an average of 329,482,871 sequence reads for 24 pigs from three pig breeds: Yorkshire (n = 5, Landrace (n = 13, and Duroc (n = 6. An average read depth of 11.7 was obtained using whole-genome resequencing on an Illumina HiSeq2000 platform. In this study, cross-population extended haplotype homozygosity and cross-population composite likelihood ratio tests were implemented to detect genes experiencing positive selection for the genome-wide resequencing data generated from three commercial pig breeds. In our results, 26, 7, and 14 genes from Yorkshire, Landrace, and Duroc, respectively were detected by two kinds of statistical tests. Significant evidence for positive selection was identified on genes ST6GALNAC2 and EPHX1 in Yorkshire, PARK2 in Landrace, and BMP6, SLA-DQA1, and PRKG1 in Duroc.These genes are reportedly relevant to lactation, reproduction, meat quality, and growth traits. To understand how these single nucleotide polymorphisms (SNPs related positive selection affect protein function, we analyzed the effect of non-synonymous SNPs. Three SNPs (rs324509622, rs80931851, and rs80937718 in the SLA-DQA1 gene were significant in the enrichment tests, indicating strong evidence for positive selection in Duroc. Our analyses identified genes under positive selection for lactation, reproduction, and meat-quality and growth traits in Yorkshire, Landrace, and Duroc, respectively.

Genome wide re-sequencing of newly developed Rice Lines from common wild rice (Oryza rufipogon Griff.) for the identification of NBS-LRR genes.

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Liu, Wen; Ghouri, Fozia; Yu, Hang; Li, Xiang; Yu, Shuhong; Shahid, Muhammad Qasim; Liu, Xiangdong

2017-01-01

Common wild rice (Oryza rufipogon Griff.) is an important germplasm for rice breeding, which contains many resistance genes. Re-sequencing provides an unprecedented opportunity to explore the abundant useful genes at whole genome level. Here, we identified the nucleotide-binding site leucine-rich repeat (NBS-LRR) encoding genes by re-sequencing of two wild rice lines (i.e. Huaye 1 and Huaye 2) that were developed from common wild rice. We obtained 128 to 147 million reads with approximately 32.5-fold coverage depth, and uniquely covered more than 89.6% (> = 1 fold) of reference genomes. Two wild rice lines showed high SNP (single-nucleotide polymorphisms) variation rate in 12 chromosomes against the reference genomes of Nipponbare (japonica cultivar) and 93-11 (indica cultivar). InDels (insertion/deletion polymorphisms) count-length distribution exhibited normal distribution in the two lines, and most of the InDels were ranged from -5 to 5 bp. With reference to the Nipponbare genome sequence, we detected a total of 1,209,308 SNPs, 161,117 InDels and 4,192 SVs (structural variations) in Huaye 1, and 1,387,959 SNPs, 180,226 InDels and 5,305 SVs in Huaye 2. A total of 44.9% and 46.9% genes exhibited sequence variations in two wild rice lines compared to the Nipponbare and 93-11 reference genomes, respectively. Analysis of NBS-LRR mutant candidate genes showed that they were mainly distributed on chromosome 11, and NBS domain was more conserved than LRR domain in both wild rice lines. NBS genes depicted higher levels of genetic diversity in Huaye 1 than that found in Huaye 2. Furthermore, protein-protein interaction analysis showed that NBS genes mostly interacted with the cytochrome C protein (Os05g0420600, Os01g0885000 and BGIOSGA038922), while some NBS genes interacted with heat shock protein, DNA-binding activity, Phosphoinositide 3-kinase and a coiled coil region. We explored abundant NBS-LRR encoding genes in two common wild rice lines through genome wide re-sequencing

Diversity and Genome Analysis of Australian and Global Oilseed Brassica napus L. Germplasm Using Transcriptomics and Whole Genome Re-sequencing

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M. Michelle Malmberg

2018-04-01

Full Text Available Intensive breeding of Brassica napus has resulted in relatively low diversity, such that B. napus would benefit from germplasm improvement schemes that sustain diversity. As such, samples representative of global germplasm pools need to be assessed for existing population structure, diversity and linkage disequilibrium (LD. Complexity reduction genotyping-by-sequencing (GBS methods, including GBS-transcriptomics (GBS-t, enable cost-effective screening of a large number of samples, while whole genome re-sequencing (WGR delivers the ability to generate large numbers of unbiased genomic single nucleotide polymorphisms (SNPs, and identify structural variants (SVs. Furthermore, the development of genomic tools based on whole genomes representative of global oilseed diversity and orientated by the reference genome has substantial industry relevance and will be highly beneficial for canola breeding. As recent studies have focused on European and Chinese varieties, a global diversity panel as well as a substantial number of Australian spring types were included in this study. Focusing on industry relevance, 633 varieties were initially genotyped using GBS-t to examine population structure using 61,037 SNPs. Subsequently, 149 samples representative of global diversity were selected for WGR and both data sets used for a side-by-side evaluation of diversity and LD. The WGR data was further used to develop genomic resources consisting of a list of 4,029,750 high-confidence SNPs annotated using SnpEff, and SVs in the form of 10,976 deletions and 2,556 insertions. These resources form the basis of a reliable and repeatable system allowing greater integration between canola genomics studies, with a strong focus on breeding germplasm and industry applicability.

Investigating Drought Tolerance in Chickpea Using Genome-Wide Association Mapping and Genomic Selection Based on Whole-Genome Resequencing Data

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Yongle Li

2018-02-01

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.

Simultaneous analysis of all SNPs in genome-wide and re-sequencing association studies.

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Clive J Hoggart

2008-07-01

Full Text Available Testing one SNP at a time does not fully realise the potential of genome-wide association studies to identify multiple causal variants, which is a plausible scenario for many complex diseases. We show that simultaneous analysis of the entire set of SNPs from a genome-wide study to identify the subset that best predicts disease outcome is now feasible, thanks to developments in stochastic search methods. We used a Bayesian-inspired penalised maximum likelihood approach in which every SNP can be considered for additive, dominant, and recessive contributions to disease risk. Posterior mode estimates were obtained for regression coefficients that were each assigned a prior with a sharp mode at zero. A non-zero coefficient estimate was interpreted as corresponding to a significant SNP. We investigated two prior distributions and show that the normal-exponential-gamma prior leads to improved SNP selection in comparison with single-SNP tests. We also derived an explicit approximation for type-I error that avoids the need to use permutation procedures. As well as genome-wide analyses, our method is well-suited to fine mapping with very dense SNP sets obtained from re-sequencing and/or imputation. It can accommodate quantitative as well as case-control phenotypes, covariate adjustment, and can be extended to search for interactions. Here, we demonstrate the power and empirical type-I error of our approach using simulated case-control data sets of up to 500 K SNPs, a real genome-wide data set of 300 K SNPs, and a sequence-based dataset, each of which can be analysed in a few hours on a desktop workstation.

Experimental evolution, genetic analysis and genome re-sequencing reveal the mutation conferring artemisinin resistance in an isogenic lineage of malaria parasites

KAUST Repository

Hunt, Paul

2010-09-16

Background: Classical and quantitative linkage analyses of genetic crosses have traditionally been used to map genes of interest, such as those conferring chloroquine or quinine resistance in malaria parasites. Next-generation sequencing technologies now present the possibility of determining genome-wide genetic variation at single base-pair resolution. Here, we combine in vivo experimental evolution, a rapid genetic strategy and whole genome re-sequencing to identify the precise genetic basis of artemisinin resistance in a lineage of the rodent malaria parasite, Plasmodium chabaudi. Such genetic markers will further the investigation of resistance and its control in natural infections of the human malaria, P. falciparum.Results: A lineage of isogenic in vivo drug-selected mutant P. chabaudi parasites was investigated. By measuring the artemisinin responses of these clones, the appearance of an in vivo artemisinin resistance phenotype within the lineage was defined. The underlying genetic locus was mapped to a region of chromosome 2 by Linkage Group Selection in two different genetic crosses. Whole-genome deep coverage short-read re-sequencing (IlluminaSolexa) defined the point mutations, insertions, deletions and copy-number variations arising in the lineage. Eight point mutations arise within the mutant lineage, only one of which appears on chromosome 2. This missense mutation arises contemporaneously with artemisinin resistance and maps to a gene encoding a de-ubiquitinating enzyme.Conclusions: This integrated approach facilitates the rapid identification of mutations conferring selectable phenotypes, without prior knowledge of biological and molecular mechanisms. For malaria, this model can identify candidate genes before resistant parasites are commonly observed in natural human malaria populations. 2010 Hunt et al; licensee BioMed Central Ltd.

The wolf reference genome sequence (Canis lupus lupus) and its implications for Canis spp. population genomics

DEFF Research Database (Denmark)

Gopalakrishnan, Shyam; Samaniego Castruita, Jose Alfredo; Sinding, Mikkel Holger Strander

2017-01-01

Background An increasing number of studies are addressing the evolutionary genomics of dog domestication, principally through resequencing dog, wolf and related canid genomes. There is, however, only one de novo assembled canid genome currently available against which to map such data - that of a......Background An increasing number of studies are addressing the evolutionary genomics of dog domestication, principally through resequencing dog, wolf and related canid genomes. There is, however, only one de novo assembled canid genome currently available against which to map such data...

Whole-Genome Resequencing of Experimental Populations Reveals Polygenic Basis of Egg-Size Variation in Drosophila melanogaster.

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Jha, Aashish R; Miles, Cecelia M; Lippert, Nodia R; Brown, Christopher D; White, Kevin P; Kreitman, Martin

2015-10-01

Complete genome resequencing of populations holds great promise in deconstructing complex polygenic traits to elucidate molecular and developmental mechanisms of adaptation. Egg size is a classic adaptive trait in insects, birds, and other taxa, but its highly polygenic architecture has prevented high-resolution genetic analysis. We used replicated experimental evolution in Drosophila melanogaster and whole-genome sequencing to identify consistent signatures of polygenic egg-size adaptation. A generalized linear-mixed model revealed reproducible allele frequency differences between replicated experimental populations selected for large and small egg volumes at approximately 4,000 single nucleotide polymorphisms (SNPs). Several hundred distinct genomic regions contain clusters of these SNPs and have lower heterozygosity than the genomic background, consistent with selection acting on polymorphisms in these regions. These SNPs are also enriched among genes expressed in Drosophila ovaries and many of these genes have well-defined functions in Drosophila oogenesis. Additional genes regulating egg development, growth, and cell size show evidence of directional selection as genes regulating these biological processes are enriched for highly differentiated SNPs. Genetic crosses performed with a subset of candidate genes demonstrated that these genes influence egg size, at least in the large genetic background. These findings confirm the highly polygenic architecture of this adaptive trait, and suggest the involvement of many novel candidate genes in regulating egg size. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Genomewide variation in an introgression line of rice-Zizania revealed by whole-genome re-sequencing.

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Zhen-Hui Wang

Full Text Available BACKGROUND: Hybridization between genetically diverged organisms is known as an important avenue that drives plant genome evolution. The possible outcomes of hybridization would be the occurrences of genetic instabilities in the resultant hybrids. It remained under-investigated however whether pollination by alien pollens of a closely related but sexually "incompatible" species could evoke genomic changes and to what extent it may result in phenotypic novelties in the derived progenies. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we have re-sequenced the genomes of Oryza sativa ssp. japonica cv. Matsumae and one of its derived introgressant RZ35 that was obtained from an introgressive hybridization between Matsumae and Zizanialatifolia Griseb. in general, 131 millions 90 base pair (bp paired-end reads were generated which covered 13.2 and 21.9 folds of the Matsumae and RZ35 genomes, respectively. Relative to Matsumae, a total of 41,724 homozygous single nucleotide polymorphisms (SNPs and 17,839 homozygous insertions/deletions (indels were identified in RZ35, of which 3,797 SNPs were nonsynonymous mutations. Furthermore, rampant mobilization of transposable elements (TEs was found in the RZ35 genome. The results of pathogen inoculation revealed that RZ35 exhibited enhanced resistance to blast relative to Matsumae. Notably, one nonsynonymous mutation was found in the known blast resistance gene Pid3/Pi25 and real-time quantitative (q RT-PCR analysis revealed constitutive up-regulation of its expression, suggesting both altered function and expression of Pid3/Pi25 may be responsible for the enhanced resistance to rice blast by RZ35. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that introgressive hybridization by Zizania has provoked genomewide, extensive genomic changes in the rice genome, and some of which have resulted in important phenotypic novelties. These findings suggest that introgressive hybridization by alien pollens of even a

Discovery of Gene Sources for Economic Traits in Hanwoo by Whole-genome Resequencing

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Younhee Shin

2016-09-01

Full Text Available Hanwoo, a Korean native cattle (Bos taurus coreana, has great economic value due to high meat quality. Also, the breed has genetic variations that are associated with production traits such as health, disease resistance, reproduction, growth as well as carcass quality. In this study, next generation sequencing technologies and the availability of an appropriate reference genome were applied to discover a large amount of single nucleotide polymorphisms (SNPs in ten Hanwoo bulls. Analysis of whole-genome resequencing generated a total of 26.5 Gb data, of which 594,716,859 and 592,990,750 reads covered 98.73% and 93.79% of the bovine reference genomes of UMD 3.1 and Btau 4.6.1, respectively. In total, 2,473,884 and 2,402,997 putative SNPs were discovered, of which 1,095,922 (44.3% and 982,674 (40.9% novel SNPs were discovered against UMD3.1 and Btau 4.6.1, respectively. Among the SNPs, the 46,301 (UMD 3.1 and 28,613 SNPs (Btau 4.6.1 that were identified as Hanwoo-specific SNPs were included in the functional genes that may be involved in the mechanisms of milk production, tenderness, juiciness, marbling of Hanwoo beef and yellow hair. Most of the Hanwoo-specific SNPs were identified in the promoter region, suggesting that the SNPs influence differential expression of the regulated genes relative to the relevant traits. In particular, the non-synonymous (ns SNPs found in CORIN, which is a negative regulator of Agouti, might be a causal variant to determine yellow hair of Hanwoo. Our results will provide abundant genetic sources of variation to characterize Hanwoo genetics and for subsequent breeding.

Integrating sequencing technologies in personal genomics: optimal low cost reconstruction of structural variants.

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Jiang Du

2009-07-01

Full Text Available The goal of human genome re-sequencing is obtaining an accurate assembly of an individual's genome. Recently, there has been great excitement in the development of many technologies for this (e.g. medium and short read sequencing from companies such as 454 and SOLiD, and high-density oligo-arrays from Affymetrix and NimbelGen, with even more expected to appear. The costs and sensitivities of these technologies differ considerably from each other. As an important goal of personal genomics is to reduce the cost of re-sequencing to an affordable point, it is worthwhile to consider optimally integrating technologies. Here, we build a simulation toolbox that will help us optimally combine different technologies for genome re-sequencing, especially in reconstructing large structural variants (SVs. SV reconstruction is considered the most challenging step in human genome re-sequencing. (It is sometimes even harder than de novo assembly of small genomes because of the duplications and repetitive sequences in the human genome. To this end, we formulate canonical problems that are representative of issues in reconstruction and are of small enough scale to be computationally tractable and simulatable. Using semi-realistic simulations, we show how we can combine different technologies to optimally solve the assembly at low cost. With mapability maps, our simulations efficiently handle the inhomogeneous repeat-containing structure of the human genome and the computational complexity of practical assembly algorithms. They quantitatively show how combining different read lengths is more cost-effective than using one length, how an optimal mixed sequencing strategy for reconstructing large novel SVs usually also gives accurate detection of SNPs/indels, how paired-end reads can improve reconstruction efficiency, and how adding in arrays is more efficient than just sequencing for disentangling some complex SVs. Our strategy should facilitate the sequencing of

A New Single Nucleotide Polymorphism Database for Rainbow Trout Generated Through Whole Genome Resequencing

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Guangtu Gao

2018-04-01

Full Text Available Single-nucleotide polymorphisms (SNPs are highly abundant markers, which are broadly distributed in animal genomes. For rainbow trout (Oncorhynchus mykiss, SNP discovery has been previously done through sequencing of restriction-site associated DNA (RAD libraries, reduced representation libraries (RRL and RNA sequencing. Recently we have performed high coverage whole genome resequencing with 61 unrelated samples, representing a wide range of rainbow trout and steelhead populations, with 49 new samples added to 12 aquaculture samples from AquaGen (Norway that we previously used for SNP discovery. Of the 49 new samples, 11 were double-haploid lines from Washington State University (WSU and 38 represented wild and hatchery populations from a wide range of geographic distribution and with divergent migratory phenotypes. We then mapped the sequences to the new rainbow trout reference genome assembly (GCA_002163495.1 which is based on the Swanson YY doubled haploid line. Variant calling was conducted with FreeBayes and SAMtools mpileup, followed by filtering of SNPs based on quality score, sequence complexity, read depth on the locus, and number of genotyped samples. Results from the two variant calling programs were compared and genotypes of the double haploid samples were used for detecting and filtering putative paralogous sequence variants (PSVs and multi-sequence variants (MSVs. Overall, 30,302,087 SNPs were identified on the rainbow trout genome 29 chromosomes and 1,139,018 on unplaced scaffolds, with 4,042,723 SNPs having high minor allele frequency (MAF > 0.25. The average SNP density on the chromosomes was one SNP per 64 bp, or 15.6 SNPs per 1 kb. Results from the phylogenetic analysis that we conducted indicate that the SNP markers contain enough population-specific polymorphisms for recovering population relationships despite the small sample size used. Intra-Population polymorphism assessment revealed high level of polymorphism and

Rare and common regulatory variation in population-scale sequenced human genomes.

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Stephen B Montgomery

2011-07-01

Full Text Available Population-scale genome sequencing allows the characterization of functional effects of a broad spectrum of genetic variants underlying human phenotypic variation. Here, we investigate the influence of rare and common genetic variants on gene expression patterns, using variants identified from sequencing data from the 1000 genomes project in an African and European population sample and gene expression data from lymphoblastoid cell lines. We detect comparable numbers of expression quantitative trait loci (eQTLs when compared to genotypes obtained from HapMap 3, but as many as 80% of the top expression quantitative trait variants (eQTVs discovered from 1000 genomes data are novel. The properties of the newly discovered variants suggest that mapping common causal regulatory variants is challenging even with full resequencing data; however, we observe significant enrichment of regulatory effects in splice-site and nonsense variants. Using RNA sequencing data, we show that 46.2% of nonsynonymous variants are differentially expressed in at least one individual in our sample, creating widespread potential for interactions between functional protein-coding and regulatory variants. We also use allele-specific expression to identify putative rare causal regulatory variants. Furthermore, we demonstrate that outlier expression values can be due to rare variant effects, and we approximate the number of such effects harboured in an individual by effect size. Our results demonstrate that integration of genomic and RNA sequencing analyses allows for the joint assessment of genome sequence and genome function.

Genome-wide DNA polymorphism in the indica rice varieties RGD-7S and Taifeng B as revealed by whole genome re-sequencing.

Science.gov (United States)

Fu, Chong-Yun; Liu, Wu-Ge; Liu, Di-Lin; Li, Ji-Hua; Zhu, Man-Shan; Liao, Yi-Long; Liu, Zhen-Rong; Zeng, Xue-Qin; Wang, Feng

2016-03-01

Next-generation sequencing technologies provide opportunities to further understand genetic variation, even within closely related cultivars. We performed whole genome resequencing of two elite indica rice varieties, RGD-7S and Taifeng B, whose F1 progeny showed hybrid weakness and hybrid vigor when grown in the early- and late-cropping seasons, respectively. Approximately 150 million 100-bp pair-end reads were generated, which covered ∼86% of the rice (Oryza sativa L. japonica 'Nipponbare') reference genome. A total of 2,758,740 polymorphic sites including 2,408,845 SNPs and 349,895 InDels were detected in RGD-7S and Taifeng B, respectively. Applying stringent parameters, we identified 961,791 SNPs and 46,640 InDels between RGD-7S and Taifeng B (RGD-7S/Taifeng B). The density of DNA polymorphisms was 256.8 SNPs and 12.5 InDels per 100 kb for RGD-7S/Taifeng B. Copy number variations (CNVs) were also investigated. In RGD-7S, 1989 of 2727 CNVs were overlapped in 218 genes, and 1231 of 2010 CNVs were annotated in 175 genes in Taifeng B. In addition, we verified a subset of InDels in the interval of hybrid weakness genes, Hw3 and Hw4, and obtained some polymorphic InDel markers, which will provide a sound foundation for cloning hybrid weakness genes. Analysis of genomic variations will also contribute to understanding the genetic basis of hybrid weakness and heterosis.

Genetic diversity, molecular phylogeny and selection evidence of the silkworm mitochondria implicated by complete resequencing of 41 genomes

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Tellier Laurent C

2010-03-01

Full Text Available Abstract Background Mitochondria are a valuable resource for studying the evolutionary process and deducing phylogeny. A few mitochondria genomes have been sequenced, but a comprehensive picture of the domestication event for silkworm mitochondria remains to be established. In this study, we integrate the extant data, and perform a whole genome resequencing of Japanese wild silkworm to obtain breakthrough results in silkworm mitochondrial (mt population, and finally use these to deduce a more comprehensive phylogeny of the Bombycidae. Results We identified 347 single nucleotide polymorphisms (SNPs in the mt genome, but found no past recombination event to have occurred in the silkworm progenitor. A phylogeny inferred from these whole genome SNPs resulted in a well-classified tree, confirming that the domesticated silkworm, Bombyx mori, most recently diverged from the Chinese wild silkworm, rather than from the Japanese wild silkworm. We showed that the population sizes of the domesticated and Chinese wild silkworms both experience neither expansion nor contraction. We also discovered that one mt gene, named cytochrome b, shows a strong signal of positive selection in the domesticated clade. This gene is related to energy metabolism, and may have played an important role during silkworm domestication. Conclusions We present a comparative analysis on 41 mt genomes of B. mori and B. mandarina from China and Japan. With these, we obtain a much clearer picture of the evolution history of the silkworm. The data and analyses presented here aid our understanding of the silkworm in general, and provide a crucial insight into silkworm phylogeny.

The wolf reference genome sequence (Canis lupus lupus) and its implications for Canis spp. population genomics

DEFF Research Database (Denmark)

Gopalakrishnan, Shyam; Samaniego Castruita, Jose Alfredo; Sinding, Mikkel Holger Strander

2017-01-01

Background An increasing number of studies are addressing the evolutionary genomics of dog domestication, principally through resequencing dog, wolf and related canid genomes. There is, however, only one de novo assembled canid genome currently available against which to map such data - that of a......Background An increasing number of studies are addressing the evolutionary genomics of dog domestication, principally through resequencing dog, wolf and related canid genomes. There is, however, only one de novo assembled canid genome currently available against which to map such data...... that regardless of the reference genome choice, most evolutionary genomic analyses yield qualitatively similar results, including those exploring the structure between the wolves and dogs using admixture and principal component analysis. However, we do observe differences in the genomic coverage of re-mapped...

Development of cleaved amplified polymorphic sequence markers and a CAPS-based genetic linkage map in watermelon (Citrullus lanatus [Thunb.] Matsum. and Nakai) constructed using whole-genome re-sequencing data.

Science.gov (United States)

Liu, Shi; Gao, Peng; Zhu, Qianglong; Luan, Feishi; Davis, Angela R; Wang, Xiaolu

2016-03-01

Cleaved amplified polymorphic sequence (CAPS) markers are useful tools for detecting single nucleotide polymorphisms (SNPs). This study detected and converted SNP sites into CAPS markers based on high-throughput re-sequencing data in watermelon, for linkage map construction and quantitative trait locus (QTL) analysis. Two inbred lines, Cream of Saskatchewan (COS) and LSW-177 had been re-sequenced and analyzed by Perl self-compiled script for CAPS marker development. 88.7% and 78.5% of the assembled sequences of the two parental materials could map to the reference watermelon genome, respectively. Comparative assembled genome data analysis provided 225,693 and 19,268 SNPs and indels between the two materials. 532 pairs of CAPS markers were designed with 16 restriction enzymes, among which 271 pairs of primers gave distinct bands of the expected length and polymorphic bands, via PCR and enzyme digestion, with a polymorphic rate of 50.94%. Using the new CAPS markers, an initial CAPS-based genetic linkage map was constructed with the F2 population, spanning 1836.51 cM with 11 linkage groups and 301 markers. 12 QTLs were detected related to fruit flesh color, length, width, shape index, and brix content. These newly CAPS markers will be a valuable resource for breeding programs and genetic studies of watermelon.

Analysis of genetic variation and potential applications in genome-scale metabolic modeling

DEFF Research Database (Denmark)

Cardoso, Joao; Andersen, Mikael Rørdam; Herrgard, Markus

2015-01-01

scale and resolution by re-sequencing thousands of strains systematically. In this article, we review challenges in the integration and analysis of large-scale re-sequencing data, present an extensive overview of bioinformatics methods for predicting the effects of genetic variants on protein function......Genetic variation is the motor of evolution and allows organisms to overcome the environmental challenges they encounter. It can be both beneficial and harmful in the process of engineering cell factories for the production of proteins and chemicals. Throughout the history of biotechnology......, there have been efforts to exploit genetic variation in our favor to create strains with favorable phenotypes. Genetic variation can either be present in natural populations or it can be artificially created by mutagenesis and selection or adaptive laboratory evolution. On the other hand, unintended genetic...

Genomic dark matter: the reliability of short read mapping illustrated by the genome mappability score.

Science.gov (United States)

Lee, Hayan; Schatz, Michael C

2012-08-15

Genome resequencing and short read mapping are two of the primary tools of genomics and are used for many important applications. The current state-of-the-art in mapping uses the quality values and mapping quality scores to evaluate the reliability of the mapping. These attributes, however, are assigned to individual reads and do not directly measure the problematic repeats across the genome. Here, we present the Genome Mappability Score (GMS) as a novel measure of the complexity of resequencing a genome. The GMS is a weighted probability that any read could be unambiguously mapped to a given position and thus measures the overall composition of the genome itself. We have developed the Genome Mappability Analyzer to compute the GMS of every position in a genome. It leverages the parallelism of cloud computing to analyze large genomes, and enabled us to identify the 5-14% of the human, mouse, fly and yeast genomes that are difficult to analyze with short reads. We examined the accuracy of the widely used BWA/SAMtools polymorphism discovery pipeline in the context of the GMS, and found discovery errors are dominated by false negatives, especially in regions with poor GMS. These errors are fundamental to the mapping process and cannot be overcome by increasing coverage. As such, the GMS should be considered in every resequencing project to pinpoint the 'dark matter' of the genome, including of known clinically relevant variations in these regions. The source code and profiles of several model organisms are available at http://gma-bio.sourceforge.net

Interspecies hybridization on DNA resequencing microarrays: efficiency of sequence recovery and accuracy of SNP detection in human, ape, and codfish mitochondrial DNA genomes sequenced on a human-specific MitoChip

Directory of Open Access Journals (Sweden)

Carr Steven M

2007-09-01

Full Text Available Abstract Background Iterative DNA "resequencing" on oligonucleotide microarrays offers a high-throughput method to measure intraspecific biodiversity, one that is especially suited to SNP-dense gene regions such as vertebrate mitochondrial (mtDNA genomes. However, costs of single-species design and microarray fabrication are prohibitive. A cost-effective, multi-species strategy is to hybridize experimental DNAs from diverse species to a common microarray that is tiled with oligonucleotide sets from multiple, homologous reference genomes. Such a strategy requires that cross-hybridization between the experimental DNAs and reference oligos from the different species not interfere with the accurate recovery of species-specific data. To determine the pattern and limits of such interspecific hybridization, we compared the efficiency of sequence recovery and accuracy of SNP identification by a 15,452-base human-specific microarray challenged with human, chimpanzee, gorilla, and codfish mtDNA genomes. Results In the human genome, 99.67% of the sequence was recovered with 100.0% accuracy. Accuracy of SNP identification declines log-linearly with sequence divergence from the reference, from 0.067 to 0.247 errors per SNP in the chimpanzee and gorilla genomes, respectively. Efficiency of sequence recovery declines with the increase of the number of interspecific SNPs in the 25b interval tiled by the reference oligonucleotides. In the gorilla genome, which differs from the human reference by 10%, and in which 46% of these 25b regions contain 3 or more SNP differences from the reference, only 88% of the sequence is recoverable. In the codfish genome, which differs from the reference by > 30%, less than 4% of the sequence is recoverable, in short islands ≥ 12b that are conserved between primates and fish. Conclusion Experimental DNAs bind inefficiently to homologous reference oligonucleotide sets on a re-sequencing microarray when their sequences differ by

Single nucleotide variants and InDels identified from whole-genome re-sequencing of Guzerat, Gyr, Girolando and Holstein cattle breeds.

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Nedenia Bonvino Stafuzza

Full Text Available Whole-genome re-sequencing, alignment and annotation analyses were undertaken for 12 sires representing four important cattle breeds in Brazil: Guzerat (multi-purpose, Gyr, Girolando and Holstein (dairy production. A total of approximately 4.3 billion reads from an Illumina HiSeq 2000 sequencer generated for each animal 10.7 to 16.4-fold genome coverage. A total of 27,441,279 single nucleotide variations (SNVs and 3,828,041 insertions/deletions (InDels were detected in the samples, of which 2,557,670 SNVs and 883,219 InDels were novel. The submission of these genetic variants to the dbSNP database significantly increased the number of known variants, particularly for the indicine genome. The concordance rate between genotypes obtained using the Bovine HD BeadChip array and the same variants identified by sequencing was about 99.05%. The annotation of variants identified numerous non-synonymous SNVs and frameshift InDels which could affect phenotypic variation. Functional enrichment analysis was performed and revealed that variants in the olfactory transduction pathway was over represented in all four cattle breeds, while the ECM-receptor interaction pathway was over represented in Girolando and Guzerat breeds, the ABC transporters pathway was over represented only in Holstein breed, and the metabolic pathways was over represented only in Gyr breed. The genetic variants discovered here provide a rich resource to help identify potential genomic markers and their associated molecular mechanisms that impact economically important traits for Gyr, Girolando, Guzerat and Holstein breeding programs.

Efficient alignment of pyrosequencing reads for re-sequencing applications

Directory of Open Access Journals (Sweden)

Russo Luis MS

2011-05-01

Full Text Available Abstract Background Over the past few years, new massively parallel DNA sequencing technologies have emerged. These platforms generate massive amounts of data per run, greatly reducing the cost of DNA sequencing. However, these techniques also raise important computational difficulties mostly due to the huge volume of data produced, but also because of some of their specific characteristics such as read length and sequencing errors. Among the most critical problems is that of efficiently and accurately mapping reads to a reference genome in the context of re-sequencing projects. Results We present an efficient method for the local alignment of pyrosequencing reads produced by the GS FLX (454 system against a reference sequence. Our approach explores the characteristics of the data in these re-sequencing applications and uses state of the art indexing techniques combined with a flexible seed-based approach, leading to a fast and accurate algorithm which needs very little user parameterization. An evaluation performed using real and simulated data shows that our proposed method outperforms a number of mainstream tools on the quantity and quality of successful alignments, as well as on the execution time. Conclusions The proposed methodology was implemented in a software tool called TAPyR--Tool for the Alignment of Pyrosequencing Reads--which is publicly available from http://www.tapyr.net.

[Identification of novel pathogenic gene mutations in pediatric acute myeloid leukemia by whole-exome resequencing].

Science.gov (United States)

Shiba, Norio

2015-12-01

A new class of gene mutations, identified in the pathogenesis of adult acute myeloid leukemia (AML), includes DNMT3A, IDH1/2, TET2 and EZH2. However, these mutations are rare in pediatric AML cases, indicating that pathogeneses differ between adult and pediatric forms of AML. Meanwhile, the recent development of massively parallel sequencing technologies has provided a new opportunity to discover genetic changes across entire genomes or proteincoding sequences. In order to reveal a complete registry of gene mutations, we performed whole exome resequencing of paired tumor-normal specimens from 19 pediatric AML cases using Illumina HiSeq 2000. In total, 80 somatic mutations or 4.2 mutations per sample were identified. Many of the recurrent mutations identified in this study involved previously reported targets in AML, such as FLT3, CEBPA, KIT, CBL, NRAS, WT1 and EZH2. On the other hand, several genes were newly identified in the current study, including BCORL1 and major cohesin components such as SMC3 and RAD21. Whole exome resequencing revealed a complex array of gene mutations in pediatric AML genomes. Our results indicate that a subset of pediatric AML represents a discrete entity that could be discriminated from its adult counterpart, in terms of the spectrum of gene mutations.

Forward genetics screen coupled with whole-genome resequencing identifies novel gene targets for improving heterologous enzyme production in Aspergillus niger.

Science.gov (United States)

Reilly, Morgann C; Kim, Joonhoon; Lynn, Jed; Simmons, Blake A; Gladden, John M; Magnuson, Jon K; Baker, Scott E

2018-02-01

Plant biomass, once reduced to its composite sugars, can be converted to fuel substitutes. One means of overcoming the recalcitrance of lignocellulose is pretreatment followed by enzymatic hydrolysis. However, currently available commercial enzyme cocktails are inhibited in the presence of residual pretreatment chemicals. Recent studies have identified a number of cellulolytic enzymes from bacteria that are tolerant to pretreatment chemicals such as ionic liquids. The challenge now is generation of these enzymes in copious amounts, an arena where fungal organisms such as Aspergillus niger have proven efficient. Fungal host strains still need to be engineered to increase production titers of heterologous protein over native enzymes, which has been a difficult task. Here, we developed a forward genetics screen coupled with whole-genome resequencing to identify specific lesions responsible for a protein hyper-production phenotype in A. niger. This strategy successfully identified novel targets, including a low-affinity glucose transporter, MstC, whose deletion significantly improved secretion of recombinant proteins driven by a glucoamylase promoter.

Forward genetics screen coupled with whole-genome resequencing identifies novel gene targets for improving heterologous enzyme production in Aspergillus niger

Energy Technology Data Exchange (ETDEWEB)

Reilly, Morgann C. [Joint BioEnergy Institute, Emeryville, CA (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Kim, Joonhoon [Joint BioEnergy Institute, Emeryville, CA (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lynn, Jed [Joint BioEnergy Institute, Emeryville, CA (United States); Wright-Patterson Air Force Base, Dayton, OH (United States); Simmons, Blake A. [Joint BioEnergy Institute, Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Gladden, John M. [Joint BioEnergy Institute, Emeryville, CA (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States); Magnuson, Jon K. [Joint BioEnergy Institute, Emeryville, CA (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Baker, Scott E. [Joint BioEnergy Institute, Emeryville, CA (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2018-01-06

Plant biomass, once reduced to its composite sugars, can be converted to fuel substitutes. One means of overcoming the recalcitrance of lignocellulose is pretreatment followed by enzymatic hydrolysis. However, currently available commercial enzyme cocktails are inhibited in the presence of residual pretreatment chemicals. Recent studies have identified a number of cellulolytic enzymes from bacteria that are tolerant to pretreatment chemicals such as ionic liquids. The challenge now is generation of these enzymes in copious amounts, an arena where fungal organisms such as Aspergillus niger have proven efficient. Fungal host strains still need to be engineered to increase production titers of heterologous protein over native enzymes, which has been a difficult task. Here, we developed a forward genetics screen coupled with whole-genome resequencing to identify specific lesions responsible for a protein hyper-production phenotype in A. niger. This strategy successfully identified novel targets, including a low-affinity glucose transporter, MstC, whose deletion significantly improved secretion of recombinant proteins driven by a glucoamylase promoter.

Genomic landscapes of Chinese hamster ovary cell lines as revealed by the Cricetulus griseus draft genome

DEFF Research Database (Denmark)

Lewis, Nathan E; Liu, Xin; Li, Yuxiang

2013-01-01

stymied by the lack of a unifying genomic resource for CHO cells. Here we report a 2.4-Gb draft genome sequence of a female Chinese hamster, Cricetulus griseus, harboring 24,044 genes. We also resequenced and analyzed the genomes of six CHO cell lines from the CHO-K1, DG44 and CHO-S lineages...

PopGenome: An Efficient Swiss Army Knife for Population Genomic Analyses in R

OpenAIRE

Pfeifer, Bastian; Wittelsbürger, Ulrich; Ramos-Onsins, Sebastian E.; Lercher, Martin J.

2014-01-01

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...

The genome of Eucalyptus grandis

Energy Technology Data Exchange (ETDEWEB)

Myburg, Alexander A.; Grattapaglia, Dario; Tuskan, Gerald A.; Hellsten, Uffe; Hayes, Richard D.; Grimwood, Jane; Jenkins, Jerry; Lindquist, Erika; Tice, Hope; Bauer, Diane; Goodstein, David M.; Dubchak, Inna; Poliakov, Alexandre; Mizrachi, Eshchar; Kullan, Anand R. K.; Hussey, Steven G.; Pinard, Desre; van der Merwe, Karen; Singh, Pooja; van Jaarsveld, Ida; Silva-Junior, Orzenil B.; Togawa, Roberto C.; Pappas, Marilia R.; Faria, Danielle A.; Sansaloni, Carolina P.; Petroli, Cesar D.; Yang, Xiaohan; Ranjan, Priya; Tschaplinski, Timothy J.; Ye, Chu-Yu; Li, Ting; Sterck, Lieven; Vanneste, Kevin; Murat, Florent; Soler, Marçal; Clemente, Hélène San; Saidi, Naijib; Cassan-Wang, Hua; Dunand, Christophe; Hefer, Charles A.; Bornberg-Bauer, Erich; Kersting, Anna R.; Vining, Kelly; Amarasinghe, Vindhya; Ranik, Martin; Naithani, Sushma; Elser, Justin; Boyd, Alexander E.; Liston, Aaron; Spatafora, Joseph W.; Dharmwardhana, Palitha; Raja, Rajani; Sullivan, Christopher; Romanel, Elisson; Alves-Ferreira, Marcio; Külheim, Carsten; Foley, William; Carocha, Victor; Paiva, Jorge; Kudrna, David; Brommonschenkel, Sergio H.; Pasquali, Giancarlo; Byrne, Margaret; Rigault, Philippe; Tibbits, Josquin; Spokevicius, Antanas; Jones, Rebecca C.; Steane, Dorothy A.; Vaillancourt, René E.; Potts, Brad M.; Joubert, Fourie; Barry, Kerrie; Pappas, Georgios J.; Strauss, Steven H.; Jaiswal, Pankaj; Grima-Pettenati, Jacqueline; Salse, Jérôme; Van de Peer, Yves; Rokhsar, Daniel S.; Schmutz, Jeremy

2014-06-11

Eucalypts are the world s most widely planted hardwood trees. Their broad adaptability, rich species diversity, fast growth and superior multipurpose wood, have made them a global renewable resource of fiber and energy that mitigates human pressures on natural forests. We sequenced and assembled >94% of the 640 Mbp genome of Eucalyptus grandis into its 11 chromosomes. A set of 36,376 protein coding genes were predicted revealing that 34% occur in tandem duplications, the largest proportion found thus far in any plant genome. Eucalypts also show the highest diversity of genes for plant specialized metabolism that act as chemical defence against biotic agents and provide unique pharmaceutical oils. Resequencing of a set of inbred tree genomes revealed regions of strongly conserved heterozygosity, likely hotspots of inbreeding depression. The resequenced genome of the sister species E. globulus underscored the high inter-specific genome colinearity despite substantial genome size variation in the genus. The genome of E. grandis is the first reference for the early diverging Rosid order Myrtales and is placed here basal to the Eurosids. This resource expands knowledge on the unique biology of large woody perennials and provides a powerful tool to accelerate comparative biology, breeding and biotechnology.

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

Science.gov (United States)

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

2017-08-01

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

Genome sequence and genetic diversity of the common carp, Cyprinus carpio.

Science.gov (United States)

Xu, Peng; Zhang, Xiaofeng; Wang, Xumin; Li, Jiongtang; Liu, Guiming; Kuang, Youyi; Xu, Jian; Zheng, Xianhu; Ren, Lufeng; Wang, Guoliang; Zhang, Yan; Huo, Linhe; Zhao, Zixia; Cao, Dingchen; Lu, Cuiyun; Li, Chao; Zhou, Yi; Liu, Zhanjiang; Fan, Zhonghua; Shan, Guangle; Li, Xingang; Wu, Shuangxiu; Song, Lipu; Hou, Guangyuan; Jiang, Yanliang; Jeney, Zsigmond; Yu, Dan; Wang, Li; Shao, Changjun; Song, Lai; Sun, Jing; Ji, Peifeng; Wang, Jian; Li, Qiang; Xu, Liming; Sun, Fanyue; Feng, Jianxin; Wang, Chenghui; Wang, Shaolin; Wang, Baosen; Li, Yan; Zhu, Yaping; Xue, Wei; Zhao, Lan; Wang, Jintu; Gu, Ying; Lv, Weihua; Wu, Kejing; Xiao, Jingfa; Wu, Jiayan; Zhang, Zhang; Yu, Jun; Sun, Xiaowen

2014-11-01

The common carp, Cyprinus carpio, is one of the most important cyprinid species and globally accounts for 10% of freshwater aquaculture production. Here we present a draft genome of domesticated C. carpio (strain Songpu), whose current assembly contains 52,610 protein-coding genes and approximately 92.3% coverage of its paleotetraploidized genome (2n = 100). The latest round of whole-genome duplication has been estimated to have occurred approximately 8.2 million years ago. Genome resequencing of 33 representative individuals from worldwide populations demonstrates a single origin for C. carpio in 2 subspecies (C. carpio Haematopterus and C. carpio carpio). Integrative genomic and transcriptomic analyses were used to identify loci potentially associated with traits including scaling patterns and skin color. In combination with the high-resolution genetic map, the draft genome paves the way for better molecular studies and improved genome-assisted breeding of C. carpio and other closely related species.

Phylogenetic distribution of large-scale genome patchiness

Directory of Open Access Journals (Sweden)

Hackenberg Michael

2008-04-01

Full Text Available Abstract Background The phylogenetic distribution of large-scale genome structure (i.e. mosaic compositional patchiness has been explored mainly by analytical ultracentrifugation of bulk DNA. However, with the availability of large, good-quality chromosome sequences, and the recently developed computational methods to directly analyze patchiness on the genome sequence, an evolutionary comparative analysis can be carried out at the sequence level. Results The local variations in the scaling exponent of the Detrended Fluctuation Analysis are used here to analyze large-scale genome structure and directly uncover the characteristic scales present in genome sequences. Furthermore, through shuffling experiments of selected genome regions, computationally-identified, isochore-like regions were identified as the biological source for the uncovered large-scale genome structure. The phylogenetic distribution of short- and large-scale patchiness was determined in the best-sequenced genome assemblies from eleven eukaryotic genomes: mammals (Homo sapiens, Pan troglodytes, Mus musculus, Rattus norvegicus, and Canis familiaris, birds (Gallus gallus, fishes (Danio rerio, invertebrates (Drosophila melanogaster and Caenorhabditis elegans, plants (Arabidopsis thaliana and yeasts (Saccharomyces cerevisiae. We found large-scale patchiness of genome structure, associated with in silico determined, isochore-like regions, throughout this wide phylogenetic range. Conclusion Large-scale genome structure is detected by directly analyzing DNA sequences in a wide range of eukaryotic chromosome sequences, from human to yeast. In all these genomes, large-scale patchiness can be associated with the isochore-like regions, as directly detected in silico at the sequence level.

Genome sequences of Phytophthora enable translational plant disease management and accelerate research

Science.gov (United States)

Niklaus J. Grünwald

2012-01-01

Whole and partial genome sequences are becoming available at an ever-increasing pace. For many plant pathogen systems, we are moving into the era of genome resequencing. The first Phytophthora genomes, P. ramorum and P. sojae, became available in 2004, followed shortly by P. infestans...

Resequencing 50 accessions of cultivated and wild rice yields markers for identifying agronomically important genes

DEFF Research Database (Denmark)

Xu, Xun; Liu, Xin; Ge, Song

2012-01-01

Rice is a staple crop that has undergone substantial phenotypic and physiological changes during domestication. Here we resequenced the genomes of 40 cultivated accessions selected from the major groups of rice and 10 accessions of their wild progenitors (Oryza rufipogon and Oryza nivara) to >15 x...... diversity in cultivated but not wild rice, which represent candidate regions selected during domestication. Some of these variants are associated with important biological features, whereas others have yet to be functionally characterized. The molecular markers we have identified should be valuable...... raw data coverage. We investigated genome-wide variation patterns in rice and obtained 6.5 million high-quality single nucleotide polymorphisms (SNPs) after excluding sites with missing data in any accession. Using these population SNP data, we identified thousands of genes with significantly lower...

Draft genome sequence of an elite Dura palm and whole-genome patterns of DNA variation in oil palm.

Science.gov (United States)

Jin, Jingjing; Lee, May; Bai, Bin; Sun, Yanwei; Qu, Jing; Rahmadsyah; Alfiko, Yuzer; Lim, Chin Huat; Suwanto, Antonius; Sugiharti, Maria; Wong, Limsoon; Ye, Jian; Chua, Nam-Hai; Yue, Gen Hua

2016-12-01

Oil palm is the world's leading source of vegetable oil and fat. Dura, Pisifera and Tenera are three forms of oil palm. The genome sequence of Pisifera is available whereas the Dura form has not been sequenced yet. We sequenced the genome of one elite Dura palm, and re-sequenced 17 palm genomes. The assemble genome sequence of the elite Dura tree contained 10,971 scaffolds and was 1.701 Gb in length, covering 94.49% of the oil palm genome. 36,105 genes were predicted. Re-sequencing of 17 additional palm trees identified 18.1 million SNPs. We found high genetic variation among palms from different geographical regions, but lower variation among Southeast Asian Dura and Pisifera palms. We mapped 10,000 SNPs on the linkage map of oil palm. In addition, high linkage disequilibrium (LD) was detected in the oil palms used in breeding populations of Southeast Asia, suggesting that LD mapping is likely to be practical in this important oil crop. Our data provide a valuable resource for accelerating genetic improvement and studying the mechanism underlying phenotypic variations of important oil palm traits. © The Author 2016. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Mutation Detection with Next-Generation Resequencing through a Mediator Genome

Energy Technology Data Exchange (ETDEWEB)

Wurtzel, Omri; Dori-Bachash, Mally; Pietrokovski, Shmuel; Jurkevitch, Edouard; Sorek, Rotem; Ben-Jacob, Eshel

2010-12-31

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.

Translational genomics and marker assisted selection in sorghum case study using brown midrib (bmr) trait

Science.gov (United States)

Translational genomics is a critical phase in harnessing the rich genomic data available for sorghum. There is a need to transform nucleotide variation data between sorghum germplasm such as that derived from RNA seq, genotype by sequencing (gbs) or whole genome resequencing thru translation and...

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

Science.gov (United States)

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

2016-03-01

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

Genome-Wide Analysis of Simple Sequence Repeats and Efficient Development of Polymorphic SSR Markers Based on Whole Genome Re-Sequencing of Multiple Isolates of the Wheat Stripe Rust Fungus.

Directory of Open Access Journals (Sweden)

Huaiyong Luo

Full Text Available The biotrophic parasitic fungus Puccinia striiformis f. sp. tritici (Pst causes stripe rust, a devastating disease of wheat, endangering global food security. Because the Pst population is highly dynamic, it is difficult to develop wheat cultivars with durable and highly effective resistance. Simple sequence repeats (SSRs are widely used as molecular markers in genetic studies to determine population structure in many organisms. However, only a small number of SSR markers have been developed for Pst. In this study, a total of 4,792 SSR loci were identified using the whole genome sequences of six isolates from different regions of the world, with a marker density of one SSR per 22.95 kb. The majority of the SSRs were di- and tri-nucleotide repeats. A database containing 1,113 SSR markers were established. Through in silico comparison, the previously reported SSR markers were found mainly in exons, whereas the SSR markers in the database were mostly in intergenic regions. Furthermore, 105 polymorphic SSR markers were confirmed in silico by their identical positions and nucleotide variations with INDELs identified among the six isolates. When 104 in silico polymorphic SSR markers were used to genotype 21 Pst isolates, 84 produced the target bands, and 82 of them were polymorphic and revealed the genetic relationships among the isolates. The results show that whole genome re-sequencing of multiple isolates provides an ideal resource for developing SSR markers, and the newly developed SSR markers are useful for genetic and population studies of the wheat stripe rust fungus.

Genome-Wide Analysis of Simple Sequence Repeats and Efficient Development of Polymorphic SSR Markers Based on Whole Genome Re-Sequencing of Multiple Isolates of the Wheat Stripe Rust Fungus.

Science.gov (United States)

Luo, Huaiyong; Wang, Xiaojie; Zhan, Gangming; Wei, Guorong; Zhou, Xinli; Zhao, Jing; Huang, Lili; Kang, Zhensheng

2015-01-01

The biotrophic parasitic fungus Puccinia striiformis f. sp. tritici (Pst) causes stripe rust, a devastating disease of wheat, endangering global food security. Because the Pst population is highly dynamic, it is difficult to develop wheat cultivars with durable and highly effective resistance. Simple sequence repeats (SSRs) are widely used as molecular markers in genetic studies to determine population structure in many organisms. However, only a small number of SSR markers have been developed for Pst. In this study, a total of 4,792 SSR loci were identified using the whole genome sequences of six isolates from different regions of the world, with a marker density of one SSR per 22.95 kb. The majority of the SSRs were di- and tri-nucleotide repeats. A database containing 1,113 SSR markers were established. Through in silico comparison, the previously reported SSR markers were found mainly in exons, whereas the SSR markers in the database were mostly in intergenic regions. Furthermore, 105 polymorphic SSR markers were confirmed in silico by their identical positions and nucleotide variations with INDELs identified among the six isolates. When 104 in silico polymorphic SSR markers were used to genotype 21 Pst isolates, 84 produced the target bands, and 82 of them were polymorphic and revealed the genetic relationships among the isolates. The results show that whole genome re-sequencing of multiple isolates provides an ideal resource for developing SSR markers, and the newly developed SSR markers are useful for genetic and population studies of the wheat stripe rust fungus.

Global assessment of genomic variation in cattle by genome resequencing and high-throughput genotyping

DEFF Research Database (Denmark)

Zhan, Bujie; Fadista, João; Thomsen, Bo

2011-01-01

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...

Emerging Genomic Tools for Legume Breeding: Current Status and Future Prospects

Science.gov (United States)

Pandey, Manish K.; Roorkiwal, Manish; Singh, Vikas K.; Ramalingam, Abirami; Kudapa, Himabindu; Thudi, Mahendar; Chitikineni, Anu; Rathore, Abhishek; Varshney, Rajeev K.

2016-01-01

Legumes play a vital role in ensuring global nutritional food security and improving soil quality through nitrogen fixation. Accelerated higher genetic gains is required to meet the demand of ever increasing global population. In recent years, speedy developments have been witnessed in legume genomics due to advancements in next-generation sequencing (NGS) and high-throughput genotyping technologies. Reference genome sequences for many legume crops have been reported in the last 5 years. The availability of the draft genome sequences and re-sequencing of elite genotypes for several important legume crops have made it possible to identify structural variations at large scale. Availability of large-scale genomic resources and low-cost and high-throughput genotyping technologies are enhancing the efficiency and resolution of genetic mapping and marker-trait association studies. Most importantly, deployment of molecular breeding approaches has resulted in development of improved lines in some legume crops such as chickpea and groundnut. In order to support genomics-driven crop improvement at a fast pace, the deployment of breeder-friendly genomics and decision support tools seems appear to be critical in breeding programs in developing countries. This review provides an overview of emerging genomics and informatics tools/approaches that will be the key driving force for accelerating genomics-assisted breeding and ultimately ensuring nutritional and food security in developing countries. PMID:27199998

Genome-scale neurogenetics: methodology and meaning.

Science.gov (United States)

McCarroll, Steven A; Feng, Guoping; Hyman, Steven E

2014-06-01

Genetic analysis is currently offering glimpses into molecular mechanisms underlying such neuropsychiatric disorders as schizophrenia, bipolar disorder and autism. After years of frustration, success in identifying disease-associated DNA sequence variation has followed from new genomic technologies, new genome data resources, and global collaborations that could achieve the scale necessary to find the genes underlying highly polygenic disorders. Here we describe early results from genome-scale studies of large numbers of subjects and the emerging significance of these results for neurobiology.

Fine-scale maps of recombination rates and hotspots in the mouse genome.

Science.gov (United States)

Brunschwig, Hadassa; Levi, Liat; Ben-David, Eyal; Williams, Robert W; Yakir, Benjamin; Shifman, Sagiv

2012-07-01

Recombination events are not uniformly distributed and often cluster in narrow regions known as recombination hotspots. Several studies using different approaches have dramatically advanced our understanding of recombination hotspot regulation. Population genetic data have been used to map and quantify hotspots in the human genome. Genetic variation in recombination rates and hotspots usage have been explored in human pedigrees, mouse intercrosses, and by sperm typing. These studies pointed to the central role of the PRDM9 gene in hotspot modulation. In this study, we used single nucleotide polymorphisms (SNPs) from whole-genome resequencing and genotyping studies of mouse inbred strains to estimate recombination rates across the mouse genome and identified 47,068 historical hotspots--an average of over 2477 per chromosome. We show by simulation that inbred mouse strains can be used to identify positions of historical hotspots. Recombination hotspots were found to be enriched for the predicted binding sequences for different alleles of the PRDM9 protein. Recombination rates were on average lower near transcription start sites (TSS). Comparing the inferred historical recombination hotspots with the recent genome-wide mapping of double-strand breaks (DSBs) in mouse sperm revealed a significant overlap, especially toward the telomeres. Our results suggest that inbred strains can be used to characterize and study the dynamics of historical recombination hotspots. They also strengthen previous findings on mouse recombination hotspots, and specifically the impact of sequence variants in Prdm9.

Strong signatures of selection in the domestic pig genome

DEFF Research Database (Denmark)

Rubin, Carl-Johan; Megens, Hendrik-Jan; Barrio, Alvaro Martinez

2012-01-01

Domestication of wild boar (Sus scrofa) and subsequent selection have resulted in dramatic phenotypic changes in domestic pigs for a number of traits, including behavior, body composition, reproduction, and coat color. Here we have used whole-genome resequencing to reveal some of the loci that un...... to strong directional selection.......Domestication of wild boar (Sus scrofa) and subsequent selection have resulted in dramatic phenotypic changes in domestic pigs for a number of traits, including behavior, body composition, reproduction, and coat color. Here we have used whole-genome resequencing to reveal some of the loci...... that underlie phenotypic evolution in European domestic pigs. Selective sweep analyses revealed strong signatures of selection at three loci harboring quantitative trait loci that explain a considerable part of one of the most characteristic morphological changes in the domestic pig—the elongation of the back...

Intra-species sequence comparisons for annotating genomes

Energy Technology Data Exchange (ETDEWEB)

Boffelli, Dario; Weer, Claire V.; Weng, Li; Lewis, Keith D.; Shoukry, Malak I.; Pachter, Lior; Keys, David N.; Rubin, Edward M.

2004-07-15

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.

A targeted resequencing gene panel for focal epilepsy.

Science.gov (United States)

Hildebrand, Michael S; Myers, Candace T; Carvill, Gemma L; Regan, Brigid M; Damiano, John A; Mullen, Saul A; Newton, Mark R; Nair, Umesh; Gazina, Elena V; Milligan, Carol J; Reid, Christopher A; Petrou, Steven; Scheffer, Ingrid E; Berkovic, Samuel F; Mefford, Heather C

2016-04-26

We report development of a targeted resequencing gene panel for focal epilepsy, the most prevalent phenotypic group of the epilepsies. The targeted resequencing gene panel was designed using molecular inversion probe (MIP) capture technology and sequenced using massively parallel Illumina sequencing. We demonstrated proof of principle that mutations can be detected in 4 previously genotyped focal epilepsy cases. We searched for both germline and somatic mutations in 251 patients with unsolved sporadic or familial focal epilepsy and identified 11 novel or very rare missense variants in 5 different genes: CHRNA4, GRIN2B, KCNT1, PCDH19, and SCN1A. Of these, 2 were predicted to be pathogenic or likely pathogenic, explaining ∼0.8% of the cohort, and 8 were of uncertain significance based on available data. We have developed and validated a targeted resequencing panel for focal epilepsies, the most important clinical class of epilepsies, accounting for about 60% of all cases. Our application of MIP technology is an innovative approach that will be advantageous in the clinical setting because it is highly sensitive, efficient, and cost-effective for screening large patient cohorts. Our findings indicate that mutations in known genes likely explain only a small proportion of focal epilepsy cases. This is not surprising given the established clinical and genetic heterogeneity of these disorders and underscores the importance of further gene discovery studies in this complex syndrome. © 2016 American Academy of Neurology.

An evaluation of Comparative Genome Sequencing (CGS by comparing two previously-sequenced bacterial genomes

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Herring Christopher D

2007-08-01

Full Text Available Abstract Background With the development of new technology, it has recently become practical to resequence the genome of a bacterium after experimental manipulation. It is critical though to know the accuracy of the technique used, and to establish confidence that all of the mutations were detected. Results In order to evaluate the accuracy of genome resequencing using the microarray-based Comparative Genome Sequencing service provided by Nimblegen Systems Inc., we resequenced the E. coli strain W3110 Kohara using MG1655 as a reference, both of which have been completely sequenced using traditional sequencing methods. CGS detected 7 of 8 small sequence differences, one large deletion, and 9 of 12 IS element insertions present in W3110, but did not detect a large chromosomal inversion. In addition, we confirmed that CGS also detected 2 SNPs, one deletion and 7 IS element insertions that are not present in the genome sequence, which we attribute to changes that occurred after the creation of the W3110 lambda clone library. The false positive rate for SNPs was one per 244 Kb of genome sequence. Conclusion CGS is an effective way to detect multiple mutations present in one bacterium relative to another, and while highly cost-effective, is prone to certain errors. Mutations occurring in repeated sequences or in sequences with a high degree of secondary structure may go undetected. It is also critical to follow up on regions of interest in which SNPs were not called because they often indicate deletions or IS element insertions.

Signatures of selection in tilapia revealed by whole genome resequencing.

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Xia, Jun Hong; Bai, Zhiyi; Meng, Zining; Zhang, Yong; Wang, Le; Liu, Feng; Jing, Wu; Wan, Zi Yi; Li, Jiale; Lin, Haoran; Yue, Gen Hua

2015-09-16

Natural selection and selective breeding for genetic improvement have left detectable signatures within the genome of a species. Identification of selection signatures is important in evolutionary biology and for detecting genes that facilitate to accelerate genetic improvement. However, selection signatures, including artificial selection and natural selection, have only been identified at the whole genome level in several genetically improved fish species. Tilapia is one of the most important genetically improved fish species in the world. Using next-generation sequencing, we sequenced the genomes of 47 tilapia individuals. We identified a total of 1.43 million high-quality SNPs and found that the LD block sizes ranged from 10-100 kb in tilapia. We detected over a hundred putative selective sweep regions in each line of tilapia. Most selection signatures were located in non-coding regions of the tilapia genome. The Wnt signaling, gonadotropin-releasing hormone receptor and integrin signaling pathways were under positive selection in all improved tilapia lines. Our study provides a genome-wide map of genetic variation and selection footprints in tilapia, which could be important for genetic studies and accelerating genetic improvement of tilapia.

Characterization of ancient and modern genomes by SNP detection and phylogenomic and metagenomic analysis using PALEOMIX

DEFF Research Database (Denmark)

Schubert, Mikkel; Ermini, Luca; Der Sarkissian, Clio

2014-01-01

a variety of computational tools. Here we present PALEOMIX (http://geogenetics.ku.dk/publications/paleomix), a flexible and user-friendly pipeline applicable to both modern and ancient genomes, which largely automates the in silico analyses behind whole-genome resequencing. Starting with next...

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

Science.gov (United States)

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

2014-01-01

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

Genome-scale biological models for industrial microbial systems.

Science.gov (United States)

Xu, Nan; Ye, Chao; Liu, Liming

2018-04-01

The primary aims and challenges associated with microbial fermentation include achieving faster cell growth, higher productivity, and more robust production processes. Genome-scale biological models, predicting the formation of an interaction among genetic materials, enzymes, and metabolites, constitute a systematic and comprehensive platform to analyze and optimize the microbial growth and production of biological products. Genome-scale biological models can help optimize microbial growth-associated traits by simulating biomass formation, predicting growth rates, and identifying the requirements for cell growth. With regard to microbial product biosynthesis, genome-scale biological models can be used to design product biosynthetic pathways, accelerate production efficiency, and reduce metabolic side effects, leading to improved production performance. The present review discusses the development of microbial genome-scale biological models since their emergence and emphasizes their pertinent application in improving industrial microbial fermentation of biological products.

The OME Framework for genome-scale systems biology

Energy Technology Data Exchange (ETDEWEB)

Palsson, Bernhard O. [Univ. of California, San Diego, CA (United States); Ebrahim, Ali [Univ. of California, San Diego, CA (United States); Federowicz, Steve [Univ. of California, San Diego, CA (United States)

2014-12-19

The life sciences are undergoing continuous and accelerating integration with computational and engineering sciences. The biology that many in the field have been trained on may be hardly recognizable in ten to twenty years. One of the major drivers for this transformation is the blistering pace of advancements in DNA sequencing and synthesis. These advances have resulted in unprecedented amounts of new data, information, and knowledge. Many software tools have been developed to deal with aspects of this transformation and each is sorely needed [1-3]. However, few of these tools have been forced to deal with the full complexity of genome-scale models along with high throughput genome- scale data. This particular situation represents a unique challenge, as it is simultaneously necessary to deal with the vast breadth of genome-scale models and the dizzying depth of high-throughput datasets. It has been observed time and again that as the pace of data generation continues to accelerate, the pace of analysis significantly lags behind [4]. It is also evident that, given the plethora of databases and software efforts [5-12], it is still a significant challenge to work with genome-scale metabolic models, let alone next-generation whole cell models [13-15]. We work at the forefront of model creation and systems scale data generation [16-18]. The OME Framework was borne out of a practical need to enable genome-scale modeling and data analysis under a unified framework to drive the next generation of genome-scale biological models. Here we present the OME Framework. It exists as a set of Python classes. However, we want to emphasize the importance of the underlying design as an addition to the discussions on specifications of a digital cell. A great deal of work and valuable progress has been made by a number of communities [13, 19-24] towards interchange formats and implementations designed to achieve similar goals. While many software tools exist for handling genome-scale

Extreme-Scale De Novo Genome Assembly

Energy Technology Data Exchange (ETDEWEB)

Georganas, Evangelos [Intel Corporation, Santa Clara, CA (United States); Hofmeyr, Steven [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Joint Genome Inst.; Egan, Rob [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Buluc, Aydin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Joint Genome Inst.; Oliker, Leonid [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Joint Genome Inst.; Rokhsar, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Yelick, Katherine [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Joint Genome Inst.

2017-09-26

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

Pooled Resequencing of 122 Ulcerative Colitis Genes in a Large Dutch Cohort Suggests Population-Specific Associations of Rare Variants in MUC2.

Science.gov (United States)

Visschedijk, Marijn C; Alberts, Rudi; Mucha, Soren; Deelen, Patrick; de Jong, Dirk J; Pierik, Marieke; Spekhorst, Lieke M; Imhann, Floris; van der Meulen-de Jong, Andrea E; van der Woude, C Janneke; van Bodegraven, Adriaan A; Oldenburg, Bas; Löwenberg, Mark; Dijkstra, Gerard; Ellinghaus, David; Schreiber, Stefan; Wijmenga, Cisca; Rivas, Manuel A; Franke, Andre; van Diemen, Cleo C; Weersma, Rinse K

2016-01-01

Genome-wide association studies have revealed several common genetic risk variants for ulcerative colitis (UC). However, little is known about the contribution of rare, large effect genetic variants to UC susceptibility. In this study, we performed a deep targeted re-sequencing of 122 genes in Dutch UC patients in order to investigate the contribution of rare variants to the genetic susceptibility to UC. The selection of genes consists of 111 established human UC susceptibility genes and 11 genes that lead to spontaneous colitis when knocked-out in mice. In addition, we sequenced the promoter regions of 45 genes where known variants exert cis-eQTL-effects. Targeted pooled re-sequencing was performed on DNA of 790 Dutch UC cases. The Genome of the Netherlands project provided sequence data of 500 healthy controls. After quality control and prioritization based on allele frequency and pathogenicity probability, follow-up genotyping of 171 rare variants was performed on 1021 Dutch UC cases and 1166 Dutch controls. Single-variant association and gene-based analyses identified an association of rare variants in the MUC2 gene with UC. The associated variants in the Dutch population could not be replicated in a German replication cohort (1026 UC cases, 3532 controls). In conclusion, this study has identified a putative role for MUC2 on UC susceptibility in the Dutch population and suggests a population-specific contribution of rare variants to UC.

Forces shaping the fastest evolving regions in the human genome

DEFF Research Database (Denmark)

Pollard, Katherine S; Salama, Sofie R; King, Bryan

2006-01-01

Comparative genomics allow us to search the human genome for segments that were extensively changed in the last approximately 5 million years since divergence from our common ancestor with chimpanzee, but are highly conserved in other species and thus are likely to be functional. We found 202...... genomic elements that are highly conserved in vertebrates but show evidence of significantly accelerated substitution rates in human. These are mostly in non-coding DNA, often near genes associated with transcription and DNA binding. Resequencing confirmed that the five most accelerated elements...... contributed to accelerated evolution of the fastest evolving elements in the human genome....

QTL Mapping by Whole Genome Re-sequencing and Analysis of Candidate Genes for Nitrogen Use Efficiency in Rice

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Xinghai Yang

2017-09-01

Full Text Available Nitrogen is a major nutritional element in rice production. However, excessive application of nitrogen fertilizer has caused severe environmental pollution. Therefore, development of rice varieties with improved nitrogen use efficiency (NUE is urgent for sustainable agriculture. In this study, bulked segregant analysis (BSA combined with whole genome re-sequencing (WGS technology was applied to finely map quantitative trait loci (QTL for NUE. A key QTL, designated as qNUE6 was identified on chromosome 6 and further validated by Insertion/Deletion (InDel marker-based substitutional mapping in recombinants from F2 population (NIL-13B4 × GH998. Forty-four genes were identified in this 266.5-kb region. According to detection and annotation analysis of variation sites, 39 genes with large-effect single-nucleotide polymorphisms (SNPs and large-effect InDels were selected as candidates and their expression levels were analyzed by qRT-PCR. Significant differences in the expression levels of LOC_Os06g15370 (peptide transporter PTR2 and LOC_Os06g15420 (asparagine synthetase were observed between two parents (Y11 and GH998. Phylogenetic analysis in Arabidopsis thaliana identified two closely related homologs, AT1G68570 (AtNPF3.1 and AT5G65010 (ASN2, which share 72.3 and 87.5% amino acid similarity with LOC_Os06g15370 and LOC_Os06g15420, respectively. Taken together, our results suggested that qNUE6 is a possible candidate gene for NUE in rice. The fine mapping and candidate gene analysis of qNUE6 provide the basis of molecular breeding for genetic improvement of rice varieties with high NUE, and lay the foundation for further cloning and functional analysis.

The Genome-Scale Integrated Networks in Microorganisms

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Tong Hao

2018-02-01

Full Text Available The genome-scale cellular network has become a necessary tool in the systematic analysis of microbes. In a cell, there are several layers (i.e., types of the molecular networks, for example, genome-scale metabolic network (GMN, transcriptional regulatory network (TRN, and signal transduction network (STN. It has been realized that the limitation and inaccuracy of the prediction exist just using only a single-layer network. Therefore, the integrated network constructed based on the networks of the three types attracts more interests. The function of a biological process in living cells is usually performed by the interaction of biological components. Therefore, it is necessary to integrate and analyze all the related components at the systems level for the comprehensively and correctly realizing the physiological function in living organisms. In this review, we discussed three representative genome-scale cellular networks: GMN, TRN, and STN, representing different levels (i.e., metabolism, gene regulation, and cellular signaling of a cell’s activities. Furthermore, we discussed the integration of the networks of the three types. With more understanding on the complexity of microbial cells, the development of integrated network has become an inevitable trend in analyzing genome-scale cellular networks of microorganisms.

Incorporating Protein Biosynthesis into the Saccharomyces cerevisiae Genome-scale Metabolic Model

DEFF Research Database (Denmark)

Olivares Hernandez, Roberto

Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been construc......Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been...

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

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Luo, Li; Zhu, Yun; Xiong, Momiao

2012-06-01

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

Development of Insertion and Deletion Markers based on Biparental Resequencing for Fine Mapping Seed Weight in Soybean

Directory of Open Access Journals (Sweden)

Ying-hui Li

2014-11-01

Full Text Available As a complement to single nucleotide polymorphisms (SNPs and simple sequence repeats (SSRs, biallelic insertions and deletions (InDels represent powerful molecular markers with desirable features for filling the gap in current genetic linkage maps. In this study, 28,908 small InDel polymorphisms (1–5 base pair, bp distributed genome-wide were identified and annotated by comparison of a whole-genome resequencing data set from two soybean [ (L. Merr.] genotypes, cultivar Zhonghunag13 (ZH and line Zhongpin03-5373 (ZP. The physical distribution of InDel polymorphisms in soybean genome was uneven, and matched closely with the distribution of previously annotated genes. The average density of InDel in the arm region was significantly higher than that in the pericentromeric region. The genomic regions that were fixed between the two elites were elucidated. With this information, five InDel markers within a putative quantitative trait locus (QTL for seed weight (SW, , were developed and used to genotype 254 recombinant inbred lines (RILs derived from the cross of ZP × ZH. Adding these five InDel markers to previously used SNP and SSR markers facilitated the discovery of further recombination events allowing fine-mapping the QTL to a 0.5 Mbp region. Our study clearly underlines the high value of InDel markers for map-based cloning and marker-assisted selection in soybean.

Genome-scale mutational signatures of aflatoxin in cells, mice, and human tumors

Science.gov (United States)

Huang, Mi Ni; Yu, Willie; Teoh, Wei Wei; Ardin, Maude; Jusakul, Apinya; Ng, Alvin Wei Tian; Boot, Arnoud; Abedi-Ardekani, Behnoush; Villar, Stephanie; Myint, Swe Swe; Othman, Rashidah; Poon, Song Ling; Heguy, Adriana; Olivier, Magali; Hollstein, Monica; Tan, Patrick; Teh, Bin Tean; Sabapathy, Kanaga; Zavadil, Jiri; Rozen, Steven G.

2017-01-01

Aflatoxin B1 (AFB1) is a mutagen and IARC (International Agency for Research on Cancer) Group 1 carcinogen that causes hepatocellular carcinoma (HCC). Here, we present the first whole-genome data on the mutational signatures of AFB1 exposure from a total of >40,000 mutations in four experimental systems: two different human cell lines, in liver tumors in wild-type mice, and in mice that carried a hepatitis B surface antigen transgene—this to model the multiplicative effects of aflatoxin exposure and hepatitis B in causing HCC. AFB1 mutational signatures from all four experimental systems were remarkably similar. We integrated the experimental mutational signatures with data from newly sequenced HCCs from Qidong County, China, a region of well-studied aflatoxin exposure. This indicated that COSMIC mutational signature 24, previously hypothesized to stem from aflatoxin exposure, indeed likely represents AFB1 exposure, possibly combined with other exposures. Among published somatic mutation data, we found evidence of AFB1 exposure in 0.7% of HCCs treated in North America, 1% of HCCs from Japan, but 16% of HCCs from Hong Kong. Thus, aflatoxin exposure apparently remains a substantial public health issue in some areas. This aspect of our study exemplifies the promise of future widespread resequencing of tumor genomes in providing new insights into the contribution of mutagenic exposures to cancer incidence. PMID:28739859

Genome scale engineering techniques for metabolic engineering.

Science.gov (United States)

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

2015-11-01

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

Annotation of the protein coding regions of the equine genome

DEFF Research Database (Denmark)

Hestand, Matthew S.; Kalbfleisch, Theodore S.; Coleman, Stephen J.

2015-01-01

Current gene annotation of the horse genome is largely derived from in silico predictions and cross-species alignments. Only a small number of genes are annotated based on equine EST and mRNA sequences. To expand the number of equine genes annotated from equine experimental evidence, we sequenced m...... and appear to be small errors in the equine reference genome, since they are also identified as homozygous variants by genomic DNA resequencing of the reference horse. Taken together, we provide a resource of equine mRNA structures and protein coding variants that will enhance equine and cross...

High-throughput multiplex cpDNA resequencing clarifies the genetic diversity and genetic relationships among Brassica napus, Brassica rapa and Brassica oleracea.

Science.gov (United States)

Qiao, Jiangwei; Cai, Mengxian; Yan, Guixin; Wang, Nian; Li, Feng; Chen, Binyun; Gao, Guizhen; Xu, Kun; Li, Jun; Wu, Xiaoming

2016-01-01

Brassica napus (rapeseed) is a recent allotetraploid plant and the second most important oilseed crop worldwide. The origin of B. napus and the genetic relationships with its diploid ancestor species remain largely unresolved. Here, chloroplast DNA (cpDNA) from 488 B. napus accessions of global origin, 139 B. rapa accessions and 49 B. oleracea accessions were populationally resequenced using Illumina Solexa sequencing technologies. The intraspecific cpDNA variants and their allelic frequencies were called genomewide and further validated via EcoTILLING analyses of the rpo region. The cpDNA of the current global B. napus population comprises more than 400 variants (SNPs and short InDels) and maintains one predominant haplotype (Bncp1). Whole-genome resequencing of the cpDNA of Bncp1 haplotype eliminated its direct inheritance from any accession of the B. rapa or B. oleracea species. The distribution of the polymorphism information content (PIC) values for each variant demonstrated that B. napus has much lower cpDNA diversity than B. rapa; however, a vast majority of the wild and cultivated B. oleracea specimens appeared to share one same distinct cpDNA haplotype, in contrast to its wild C-genome relatives. This finding suggests that the cpDNA of the three Brassica species is well differentiated. The predominant B. napus cpDNA haplotype may have originated from uninvestigated relatives or from interactions between cpDNA mutations and natural/artificial selection during speciation and evolution. These exhaustive data on variation in cpDNA would provide fundamental data for research on cpDNA and chloroplasts. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Use of genome-scale microbial models for metabolic engineering

DEFF Research Database (Denmark)

Patil, Kiran Raosaheb; Åkesson, M.; Nielsen, Jens

2004-01-01

Metabolic engineering serves as an integrated approach to design new cell factories by providing rational design procedures and valuable mathematical and experimental tools. Mathematical models have an important role for phenotypic analysis, but can also be used for the design of optimal metaboli...... network structures. The major challenge for metabolic engineering in the post-genomic era is to broaden its design methodologies to incorporate genome-scale biological data. Genome-scale stoichiometric models of microorganisms represent a first step in this direction....

Population-based resequencing revealed an ancestral winter group of cultivated flax: implication for flax domestication processes

Science.gov (United States)

Fu, Yong-Bi

2012-01-01

Cultivated flax (Linum usitatissimum L.) is the earliest oil and fiber crop and its early domestication history may involve multiple events of domestication for oil, fiber, capsular indehiscence, and winter hardiness. Genetic studies have demonstrated that winter cultivated flax is closely related to oil and fiber cultivated flax and shows little relatedness to its progenitor, pale flax (L. bienne Mill.), but winter hardiness is one major characteristic of pale flax. Here, we assessed the genetic relationships of 48 Linum samples representing pale flax and four trait-specific groups of cultivated flax (dehiscent, fiber, oil, and winter) through population-based resequencing at 24 genomic regions, and revealed a winter group of cultivated flax that displayed close relatedness to the pale flax samples. Overall, the cultivated flax showed a 27% reduction of nucleotide diversity when compared with the pale flax. Recombination frequently occurred at these sampled genomic regions, but the signal of selection and bottleneck was relatively weak. These findings provide some insight into the impact and processes of flax domestication and are significant for expanding our knowledge about early flax domestication, particularly for winter hardiness. PMID:22822439

Multi-scale structural community organisation of the human genome.

Science.gov (United States)

Boulos, Rasha E; Tremblay, Nicolas; Arneodo, Alain; Borgnat, Pierre; Audit, Benjamin

2017-04-11

Structural interaction frequency matrices between all genome loci are now experimentally achievable thanks to high-throughput chromosome conformation capture technologies. This ensues a new methodological challenge for computational biology which consists in objectively extracting from these data the structural motifs characteristic of genome organisation. We deployed the fast multi-scale community mining algorithm based on spectral graph wavelets to characterise the networks of intra-chromosomal interactions in human cell lines. We observed that there exist structural domains of all sizes up to chromosome length and demonstrated that the set of structural communities forms a hierarchy of chromosome segments. Hence, at all scales, chromosome folding predominantly involves interactions between neighbouring sites rather than the formation of links between distant loci. Multi-scale structural decomposition of human chromosomes provides an original framework to question structural organisation and its relationship to functional regulation across the scales. By construction the proposed methodology is independent of the precise assembly of the reference genome and is thus directly applicable to genomes whose assembly is not fully determined.

Large-scale genomic 2D visualization reveals extensive CG-AT skew correlation in bird genomes

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Deng Xuemei

2007-11-01

Full Text Available Abstract Background Bird genomes have very different compositional structure compared with other warm-blooded animals. The variation in the base skew rules in the vertebrate genomes remains puzzling, but it must relate somehow to large-scale genome evolution. Current research is inclined to relate base skew with mutations and their fixation. Here we wish to explore base skew correlations in bird genomes, to develop methods for displaying and quantifying such correlations at different scales, and to discuss possible explanations for the peculiarities of the bird genomes in skew correlation. Results We have developed a method called Base Skew Double Triangle (BSDT for exhibiting the genome-scale change of AT/CG skew as a two-dimensional square picture, showing base skews at many scales simultaneously in a single image. By this method we found that most chicken chromosomes have high AT/CG skew correlation (symmetry in 2D picture, except for some microchromosomes. No other organisms studied (18 species show such high skew correlations. This visualized high correlation was validated by three kinds of quantitative calculations with overlapping and non-overlapping windows, all indicating that chicken and birds in general have a special genome structure. Similar features were also found in some of the mammal genomes, but clearly much weaker than in chickens. We presume that the skew correlation feature evolved near the time that birds separated from other vertebrate lineages. When we eliminated the repeat sequences from the genomes, the AT and CG skews correlation increased for some mammal genomes, but were still clearly lower than in chickens. Conclusion Our results suggest that BSDT is an expressive visualization method for AT and CG skew and enabled the discovery of the very high skew correlation in bird genomes; this peculiarity is worth further study. Computational analysis indicated that this correlation might be a compositional characteristic

Soybean (Glycine max) SWEET gene family: insights through comparative genomics, transcriptome profiling and whole genome re-sequence analysis.

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Patil, Gunvant; Valliyodan, Babu; Deshmukh, Rupesh; Prince, Silvas; Nicander, Bjorn; Zhao, Mingzhe; Sonah, Humira; Song, Li; Lin, Li; Chaudhary, Juhi; Liu, Yang; Joshi, Trupti; Xu, Dong; Nguyen, Henry T

2015-07-11

SWEET (MtN3_saliva) domain proteins, a recently identified group of efflux transporters, play an indispensable role in sugar efflux, phloem loading, plant-pathogen interaction and reproductive tissue development. The SWEET gene family is predominantly studied in Arabidopsis and members of the family are being investigated in rice. To date, no transcriptome or genomics analysis of soybean SWEET genes has been reported. In the present investigation, we explored the evolutionary aspect of the SWEET gene family in diverse plant species including primitive single cell algae to angiosperms with a major emphasis on Glycine max. Evolutionary features showed expansion and duplication of the SWEET gene family in land plants. Homology searches with BLAST tools and Hidden Markov Model-directed sequence alignments identified 52 SWEET genes that were mapped to 15 chromosomes in the soybean genome as tandem duplication events. Soybean SWEET (GmSWEET) genes showed a wide range of expression profiles in different tissues and developmental stages. Analysis of public transcriptome data and expression profiling using quantitative real time PCR (qRT-PCR) showed that a majority of the GmSWEET genes were confined to reproductive tissue development. Several natural genetic variants (non-synonymous SNPs, premature stop codons and haplotype) were identified in the GmSWEET genes using whole genome re-sequencing data analysis of 106 soybean genotypes. A significant association was observed between SNP-haplogroup and seed sucrose content in three gene clusters on chromosome 6. Present investigation utilized comparative genomics, transcriptome profiling and whole genome re-sequencing approaches and provided a systematic description of soybean SWEET genes and identified putative candidates with probable roles in the reproductive tissue development. Gene expression profiling at different developmental stages and genomic variation data will aid as an important resource for the soybean research

Using Genome-scale Models to Predict Biological Capabilities

DEFF Research Database (Denmark)

O’Brien, Edward J.; Monk, Jonathan M.; Palsson, Bernhard O.

2015-01-01

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...

Genome-wide DNA polymorphisms in Kavuni, a traditional rice cultivar with nutritional and therapeutic properties.

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Rathinasabapathi, Pasupathi; Purushothaman, Natarajan; Parani, Madasamy

2016-05-01

Although rice genome was sequenced in the year 2002, efforts in resequencing the large number of available accessions, landraces, traditional cultivars, and improved varieties of this important food crop are limited. We have initiated resequencing of the traditional cultivars from India. Kavuni is an important traditional rice cultivar from South India that attracts premium price for its nutritional and therapeutic properties. Whole-genome sequencing of Kavuni using Illumina platform and SNPs analysis using Nipponbare reference genome identified 1 150 711 SNPs of which 377 381 SNPs were located in the genic regions. Non-synonymous SNPs (62 708) were distributed in 19 251 genes, and their number varied between 1 and 115 per gene. Large-effect DNA polymorphisms (7769) were present in 3475 genes. Pathway mapping of these polymorphisms revealed the involvement of genes related to carbohydrate metabolism, translation, protein-folding, and cell death. Analysis of the starch biosynthesis related genes revealed that the granule-bound starch synthase I gene had T/G SNPs at the first intron/exon junction and a two-nucleotide combination, which were reported to favour high amylose content and low glycemic index. The present study provided a valuable genomics resource to study the rice varieties with nutritional and medicinal properties.

Genome scale metabolic modeling of cancer

DEFF Research Database (Denmark)

Nilsson, Avlant; Nielsen, Jens

2017-01-01

of metabolism which allows simulation and hypotheses testing of metabolic strategies. It has successfully been applied to many microorganisms and is now used to study cancer metabolism. Generic models of human metabolism have been reconstructed based on the existence of metabolic genes in the human genome......Cancer cells reprogram metabolism to support rapid proliferation and survival. Energy metabolism is particularly important for growth and genes encoding enzymes involved in energy metabolism are frequently altered in cancer cells. A genome scale metabolic model (GEM) is a mathematical formalization...

pyAmpli: an amplicon-based variant filter pipeline for targeted resequencing data.

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Beyens, Matthias; Boeckx, Nele; Van Camp, Guy; Op de Beeck, Ken; Vandeweyer, Geert

2017-12-14

Haloplex targeted resequencing is a popular method to analyze both germline and somatic variants in gene panels. However, involved wet-lab procedures may introduce false positives that need to be considered in subsequent data-analysis. No variant filtering rationale addressing amplicon enrichment related systematic errors, in the form of an all-in-one package, exists to our knowledge. We present pyAmpli, a platform independent parallelized Python package that implements an amplicon-based germline and somatic variant filtering strategy for Haloplex data. pyAmpli can filter variants for systematic errors by user pre-defined criteria. We show that pyAmpli significantly increases specificity, without reducing sensitivity, essential for reporting true positive clinical relevant mutations in gene panel data. pyAmpli is an easy-to-use software tool which increases the true positive variant call rate in targeted resequencing data. It specifically reduces errors related to PCR-based enrichment of targeted regions.

Analysing human genomes at different scales

DEFF Research Database (Denmark)

Liu, Siyang

The thriving of the Next-Generation sequencing (NGS) technologies in the past decade has dramatically revolutionized the field of human genetics. We are experiencing a wave of several large-scale whole genome sequencing studies of humans in the world. Those studies vary greatly regarding cohort...... will be reflected by the analysis of real data. This thesis covers studies in two human genome sequencing projects that distinctly differ in terms of studied population, sample size and sequencing depth. In the first project, we sequenced 150 Danish individuals from 50 trio families to 78x coverage....... The sophisticated experimental design enables high-quality de novo assembly of the genomes and provides a good opportunity for mapping the structural variations in the human population. We developed the AsmVar approach to discover, genotype and characterize the structural variations from the assemblies. Our...

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

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

2012-01-01

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

The Amaranth Genome: Genome, Transcriptome, and Physical Map Assembly

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J. W. Clouse

2016-03-01

Full Text Available Amaranth ( L. is an emerging pseudocereal native to the New World that has garnered increased attention in recent years because of its nutritional quality, in particular its seed protein and more specifically its high levels of the essential amino acid lysine. It belongs to the Amaranthaceae family, is an ancient paleopolyploid that shows disomic inheritance (2 = 32, and has an estimated genome size of 466 Mb. Here we present a high-quality draft genome sequence of the grain amaranth. The genome assembly consisted of 377 Mb in 3518 scaffolds with an N of 371 kb. Repetitive element analysis predicted that 48% of the genome is comprised of repeat sequences, of which -like elements were the most commonly classified retrotransposon. A de novo transcriptome consisting of 66,370 contigs was assembled from eight different amaranth tissue and abiotic stress libraries. Annotation of the genome identified 23,059 protein-coding genes. Seven grain amaranths (, , and and their putative progenitor ( were resequenced. A single nucleotide polymorphism (SNP phylogeny supported the classification of as the progenitor species of the grain amaranths. Lastly, we generated a de novo physical map for using the BioNano Genomics’ Genome Mapping platform. The physical map spanned 340 Mb and a hybrid assembly using the BioNano physical maps nearly doubled the N of the assembly to 697 kb. Moreover, we analyzed synteny between amaranth and sugar beet ( L. and estimated, using analysis, the age of the most recent polyploidization event in amaranth.

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

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Song, Yun S.

2012-01-01

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

Genome-scale metabolic representation of Amycolatopsis balhimycina

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Vongsangnak, Wanwipa; Figueiredo, L. F.; Förster, Jochen

2012-01-01

Infection caused by methicillin‐resistant Staphylococcus aureus (MRSA) is an increasing societal problem. Typically, glycopeptide antibiotics are used in the treatment of these infections. The most comprehensively studied glycopeptide antibiotic biosynthetic pathway is that of balhimycin...... to reconstruct a genome‐scale metabolic model for the organism. Here we generated an almost complete A. balhimycina genome sequence comprising 10,562,587 base pairs assembled into 2,153 contigs. The high GC‐genome (∼69%) includes 8,585 open reading frames (ORFs). We used our integrative toolbox called SEQTOR...

QTL Analysis and Functional Genomics of Animal Model

DEFF Research Database (Denmark)

Farajzadeh, Leila

, for example, has enabled scientists to examine more complex interactions in connection with studies of properties and diseases. In her PhD project, Leila Farajzadeh integrated different organisational levels in biology, including genotype, phenotype, association studies, transcription profiles and genetic......In recent years, the use of functional genomics and next-generation sequencing technologies has increased the probability of success in studies of complex properties. The integration of large data sets from association studies, DNA resequencing, gene expression profiles and phenotypic data...

Molecular footprints of domestication and improvement in soybean revealed by whole genome re-sequencing

DEFF Research Database (Denmark)

Li, Ying-hui; Zhao, Shan-cen; Ma, Jian-xin

2013-01-01

and genetic improvement were identified.CONCLUSIONS:Given the uniqueness of the soybean germplasm sequenced, this study drew a clear picture of human-mediated evolution of the soybean genomes. The genomic resources and information provided by this study would also facilitate the discovery of genes......BACKGROUND:Artificial selection played an important role in the origin of modern Glycine max cultivars from the wild soybean Glycine soja. To elucidate the consequences of artificial selection accompanying the domestication and modern improvement of soybean, 25 new and 30 published whole-genome re...

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

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

2016-12-01

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

Inexpensive multiplexed library preparation for megabase-sized genomes.

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Michael Baym

Full Text Available Whole-genome sequencing has become an indispensible tool of modern biology. However, the cost of sample preparation relative to the cost of sequencing remains high, especially for small genomes where the former is dominant. Here we present a protocol for rapid and inexpensive preparation of hundreds of multiplexed genomic libraries for Illumina sequencing. By carrying out the Nextera tagmentation reaction in small volumes, replacing costly reagents with cheaper equivalents, and omitting unnecessary steps, we achieve a cost of library preparation of $8 per sample, approximately 6 times cheaper than the standard Nextera XT protocol. Furthermore, our procedure takes less than 5 hours for 96 samples. Several hundred samples can then be pooled on the same HiSeq lane via custom barcodes. Our method will be useful for re-sequencing of microbial or viral genomes, including those from evolution experiments, genetic screens, and environmental samples, as well as for other sequencing applications including large amplicon, open chromosome, artificial chromosomes, and RNA sequencing.

Quantification of differential gene expression by multiplexed targeted resequencing of cDNA

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Arts, Peer; van der Raadt, Jori; van Gestel, Sebastianus H.C.; Steehouwer, Marloes; Shendure, Jay; Hoischen, Alexander; Albers, Cornelis A.

2017-01-01

Whole-transcriptome or RNA sequencing (RNA-Seq) is a powerful and versatile tool for functional analysis of different types of RNA molecules, but sample reagent and sequencing cost can be prohibitive for hypothesis-driven studies where the aim is to quantify differential expression of a limited number of genes. Here we present an approach for quantification of differential mRNA expression by targeted resequencing of complementary DNA using single-molecule molecular inversion probes (cDNA-smMIPs) that enable highly multiplexed resequencing of cDNA target regions of ∼100 nucleotides and counting of individual molecules. We show that accurate estimates of differential expression can be obtained from molecule counts for hundreds of smMIPs per reaction and that smMIPs are also suitable for quantification of relative gene expression and allele-specific expression. Compared with low-coverage RNA-Seq and a hybridization-based targeted RNA-Seq method, cDNA-smMIPs are a cost-effective high-throughput tool for hypothesis-driven expression analysis in large numbers of genes (10 to 500) and samples (hundreds to thousands). PMID:28474677

Australian wild rice reveals pre-domestication origin of polymorphism deserts in rice genome.

Science.gov (United States)

Krishnan S, Gopala; Waters, Daniel L E; Henry, Robert J

2014-01-01

Rice is a major source of human food with a predominantly Asian production base. Domestication involved selection of traits that are desirable for agriculture and to human consumers. Wild relatives of crop plants are a source of useful variation which is of immense value for crop improvement. Australian wild rices have been isolated from the impacts of domestication in Asia and represents a source of novel diversity for global rice improvement. Oryza rufipogon is a perennial wild progenitor of cultivated rice. Oryza meridionalis is a related annual species in Australia. We have examined the sequence of the genomes of AA genome wild rices from Australia that are close relatives of cultivated rice through whole genome re-sequencing. Assembly of the resequencing data to the O. sativa ssp. japonica cv. Nipponbare shows that Australian wild rices possess 2.5 times more single nucleotide polymorphisms than in the Asian wild rice and cultivated O. sativa ssp. indica. Analysis of the genome of domesticated rice reveals regions of low diversity that show very little variation (polymorphism deserts). Both the perennial and annual wild rice from Australia show a high degree of conservation of sequence with that found in cultivated rice in the same 4.58 Mbp region on chromosome 5, which suggests that some of the 'polymorphism deserts' in this and other parts of the rice genome may have originated prior to domestication due to natural selection. Analysis of genes in the 'polymorphism deserts' indicates that this selection may have been due to biotic or abiotic stress in the environment of early rice relatives. Despite having closely related sequences in these genome regions, the Australian wild populations represent an invaluable source of diversity supporting rice food security.

Australian wild rice reveals pre-domestication origin of polymorphism deserts in rice genome.

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Gopala Krishnan S

Full Text Available BACKGROUND: Rice is a major source of human food with a predominantly Asian production base. Domestication involved selection of traits that are desirable for agriculture and to human consumers. Wild relatives of crop plants are a source of useful variation which is of immense value for crop improvement. Australian wild rices have been isolated from the impacts of domestication in Asia and represents a source of novel diversity for global rice improvement. Oryza rufipogon is a perennial wild progenitor of cultivated rice. Oryza meridionalis is a related annual species in Australia. RESULTS: We have examined the sequence of the genomes of AA genome wild rices from Australia that are close relatives of cultivated rice through whole genome re-sequencing. Assembly of the resequencing data to the O. sativa ssp. japonica cv. Nipponbare shows that Australian wild rices possess 2.5 times more single nucleotide polymorphisms than in the Asian wild rice and cultivated O. sativa ssp. indica. Analysis of the genome of domesticated rice reveals regions of low diversity that show very little variation (polymorphism deserts. Both the perennial and annual wild rice from Australia show a high degree of conservation of sequence with that found in cultivated rice in the same 4.58 Mbp region on chromosome 5, which suggests that some of the 'polymorphism deserts' in this and other parts of the rice genome may have originated prior to domestication due to natural selection. CONCLUSIONS: Analysis of genes in the 'polymorphism deserts' indicates that this selection may have been due to biotic or abiotic stress in the environment of early rice relatives. Despite having closely related sequences in these genome regions, the Australian wild populations represent an invaluable source of diversity supporting rice food security.

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

Science.gov (United States)

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

2018-02-01

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

RelocaTE2: a high resolution transposable element insertion site mapping tool for population resequencing

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Jinfeng Chen

2017-01-01

Full Text Available Background Transposable element (TE polymorphisms are important components of population genetic variation. The functional impacts of TEs in gene regulation and generating genetic diversity have been observed in multiple species, but the frequency and magnitude of TE variation is under appreciated. Inexpensive and deep sequencing technology has made it affordable to apply population genetic methods to whole genomes with methods that identify single nucleotide and insertion/deletion polymorphisms. However, identifying TE polymorphisms, particularly transposition events or non-reference insertion sites can be challenging due to the repetitive nature of these sequences, which hamper both the sensitivity and specificity of analysis tools. Methods We have developed the tool RelocaTE2 for identification of TE insertion sites at high sensitivity and specificity. RelocaTE2 searches for known TE sequences in whole genome sequencing reads from second generation sequencing platforms such as Illumina. These sequence reads are used as seeds to pinpoint chromosome locations where TEs have transposed. RelocaTE2 detects target site duplication (TSD of TE insertions allowing it to report TE polymorphism loci with single base pair precision. Results and Discussion The performance of RelocaTE2 is evaluated using both simulated and real sequence data. RelocaTE2 demonstrate high level of sensitivity and specificity, particularly when the sequence coverage is not shallow. In comparison to other tools tested, RelocaTE2 achieves the best balance between sensitivity and specificity. In particular, RelocaTE2 performs best in prediction of TSDs for TE insertions. Even in highly repetitive regions, such as those tested on rice chromosome 4, RelocaTE2 is able to report up to 95% of simulated TE insertions with less than 0.1% false positive rate using 10-fold genome coverage resequencing data. RelocaTE2 provides a robust solution to identify TE insertion sites and can be

High-throughput interpretation of gene structure changes in human and nonhuman resequencing data, using ACE.

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Majoros, William H; Campbell, Michael S; Holt, Carson; DeNardo, Erin K; Ware, Doreen; Allen, Andrew S; Yandell, Mark; Reddy, Timothy E

2017-05-15

The accurate interpretation of genetic variants is critical for characterizing genotype-phenotype associations. Because the effects of genetic variants can depend strongly on their local genomic context, accurate genome annotations are essential. Furthermore, as some variants have the potential to disrupt or alter gene structure, variant interpretation efforts stand to gain from the use of individualized annotations that account for differences in gene structure between individuals or strains. We describe a suite of software tools for identifying possible functional changes in gene structure that may result from sequence variants. ACE ('Assessing Changes to Exons') converts phased genotype calls to a collection of explicit haplotype sequences, maps transcript annotations onto them, detects gene-structure changes and their possible repercussions, and identifies several classes of possible loss of function. Novel transcripts predicted by ACE are commonly supported by spliced RNA-seq reads, and can be used to improve read alignment and transcript quantification when an individual-specific genome sequence is available. Using publicly available RNA-seq data, we show that ACE predictions confirm earlier results regarding the quantitative effects of nonsense-mediated decay, and we show that predicted loss-of-function events are highly concordant with patterns of intolerance to mutations across the human population. ACE can be readily applied to diverse species including animals and plants, making it a broadly useful tool for use in eukaryotic population-based resequencing projects, particularly for assessing the joint impact of all variants at a locus. ACE is written in open-source C ++ and Perl and is available from geneprediction.org/ACE. myandell@genetics.utah.edu or tim.reddy@duke.edu. Supplementary information is available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e

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

Science.gov (United States)

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

2018-01-01

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

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

Directory of Open Access Journals (Sweden)

Jian Huang

2016-12-01

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

Integration of expression data in genome-scale metabolic network reconstructions

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Anna S. Blazier

2012-08-01

Full Text Available With the advent of high-throughput technologies, the field of systems biology has amassed an abundance of omics data, quantifying thousands of cellular components across a variety of scales, ranging from mRNA transcript levels to metabolite quantities. Methods are needed to not only integrate this omics data but to also use this data to heighten the predictive capabilities of computational models. Several recent studies have successfully demonstrated how flux balance analysis (FBA, a constraint-based modeling approach, can be used to integrate transcriptomic data into genome-scale metabolic network reconstructions to generate predictive computational models. In this review, we summarize such FBA-based methods for integrating expression data into genome-scale metabolic network reconstructions, highlighting their advantages as well as their limitations.

Sequence assembly

DEFF Research Database (Denmark)

Scheibye-Alsing, Karsten; Hoffmann, S.; Frankel, Annett Maria

2009-01-01

Despite the rapidly increasing number of sequenced and re-sequenced genomes, many issues regarding the computational assembly of large-scale sequencing data have remain unresolved. Computational assembly is crucial in large genome projects as well for the evolving high-throughput technologies and...... in genomic DNA, highly expressed genes and alternative transcripts in EST sequences. We summarize existing comparisons of different assemblers and provide a detailed descriptions and directions for download of assembly programs at: http://genome.ku.dk/resources/assembly/methods.html....

Rapid Prototyping of Microbial Cell Factories via Genome-scale Engineering

Science.gov (United States)

Si, Tong; Xiao, Han; Zhao, Huimin

2014-01-01

Advances in reading, writing and editing genetic materials have greatly expanded our ability to reprogram biological systems at the resolution of a single nucleotide and on the scale of a whole genome. Such capacity has greatly accelerated the cycles of design, build and test to engineer microbes for efficient synthesis of fuels, chemicals and drugs. In this review, we summarize the emerging technologies that have been applied, or are potentially useful for genome-scale engineering in microbial systems. We will focus on the development of high-throughput methodologies, which may accelerate the prototyping of microbial cell factories. PMID:25450192

An Integrative Bioinformatics Framework for Genome-scale Multiple Level Network Reconstruction of Rice

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Liu Lili

2013-06-01

Full Text Available Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs, protein-protein interactions (PPIs and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However, the lack of curated metabolic model of rice is blocking the exploration of genome-scale multi-level network reconstruction. Here, we have merged GRNs, PPIs and genome-scale metabolic networks (GSMNs approaches into a single framework for rice via omics’ regulatory information reconstruction and integration. Firstly, we reconstructed a genome-scale metabolic model, containing 4,462 function genes, 2,986 metabolites involved in 3,316 reactions, and compartmentalized into ten subcellular locations. Furthermore, 90,358 pairs of protein-protein interactions, 662,936 pairs of gene regulations and 1,763 microRNA-target interactions were integrated into the metabolic model. Eventually, a database was developped for systematically storing and retrieving the genome-scale multi-level network of rice. This provides a reference for understanding genotype-phenotype relationship of rice, and for analysis of its molecular regulatory network.

Natural selection affects multiple aspects of genetic variation at putatively peutral sites across the human genome

DEFF Research Database (Denmark)

Lohmueller, Kirk E; Albrechtsen, Anders; Li, Yingrui

2011-01-01

A major question in evolutionary biology is how natural selection has shaped patterns of genetic variation across the human genome. Previous work has documented a reduction in genetic diversity in regions of the genome with low recombination rates. However, it is unclear whether other summaries...... these questions by analyzing three different genome-wide resequencing datasets from European individuals. We document several significant correlations between different genomic features. In particular, we find that average minor allele frequency and diversity are reduced in regions of low recombination...... and that human diversity, human-chimp divergence, and average minor allele frequency are reduced near genes. Population genetic simulations show that either positive natural selection acting on favorable mutations or negative natural selection acting against deleterious mutations can explain these correlations...

Power Laws, Scale-Free Networks and Genome Biology

CERN Document Server

Koonin, Eugene V; Karev, Georgy P

2006-01-01

Power Laws, Scale-free Networks and Genome Biology deals with crucial aspects of the theoretical foundations of systems biology, namely power law distributions and scale-free networks which have emerged as the hallmarks of biological organization in the post-genomic era. The chapters in the book not only describe the interesting mathematical properties of biological networks but moves beyond phenomenology, toward models of evolution capable of explaining the emergence of these features. The collection of chapters, contributed by both physicists and biologists, strives to address the problems in this field in a rigorous but not excessively mathematical manner and to represent different viewpoints, which is crucial in this emerging discipline. Each chapter includes, in addition to technical descriptions of properties of biological networks and evolutionary models, a more general and accessible introduction to the respective problems. Most chapters emphasize the potential of theoretical systems biology for disco...

Application of broad-spectrum resequencing microarray for genotyping rhabdoviruses.

Science.gov (United States)

Dacheux, Laurent; Berthet, Nicolas; Dissard, Gabriel; Holmes, Edward C; Delmas, Olivier; Larrous, Florence; Guigon, Ghislaine; Dickinson, Philip; Faye, Ousmane; Sall, Amadou A; Old, Iain G; Kong, Katherine; Kennedy, Giulia C; Manuguerra, Jean-Claude; Cole, Stewart T; Caro, Valérie; Gessain, Antoine; Bourhy, Hervé

2010-09-01

The rapid and accurate identification of pathogens is critical in the control of infectious disease. To this end, we analyzed the capacity for viral detection and identification of a newly described high-density resequencing microarray (RMA), termed PathogenID, which was designed for multiple pathogen detection using database similarity searching. We focused on one of the largest and most diverse viral families described to date, the family Rhabdoviridae. We demonstrate that this approach has the potential to identify both known and related viruses for which precise sequence information is unavailable. In particular, we demonstrate that a strategy based on consensus sequence determination for analysis of RMA output data enabled successful detection of viruses exhibiting up to 26% nucleotide divergence with the closest sequence tiled on the array. Using clinical specimens obtained from rabid patients and animals, this method also shows a high species level concordance with standard reference assays, indicating that it is amenable for the development of diagnostic assays. Finally, 12 animal rhabdoviruses which were currently unclassified, unassigned, or assigned as tentative species within the family Rhabdoviridae were successfully detected. These new data allowed an unprecedented phylogenetic analysis of 106 rhabdoviruses and further suggest that the principles and methodology developed here may be used for the broad-spectrum surveillance and the broader-scale investigation of biodiversity in the viral world.

Application of Broad-Spectrum Resequencing Microarray for Genotyping Rhabdoviruses▿

Science.gov (United States)

Dacheux, Laurent; Berthet, Nicolas; Dissard, Gabriel; Holmes, Edward C.; Delmas, Olivier; Larrous, Florence; Guigon, Ghislaine; Dickinson, Philip; Faye, Ousmane; Sall, Amadou A.; Old, Iain G.; Kong, Katherine; Kennedy, Giulia C.; Manuguerra, Jean-Claude; Cole, Stewart T.; Caro, Valérie; Gessain, Antoine; Bourhy, Hervé

2010-01-01

The rapid and accurate identification of pathogens is critical in the control of infectious disease. To this end, we analyzed the capacity for viral detection and identification of a newly described high-density resequencing microarray (RMA), termed PathogenID, which was designed for multiple pathogen detection using database similarity searching. We focused on one of the largest and most diverse viral families described to date, the family Rhabdoviridae. We demonstrate that this approach has the potential to identify both known and related viruses for which precise sequence information is unavailable. In particular, we demonstrate that a strategy based on consensus sequence determination for analysis of RMA output data enabled successful detection of viruses exhibiting up to 26% nucleotide divergence with the closest sequence tiled on the array. Using clinical specimens obtained from rabid patients and animals, this method also shows a high species level concordance with standard reference assays, indicating that it is amenable for the development of diagnostic assays. Finally, 12 animal rhabdoviruses which were currently unclassified, unassigned, or assigned as tentative species within the family Rhabdoviridae were successfully detected. These new data allowed an unprecedented phylogenetic analysis of 106 rhabdoviruses and further suggest that the principles and methodology developed here may be used for the broad-spectrum surveillance and the broader-scale investigation of biodiversity in the viral world. PMID:20610710

The draft genome of watermelon (Citrullus lanatus) and resequencing of 20 diverse accessions

DEFF Research Database (Denmark)

Guo, Shaogui; Zhang, Jianguo; Sun, Honghe

2013-01-01

Watermelon, Citrullus lanatus, is an important cucurbit crop grown throughout the world. Here we report a high-quality draft genome sequence of the east Asia watermelon cultivar 97103 (2n = 2× = 22) containing 23,440 predicted protein-coding genes. Comparative genomics analysis provided an evolut...

The genome sequence of the outbreeding globe artichoke constructed de novo incorporating a phase-aware low-pass sequencing strategy of F1 progeny

Science.gov (United States)

Scaglione, Davide; Reyes-Chin-Wo, Sebastian; Acquadro, Alberto; Froenicke, Lutz; Portis, Ezio; Beitel, Christopher; Tirone, Matteo; Mauro, Rosario; Lo Monaco, Antonino; Mauromicale, Giovanni; Faccioli, Primetta; Cattivelli, Luigi; Rieseberg, Loren; Michelmore, Richard; Lanteri, Sergio

2016-01-01

Globe artichoke (Cynara cardunculus var. scolymus) is an out-crossing, perennial, multi-use crop species that is grown worldwide and belongs to the Compositae, one of the most successful Angiosperm families. We describe the first genome sequence of globe artichoke. The assembly, comprising of 13,588 scaffolds covering 725 of the 1,084 Mb genome, was generated using ~133-fold Illumina sequencing data and encodes 26,889 predicted genes. Re-sequencing (30×) of globe artichoke and cultivated cardoon (C. cardunculus var. altilis) parental genotypes and low-coverage (0.5 to 1×) genotyping-by-sequencing of 163 F1 individuals resulted in 73% of the assembled genome being anchored in 2,178 genetic bins ordered along 17 chromosomal pseudomolecules. This was achieved using a novel pipeline, SOILoCo (Scaffold Ordering by Imputation with Low Coverage), to detect heterozygous regions and assign parental haplotypes with low sequencing read depth and of unknown phase. SOILoCo provides a powerful tool for de novo genome analysis of outcrossing species. Our data will enable genome-scale analyses of evolutionary processes among crops, weeds, and wild species within and beyond the Compositae, and will facilitate the identification of economically important genes from related species. PMID:26786968

Genome-wide comparison of ultraviolet and ethyl methanesulphonate mutagenesis methods for the brown alga Ectocarpus.

Science.gov (United States)

Godfroy, Olivier; Peters, Akira F; Coelho, Susana M; Cock, J Mark

2015-12-01

Ectocarpus has emerged as a model organism for the brown algae and a broad range of genetic and genomic resources are being generated for this species. The aim of the work presented here was to evaluate two mutagenesis protocols based on ultraviolet irradiation and ethyl methanesulphonate treatment using genome resequencing to measure the number, type and distribution of mutations generated by the two methods. Ultraviolet irradiation generated a greater number of genetic lesions than ethyl methanesulphonate treatment, with more than 400 mutations being detected in the genome of the mutagenised individual. This study therefore confirms that the ultraviolet mutagenesis protocol is suitable for approaches that require a high density of mutations, such as saturation mutagenesis or Targeting Induced Local Lesions in Genomes (TILLING). Copyright © 2015 Elsevier B.V. All rights reserved.

Rapid prototyping of microbial cell factories via genome-scale engineering.

Science.gov (United States)

Si, Tong; Xiao, Han; Zhao, Huimin

2015-11-15

Advances in reading, writing and editing genetic materials have greatly expanded our ability to reprogram biological systems at the resolution of a single nucleotide and on the scale of a whole genome. Such capacity has greatly accelerated the cycles of design, build and test to engineer microbes for efficient synthesis of fuels, chemicals and drugs. In this review, we summarize the emerging technologies that have been applied, or are potentially useful for genome-scale engineering in microbial systems. We will focus on the development of high-throughput methodologies, which may accelerate the prototyping of microbial cell factories. Copyright © 2014 Elsevier Inc. All rights reserved.

Genome-scale metabolic models as platforms for strain design and biological discovery.

Science.gov (United States)

Mienda, Bashir Sajo

2017-07-01

Genome-scale metabolic models (GEMs) have been developed and used in guiding systems' metabolic engineering strategies for strain design and development. This strategy has been used in fermentative production of bio-based industrial chemicals and fuels from alternative carbon sources. However, computer-aided hypotheses building using established algorithms and software platforms for biological discovery can be integrated into the pipeline for strain design strategy to create superior strains of microorganisms for targeted biosynthetic goals. Here, I described an integrated workflow strategy using GEMs for strain design and biological discovery. Specific case studies of strain design and biological discovery using Escherichia coli genome-scale model are presented and discussed. The integrated workflow presented herein, when applied carefully would help guide future design strategies for high-performance microbial strains that have existing and forthcoming genome-scale metabolic models.

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

Science.gov (United States)

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

2015-01-01

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

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

Science.gov (United States)

2016-07-18

affordable ap- proach to genome-wide characterization of genetic varia - tion in bacterial and eukaryotic genomes (1–3). In addition to small-scale...Paired-End Reads), that uses a graph-based al- gorithm (27) capable of detecting most large-scale varia - tion involving repetitive regions, including novel...Avila,P., Grinsted,J. and De La Cruz,F. (1988) Analysis of the variable endpoints generated by one-ended transposition of Tn21.. J. Bacteriol., 170

TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks

Directory of Open Access Journals (Sweden)

Jensen Paul A

2011-09-01

Full Text Available Abstract Background Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict relationships between metabolic flux and the genes that encode and regulate enzyme activity. Recently, mixed integer programming has been used to encode these gene-protein-reaction (GPR relationships into a single optimization problem, but these techniques are often of limited generality and lack a tool for automating the conversion of rules to a coupled regulatory/metabolic model. Results We present TIGER, a Toolbox for Integrating Genome-scale Metabolism, Expression, and Regulation. TIGER converts a series of generalized, Boolean or multilevel rules into a set of mixed integer inequalities. The package also includes implementations of existing algorithms to integrate high-throughput expression data with genome-scale models of metabolism and transcriptional regulation. We demonstrate how TIGER automates the coupling of a genome-scale metabolic model with GPR logic and models of transcriptional regulation, thereby serving as a platform for algorithm development and large-scale metabolic analysis. Additionally, we demonstrate how TIGER's algorithms can be used to identify inconsistencies and improve existing models of transcriptional regulation with examples from the reconstructed transcriptional regulatory network of Saccharomyces cerevisiae. Conclusion The TIGER package provides a consistent platform for algorithm development and extending existing genome-scale metabolic models with regulatory networks and high-throughput data.

Whole-genome resequencing reveals candidate mutations for pig prolificacy.

Science.gov (United States)

Li, Wen-Ting; Zhang, Meng-Meng; Li, Qi-Gang; Tang, Hui; Zhang, Li-Fan; Wang, Ke-Jun; Zhu, Mu-Zhen; Lu, Yun-Feng; Bao, Hai-Gang; Zhang, Yuan-Ming; Li, Qiu-Yan; Wu, Ke-Liang; Wu, Chang-Xin

2017-12-20

Changes in pig fertility have occurred as a result of domestication, but are not understood at the level of genetic variation. To identify variations potentially responsible for prolificacy, we sequenced the genomes of the highly prolific Taihu pig breed and four control breeds. Genes involved in embryogenesis and morphogenesis were targeted in the Taihu pig, consistent with the morphological differences observed between the Taihu pig and others during pregnancy. Additionally, excessive functional non-coding mutations have been specifically fixed or nearly fixed in the Taihu pig. We focused attention on an oestrogen response element (ERE) within the first intron of the bone morphogenetic protein receptor type-1B gene ( BMPR1B ) that overlaps with a known quantitative trait locus (QTL) for pig fecundity. Using 242 pigs from 30 different breeds, we confirmed that the genotype of the ERE was nearly fixed in the Taihu pig. ERE function was assessed by luciferase assays, examination of histological sections, chromatin immunoprecipitation, quantitative polymerase chain reactions, and western blots. The results suggest that the ERE may control pig prolificacy via the cis-regulation of BMPR1B expression. This study provides new insight into changes in reproductive performance and highlights the role of non-coding mutations in generating phenotypic diversity between breeds. © 2017 The Author(s).

Next-Generation Genomics Facility at C-CAMP: Accelerating Genomic Research in India

Science.gov (United States)

S, Chandana; Russiachand, Heikham; H, Pradeep; S, Shilpa; M, Ashwini; S, Sahana; B, Jayanth; Atla, Goutham; Jain, Smita; Arunkumar, Nandini; Gowda, Malali

2014-01-01

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

Universal Detection and Identification of Avian Influenza Virus by Use of Resequencing Microarrays

Science.gov (United States)

2009-04-01

Recent outbreaks of Nipah virus , severe acute respiratory syndrome virus , and avian influenza virus reiterate the impor- tance of zoonotic microbes as...Society for Microbiology. All Rights Reserved. Universal Detection and Identification of Avian Influenza Virus by Use of Resequencing Microarrays...been, and continue to emerge as, threats to human health. The recent outbreaks of highly pathogenic avian influenza virus in bird populations and the

Complete resequencing of 40 genomes reveals domestication events and genes in silkworm (Bombyx)

DEFF Research Database (Denmark)

Xia, Qingyou; Guo, Yiran; Zhang, Ze

2009-01-01

A single-base pair resolution silkworm genetic variation map was constructed from 40 domesticated and wild silkworms, each sequenced to approximately threefold coverage, representing 99.88% of the genome. We identified ~16 million single-nucleotide polymorphisms, many indels, and structural varia...

Decoding Synteny Blocks and Large-Scale Duplications in Mammalian and Plant Genomes

Science.gov (United States)

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.

Genomic divergences among cattle, dog and human estimated from large-scale alignments of genomic sequences

Directory of Open Access Journals (Sweden)

Shade Larry L

2006-06-01

Full Text Available Abstract Background Approximately 11 Mb of finished high quality genomic sequences were sampled from cattle, dog and human to estimate genomic divergences and their regional variation among these lineages. Results Optimal three-way multi-species global sequence alignments for 84 cattle clones or loci (each >50 kb of genomic sequence were constructed using the human and dog genome assemblies as references. Genomic divergences and substitution rates were examined for each clone and for various sequence classes under different functional constraints. Analysis of these alignments revealed that the overall genomic divergences are relatively constant (0.32–0.37 change/site for pairwise comparisons among cattle, dog and human; however substitution rates vary across genomic regions and among different sequence classes. A neutral mutation rate (2.0–2.2 × 10(-9 change/site/year was derived from ancestral repetitive sequences, whereas the substitution rate in coding sequences (1.1 × 10(-9 change/site/year was approximately half of the overall rate (1.9–2.0 × 10(-9 change/site/year. Relative rate tests also indicated that cattle have a significantly faster rate of substitution as compared to dog and that this difference is about 6%. Conclusion This analysis provides a large-scale and unbiased assessment of genomic divergences and regional variation of substitution rates among cattle, dog and human. It is expected that these data will serve as a baseline for future mammalian molecular evolution studies.

Opposing Forces of A/T-Biased Mutations and G/C-Biased Gene Conversions Shape the Genome of the Nematode Pristionchus pacificus

Science.gov (United States)

Weller, Andreas M.; Rödelsperger, Christian; Eberhardt, Gabi; Molnar, Ruxandra I.; Sommer, Ralf J.

2014-01-01

Base substitution mutations are a major source of genetic novelty and mutation accumulation line (MAL) studies revealed a nearly universal AT bias in de novo mutation spectra. While a comparison of de novo mutation spectra with the actual nucleotide composition in the genome suggests the existence of general counterbalancing mechanisms, little is known about the evolutionary and historical details of these opposing forces. Here, we correlate MAL-derived mutation spectra with patterns observed from population resequencing. Variation observed in natural populations has already been subject to evolutionary forces. Distinction between rare and common alleles, the latter of which are close to fixation and of presumably older age, can provide insight into mutational processes and their influence on genome evolution. We provide a genome-wide analysis of de novo mutations in 22 MALs of the nematode Pristionchus pacificus and compare the spectra with natural variants observed in resequencing of 104 natural isolates. MALs show an AT bias of 5.3, one of the highest values observed to date. In contrast, the AT bias in natural variants is much lower. Specifically, rare derived alleles show an AT bias of 2.4, whereas common derived alleles close to fixation show no AT bias at all. These results indicate the existence of a strong opposing force and they suggest that the GC content of the P. pacificus genome is in equilibrium. We discuss GC-biased gene conversion as a potential mechanism acting against AT-biased mutations. This study provides insight into genome evolution by combining MAL studies with natural variation. PMID:24414549

Estimated allele substitution effects underlying genomic evaluation models depend on the scaling of allele counts

NARCIS (Netherlands)

Bouwman, Aniek C.; Hayes, Ben J.; Calus, Mario P.L.

2017-01-01

Background: Genomic evaluation is used to predict direct genomic values (DGV) for selection candidates in breeding programs, but also to estimate allele substitution effects (ASE) of single nucleotide polymorphisms (SNPs). Scaling of allele counts influences the estimated ASE, because scaling of

The Rosa genome provides new insights into the domestication of modern roses.

Science.gov (United States)

Raymond, Olivier; Gouzy, Jérôme; Just, Jérémy; Badouin, Hélène; Verdenaud, Marion; Lemainque, Arnaud; Vergne, Philippe; Moja, Sandrine; Choisne, Nathalie; Pont, Caroline; Carrère, Sébastien; Caissard, Jean-Claude; Couloux, Arnaud; Cottret, Ludovic; Aury, Jean-Marc; Szécsi, Judit; Latrasse, David; Madoui, Mohammed-Amin; François, Léa; Fu, Xiaopeng; Yang, Shu-Hua; Dubois, Annick; Piola, Florence; Larrieu, Antoine; Perez, Magali; Labadie, Karine; Perrier, Lauriane; Govetto, Benjamin; Labrousse, Yoan; Villand, Priscilla; Bardoux, Claudia; Boltz, Véronique; Lopez-Roques, Céline; Heitzler, Pascal; Vernoux, Teva; Vandenbussche, Michiel; Quesneville, Hadi; Boualem, Adnane; Bendahmane, Abdelhafid; Liu, Chang; Le Bris, Manuel; Salse, Jérôme; Baudino, Sylvie; Benhamed, Moussa; Wincker, Patrick; Bendahmane, Mohammed

2018-06-01

Roses have high cultural and economic importance as ornamental plants and in the perfume industry. We report the rose whole-genome sequencing and assembly and resequencing of major genotypes that contributed to rose domestication. We generated a homozygous genotype from a heterozygous diploid modern rose progenitor, Rosa chinensis 'Old Blush'. Using single-molecule real-time sequencing and a meta-assembly approach, we obtained one of the most comprehensive plant genomes to date. Diversity analyses highlighted the mosaic origin of 'La France', one of the first hybrids combining the growth vigor of European species and the recurrent blooming of Chinese species. Genomic segments of Chinese ancestry identified new candidate genes for recurrent blooming. Reconstructing regulatory and secondary metabolism pathways allowed us to propose a model of interconnected regulation of scent and flower color. This genome provides a foundation for understanding the mechanisms governing rose traits and should accelerate improvement in roses, Rosaceae and ornamentals.

Genome-wide re-sequencing of multidrug-resistant Mycobacterium leprae Airaku-3.

Science.gov (United States)

Singh, P; Benjak, A; Carat, S; Kai, M; Busso, P; Avanzi, C; Paniz-Mondolfi, A; Peter, C; Harshman, K; Rougemont, J; Matsuoka, M; Cole, S T

2014-10-01

Genotyping and molecular characterization of drug resistance mechanisms in Mycobacterium leprae enables disease transmission and drug resistance trends to be monitored. In the present study, we performed genome-wide analysis of Airaku-3, a multidrug-resistant strain with an unknown mechanism of resistance to rifampicin. We identified 12 unique non-synonymous single-nucleotide polymorphisms (SNPs) including two in the transporter-encoding ctpC and ctpI genes. In addition, two SNPs were found that improve the resolution of SNP-based genotyping, particularly for Venezuelan and South East Asian strains of M. leprae. © 2014 The Authors Clinical Microbiology and Infection © 2014 European Society of Clinical Microbiology and Infectious Diseases.

Genome-scale cold stress response regulatory networks in ten Arabidopsis thaliana ecotypes

DEFF Research Database (Denmark)

Barah, Pankaj; Jayavelu, Naresh Doni; Rasmussen, Simon

2013-01-01

available from Arabidopsis thaliana 1001 genome project, we further investigated sequence polymorphisms in the core cold stress regulon genes. Significant numbers of non-synonymous amino acid changes were observed in the coding region of the CBF regulon genes. Considering the limited knowledge about......BACKGROUND: Low temperature leads to major crop losses every year. Although several studies have been conducted focusing on diversity of cold tolerance level in multiple phenotypically divergent Arabidopsis thaliana (A. thaliana) ecotypes, genome-scale molecular understanding is still lacking....... RESULTS: In this study, we report genome-scale transcript response diversity of 10 A. thaliana ecotypes originating from different geographical locations to non-freezing cold stress (10°C). To analyze the transcriptional response diversity, we initially compared transcriptome changes in all 10 ecotypes...

Genome Structural Diversity among 31 Bordetella pertussis Isolates from Two Recent U.S. Whooping Cough Statewide Epidemics.

Science.gov (United States)

Bowden, Katherine E; Weigand, Michael R; Peng, Yanhui; Cassiday, Pamela K; Sammons, Scott; Knipe, Kristen; Rowe, Lori A; Loparev, Vladimir; Sheth, Mili; Weening, Keeley; Tondella, M Lucia; Williams, Margaret M

2016-01-01

During 2010 and 2012, California and Vermont, respectively, experienced statewide epidemics of pertussis with differences seen in the demographic affected, case clinical presentation, and molecular epidemiology of the circulating strains. To overcome limitations of the current molecular typing methods for pertussis, we utilized whole-genome sequencing to gain a broader understanding of how current circulating strains are causing large epidemics. Through the use of combined next-generation sequencing technologies, this study compared de novo, single-contig genome assemblies from 31 out of 33 Bordetella pertussis isolates collected during two separate pertussis statewide epidemics and 2 resequenced vaccine strains. Final genome architecture assemblies were verified with whole-genome optical mapping. Sixteen distinct genome rearrangement profiles were observed in epidemic isolate genomes, all of which were distinct from the genome structures of the two resequenced vaccine strains. These rearrangements appear to be mediated by repetitive sequence elements, such as high-copy-number mobile genetic elements and rRNA operons. Additionally, novel and previously identified single nucleotide polymorphisms were detected in 10 virulence-related genes in the epidemic isolates. Whole-genome variation analysis identified state-specific variants, and coding regions bearing nonsynonymous mutations were classified into functional annotated orthologous groups. Comprehensive studies on whole genomes are needed to understand the resurgence of pertussis and develop novel tools to better characterize the molecular epidemiology of evolving B. pertussis populations. IMPORTANCE Pertussis, or whooping cough, is the most poorly controlled vaccine-preventable bacterial disease in the United States, which has experienced a resurgence for more than a decade. Once viewed as a monomorphic pathogen, B. pertussis strains circulating during epidemics exhibit diversity visible on a genome structural

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

Science.gov (United States)

Chechetkin, V R; Lobzin, V V

2017-08-07

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

Host imprints on bacterial genomes--rapid, divergent evolution in individual patients.

Directory of Open Access Journals (Sweden)

Jaroslaw Zdziarski

Full Text Available Bacteria lose or gain genetic material and through selection, new variants become fixed in the population. Here we provide the first, genome-wide example of a single bacterial strain's evolution in different deliberately colonized patients and the surprising insight that hosts appear to personalize their microflora. By first obtaining the complete genome sequence of the prototype asymptomatic bacteriuria strain E. coli 83972 and then resequencing its descendants after therapeutic bladder colonization of different patients, we identified 34 mutations, which affected metabolic and virulence-related genes. Further transcriptome and proteome analysis proved that these genome changes altered bacterial gene expression resulting in unique adaptation patterns in each patient. Our results provide evidence that, in addition to stochastic events, adaptive bacterial evolution is driven by individual host environments. Ongoing loss of gene function supports the hypothesis that evolution towards commensalism rather than virulence is favored during asymptomatic bladder colonization.

Whole-genome resequencing of honeybee drones to detect genomic selection in a population managed for royal jelly.

Science.gov (United States)

Wragg, David; Marti-Marimon, Maria; Basso, Benjamin; Bidanel, Jean-Pierre; Labarthe, Emmanuelle; Bouchez, Olivier; Le Conte, Yves; Vignal, Alain

2016-06-03

Four main evolutionary lineages of A. mellifera have been described including eastern Europe (C) and western and northern Europe (M). Many apiculturists prefer bees from the C lineage due to their docility and high productivity. In France, the routine importation of bees from the C lineage has resulted in the widespread admixture of bees from the M lineage. The haplodiploid nature of the honeybee Apis mellifera, and its small genome size, permits affordable and extensive genomics studies. As a pilot study of a larger project to characterise French honeybee populations, we sequenced 60 drones sampled from two commercial populations managed for the production of honey and royal jelly. Results indicate a C lineage origin, whilst mitochondrial analysis suggests two drones originated from the O lineage. Analysis of heterozygous SNPs identified potential copy number variants near to genes encoding odorant binding proteins and several cytochrome P450 genes. Signatures of selection were detected using the hapFLK haplotype-based method, revealing several regions under putative selection for royal jelly production. The framework developed during this study will be applied to a broader sampling regime, allowing the genetic diversity of French honeybees to be characterised in detail.

Genome sequence of the hot pepper provides insights into the evolution of pungency in Capsicum species.

Science.gov (United States)

Kim, Seungill; Park, Minkyu; Yeom, Seon-In; Kim, Yong-Min; Lee, Je Min; Lee, Hyun-Ah; Seo, Eunyoung; Choi, Jaeyoung; Cheong, Kyeongchae; Kim, Ki-Tae; Jung, Kyongyong; Lee, Gir-Won; Oh, Sang-Keun; Bae, Chungyun; Kim, Saet-Byul; Lee, Hye-Young; Kim, Shin-Young; Kim, Myung-Shin; Kang, Byoung-Cheorl; Jo, Yeong Deuk; Yang, Hee-Bum; Jeong, Hee-Jin; Kang, Won-Hee; Kwon, Jin-Kyung; Shin, Chanseok; Lim, Jae Yun; Park, June Hyun; Huh, Jin Hoe; Kim, June-Sik; Kim, Byung-Dong; Cohen, Oded; Paran, Ilan; Suh, Mi Chung; Lee, Saet Buyl; Kim, Yeon-Ki; Shin, Younhee; Noh, Seung-Jae; Park, Junhyung; Seo, Young Sam; Kwon, Suk-Yoon; Kim, Hyun A; Park, Jeong Mee; Kim, Hyun-Jin; Choi, Sang-Bong; Bosland, Paul W; Reeves, Gregory; Jo, Sung-Hwan; Lee, Bong-Woo; Cho, Hyung-Taeg; Choi, Hee-Seung; Lee, Min-Soo; Yu, Yeisoo; Do Choi, Yang; Park, Beom-Seok; van Deynze, Allen; Ashrafi, Hamid; Hill, Theresa; Kim, Woo Taek; Pai, Hyun-Sook; Ahn, Hee Kyung; Yeam, Inhwa; Giovannoni, James J; Rose, Jocelyn K C; Sørensen, Iben; Lee, Sang-Jik; Kim, Ryan W; Choi, Ik-Young; Choi, Beom-Soon; Lim, Jong-Sung; Lee, Yong-Hwan; Choi, Doil

2014-03-01

Hot pepper (Capsicum annuum), one of the oldest domesticated crops in the Americas, is the most widely grown spice crop in the world. We report whole-genome sequencing and assembly of the hot pepper (Mexican landrace of Capsicum annuum cv. CM334) at 186.6× coverage. We also report resequencing of two cultivated peppers and de novo sequencing of the wild species Capsicum chinense. The genome size of the hot pepper was approximately fourfold larger than that of its close relative tomato, and the genome showed an accumulation of Gypsy and Caulimoviridae family elements. Integrative genomic and transcriptomic analyses suggested that change in gene expression and neofunctionalization of capsaicin synthase have shaped capsaicinoid biosynthesis. We found differential molecular patterns of ripening regulators and ethylene synthesis in hot pepper and tomato. The reference genome will serve as a platform for improving the nutritional and medicinal values of Capsicum species.

Genome-wide indel markers shared by diverse Asian rice cultivars compared to Japanese rice cultivar ?Koshihikari?

OpenAIRE

Yonemaru, Jun-ichi; Choi, Sun Hee; Sakai, Hiroaki; Ando, Tsuyu; Shomura, Ayahiko; Yano, Masahiro; Wu, Jianzhong; Fukuoka, Shuichi

2015-01-01

Insertion-deletion (indel) polymorphisms, such as simple sequence repeats, have been widely used as DNA markers to identify QTLs and genes and to facilitate rice breeding. Recently, next-generation sequencing has produced deep sequences that allow genome-wide detection of indels. These polymorphisms can potentially be used to develop high-accuracy polymerase chain reaction (PCR)-based markers. Here, re-sequencing of 5 indica, 2 aus, and 3 tropical japonica cultivars and Japanese elite cultiva...

Improved annotation through genome-scale metabolic modeling of Aspergillus oryzae

DEFF Research Database (Denmark)

Vongsangnak, Wanwipa; Olsen, Peter; Hansen, Kim

2008-01-01

Background: Since ancient times the filamentous fungus Aspergillus oryzae has been used in the fermentation industry for the production of fermented sauces and the production of industrial enzymes. Recently, the genome sequence of A. oryzae with 12,074 annotated genes was released but the number...... to a genome scale metabolic model of A. oryzae. Results: Our assembled EST sequences we identified 1,046 newly predicted genes in the A. oryzae genome. Furthermore, it was possible to assign putative protein functions to 398 of the newly predicted genes. Noteworthy, our annotation strategy resulted...... model was validated and shown to correctly describe the phenotypic behavior of A. oryzae grown on different carbon sources. Conclusion: A much enhanced annotation of the A. oryzae genome was performed and a genomescale metabolic model of A. oryzae was reconstructed. The model accurately predicted...

Bionimbus: a cloud for managing, analyzing and sharing large genomics datasets.

Science.gov (United States)

Heath, Allison P; Greenway, Matthew; Powell, Raymond; Spring, Jonathan; Suarez, Rafael; Hanley, David; Bandlamudi, Chai; McNerney, Megan E; White, Kevin P; Grossman, Robert L

2014-01-01

As large genomics and phenotypic datasets are becoming more common, it is increasingly difficult for most researchers to access, manage, and analyze them. One possible approach is to provide the research community with several petabyte-scale cloud-based computing platforms containing these data, along with tools and resources to analyze it. Bionimbus is an open source cloud-computing platform that is based primarily upon OpenStack, which manages on-demand virtual machines that provide the required computational resources, and GlusterFS, which is a high-performance clustered file system. Bionimbus also includes Tukey, which is a portal, and associated middleware that provides a single entry point and a single sign on for the various Bionimbus resources; and Yates, which automates the installation, configuration, and maintenance of the software infrastructure required. Bionimbus is used by a variety of projects to process genomics and phenotypic data. For example, it is used by an acute myeloid leukemia resequencing project at the University of Chicago. The project requires several computational pipelines, including pipelines for quality control, alignment, variant calling, and annotation. For each sample, the alignment step requires eight CPUs for about 12 h. BAM file sizes ranged from 5 GB to 10 GB for each sample. Most members of the research community have difficulty downloading large genomics datasets and obtaining sufficient storage and computer resources to manage and analyze the data. Cloud computing platforms, such as Bionimbus, with data commons that contain large genomics datasets, are one choice for broadening access to research data in genomics. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

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

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

2007-04-26

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

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

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Gould John

2007-04-01

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

In Silico Genome-Scale Reconstruction and Validation of the Staphylococcus aureus Metabolic Network

NARCIS (Netherlands)

Heinemann, Matthias; Kümmel, Anne; Ruinatscha, Reto; Panke, Sven

2005-01-01

A genome-scale metabolic model of the Gram-positive, facultative anaerobic opportunistic pathogen Staphylococcus aureus N315 was constructed based on current genomic data, literature, and physiological information. The model comprises 774 metabolic processes representing approximately 23% of all

Enumeration of smallest intervention strategies in genome-scale metabolic networks.

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Axel von Kamp

2014-01-01

Full Text Available One ultimate goal of metabolic network modeling is the rational redesign of biochemical networks to optimize the production of certain compounds by cellular systems. Although several constraint-based optimization techniques have been developed for this purpose, methods for systematic enumeration of intervention strategies in genome-scale metabolic networks are still lacking. In principle, Minimal Cut Sets (MCSs; inclusion-minimal combinations of reaction or gene deletions that lead to the fulfilment of a given intervention goal provide an exhaustive enumeration approach. However, their disadvantage is the combinatorial explosion in larger networks and the requirement to compute first the elementary modes (EMs which itself is impractical in genome-scale networks. We present MCSEnumerator, a new method for effective enumeration of the smallest MCSs (with fewest interventions in genome-scale metabolic network models. For this we combine two approaches, namely (i the mapping of MCSs to EMs in a dual network, and (ii a modified algorithm by which shortest EMs can be effectively determined in large networks. In this way, we can identify the smallest MCSs by calculating the shortest EMs in the dual network. Realistic application examples demonstrate that our algorithm is able to list thousands of the most efficient intervention strategies in genome-scale networks for various intervention problems. For instance, for the first time we could enumerate all synthetic lethals in E.coli with combinations of up to 5 reactions. We also applied the new algorithm exemplarily to compute strain designs for growth-coupled synthesis of different products (ethanol, fumarate, serine by E.coli. We found numerous new engineering strategies partially requiring less knockouts and guaranteeing higher product yields (even without the assumption of optimal growth than reported previously. The strength of the presented approach is that smallest intervention strategies can be

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

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Eyal Elyashiv

2016-08-01

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

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

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

2016-08-01

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

Genome-scale modeling of yeast: chronology, applications and critical perspectives.

Science.gov (United States)

Lopes, Helder; Rocha, Isabel

2017-08-01

Over the last 15 years, several genome-scale metabolic models (GSMMs) were developed for different yeast species, aiding both the elucidation of new biological processes and the shift toward a bio-based economy, through the design of in silico inspired cell factories. Here, an historical perspective of the GSMMs built over time for several yeast species is presented and the main inheritance patterns among the metabolic reconstructions are highlighted. We additionally provide a critical perspective on the overall genome-scale modeling procedure, underlining incomplete model validation and evaluation approaches and the quest for the integration of regulatory and kinetic information into yeast GSMMs. A summary of experimentally validated model-based metabolic engineering applications of yeast species is further emphasized, while the main challenges and future perspectives for the field are finally addressed. © FEMS 2017.

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

Science.gov (United States)

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

2018-01-01

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

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

Science.gov (United States)

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

2017-09-07

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

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

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David L. Oldeschulte

2017-09-01

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

The complete chloroplast genome of Capsicum annuum var. glabriusculum using Illumina sequencing.

Science.gov (United States)

Raveendar, Sebastin; Na, Young-Wang; Lee, Jung-Ro; Shim, Donghwan; Ma, Kyung-Ho; Lee, Sok-Young; Chung, Jong-Wook

2015-07-20

Chloroplast (cp) genome sequences provide a valuable source for DNA barcoding. Molecular phylogenetic studies have concentrated on DNA sequencing of conserved gene loci. However, this approach is time consuming and more difficult to implement when gene organization differs among species. Here we report the complete re-sequencing of the cp genome of Capsicum pepper (Capsicum annuum var. glabriusculum) using the Illumina platform. The total length of the cp genome is 156,817 bp with a 37.7% overall GC content. A pair of inverted repeats (IRs) of 50,284 bp were separated by a small single copy (SSC; 18,948 bp) and a large single copy (LSC; 87,446 bp). The number of cp genes in C. annuum var. glabriusculum is the same as that in other Capsicum species. Variations in the lengths of LSC; SSC and IR regions were the main contributors to the size variation in the cp genome of this species. A total of 125 simple sequence repeat (SSR) and 48 insertions or deletions variants were found by sequence alignment of Capsicum cp genome. These findings provide a foundation for further investigation of cp genome evolution in Capsicum and other higher plants.

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

Science.gov (United States)

Mackey, Aaron J; Pearson, William R

2004-10-01

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

Population-based resequencing of experimentally evolved populations reveals the genetic basis of body size variation in Drosophila melanogaster.

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Thomas L Turner

2011-03-01

Full Text Available Body size is a classic quantitative trait with evolutionarily significant variation within many species. Locating the alleles responsible for this variation would help understand the maintenance of variation in body size in particular, as well as quantitative traits in general. However, successful genome-wide association of genotype and phenotype may require very large sample sizes if alleles have low population frequencies or modest effects. As a complementary approach, we propose that population-based resequencing of experimentally evolved populations allows for considerable power to map functional variation. Here, we use this technique to investigate the genetic basis of natural variation in body size in Drosophila melanogaster. Significant differentiation of hundreds of loci in replicate selection populations supports the hypothesis that the genetic basis of body size variation is very polygenic in D. melanogaster. Significantly differentiated variants are limited to single genes at some loci, allowing precise hypotheses to be formed regarding causal polymorphisms, while other significant regions are large and contain many genes. By using significantly associated polymorphisms as a priori candidates in follow-up studies, these data are expected to provide considerable power to determine the genetic basis of natural variation in body size.

MAGERI: Computational pipeline for molecular-barcoded targeted resequencing.

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Mikhail Shugay

2017-05-01

Full Text Available Unique molecular identifiers (UMIs show outstanding performance in targeted high-throughput resequencing, being the most promising approach for the accurate identification of rare variants in complex DNA samples. This approach has application in multiple areas, including cancer diagnostics, thus demanding dedicated software and algorithms. Here we introduce MAGERI, a computational pipeline that efficiently handles all caveats of UMI-based analysis to obtain high-fidelity mutation profiles and call ultra-rare variants. Using an extensive set of benchmark datasets including gold-standard biological samples with known variant frequencies, cell-free DNA from tumor patient blood samples and publicly available UMI-encoded datasets we demonstrate that our method is both robust and efficient in calling rare variants. The versatility of our software is supported by accurate results obtained for both tumor DNA and viral RNA samples in datasets prepared using three different UMI-based protocols.

Application of genomic tools in plant breeding.

Science.gov (United States)

Pérez-de-Castro, A M; Vilanova, S; Cañizares, J; Pascual, L; Blanca, J M; Díez, M J; Prohens, J; Picó, B

2012-05-01

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.

Complete genome sequence of the fire blight pathogen Erwinia pyrifoliae DSM 12163T and comparative genomic insights into plant pathogenicity

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Frey Jürg E

2010-01-01

Full Text Available Abstract Background Erwinia pyrifoliae is a newly described necrotrophic pathogen, which causes fire blight on Asian (Nashi pear and is geographically restricted to Eastern Asia. Relatively little is known about its genetics compared to the closely related main fire blight pathogen E. amylovora. Results The genome of the type strain of E. pyrifoliae strain DSM 12163T, was sequenced using both 454 and Solexa pyrosequencing and annotated. The genome contains a circular chromosome of 4.026 Mb and four small plasmids. Based on their respective role in virulence in E. amylovora or related organisms, we identified several putative virulence factors, including type III and type VI secretion systems and their effectors, flagellar genes, sorbitol metabolism, iron uptake determinants, and quorum-sensing components. A deletion in the rpoS gene covering the most conserved region of the protein was identified which may contribute to the difference in virulence/host-range compared to E. amylovora. Comparative genomics with the pome fruit epiphyte Erwinia tasmaniensis Et1/99 showed that both species are overall highly similar, although specific differences were identified, for example the presence of some phage gene-containing regions and a high number of putative genomic islands containing transposases in the E. pyrifoliae DSM 12163T genome. Conclusions The E. pyrifoliae genome is an important addition to the published genome of E. tasmaniensis and the unfinished genome of E. amylovora providing a foundation for re-sequencing additional strains that may shed light on the evolution of the host-range and virulence/pathogenicity of this important group of plant-associated bacteria.

Genome-wide comparative analysis reveals similar types of NBS genes in hybrid Citrus sinensis genome and original Citrus clementine genome and provides new insights into non-TIR NBS genes.

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Yunsheng Wang

Full Text Available In this study, we identified and compared nucleotide-binding site (NBS domain-containing genes from three Citrus genomes (C. clementina, C. sinensis from USA and C. sinensis from China. Phylogenetic analysis of all Citrus NBS genes across these three genomes revealed that there are three approximately evenly numbered groups: one group contains the Toll-Interleukin receptor (TIR domain and two different Non-TIR groups in which most of proteins contain the Coiled Coil (CC domain. Motif analysis confirmed that the two groups of CC-containing NBS genes are from different evolutionary origins. We partitioned NBS genes into clades using NBS domain sequence distances and found most clades include NBS genes from all three Citrus genomes. This suggests that three Citrus genomes have similar numbers and types of NBS genes. We also mapped the re-sequenced reads of three pomelo and three mandarin genomes onto the C. sinensis genome. We found that most NBS genes of the hybrid C. sinensis genome have corresponding homologous genes in both pomelo and mandarin genomes. The homologous NBS genes in pomelo and mandarin suggest that the parental species of C. sinensis may contain similar types of NBS genes. This explains why the hybrid C. sinensis and original C. clementina have similar types of NBS genes in this study. Furthermore, we found that sequence variation amongst Citrus NBS genes were shaped by multiple independent and shared accelerated mutation accumulation events among different groups of NBS genes and in different Citrus genomes. Our comparative analyses yield valuable insight into the structure, organization and evolution of NBS genes in Citrus genomes. Furthermore, our comprehensive analysis showed that the non-TIR NBS genes can be divided into two groups that come from different evolutionary origins. This provides new insights into non-TIR genes, which have not received much attention.

Reconstruction and analysis of a genome-scale metabolic model for Scheffersomyces stipitis

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Balagurunathan Balaji

2012-02-01

Full Text Available Abstract Background Fermentation of xylose, the major component in hemicellulose, is essential for economic conversion of lignocellulosic biomass to fuels and chemicals. The yeast Scheffersomyces stipitis (formerly known as Pichia stipitis has the highest known native capacity for xylose fermentation and possesses several genes for lignocellulose bioconversion in its genome. Understanding the metabolism of this yeast at a global scale, by reconstructing the genome scale metabolic model, is essential for manipulating its metabolic capabilities and for successful transfer of its capabilities to other industrial microbes. Results We present a genome-scale metabolic model for Scheffersomyces stipitis, a native xylose utilizing yeast. The model was reconstructed based on genome sequence annotation, detailed experimental investigation and known yeast physiology. Macromolecular composition of Scheffersomyces stipitis biomass was estimated experimentally and its ability to grow on different carbon, nitrogen, sulphur and phosphorus sources was determined by phenotype microarrays. The compartmentalized model, developed based on an iterative procedure, accounted for 814 genes, 1371 reactions, and 971 metabolites. In silico computed growth rates were compared with high-throughput phenotyping data and the model could predict the qualitative outcomes in 74% of substrates investigated. Model simulations were used to identify the biosynthetic requirements for anaerobic growth of Scheffersomyces stipitis on glucose and the results were validated with published literature. The bottlenecks in Scheffersomyces stipitis metabolic network for xylose uptake and nucleotide cofactor recycling were identified by in silico flux variability analysis. The scope of the model in enhancing the mechanistic understanding of microbial metabolism is demonstrated by identifying a mechanism for mitochondrial respiration and oxidative phosphorylation. Conclusion The genome-scale

Metingear: a development environment for annotating genome-scale metabolic models.

Science.gov (United States)

May, John W; James, A Gordon; Steinbeck, Christoph

2013-09-01

Genome-scale metabolic models often lack annotations that would allow them to be used for further analysis. Previous efforts have focused on associating metabolites in the model with a cross reference, but this can be problematic if the reference is not freely available, multiple resources are used or the metabolite is added from a literature review. Associating each metabolite with chemical structure provides unambiguous identification of the components and a more detailed view of the metabolism. We have developed an open-source desktop application that simplifies the process of adding database cross references and chemical structures to genome-scale metabolic models. Annotated models can be exported to the Systems Biology Markup Language open interchange format. Source code, binaries, documentation and tutorials are freely available at http://johnmay.github.com/metingear. The application is implemented in Java with bundles available for MS Windows and Macintosh OS X.

Selection against recombinant hybrids maintains reproductive isolation in hybridizing Populus species despite F1 fertility and recurrent gene flow.

Science.gov (United States)

Christe, Camille; Stölting, Kai N; Bresadola, Luisa; Fussi, Barbara; Heinze, Berthold; Wegmann, Daniel; Lexer, Christian

2016-06-01

Natural hybrid zones have proven to be precious tools for understanding the origin and maintenance of reproductive isolation (RI) and therefore species. Most available genomic studies of hybrid zones using whole- or partial-genome resequencing approaches have focused on comparisons of the parental source populations involved in genome admixture, rather than exploring fine-scale patterns of chromosomal ancestry across the full admixture gradient present between hybridizing species. We have studied three well-known European 'replicate' hybrid zones of Populus alba and P. tremula, two widespread, ecologically divergent forest trees, using up to 432 505 single-nucleotide polymorphisms (SNPs) from restriction site-associated DNA (RAD) sequencing. Estimates of fine-scale chromosomal ancestry, genomic divergence and differentiation across all 19 poplar chromosomes revealed strikingly contrasting results, including an unexpected preponderance of F1 hybrids in the centre of genomic clines on the one hand, and genomically localized, spatially variable shared variants consistent with ancient introgression between the parental species on the other. Genetic ancestry had a significant effect on survivorship of hybrid seedlings in a common garden trial, pointing to selection against early-generation recombinants. Our results indicate a role for selection against recombinant genotypes in maintaining RI in the face of apparent F1 fertility, consistent with the intragenomic 'coadaptation' model of barriers to introgression upon secondary contact. Whole-genome resequencing of hybridizing populations will clarify the roles of specific genetic pathways in RI between these model forest trees and may reveal which loci are affected most strongly by its cyclic breakdown. © 2016 John Wiley & Sons Ltd.

Ion Torrent sequencing as a tool for mutation discovery in the flax (Linum usitatissimum L.) genome.

Science.gov (United States)

Galindo-González, Leonardo; Pinzón-Latorre, David; Bergen, Erik A; Jensen, Dustin C; Deyholos, Michael K

2015-01-01

Detection of induced mutations is valuable for inferring gene function and for developing novel germplasm for crop improvement. Many reverse genetics approaches have been developed to identify mutations in genes of interest within a mutagenized population, including some approaches that rely on next-generation sequencing (e.g. exome capture, whole genome resequencing). As an alternative to these genome or exome-scale methods, we sought to develop a scalable and efficient method for detection of induced mutations that could be applied to a small number of target genes, using Ion Torrent technology. We developed this method in flax (Linum usitatissimum), to demonstrate its utility in a crop species. We used an amplicon-based approach in which DNA samples from an ethyl methanesulfonate (EMS)-mutagenized population were pooled and used as template in PCR reactions to amplify a region of each gene of interest. Barcodes were incorporated during PCR, and the pooled amplicons were sequenced using an Ion Torrent PGM. A pilot experiment with known SNPs showed that they could be detected at a frequency > 0.3% within the pools. We then selected eight genes for which we wanted to discover novel mutations, and applied our approach to screen 768 individuals from the EMS population, using either the Ion 314 or Ion 316 chips. Out of 29 potential mutations identified after processing the NGS reads, 16 mutations were confirmed using Sanger sequencing. The methodology presented here demonstrates the utility of Ion Torrent technology in detecting mutation variants in specific genome regions for large populations of a species such as flax. The methodology could be scaled-up to test >100 genes using the higher capacity chips now available from Ion Torrent.

Forces shaping the fastest evolving regions in the human genome.

Directory of Open Access Journals (Sweden)

Katherine S Pollard

2006-10-01

Full Text Available Comparative genomics allow us to search the human genome for segments that were extensively changed in the last approximately 5 million years since divergence from our common ancestor with chimpanzee, but are highly conserved in other species and thus are likely to be functional. We found 202 genomic elements that are highly conserved in vertebrates but show evidence of significantly accelerated substitution rates in human. These are mostly in non-coding DNA, often near genes associated with transcription and DNA binding. Resequencing confirmed that the five most accelerated elements are dramatically changed in human but not in other primates, with seven times more substitutions in human than in chimp. The accelerated elements, and in particular the top five, show a strong bias for adenine and thymine to guanine and cytosine nucleotide changes and are disproportionately located in high recombination and high guanine and cytosine content environments near telomeres, suggesting either biased gene conversion or isochore selection. In addition, there is some evidence of directional selection in the regions containing the two most accelerated regions. A combination of evolutionary forces has contributed to accelerated evolution of the fastest evolving elements in the human genome.

Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

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Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

2016-09-19

Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

Large-Scale Sequencing: The Future of Genomic Sciences Colloquium

Energy Technology Data Exchange (ETDEWEB)

Margaret Riley; Merry Buckley

2009-01-01

Genetic sequencing and the various molecular techniques it has enabled have revolutionized the field of microbiology. Examining and comparing the genetic sequences borne by microbes - including bacteria, archaea, viruses, and microbial eukaryotes - provides researchers insights into the processes microbes carry out, their pathogenic traits, and new ways to use microorganisms in medicine and manufacturing. Until recently, sequencing entire microbial genomes has been laborious and expensive, and the decision to sequence the genome of an organism was made on a case-by-case basis by individual researchers and funding agencies. Now, thanks to new technologies, the cost and effort of sequencing is within reach for even the smallest facilities, and the ability to sequence the genomes of a significant fraction of microbial life may be possible. The availability of numerous microbial genomes will enable unprecedented insights into microbial evolution, function, and physiology. However, the current ad hoc approach to gathering sequence data has resulted in an unbalanced and highly biased sampling of microbial diversity. A well-coordinated, large-scale effort to target the breadth and depth of microbial diversity would result in the greatest impact. The American Academy of Microbiology convened a colloquium to discuss the scientific benefits of engaging in a large-scale, taxonomically-based sequencing project. A group of individuals with expertise in microbiology, genomics, informatics, ecology, and evolution deliberated on the issues inherent in such an effort and generated a set of specific recommendations for how best to proceed. The vast majority of microbes are presently uncultured and, thus, pose significant challenges to such a taxonomically-based approach to sampling genome diversity. However, we have yet to even scratch the surface of the genomic diversity among cultured microbes. A coordinated sequencing effort of cultured organisms is an appropriate place to begin

Whole-genome sequencing of cultivated and wild peppers provides insights into Capsicum domestication and specialization

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Qin, Cheng; Yu, Changshui; Shen, Yaou; Fang, Xiaodong; Chen, Lang; Min, Jiumeng; Cheng, Jiaowen; Zhao, Shancen; Xu, Meng; Luo, Yong; Yang, Yulan; Wu, Zhiming; Mao, Likai; Wu, Haiyang; Ling-Hu, Changying; Zhou, Huangkai; Lin, Haijian; González-Morales, Sandra; Trejo-Saavedra, Diana L.; Tian, Hao; Tang, Xin; Zhao, Maojun; Huang, Zhiyong; Zhou, Anwei; Yao, Xiaoming; Cui, Junjie; Li, Wenqi; Chen, Zhe; Feng, Yongqiang; Niu, Yongchao; Bi, Shimin; Yang, Xiuwei; Li, Weipeng; Cai, Huimin; Luo, Xirong; Montes-Hernández, Salvador; Leyva-González, Marco A.; Xiong, Zhiqiang; He, Xiujing; Bai, Lijun; Tan, Shu; Tang, Xiangqun; Liu, Dan; Liu, Jinwen; Zhang, Shangxing; Chen, Maoshan; Zhang, Lu; Zhang, Li; Zhang, Yinchao; Liao, Weiqin; Zhang, Yan; Wang, Min; Lv, Xiaodan; Wen, Bo; Liu, Hongjun; Luan, Hemi; Zhang, Yonggang; Yang, Shuang; Wang, Xiaodian; Xu, Jiaohui; Li, Xueqin; Li, Shuaicheng; Wang, Junyi; Palloix, Alain; Bosland, Paul W.; Li, Yingrui; Krogh, Anders; Rivera-Bustamante, Rafael F.; Herrera-Estrella, Luis; Yin, Ye; Yu, Jiping; Hu, Kailin; Zhang, Zhiming

2014-01-01

As an economic crop, pepper satisfies people’s spicy taste and has medicinal uses worldwide. To gain a better understanding of Capsicum evolution, domestication, and specialization, we present here the genome sequence of the cultivated pepper Zunla-1 (C. annuum L.) and its wild progenitor Chiltepin (C. annuum var. glabriusculum). We estimate that the pepper genome expanded ∼0.3 Mya (with respect to the genome of other Solanaceae) by a rapid amplification of retrotransposons elements, resulting in a genome comprised of ∼81% repetitive sequences. Approximately 79% of 3.48-Gb scaffolds containing 34,476 protein-coding genes were anchored to chromosomes by a high-density genetic map. Comparison of cultivated and wild pepper genomes with 20 resequencing accessions revealed molecular footprints of artificial selection, providing us with a list of candidate domestication genes. We also found that dosage compensation effect of tandem duplication genes probably contributed to the pungent diversification in pepper. The Capsicum reference genome provides crucial information for the study of not only the evolution of the pepper genome but also, the Solanaceae family, and it will facilitate the establishment of more effective pepper breeding programs. PMID:24591624

Genome scale models of yeast: towards standardized evaluation and consistent omic integration

DEFF Research Database (Denmark)

Sanchez, Benjamin J.; Nielsen, Jens

2015-01-01

Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published and are curre......Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published...... in which all levels of omics data (from gene expression to flux) have been integrated in yeast GEMs. Relevant conclusions and current challenges for both GEM evaluation and omic integration are highlighted....

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

NARCIS (Netherlands)

Speth, D.R.; Zandt, M.H. in 't; Guerrero Cruz, S.; Dutilh, B.E.; Jetten, M.S.M.

2016-01-01

Partial-nitritation anammox (PNA) is a novel wastewater treatment procedure for energy-efficient ammonium removal. Here we use genome-resolved metagenomics to build a genome-based ecological model of the microbial community in a full-scale PNA reactor. Sludge from the bioreactor examined here is

Single-nucleotide polymorphism discovery in Leptographium longiclavatum, a mountain pine beetle-associated symbiotic fungus, using whole-genome resequencing.

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Ojeda, Dario I; Dhillon, Braham; Tsui, Clement K M; Hamelin, Richard C

2014-03-01

Single-nucleotide polymorphisms (SNPs) are rapidly becoming the standard markers in population genomics studies; however, their use in nonmodel organisms is limited due to the lack of cost-effective approaches to uncover genome-wide variation, and the large number of individuals needed in the screening process to reduce ascertainment bias. To discover SNPs for population genomics studies in the fungal symbionts of the mountain pine beetle (MPB), we developed a road map to discover SNPs and to produce a genotyping platform. We undertook a whole-genome sequencing approach of Leptographium longiclavatum in combination with available genomics resources of another MPB symbiont, Grosmannia clavigera. We sequenced 71 individuals pooled into four groups using the Illumina sequencing technology. We generated between 27 and 30 million reads of 75 bp that resulted in a total of 1, 181 contigs longer than 2 kb and an assembled genome size of 28.9 Mb (N50 = 48 kb, average depth = 125x). A total of 9052 proteins were annotated, and between 9531 and 17,266 SNPs were identified in the four pools. A subset of 206 genes (containing 574 SNPs, 11% false positives) was used to develop a genotyping platform for this species. Using this roadmap, we developed a genotyping assay with a total of 147 SNPs located in 121 genes using the Illumina(®) Sequenom iPLEX Gold. Our preliminary genotyping (success rate = 85%) of 304 individuals from 36 populations supports the utility of this approach for population genomics studies in other MPB fungal symbionts and other fungal nonmodel species. © 2013 John Wiley & Sons Ltd.

Identification and characterization of short tandem repeats in the Tibetan macaque genome based on resequencing data.

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Liu, San-Xu; Hou, Wei; Zhang, Xue-Yan; Peng, Chang-Jun; Yue, Bi-Song; Fan, Zhen-Xin; Li, Jing

2018-07-18

The Tibetan macaque, which is endemic to China, is currently listed as a Near Endangered primate species by the International Union for Conservation of Nature (IUCN). Short tandem repeats (STRs) refer to repetitive elements of genome sequence that range in length from 1-6 bp. They are found in many organisms and are widely applied in population genetic studies. To clarify the distribution characteristics of genome-wide STRs and understand their variation among Tibetan macaques, we conducted a genome-wide survey of STRs with next-generation sequencing of five macaque samples. A total of 1 077 790 perfect STRs were mined from our assembly, with an N50 of 4 966 bp. Mono-nucleotide repeats were the most abundant, followed by tetra- and di-nucleotide repeats. Analysis of GC content and repeats showed consistent results with other macaques. Furthermore, using STR analysis software (lobSTR), we found that the proportion of base pair deletions in the STRs was greater than that of insertions in the five Tibetan macaque individuals (Pgenome showed good amplification efficiency and could be used to study population genetics in Tibetan macaques. The neighbor-joining tree classified the five macaques into two different branches according to their geographical origin, indicating high genetic differentiation between the Huangshan and Sichuan populations. We elucidated the distribution characteristics of STRs in the Tibetan macaque genome and provided an effective method for screening polymorphic STRs. Our results also lay a foundation for future genetic variation studies of macaques.

Modeling Lactococcus lactis using a genome-scale flux model

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Nielsen Jens

2005-06-01

Full Text Available Abstract Background Genome-scale flux models are useful tools to represent and analyze microbial metabolism. In this work we reconstructed the metabolic network of the lactic acid bacteria Lactococcus lactis and developed a genome-scale flux model able to simulate and analyze network capabilities and whole-cell function under aerobic and anaerobic continuous cultures. Flux balance analysis (FBA and minimization of metabolic adjustment (MOMA were used as modeling frameworks. Results The metabolic network was reconstructed using the annotated genome sequence from L. lactis ssp. lactis IL1403 together with physiological and biochemical information. The established network comprised a total of 621 reactions and 509 metabolites, representing the overall metabolism of L. lactis. Experimental data reported in the literature was used to fit the model to phenotypic observations. Regulatory constraints had to be included to simulate certain metabolic features, such as the shift from homo to heterolactic fermentation. A minimal medium for in silico growth was identified, indicating the requirement of four amino acids in addition to a sugar. Remarkably, de novo biosynthesis of four other amino acids was observed even when all amino acids were supplied, which is in good agreement with experimental observations. Additionally, enhanced metabolic engineering strategies for improved diacetyl producing strains were designed. Conclusion The L. lactis metabolic network can now be used for a better understanding of lactococcal metabolic capabilities and potential, for the design of enhanced metabolic engineering strategies and for integration with other types of 'omic' data, to assist in finding new information on cellular organization and function.

Assessing the evolutionary impact of amino acid mutations in the human genome

DEFF Research Database (Denmark)

Boyko, Adam R; Williamson, Scott H; Indap, Amit R

2008-01-01

Quantifying the distribution of fitness effects among newly arising mutations in the human genome is key to resolving important debates in medical and evolutionary genetics. Here, we present a method for inferring this distribution using Single Nucleotide Polymorphism (SNP) data from a population...... of demographic and selective effects to patterning amino acid variation in the human genome. We find evidence of an ancient population expansion in the sample with African ancestry and a relatively recent bottleneck in the sample with European ancestry. After accounting for these demographic effects, we find...... with non-stationary demographic history (such as that of modern humans). Application of our method to 47,576 coding SNPs found by direct resequencing of 11,404 protein coding-genes in 35 individuals (20 European Americans and 15 African Americans) allows us to assess the relative contribution...

Smallpox virus resequencing GeneChips can also rapidly ascertain species status for some zoonotic non-variola orthopoxviruses.

Science.gov (United States)

Sulaiman, Irshad M; Sammons, Scott A; Wohlhueter, Robert M

2008-04-01

We recently developed a set of seven resequencing GeneChips for the rapid sequencing of Variola virus strains in the WHO Repository of the Centers for Disease Control and Prevention. In this study, we attempted to hybridize these GeneChips with some known non-Variola orthopoxvirus isolates, including monkeypox, cowpox, and vaccinia viruses, for rapid detection.

Rainbow: a tool for large-scale whole-genome sequencing data analysis using cloud computing.

Science.gov (United States)

Zhao, Shanrong; Prenger, Kurt; Smith, Lance; Messina, Thomas; Fan, Hongtao; Jaeger, Edward; Stephens, Susan

2013-06-27

Technical improvements have decreased sequencing costs and, as a result, the size and number of genomic datasets have increased rapidly. Because of the lower cost, large amounts of sequence data are now being produced by small to midsize research groups. Crossbow is a software tool that can detect single nucleotide polymorphisms (SNPs) in whole-genome sequencing (WGS) data from a single subject; however, Crossbow has a number of limitations when applied to multiple subjects from large-scale WGS projects. The data storage and CPU resources that are required for large-scale whole genome sequencing data analyses are too large for many core facilities and individual laboratories to provide. To help meet these challenges, we have developed Rainbow, a cloud-based software package that can assist in the automation of large-scale WGS data analyses. Here, we evaluated the performance of Rainbow by analyzing 44 different whole-genome-sequenced subjects. Rainbow has the capacity to process genomic data from more than 500 subjects in two weeks using cloud computing provided by the Amazon Web Service. The time includes the import and export of the data using Amazon Import/Export service. The average cost of processing a single sample in the cloud was less than 120 US dollars. Compared with Crossbow, the main improvements incorporated into Rainbow include the ability: (1) to handle BAM as well as FASTQ input files; (2) to split large sequence files for better load balance downstream; (3) to log the running metrics in data processing and monitoring multiple Amazon Elastic Compute Cloud (EC2) instances; and (4) to merge SOAPsnp outputs for multiple individuals into a single file to facilitate downstream genome-wide association studies. Rainbow is a scalable, cost-effective, and open-source tool for large-scale WGS data analysis. For human WGS data sequenced by either the Illumina HiSeq 2000 or HiSeq 2500 platforms, Rainbow can be used straight out of the box. Rainbow is available

High-resolution genetic maps of Eucalyptus improve Eucalyptus grandis genome assembly.

Science.gov (United States)

Bartholomé, Jérôme; Mandrou, Eric; Mabiala, André; Jenkins, Jerry; Nabihoudine, Ibouniyamine; Klopp, Christophe; Schmutz, Jeremy; Plomion, Christophe; Gion, Jean-Marc

2015-06-01

Genetic maps are key tools in genetic research as they constitute the framework for many applications, such as quantitative trait locus analysis, and support the assembly of genome sequences. The resequencing of the two parents of a cross between Eucalyptus urophylla and Eucalyptus grandis was used to design a single nucleotide polymorphism (SNP) array of 6000 markers evenly distributed along the E. grandis genome. The genotyping of 1025 offspring enabled the construction of two high-resolution genetic maps containing 1832 and 1773 markers with an average marker interval of 0.45 and 0.5 cM for E. grandis and E. urophylla, respectively. The comparison between genetic maps and the reference genome highlighted 85% of collinear regions. A total of 43 noncollinear regions and 13 nonsynthetic regions were detected and corrected in the new genome assembly. This improved version contains 4943 scaffolds totalling 691.3 Mb of which 88.6% were captured by the 11 chromosomes. The mapping data were also used to investigate the effect of population size and number of markers on linkage mapping accuracy. This study provides the most reliable linkage maps for Eucalyptus and version 2.0 of the E. grandis genome. © 2014 CIRAD. New Phytologist © 2014 New Phytologist Trust.

Discovery of candidate disease genes in ENU-induced mouse mutants by large-scale sequencing, including a splice-site mutation in nucleoredoxin.

Directory of Open Access Journals (Sweden)

Melissa K Boles

2009-12-01

Full Text Available An accurate and precisely annotated genome assembly is a fundamental requirement for functional genomic analysis. Here, the complete DNA sequence and gene annotation of mouse Chromosome 11 was used to test the efficacy of large-scale sequencing for mutation identification. We re-sequenced the 14,000 annotated exons and boundaries from over 900 genes in 41 recessive mutant mouse lines that were isolated in an N-ethyl-N-nitrosourea (ENU mutation screen targeted to mouse Chromosome 11. Fifty-nine sequence variants were identified in 55 genes from 31 mutant lines. 39% of the lesions lie in coding sequences and create primarily missense mutations. The other 61% lie in noncoding regions, many of them in highly conserved sequences. A lesion in the perinatal lethal line l11Jus13 alters a consensus splice site of nucleoredoxin (Nxn, inserting 10 amino acids into the resulting protein. We conclude that point mutations can be accurately and sensitively recovered by large-scale sequencing, and that conserved noncoding regions should be included for disease mutation identification. Only seven of the candidate genes we report have been previously targeted by mutation in mice or rats, showing that despite ongoing efforts to functionally annotate genes in the mammalian genome, an enormous gap remains between phenotype and function. Our data show that the classical positional mapping approach of disease mutation identification can be extended to large target regions using high-throughput sequencing.

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

Science.gov (United States)

Sadhukhan, Priyanka P; Raghunathan, Anu

2014-01-01

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

Next-generation genome-scale models for metabolic engineering

DEFF Research Database (Denmark)

King, Zachary A.; Lloyd, Colton J.; Feist, Adam M.

2015-01-01

Constraint-based reconstruction and analysis (COBRA) methods have become widely used tools for metabolic engineering in both academic and industrial laboratories. By employing a genome-scale in silico representation of the metabolic network of a host organism, COBRA methods can be used to predict...... examples of applying COBRA methods to strain optimization are presented and discussed. Then, an outlook is provided on the next generation of COBRA models and the new types of predictions they will enable for systems metabolic engineering....

Inferring the demographic history of African farmers and pygmy hunter-gatherers using a multilocus resequencing data set.

Directory of Open Access Journals (Sweden)

Etienne Patin

2009-04-01

Full Text Available The transition from hunting and gathering to farming involved a major cultural innovation that has spread rapidly over most of the globe in the last ten millennia. In sub-Saharan Africa, hunter-gatherers have begun to shift toward an agriculture-based lifestyle over the last 5,000 years. Only a few populations still base their mode of subsistence on hunting and gathering. The Pygmies are considered to be the largest group of mobile hunter-gatherers of Africa. They dwell in equatorial rainforests and are characterized by their short mean stature. However, little is known about the chronology of the demographic events-size changes, population splits, and gene flow--ultimately giving rise to contemporary Pygmy (Western and Eastern groups and neighboring agricultural populations. We studied the branching history of Pygmy hunter-gatherers and agricultural populations from Africa and estimated separation times and gene flow between these populations. We resequenced 24 independent noncoding regions across the genome, corresponding to a total of approximately 33 kb per individual, in 236 samples from seven Pygmy and five agricultural populations dispersed over the African continent. We used simulation-based inference to identify the historical model best fitting our data. The model identified included the early divergence of the ancestors of Pygmy hunter-gatherers and farming populations approximately 60,000 years ago, followed by a split of the Pygmies' ancestors into the Western and Eastern Pygmy groups approximately 20,000 years ago. Our findings increase knowledge of the history of the peopling of the African continent in a region lacking archaeological data. An appreciation of the demographic and adaptive history of African populations with different modes of subsistence should improve our understanding of the influence of human lifestyles on genome diversity.

Multiplex amplification of large sets of human exons.

Science.gov (United States)

Porreca, Gregory J; Zhang, Kun; Li, Jin Billy; Xie, Bin; Austin, Derek; Vassallo, Sara L; LeProust, Emily M; Peck, Bill J; Emig, Christopher J; Dahl, Fredrik; Gao, Yuan; Church, George M; Shendure, Jay

2007-11-01

A new generation of technologies is poised to reduce DNA sequencing costs by several orders of magnitude. But our ability to fully leverage the power of these technologies is crippled by the absence of suitable 'front-end' methods for isolating complex subsets of a mammalian genome at a scale that matches the throughput at which these platforms will routinely operate. We show that targeting oligonucleotides released from programmable microarrays can be used to capture and amplify approximately 10,000 human exons in a single multiplex reaction. Additionally, we show integration of this protocol with ultra-high-throughput sequencing for targeted variation discovery. Although the multiplex capture reaction is highly specific, we found that nonuniform capture is a key issue that will need to be resolved by additional optimization. We anticipate that highly multiplexed methods for targeted amplification will enable the comprehensive resequencing of human exons at a fraction of the cost of whole-genome resequencing.

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

Science.gov (United States)

Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen

2017-02-01

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

Efficiency to Discovery Transgenic Loci in GM Rice Using Next Generation Sequencing Whole Genome Re-sequencing

Directory of Open Access Journals (Sweden)

Doori Park

2015-09-01

Full Text Available Molecular characterization technology in genetically modified organisms, in addition to how transgenic biotechnologies are developed now require full transparency to assess the risk to living modified and non-modified organisms. Next generation sequencing (NGS methodology is suggested as an effective means in genome characterization and detection of transgenic insertion locations. In the present study, we applied NGS to insert transgenic loci, specifically the epidermal growth factor (EGF in genetically modified rice cells. A total of 29.3 Gb (~72× coverage was sequenced with a 2 × 150 bp paired end method by Illumina HiSeq2500, which was consecutively mapped to the rice genome and T-vector sequence. The compatible pairs of reads were successfully mapped to 10 loci on the rice chromosome and vector sequences were validated to the insertion location by polymerase chain reaction (PCR amplification. The EGF transgenic site was confirmed only on chromosome 4 by PCR. Results of this study demonstrated the success of NGS data to characterize the rice genome. Bioinformatics analyses must be developed in association with NGS data to identify highly accurate transgenic sites.

Genomic DNA Enrichment Using Sequence Capture Microarrays: a Novel Approach to Discover Sequence Nucleotide Polymorphisms (SNP) in Brassica napus L

Science.gov (United States)

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.

2013-01-01

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

Human apolipoprotein e resequencing by proteomic analysis and its application to serotyping.

Directory of Open Access Journals (Sweden)

Motoi Nishimura

Full Text Available BACKGROUND: Apolipoprotein E (ApoE typing is considered important because of the association between ApoE and Alzheimer's disease and familial dyslipidemia and is currently performed by genetic testing (APOE genotyping. ApoE levels in plasma and serum are clinically determined by immunoassay. METHODS: Combining an ApoE immunoassay reagent with proteomic analysis using an Orbitrap mass spectrometer, we attempted to resequence ApoE from trace amounts of serum for typing (serotyping. Most (24 of 33 ApoE mutant proteins registered to date with Online Mendelian Inheritance in Man, such as ApoE2 and ApoE4, involve lysine and arginine mutations. Digestion of mutant ApoE with trypsin will thus result in fragments that differ substantially from wild-type ApoE3 in terms of mass, making serotyping ideally suited to mass spectrometry analysis. RESULTS: The mean coverage of the amino acid sequence of full-length ApoE was 91.6% in the protein resequence. Residues 112 and 158 (which are mutated in ApoE2 and ApoE4 were covered in all samples, and the protein sequences were used for serotyping. Serotypes including all heterozygous combinations (ApoE2/E3, E2/E4, E3/E4 corresponded exactly to the APOE genotyping results in each of the subjects. CONCLUSION: Our novel ApoE serotyping method with protein resequencing requires no synthesis of stable isotope-labeled peptides or genome analysis. The method can use residual blood from samples collected for routine clinical tests, thus enabling retrospective studies with preserved body fluids. The test could be applied to samples from subjects whose DNA is unavailable. In future studies, we hope to demonstrate the capability of our method to detect rare ApoE mutations.

Survey of protein–DNA interactions in Aspergillus oryzae on a genomic scale

Science.gov (United States)

Wang, Chao; Lv, Yangyong; Wang, Bin; Yin, Chao; Lin, Ying; Pan, Li

2015-01-01

The genome-scale delineation of in vivo protein–DNA interactions is key to understanding genome function. Only ∼5% of transcription factors (TFs) in the Aspergillus genus have been identified using traditional methods. Although the Aspergillus oryzae genome contains >600 TFs, knowledge of the in vivo genome-wide TF-binding sites (TFBSs) in aspergilli remains limited because of the lack of high-quality antibodies. We investigated the landscape of in vivo protein–DNA interactions across the A. oryzae genome through coupling the DNase I digestion of intact nuclei with massively parallel sequencing and the analysis of cleavage patterns in protein–DNA interactions at single-nucleotide resolution. The resulting map identified overrepresented de novo TF-binding motifs from genomic footprints, and provided the detailed chromatin remodeling patterns and the distribution of digital footprints near transcription start sites. The TFBSs of 19 known Aspergillus TFs were also identified based on DNase I digestion data surrounding potential binding sites in conjunction with TF binding specificity information. We observed that the cleavage patterns of TFBSs were dependent on the orientation of TF motifs and independent of strand orientation, consistent with the DNA shape features of binding motifs with flanking sequences. PMID:25883143

Comparison of variations detection between whole-genome amplification methods used in single-cell resequencing

DEFF Research Database (Denmark)

Hou, Yong; Wu, Kui; Shi, Xulian

2015-01-01

methods, focusing particularly on variations detection. Low-coverage whole-genome sequencing revealed that DOP-PCR had the highest duplication ratio, but an even read distribution and the best reproducibility and accuracy for detection of copy-number variations (CNVs). However, MDA had significantly...... performance using SCRS amplified by different WGA methods. It will guide researchers to determine which WGA method is best suited to individual experimental needs at single-cell level....

The humankind genome: from genetic diversity to the origin of human diseases.

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Belizário, Jose E

2013-12-01

Genome-wide association studies have failed to establish common variant risk for the majority of common human diseases. The underlying reasons for this failure are explained by recent studies of resequencing and comparison of over 1200 human genomes and 10 000 exomes, together with the delineation of DNA methylation patterns (epigenome) and full characterization of coding and noncoding RNAs (transcriptome) being transcribed. These studies have provided the most comprehensive catalogues of functional elements and genetic variants that are now available for global integrative analysis and experimental validation in prospective cohort studies. With these datasets, researchers will have unparalleled opportunities for the alignment, mining, and testing of hypotheses for the roles of specific genetic variants, including copy number variations, single nucleotide polymorphisms, and indels as the cause of specific phenotypes and diseases. Through the use of next-generation sequencing technologies for genotyping and standardized ontological annotation to systematically analyze the effects of genomic variation on humans and model organism phenotypes, we will be able to find candidate genes and new clues for disease's etiology and treatment. This article describes essential concepts in genetics and genomic technologies as well as the emerging computational framework to comprehensively search websites and platforms available for the analysis and interpretation of genomic data.

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

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Thiele, Ines; Palsson, Bernhard Ø

2010-01-01

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

Inclusion of Population-specific Reference Panel from India to the 1000 Genomes Phase 3 Panel Improves Imputation Accuracy.

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Ahmad, Meraj; Sinha, Anubhav; Ghosh, Sreya; Kumar, Vikrant; Davila, Sonia; Yajnik, Chittaranjan S; Chandak, Giriraj R

2017-07-27

Imputation is a computational method based on the principle of haplotype sharing allowing enrichment of genome-wide association study datasets. It depends on the haplotype structure of the population and density of the genotype data. The 1000 Genomes Project led to the generation of imputation reference panels which have been used globally. However, recent studies have shown that population-specific panels provide better enrichment of genome-wide variants. We compared the imputation accuracy using 1000 Genomes phase 3 reference panel and a panel generated from genome-wide data on 407 individuals from Western India (WIP). The concordance of imputed variants was cross-checked with next-generation re-sequencing data on a subset of genomic regions. Further, using the genome-wide data from 1880 individuals, we demonstrate that WIP works better than the 1000 Genomes phase 3 panel and when merged with it, significantly improves the imputation accuracy throughout the minor allele frequency range. We also show that imputation using only South Asian component of the 1000 Genomes phase 3 panel works as good as the merged panel, making it computationally less intensive job. Thus, our study stresses that imputation accuracy using 1000 Genomes phase 3 panel can be further improved by including population-specific reference panels from South Asia.

Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network

OpenAIRE

Mart?n-Jim?nez, Cynthia A.; Salazar-Barreto, Diego; Barreto, George E.; Gonz?lez, Janneth

2017-01-01

Astrocytes are the most abundant cells of the central nervous system; they have a predominant role in maintaining brain metabolism. In this sense, abnormal metabolic states have been found in different neuropathological diseases. Determination of metabolic states of astrocytes is difficult to model using current experimental approaches given the high number of reactions and metabolites present. Thus, genome-scale metabolic networks derived from transcriptomic data can be used as a framework t...

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

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

2017-01-01

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

Multi-scale coding of genomic information: From DNA sequence to genome structure and function

International Nuclear Information System (INIS)

Arneodo, Alain; Vaillant, Cedric; Audit, Benjamin; Argoul, Francoise; D'Aubenton-Carafa, Yves; Thermes, Claude

2011-01-01

Understanding how chromatin is spatially and dynamically organized in the nucleus of eukaryotic cells and how this affects genome functions is one of the main challenges of cell biology. Since the different orders of packaging in the hierarchical organization of DNA condition the accessibility of DNA sequence elements to trans-acting factors that control the transcription and replication processes, there is actually a wealth of structural and dynamical information to learn in the primary DNA sequence. In this review, we show that when using concepts, methodologies, numerical and experimental techniques coming from statistical mechanics and nonlinear physics combined with wavelet-based multi-scale signal processing, we are able to decipher the multi-scale sequence encoding of chromatin condensation-decondensation mechanisms that play a fundamental role in regulating many molecular processes involved in nuclear functions.

High-Throughput Sequencing, a VersatileWeapon to Support Genome-Based Diagnosis in Infectious Diseases: Applications to Clinical Bacteriology

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Ségolène Caboche

2014-04-01

Full Text Available The recent progresses of high-throughput sequencing (HTS technologies enable easy and cost-reduced access to whole genome sequencing (WGS or re-sequencing. HTS associated with adapted, automatic and fast bioinformatics solutions for sequencing applications promises an accurate and timely identification and characterization of pathogenic agents. Many studies have demonstrated that data obtained from HTS analysis have allowed genome-based diagnosis, which has been consistent with phenotypic observations. These proofs of concept are probably the first steps toward the future of clinical microbiology. From concept to routine use, many parameters need to be considered to promote HTS as a powerful tool to help physicians and clinicians in microbiological investigations. This review highlights the milestones to be completed toward this purpose.

Quantitation of heteroplasmy of mtDNA sequence variants identified in a population of AD patients and controls by array-based resequencing.

Science.gov (United States)

Coon, Keith D; Valla, Jon; Szelinger, Szabolics; Schneider, Lonnie E; Niedzielko, Tracy L; Brown, Kevin M; Pearson, John V; Halperin, Rebecca; Dunckley, Travis; Papassotiropoulos, Andreas; Caselli, Richard J; Reiman, Eric M; Stephan, Dietrich A

2006-08-01

The role of mitochondrial dysfunction in the pathogenesis of Alzheimer's disease (AD) has been well documented. Though evidence for the role of mitochondria in AD seems incontrovertible, the impact of mitochondrial DNA (mtDNA) mutations in AD etiology remains controversial. Though mutations in mitochondrially encoded genes have repeatedly been implicated in the pathogenesis of AD, many of these studies have been plagued by lack of replication as well as potential contamination of nuclear-encoded mitochondrial pseudogenes. To assess the role of mtDNA mutations in the pathogenesis of AD, while avoiding the pitfalls of nuclear-encoded mitochondrial pseudogenes encountered in previous investigations and showcasing the benefits of a novel resequencing technology, we sequenced the entire coding region (15,452 bp) of mtDNA from 19 extremely well-characterized AD patients and 18 age-matched, unaffected controls utilizing a new, reliable, high-throughput array-based resequencing technique, the Human MitoChip. High-throughput, array-based DNA resequencing of the entire mtDNA coding region from platelets of 37 subjects revealed the presence of 208 loci displaying a total of 917 sequence variants. There were no statistically significant differences in overall mutational burden between cases and controls, however, 265 independent sites of statistically significant change between cases and controls were identified. Changed sites were found in genes associated with complexes I (30.2%), III (3.0%), IV (33.2%), and V (9.1%) as well as tRNA (10.6%) and rRNA (14.0%). Despite their statistical significance, the subtle nature of the observed changes makes it difficult to determine whether they represent true functional variants involved in AD etiology or merely naturally occurring dissimilarity. Regardless, this study demonstrates the tremendous value of this novel mtDNA resequencing platform, which avoids the pitfalls of erroneously amplifying nuclear-encoded mtDNA pseudogenes, and

The draft genome of Tibetan hulless barley reveals adaptive patterns to the high stressful Tibetan Plateau.

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Zeng, Xingquan; Long, Hai; Wang, Zhuo; Zhao, Shancen; Tang, Yawei; Huang, Zhiyong; Wang, Yulin; Xu, Qijun; Mao, Likai; Deng, Guangbing; Yao, Xiaoming; Li, Xiangfeng; Bai, Lijun; Yuan, Hongjun; Pan, Zhifen; Liu, Renjian; Chen, Xin; WangMu, QiMei; Chen, Ming; Yu, Lili; Liang, Junjun; DunZhu, DaWa; Zheng, Yuan; Yu, Shuiyang; LuoBu, ZhaXi; Guang, Xuanmin; Li, Jiang; Deng, Cao; Hu, Wushu; Chen, Chunhai; TaBa, XiongNu; Gao, Liyun; Lv, Xiaodan; Abu, Yuval Ben; Fang, Xiaodong; Nevo, Eviatar; Yu, Maoqun; Wang, Jun; Tashi, Nyima

2015-01-27

The Tibetan hulless barley (Hordeum vulgare L. var. nudum), also called "Qingke" in Chinese and "Ne" in Tibetan, is the staple food for Tibetans and an important livestock feed in the Tibetan Plateau. The diploid nature and adaptation to diverse environments of the highland give it unique resources for genetic research and crop improvement. Here we produced a 3.89-Gb draft assembly of Tibetan hulless barley with 36,151 predicted protein-coding genes. Comparative analyses revealed the divergence times and synteny between barley and other representative Poaceae genomes. The expansion of the gene family related to stress responses was found in Tibetan hulless barley. Resequencing of 10 barley accessions uncovered high levels of genetic variation in Tibetan wild barley and genetic divergence between Tibetan and non-Tibetan barley genomes. Selective sweep analyses demonstrate adaptive correlations of genes under selection with extensive environmental variables. Our results not only construct a genomic framework for crop improvement but also provide evolutionary insights of highland adaptation of Tibetan hulless barley.

Eimeria genomics: Where are we now and where are we going?

Science.gov (United States)

Blake, Damer P

2015-08-15

The evolution of sequencing technologies, from Sanger to next generation (NGS) and now the emerging third generation, has prompted a radical frameshift moving genomics from the specialist to the mainstream. For parasitology, genomics has moved fastest for the protozoa with sequence assemblies becoming available for multiple genera including Babesia, Cryptosporidium, Eimeria, Giardia, Leishmania, Neospora, Plasmodium, Theileria, Toxoplasma and Trypanosoma. Progress has commonly been slower for parasites of animals which lack zoonotic potential, but the deficit is now being redressed with impact likely in the areas of drug and vaccine development, molecular diagnostics and population biology. Genomics studies with the apicomplexan Eimeria species clearly illustrate the approaches and opportunities available. Specifically, more than ten years after initiation of a genome sequencing project a sequence assembly was published for Eimeria tenella in 2014, complemented by assemblies for all other Eimeria species which infect the chicken and Eimeria falciformis, a parasite of the mouse. Public access to these and other coccidian genome assemblies through resources such as GeneDB and ToxoDB now promotes comparative analysis, encouraging better use of shared resources and enhancing opportunities for development of novel diagnostic and control strategies. In the short term genomics resources support development of targeted and genome-wide genetic markers such as single nucleotide polymorphisms (SNPs), with whole genome re-sequencing becoming viable in the near future. Experimental power will develop rapidly as additional species, strains and isolates are sampled with particular emphasis on population structure and allelic diversity. Copyright © 2015 Elsevier B.V. All rights reserved.

Analysis of Genome-Scale Data

NARCIS (Netherlands)

Kemmeren, P.P.C.W.

2005-01-01

The genetic material of every cell in an organism is stored inside DNA in the form of genes, which together form the genome. The information stored in the DNA is translated to RNA and subsequently to proteins, which form complex biological systems. The availability of whole genome sequences has

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

Science.gov (United States)

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

2016-03-31

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

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

Directory of Open Access Journals (Sweden)

Marko Budinich

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.

Genomics of crop wild relatives: expanding the gene pool for crop improvement.

Science.gov (United States)

Brozynska, Marta; Furtado, Agnelo; Henry, Robert J

2016-04-01

Plant breeders require access to new genetic diversity to satisfy the demands of a growing human population for more food that can be produced in a variable or changing climate and to deliver the high-quality food with nutritional and health benefits demanded by consumers. The close relatives of domesticated plants, crop wild relatives (CWRs), represent a practical gene pool for use by plant breeders. Genomics of CWR generates data that support the use of CWR to expand the genetic diversity of crop plants. Advances in DNA sequencing technology are enabling the efficient sequencing of CWR and their increased use in crop improvement. As the sequencing of genomes of major crop species is completed, attention has shifted to analysis of the wider gene pool of major crops including CWR. A combination of de novo sequencing and resequencing is required to efficiently explore useful genetic variation in CWR. Analysis of the nuclear genome, transcriptome and maternal (chloroplast and mitochondrial) genome of CWR is facilitating their use in crop improvement. Genome analysis results in discovery of useful alleles in CWR and identification of regions of the genome in which diversity has been lost in domestication bottlenecks. Targeting of high priority CWR for sequencing will maximize the contribution of genome sequencing of CWR. Coordination of global efforts to apply genomics has the potential to accelerate access to and conservation of the biodiversity essential to the sustainability of agriculture and food production. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Targeted resequencing in epileptic encephalopathies identifies de novo mutations in CHD2 and SYNGAP1

DEFF Research Database (Denmark)

Carvill, Gemma L; Heavin, Sinéad B; Yendle, Simone C

2013-01-01

Epileptic encephalopathies are a devastating group of epilepsies with poor prognosis, of which the majority are of unknown etiology. We perform targeted massively parallel resequencing of 19 known and 46 candidate genes for epileptic encephalopathy in 500 affected individuals (cases) to identify...... CHD2 and SYNGAP1 mutations are new causes of epileptic encephalopathies, accounting for 1.2% and 1% of cases, respectively. We also expand the phenotypic spectra explained by SCN1A, SCN2A and SCN8A mutations. To our knowledge, this is the largest cohort of cases with epileptic encephalopathies...

Matrix-assisted laser desorption/ionisation, time-of-flight mass spectrometry in genomics research.

Directory of Open Access Journals (Sweden)

Jiannis Ragoussis

2006-07-01

Full Text Available The beginning of this millennium has seen dramatic advances in genomic research. Milestones such as the complete sequencing of the human genome and of many other species were achieved and complemented by the systematic discovery of variation at the single nucleotide (SNP and whole segment (copy number polymorphism level. Currently most genomics research efforts are concentrated on the production of whole genome functional annotations, as well as on mapping the epigenome by identifying the methylation status of CpGs, mainly in CpG islands, in different tissues. These recent advances have a major impact on the way genetic research is conducted and have accelerated the discovery of genetic factors contributing to disease. Technology was the critical driving force behind genomics projects: both the combination of Sanger sequencing with high-throughput capillary electrophoresis and the rapid advances in microarray technologies were keys to success. MALDI-TOF MS-based genome analysis represents a relative newcomer in this field. Can it establish itself as a long-term contributor to genetics research, or is it only suitable for niche areas and for laboratories with a passion for mass spectrometry? In this review, we will highlight the potential of MALDI-TOF MS-based tools for resequencing and for epigenetics research applications, as well as for classical complex genetic studies, allele quantification, and quantitative gene expression analysis. We will also identify the current limitations of this approach and attempt to place it in the context of other genome analysis technologies.

Genomic Analyses Reveal Demographic History and Temperate Adaptation of the Newly Discovered Honey Bee Subspecies Apis mellifera sinisxinyuan n. ssp.

Science.gov (United States)

Chen, Chao; Liu, Zhiguang; Pan, Qi; Chen, Xiao; Wang, Huihua; Guo, Haikun; Liu, Shidong; Lu, Hongfeng; Tian, Shilin; Li, Ruiqiang; Shi, Wei

2016-05-01

Studying the genetic signatures of climate-driven selection can produce insights into local adaptation and the potential impacts of climate change on populations. The honey bee (Apis mellifera) is an interesting species to study local adaptation because it originated in tropical/subtropical climatic regions and subsequently spread into temperate regions. However, little is known about the genetic basis of its adaptation to temperate climates. Here, we resequenced the whole genomes of ten individual bees from a newly discovered population in temperate China and downloaded resequenced data from 35 individuals from other populations. We found that the new population is an undescribed subspecies in the M-lineage of A. mellifera (Apis mellifera sinisxinyuan). Analyses of population history show that long-term global temperature has strongly influenced the demographic history of A. m. sinisxinyuan and its divergence from other subspecies. Further analyses comparing temperate and tropical populations identified several candidate genes related to fat body and the Hippo signaling pathway that are potentially involved in adaptation to temperate climates. Our results provide insights into the demographic history of the newly discovered A. m. sinisxinyuan, as well as the genetic basis of adaptation of A. mellifera to temperate climates at the genomic level. These findings will facilitate the selective breeding of A. mellifera to improve the survival of overwintering colonies. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

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

Science.gov (United States)

diCenzo, George C; Finan, Turlough M

2018-01-01

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

A re-sequencing based assessment of genomic heterogeneity and fast neutron-induced deletions in a common bean cultivar

Directory of Open Access Journals (Sweden)

Jamie A. O'Rourke

2013-06-01

Full Text Available A small fast neutron mutant population has been established from Phaseolus vulgaris cv. Red Hawk. We leveraged the available P. vulgaris genome sequence and high throughput next generation DNA sequencing to examine the genomic structure of five Phaseolus vulgaris cv. Red Hawk fast neutron mutants with striking visual phenotypes. Analysis of these genomes identified three classes of structural variation; between cultivar variation, natural variation within the fast neutron mutant population, and fast neutron induced mutagenesis. Our analyses focused on the latter two classes. We identified 23 large deletions (>40 bp common to multiple individuals, illustrating residual heterogeneity and regions of structural variation within the common bean cv. Red Hawk. An additional 18 large deletions were identified in individual mutant plants. These deletions, ranging in size from 40 bp to 43,000 bp, are potentially the result of fast neutron mutagenesis. Six of the 18 deletions lie near or within gene coding regions, identifying potential candidate genes causing the mutant phenotype.

Genome-wide evolutionary dynamics of influenza B viruses on a global scale.

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Pinky Langat

2017-12-01

Full Text Available The global-scale epidemiology and genome-wide evolutionary dynamics of influenza B remain poorly understood compared with influenza A viruses. We compiled a spatio-temporally comprehensive dataset of influenza B viruses, comprising over 2,500 genomes sampled worldwide between 1987 and 2015, including 382 newly-sequenced genomes that fill substantial gaps in previous molecular surveillance studies. Our contributed data increase the number of available influenza B virus genomes in Europe, Africa and Central Asia, improving the global context to study influenza B viruses. We reveal Yamagata-lineage diversity results from co-circulation of two antigenically-distinct groups that also segregate genetically across the entire genome, without evidence of intra-lineage reassortment. In contrast, Victoria-lineage diversity stems from geographic segregation of different genetic clades, with variability in the degree of geographic spread among clades. Differences between the lineages are reflected in their antigenic dynamics, as Yamagata-lineage viruses show alternating dominance between antigenic groups, while Victoria-lineage viruses show antigenic drift of a single lineage. Structural mapping of amino acid substitutions on trunk branches of influenza B gene phylogenies further supports these antigenic differences and highlights two potential mechanisms of adaptation for polymerase activity. Our study provides new insights into the epidemiological and molecular processes shaping influenza B virus evolution globally.

Genome-wide evolutionary dynamics of influenza B viruses on a global scale

Science.gov (United States)

Langat, Pinky; Bowden, Thomas A.; Edwards, Stephanie; Gall, Astrid; Rambaut, Andrew; Daniels, Rodney S.; Russell, Colin A.; Pybus, Oliver G.; McCauley, John

2017-01-01

The global-scale epidemiology and genome-wide evolutionary dynamics of influenza B remain poorly understood compared with influenza A viruses. We compiled a spatio-temporally comprehensive dataset of influenza B viruses, comprising over 2,500 genomes sampled worldwide between 1987 and 2015, including 382 newly-sequenced genomes that fill substantial gaps in previous molecular surveillance studies. Our contributed data increase the number of available influenza B virus genomes in Europe, Africa and Central Asia, improving the global context to study influenza B viruses. We reveal Yamagata-lineage diversity results from co-circulation of two antigenically-distinct groups that also segregate genetically across the entire genome, without evidence of intra-lineage reassortment. In contrast, Victoria-lineage diversity stems from geographic segregation of different genetic clades, with variability in the degree of geographic spread among clades. Differences between the lineages are reflected in their antigenic dynamics, as Yamagata-lineage viruses show alternating dominance between antigenic groups, while Victoria-lineage viruses show antigenic drift of a single lineage. Structural mapping of amino acid substitutions on trunk branches of influenza B gene phylogenies further supports these antigenic differences and highlights two potential mechanisms of adaptation for polymerase activity. Our study provides new insights into the epidemiological and molecular processes shaping influenza B virus evolution globally. PMID:29284042

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

Science.gov (United States)

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

2017-01-01

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

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

Directory of Open Access Journals (Sweden)

Matthias Christen

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

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

Science.gov (United States)

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

2013-11-01

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

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

OpenAIRE

Speth, D.R.; Zandt, M.H. in 't; Guerrero Cruz, S.; Dutilh, B.E.; Jetten, M.S.M.

2016-01-01

Partial-nitritation anammox (PNA) is a novel wastewater treatment procedure for energy-efficient ammonium removal. Here we use genome-resolved metagenomics to build a genome-based ecological model of the microbial community in a full-scale PNA reactor. Sludge from the bioreactor examined here is used to seed reactors in wastewater treatment plants around the world; however, the role of most of its microbial community in ammonium removal remains unknown. Our analysis yielded 23 near-complete d...

Metabolite coupling in genome-scale metabolic networks

Directory of Open Access Journals (Sweden)

Palsson Bernhard Ø

2006-03-01

Full Text Available Abstract Background Biochemically detailed stoichiometric matrices have now been reconstructed for various bacteria, yeast, and for the human cardiac mitochondrion based on genomic and proteomic data. These networks have been manually curated based on legacy data and elementally and charge balanced. Comparative analysis of these well curated networks is now possible. Pairs of metabolites often appear together in several network reactions, linking them topologically. This co-occurrence of pairs of metabolites in metabolic reactions is termed herein "metabolite coupling." These metabolite pairs can be directly computed from the stoichiometric matrix, S. Metabolite coupling is derived from the matrix ŜŜT, whose off-diagonal elements indicate the number of reactions in which any two metabolites participate together, where Ŝ is the binary form of S. Results Metabolite coupling in the studied networks was found to be dominated by a relatively small group of highly interacting pairs of metabolites. As would be expected, metabolites with high individual metabolite connectivity also tended to be those with the highest metabolite coupling, as the most connected metabolites couple more often. For metabolite pairs that are not highly coupled, we show that the number of reactions a pair of metabolites shares across a metabolic network closely approximates a line on a log-log scale. We also show that the preferential coupling of two metabolites with each other is spread across the spectrum of metabolites and is not unique to the most connected metabolites. We provide a measure for determining which metabolite pairs couple more often than would be expected based on their individual connectivity in the network and show that these metabolites often derive their principal biological functions from existing in pairs. Thus, analysis of metabolite coupling provides information beyond that which is found from studying the individual connectivity of individual

Population genomics of the Wolbachia endosymbiont in Drosophila melanogaster.

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Mark F Richardson

Full Text Available Wolbachia are maternally inherited symbiotic bacteria, commonly found in arthropods, which are able to manipulate the reproduction of their host in order to maximise their transmission. The evolutionary history of endosymbionts like Wolbachia can be revealed by integrating information on infection status in natural populations with patterns of sequence variation in Wolbachia and host mitochondrial genomes. Here we use whole-genome resequencing data from 290 lines of Drosophila melanogaster from North America, Europe, and Africa to predict Wolbachia infection status, estimate relative cytoplasmic genome copy number, and reconstruct Wolbachia and mitochondrial genome sequences. Overall, 63% of Drosophila strains were predicted to be infected with Wolbachia by our in silico analysis pipeline, which shows 99% concordance with infection status determined by diagnostic PCR. Complete Wolbachia and mitochondrial genomes show congruent phylogenies, consistent with strict vertical transmission through the maternal cytoplasm and imperfect transmission of Wolbachia. Bayesian phylogenetic analysis reveals that the most recent common ancestor of all Wolbachia and mitochondrial genomes in D. melanogaster dates to around 8,000 years ago. We find evidence for a recent global replacement of ancestral Wolbachia and mtDNA lineages, but our data suggest that the derived wMel lineage arose several thousand years ago, not in the 20th century as previously proposed. Our data also provide evidence that this global replacement event is incomplete and is likely to be one of several similar incomplete replacement events that have occurred since the out-of-Africa migration that allowed D. melanogaster to colonize worldwide habitats. This study provides a complete genomic analysis of the evolutionary mode and temporal dynamics of the D. melanogaster-Wolbachia symbiosis, as well as important resources for further analyses of the impact of Wolbachia on host biology.

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

DEFF Research Database (Denmark)

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

2016-01-01

Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repo...

A systems approach to predict oncometabolites via context-specific genome-scale metabolic networks.

Directory of Open Access Journals (Sweden)

Hojung Nam

2014-09-01

Full Text Available Altered metabolism in cancer cells has been viewed as a passive response required for a malignant transformation. However, this view has changed through the recently described metabolic oncogenic factors: mutated isocitrate dehydrogenases (IDH, succinate dehydrogenase (SDH, and fumarate hydratase (FH that produce oncometabolites that competitively inhibit epigenetic regulation. In this study, we demonstrate in silico predictions of oncometabolites that have the potential to dysregulate epigenetic controls in nine types of cancer by incorporating massive scale genetic mutation information (collected from more than 1,700 cancer genomes, expression profiling data, and deploying Recon 2 to reconstruct context-specific genome-scale metabolic models. Our analysis predicted 15 compounds and 24 substructures of potential oncometabolites that could result from the loss-of-function and gain-of-function mutations of metabolic enzymes, respectively. These results suggest a substantial potential for discovering unidentified oncometabolites in various forms of cancers.

Analysis of Genome-Scale Data

OpenAIRE

Kemmeren, P.P.C.W.

2005-01-01

The genetic material of every cell in an organism is stored inside DNA in the form of genes, which together form the genome. The information stored in the DNA is translated to RNA and subsequently to proteins, which form complex biological systems. The availability of whole genome sequences has given rise to the parallel development of other high-throughput approaches such as determining mRNA expression level changes, gene-deletion phenotypes, chromosomal location of DNA binding proteins, cel...

Ensembl Genomes 2016: more genomes, more complexity.

Science.gov (United States)

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

2016-01-04

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

Analysis of growth of Lactobacillus plantarum WCFS1 on a complex medium using a genome-scale metabolic model

NARCIS (Netherlands)

Teusink, B.; Wiersma, A.; Molenaar, D.; Francke, C.; Vos, de W.M.; Siezen, R.J.; Smid, E.J.

2006-01-01

A genome-scale metabolic model of the lactic acid bacterium Lactobacillus plantarum WCFS1 was constructed based on genomic content and experimental data. The complete model includes 721 genes, 643 reactions, and 531 metabolites. Different stoichiometric modeling techniques were used for

MicroScope-an integrated resource for community expertise of gene functions and comparative analysis of microbial genomic and metabolic data.

Science.gov (United States)

Médigue, Claudine; Calteau, Alexandra; Cruveiller, Stéphane; Gachet, Mathieu; Gautreau, Guillaume; Josso, Adrien; Lajus, Aurélie; Langlois, Jordan; Pereira, Hugo; Planel, Rémi; Roche, David; Rollin, Johan; Rouy, Zoe; Vallenet, David

2017-09-12

The overwhelming list of new bacterial genomes becoming available on a daily basis makes accurate genome annotation an essential step that ultimately determines the relevance of thousands of genomes stored in public databanks. The MicroScope platform (http://www.genoscope.cns.fr/agc/microscope) is an integrative resource that supports systematic and efficient revision of microbial genome annotation, data management and comparative analysis. Starting from the results of our syntactic, functional and relational annotation pipelines, MicroScope provides an integrated environment for the expert annotation and comparative analysis of prokaryotic genomes. It combines tools and graphical interfaces to analyze genomes and to perform the manual curation of gene function in a comparative genomics and metabolic context. In this article, we describe the free-of-charge MicroScope services for the annotation and analysis of microbial (meta)genomes, transcriptomic and re-sequencing data. Then, the functionalities of the platform are presented in a way providing practical guidance and help to the nonspecialists in bioinformatics. Newly integrated analysis tools (i.e. prediction of virulence and resistance genes in bacterial genomes) and original method recently developed (the pan-genome graph representation) are also described. Integrated environments such as MicroScope clearly contribute, through the user community, to help maintaining accurate resources. © The Author 2017. Published by Oxford University Press.

Sequence capture by hybridization to explore modern and ancient genomic diversity in model and nonmodel organisms.

Science.gov (United States)

Gasc, Cyrielle; Peyretaillade, Eric; Peyret, Pierre

2016-06-02

The recent expansion of next-generation sequencing has significantly improved biological research. Nevertheless, deep exploration of genomes or metagenomic samples remains difficult because of the sequencing depth and the associated costs required. Therefore, different partitioning strategies have been developed to sequence informative subsets of studied genomes. Among these strategies, hybridization capture has proven to be an innovative and efficient tool for targeting and enriching specific biomarkers in complex DNA mixtures. It has been successfully applied in numerous areas of biology, such as exome resequencing for the identification of mutations underlying Mendelian or complex diseases and cancers, and its usefulness has been demonstrated in the agronomic field through the linking of genetic variants to agricultural phenotypic traits of interest. Moreover, hybridization capture has provided access to underexplored, but relevant fractions of genomes through its ability to enrich defined targets and their flanking regions. Finally, on the basis of restricted genomic information, this method has also allowed the expansion of knowledge of nonreference species and ancient genomes and provided a better understanding of metagenomic samples. In this review, we present the major advances and discoveries permitted by hybridization capture and highlight the potency of this approach in all areas of biology. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

The Impact of Recombination Hotspots on Genome Evolution of a Fungal Plant Pathogen.

Science.gov (United States)

Croll, Daniel; Lendenmann, Mark H; Stewart, Ethan; McDonald, Bruce A

2015-11-01

Recombination has an impact on genome evolution by maintaining chromosomal integrity, affecting the efficacy of selection, and increasing genetic variability in populations. Recombination rates are a key determinant of the coevolutionary dynamics between hosts and their pathogens. Historic recombination events created devastating new pathogens, but the impact of ongoing recombination in sexual pathogens is poorly understood. Many fungal pathogens of plants undergo regular sexual cycles, and sex is considered to be a major factor contributing to virulence. We generated a recombination map at kilobase-scale resolution for the haploid plant pathogenic fungus Zymoseptoria tritici. To account for intraspecific variation in recombination rates, we constructed genetic maps from two independent crosses. We localized a total of 10,287 crossover events in 441 progeny and found that recombination rates were highly heterogeneous within and among chromosomes. Recombination rates on large chromosomes were inversely correlated with chromosome length. Short accessory chromosomes often lacked evidence for crossovers between parental chromosomes. Recombination was concentrated in narrow hotspots that were preferentially located close to telomeres. Hotspots were only partially conserved between the two crosses, suggesting that hotspots are short-lived and may vary according to genomic background. Genes located in hotspot regions were enriched in genes encoding secreted proteins. Population resequencing showed that chromosomal regions with high recombination rates were strongly correlated with regions of low linkage disequilibrium. Hence, genes in pathogen recombination hotspots are likely to evolve faster in natural populations and may represent a greater threat to the host. Copyright © 2015 by the Genetics Society of America.

Fungal Genomics Program

Energy Technology Data Exchange (ETDEWEB)

Grigoriev, Igor

2012-03-12

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.

A genome-wide, fine-scale map of natural pigmentation variation in Drosophila melanogaster.

Directory of Open Access Journals (Sweden)

Héloïse Bastide

2013-06-01

Full Text Available Various approaches can be applied to uncover the genetic basis of natural phenotypic variation, each with their specific strengths and limitations. Here, we use a replicated genome-wide association approach (Pool-GWAS to fine-scale map genomic regions contributing to natural variation in female abdominal pigmentation in Drosophila melanogaster, a trait that is highly variable in natural populations and highly heritable in the laboratory. We examined abdominal pigmentation phenotypes in approximately 8000 female European D. melanogaster, isolating 1000 individuals with extreme phenotypes. We then used whole-genome Illumina sequencing to identify single nucleotide polymorphisms (SNPs segregating in our sample, and tested these for associations with pigmentation by contrasting allele frequencies between replicate pools of light and dark individuals. We identify two small regions near the pigmentation genes tan and bric-à-brac 1, both corresponding to known cis-regulatory regions, which contain SNPs showing significant associations with pigmentation variation. While the Pool-GWAS approach suffers some limitations, its cost advantage facilitates replication and it can be applied to any non-model system with an available reference genome.

A genome-wide, fine-scale map of natural pigmentation variation in Drosophila melanogaster.

Science.gov (United States)

Bastide, Héloïse; Betancourt, Andrea; Nolte, Viola; Tobler, Raymond; Stöbe, Petra; Futschik, Andreas; Schlötterer, Christian

2013-06-01

Various approaches can be applied to uncover the genetic basis of natural phenotypic variation, each with their specific strengths and limitations. Here, we use a replicated genome-wide association approach (Pool-GWAS) to fine-scale map genomic regions contributing to natural variation in female abdominal pigmentation in Drosophila melanogaster, a trait that is highly variable in natural populations and highly heritable in the laboratory. We examined abdominal pigmentation phenotypes in approximately 8000 female European D. melanogaster, isolating 1000 individuals with extreme phenotypes. We then used whole-genome Illumina sequencing to identify single nucleotide polymorphisms (SNPs) segregating in our sample, and tested these for associations with pigmentation by contrasting allele frequencies between replicate pools of light and dark individuals. We identify two small regions near the pigmentation genes tan and bric-à-brac 1, both corresponding to known cis-regulatory regions, which contain SNPs showing significant associations with pigmentation variation. While the Pool-GWAS approach suffers some limitations, its cost advantage facilitates replication and it can be applied to any non-model system with an available reference genome.

Genomic Variants Revealed by Invariably Missing Genotypes in Nelore Cattle.

Directory of Open Access Journals (Sweden)

Joaquim Manoel da Silva

Full Text Available High density genotyping panels have been used in a wide range of applications. From population genetics to genome-wide association studies, this technology still offers the lowest cost and the most consistent solution for generating SNP data. However, in spite of the application, part of the generated data is always discarded from final datasets based on quality control criteria used to remove unreliable markers. Some discarded data consists of markers that failed to generate genotypes, labeled as missing genotypes. A subset of missing genotypes that occur in the whole population under study may be caused by technical issues but can also be explained by the presence of genomic variations that are in the vicinity of the assayed SNP and that prevent genotyping probes from annealing. The latter case may contain relevant information because these missing genotypes might be used to identify population-specific genomic variants. In order to assess which case is more prevalent, we used Illumina HD Bovine chip genotypes from 1,709 Nelore (Bos indicus samples. We found 3,200 missing genotypes among the whole population. NGS re-sequencing data from 8 sires were used to verify the presence of genomic variations within their flanking regions in 81.56% of these missing genotypes. Furthermore, we discovered 3,300 novel SNPs/Indels, 31% of which are located in genes that may affect traits of importance for the genetic improvement of cattle production.

An evolutionary framework for association testing in resequencing studies.

Directory of Open Access Journals (Sweden)

C Ryan King

2010-11-01

Full Text Available Sequencing technologies are becoming cheap enough to apply to large numbers of study participants and promise to provide new insights into human phenotypes by bringing to light rare and previously unknown genetic variants. We develop a new framework for the analysis of sequence data that incorporates all of the major features of previously proposed approaches, including those focused on allele counts and allele burden, but is both more general and more powerful. We harness population genetic theory to provide prior information on effect sizes and to create a pooling strategy for information from rare variants. Our method, EMMPAT (Evolutionary Mixed Model for Pooled Association Testing, generates a single test per gene (substantially reducing multiple testing concerns, facilitates graphical summaries, and improves the interpretation of results by allowing calculation of attributable variance. Simulations show that, relative to previously used approaches, our method increases the power to detect genes that affect phenotype when natural selection has kept alleles with large effect sizes rare. We demonstrate our approach on a population-based re-sequencing study of association between serum triglycerides and variation in ANGPTL4.

Quantitative phenotyping via deep barcode sequencing.

Science.gov (United States)

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

2009-10-01

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

GMATA: An Integrated Software Package for Genome-Scale SSR Mining, Marker Development and Viewing.

Science.gov (United States)

Wang, Xuewen; Wang, Le

2016-01-01

Simple sequence repeats (SSRs), also referred to as microsatellites, are highly variable tandem DNAs that are widely used as genetic markers. The increasing availability of whole-genome and transcript sequences provides information resources for SSR marker development. However, efficient software is required to efficiently identify and display SSR information along with other gene features at a genome scale. We developed novel software package Genome-wide Microsatellite Analyzing Tool Package (GMATA) integrating SSR mining, statistical analysis and plotting, marker design, polymorphism screening and marker transferability, and enabled simultaneously display SSR markers with other genome features. GMATA applies novel strategies for SSR analysis and primer design in large genomes, which allows GMATA to perform faster calculation and provides more accurate results than existing tools. Our package is also capable of processing DNA sequences of any size on a standard computer. GMATA is user friendly, only requires mouse clicks or types inputs on the command line, and is executable in multiple computing platforms. We demonstrated the application of GMATA in plants genomes and reveal a novel distribution pattern of SSRs in 15 grass genomes. The most abundant motifs are dimer GA/TC, the A/T monomer and the GCG/CGC trimer, rather than the rich G/C content in DNA sequence. We also revealed that SSR count is a linear to the chromosome length in fully assembled grass genomes. GMATA represents a powerful application tool that facilitates genomic sequence analyses. GAMTA is freely available at http://sourceforge.net/projects/gmata/?source=navbar.

Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

Energy Technology Data Exchange (ETDEWEB)

Seaver, Samuel M. D.; Bradbury, Louis M. T.; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

2015-03-10

There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.

Characterization of GM events by insert knowledge adapted re-sequencing approaches.

Science.gov (United States)

Yang, Litao; Wang, Congmao; Holst-Jensen, Arne; Morisset, Dany; Lin, Yongjun; Zhang, Dabing

2013-10-03

Detection methods and data from molecular characterization of genetically modified (GM) events are needed by stakeholders of public risk assessors and regulators. Generally, the molecular characteristics of GM events are incomprehensively revealed by current approaches and biased towards detecting transformation vector derived sequences. GM events are classified based on available knowledge of the sequences of vectors and inserts (insert knowledge). Herein we present three insert knowledge-adapted approaches for characterization GM events (TT51-1 and T1c-19 rice as examples) based on paired-end re-sequencing with the advantages of comprehensiveness, accuracy, and automation. The comprehensive molecular characteristics of two rice events were revealed with additional unintended insertions comparing with the results from PCR and Southern blotting. Comprehensive transgene characterization of TT51-1 and T1c-19 is shown to be independent of a priori knowledge of the insert and vector sequences employing the developed approaches. This provides an opportunity to identify and characterize also unknown GM events.

Sexagesimal scale for mapping human genome Escala sexagesimal para mapear el genoma humano

Directory of Open Access Journals (Sweden)

RICARDO CRUZ-COKE

2001-03-01

Full Text Available In a previous work I designed a diagram of the human genome based on a circular ideogram of the haploid set of chromosomes, using a low resolution scale of Megabase units. The purpose of this work is to draft a new scale to measure the physical map of the human genome at the highest resolution level. The entire length of the haploid genome of males is deployed in a circumference, marked with a sexagesimal scale with 360 degrees and 1296000 arc seconds. The radio of this circunference displays a semilogaritmic metric scale from 1 m up to the nanometer level. The base pair level of DNA sequences, 10-9 of this circunsference, is measured in milliarsec unit (mas, equivalent to a thousand of arcsecond. The "mas" unit, correspond to 1.27 nanometers (nm or 0.427 base pair (bp and it is the framework for measure DNA sequences. Thus the three billion base pairs of the human genome may be identified by 1296000000 "mas" units in continous correlation from number 1 to number 1296000000. This sexagesimal scale covers all the levels of the nuclear genetic material, from nucleotides to chromosomes. The locations of every codon and every gene may be numbered in the physical map of chomosome regions according to this new scale, instead of the partial kilobase and Megabase scales used today. The advantage of the new scale is the unification of the set of chromosomes under a continous scale of measurement at the DNA level, facilitating the correlation with the phenotypes of man and other speciesEn un trabajo anterior yo diseñé un diagrama del genoma humano basado en un ideograma circular del conjunto haploide de cromosomas, usando una escala de baja resolución en megabases. El propósito de este trabajo es el de diseñar una nueva escala para medir el mapa físico del genoma humano al más alto nivel de resolución. La longitud completa del genoma haploide del varon es extendido en una circunsferencia, marcada con una escala sexagesimal de 360 grados y 1296000

Integrative Genomic and Proteomic Analysis of the Response of Lactobacillus casei Zhang to Glucose Restriction.

Science.gov (United States)

Yu, Jie; Hui, Wenyan; Cao, Chenxia; Pan, Lin; Zhang, Heping; Zhang, Wenyi

2018-03-02

Nutrient starvation is an important survival challenge for bacteria during industrial production of functional foods. As next-generation sequencing technology has greatly advanced, we performed proteomic and genomic analysis to investigate the response of Lactobacillus casei Zhang to a glucose-restricted environment. L. casei Zhang strains were permitted to evolve in glucose-restricted or normal medium from a common ancestor over a 3 year period, and they were sampled at 1000, 2000, 3000, 4000, 5000, 6000, 7000, and 8000 generations and subjected to proteomic and genomic analyses. Genomic resequencing data revealed different point mutations and other mutational events in each selected generation of L. casei Zhang under glucose restriction stress. The differentially expressed proteins induced by glucose restriction were mostly related to fructose and mannose metabolism, carbohydrate metabolic processes, lyase activity, and amino-acid-transporting ATPase activity. Integrative proteomic and genomic analysis revealed that the mutations protected L. casei Zhang against glucose starvation by regulating other cellular carbohydrate, fatty acid, and amino acid catabolism; phosphoenolpyruvate system pathway activation; glycogen synthesis; ATP consumption; pyruvate metabolism; and general stress-response protein expression. The results help reveal the mechanisms of adapting to glucose starvation and provide new strategies for enhancing the industrial utility of L. casei Zhang.

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

Science.gov (United States)

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

2017-11-16

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

Genome-scale modeling of the protein secretory machinery in yeast

DEFF Research Database (Denmark)

Feizi, Amir; Österlund, Tobias; Petranovic, Dina

2013-01-01

The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking....... Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm...

Short template switch events explain mutation clusters in the human genome.

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Löytynoja, Ari; Goldman, Nick

2017-06-01

Resequencing efforts are uncovering the extent of genetic variation in humans and provide data to study the evolutionary processes shaping our genome. One recurring puzzle in both intra- and inter-species studies is the high frequency of complex mutations comprising multiple nearby base substitutions or insertion-deletions. We devised a generalized mutation model of template switching during replication that extends existing models of genome rearrangement and used this to study the role of template switch events in the origin of short mutation clusters. Applied to the human genome, our model detects thousands of template switch events during the evolution of human and chimp from their common ancestor and hundreds of events between two independently sequenced human genomes. Although many of these are consistent with a template switch mechanism previously proposed for bacteria, our model also identifies new types of mutations that create short inversions, some flanked by paired inverted repeats. The local template switch process can create numerous complex mutation patterns, including hairpin loop structures, and explains multinucleotide mutations and compensatory substitutions without invoking positive selection, speculative mechanisms, or implausible coincidence. Clustered sequence differences are challenging for current mapping and variant calling methods, and we show that many erroneous variant annotations exist in human reference data. Local template switch events may have been neglected as an explanation for complex mutations because of biases in commonly used analyses. Incorporation of our model into reference-based analysis pipelines and comparisons of de novo assembled genomes will lead to improved understanding of genome variation and evolution. © 2017 Löytynoja and Goldman; Published by Cold Spring Harbor Laboratory Press.

The European sea bass Dicentrarchus labrax genome puzzle: comparative BAC-mapping and low coverage shotgun sequencing

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Volckaert Filip AM

2010-01-01

Full Text Available Abstract Background Food supply from the ocean is constrained by the shortage of domesticated and selected fish. Development of genomic models of economically important fishes should assist with the removal of this bottleneck. European sea bass Dicentrarchus labrax L. (Moronidae, Perciformes, Teleostei is one of the most important fishes in European marine aquaculture; growing genomic resources put it on its way to serve as an economic model. Results End sequencing of a sea bass genomic BAC-library enabled the comparative mapping of the sea bass genome using the three-spined stickleback Gasterosteus aculeatus genome as a reference. BAC-end sequences (102,690 were aligned to the stickleback genome. The number of mappable BACs was improved using a two-fold coverage WGS dataset of sea bass resulting in a comparative BAC-map covering 87% of stickleback chromosomes with 588 BAC-contigs. The minimum size of 83 contigs covering 50% of the reference was 1.2 Mbp; the largest BAC-contig comprised 8.86 Mbp. More than 22,000 BAC-clones aligned with both ends to the reference genome. Intra-chromosomal rearrangements between sea bass and stickleback were identified. Size distributions of mapped BACs were used to calculate that the genome of sea bass may be only 1.3 fold larger than the 460 Mbp stickleback genome. Conclusions The BAC map is used for sequencing single BACs or BAC-pools covering defined genomic entities by second generation sequencing technologies. Together with the WGS dataset it initiates a sea bass genome sequencing project. This will allow the quantification of polymorphisms through resequencing, which is important for selecting highly performing domesticated fish.

MicroScope in 2017: an expanding and evolving integrated resource for community expertise of microbial genomes.

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Vallenet, David; Calteau, Alexandra; Cruveiller, Stéphane; Gachet, Mathieu; Lajus, Aurélie; Josso, Adrien; Mercier, Jonathan; Renaux, Alexandre; Rollin, Johan; Rouy, Zoe; Roche, David; Scarpelli, Claude; Médigue, Claudine

2017-01-04

The annotation of genomes from NGS platforms needs to be automated and fully integrated. However, maintaining consistency and accuracy in genome annotation is a challenging problem because millions of protein database entries are not assigned reliable functions. This shortcoming limits the knowledge that can be extracted from genomes and metabolic models. Launched in 2005, the MicroScope platform (http://www.genoscope.cns.fr/agc/microscope) is an integrative resource that supports systematic and efficient revision of microbial genome annotation, data management and comparative analysis. Effective comparative analysis requires a consistent and complete view of biological data, and therefore, support for reviewing the quality of functional annotation is critical. MicroScope allows users to analyze microbial (meta)genomes together with post-genomic experiment results if any (i.e. transcriptomics, re-sequencing of evolved strains, mutant collections, phenotype data). It combines tools and graphical interfaces to analyze genomes and to perform the expert curation of gene functions in a comparative context. Starting with a short overview of the MicroScope system, this paper focuses on some major improvements of the Web interface, mainly for the submission of genomic data and on original tools and pipelines that have been developed and integrated in the platform: computation of pan-genomes and prediction of biosynthetic gene clusters. Today the resource contains data for more than 6000 microbial genomes, and among the 2700 personal accounts (65% of which are now from foreign countries), 14% of the users are performing expert annotations, on at least a weekly basis, contributing to improve the quality of microbial genome annotations. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Experience from large scale use of the EuroGenomics custom SNP chip in cattle

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Boichard, Didier A; Boussaha, Mekki; Capitan, Aurélien

2018-01-01

This article presents the strategy to evaluate candidate mutations underlying QTL or responsible for genetic defects, based upon the design and large-scale use of the Eurogenomics custom SNP chip set up for bovine genomic selection. Some variants under study originated from mapping genetic defect...

Whole exome re-sequencing implicates CCDC38 and cilia structure and function in resistance to smoking related airflow obstruction.

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Louise V Wain

2014-05-01

Full Text Available Chronic obstructive pulmonary disease (COPD is a leading cause of global morbidity and mortality and, whilst smoking remains the single most important risk factor, COPD risk is heritable. Of 26 independent genomic regions showing association with lung function in genome-wide association studies, eleven have been reported to show association with airflow obstruction. Although the main risk factor for COPD is smoking, some individuals are observed to have a high forced expired volume in 1 second (FEV1 despite many years of heavy smoking. We hypothesised that these "resistant smokers" may harbour variants which protect against lung function decline caused by smoking and provide insight into the genetic determinants of lung health. We undertook whole exome re-sequencing of 100 heavy smokers who had healthy lung function given their age, sex, height and smoking history and applied three complementary approaches to explore the genetic architecture of smoking resistance. Firstly, we identified novel functional variants in the "resistant smokers" and looked for enrichment of these novel variants within biological pathways. Secondly, we undertook association testing of all exonic variants individually with two independent control sets. Thirdly, we undertook gene-based association testing of all exonic variants. Our strongest signal of association with smoking resistance for a non-synonymous SNP was for rs10859974 (P = 2.34 × 10(-4 in CCDC38, a gene which has previously been reported to show association with FEV1/FVC, and we demonstrate moderate expression of CCDC38 in bronchial epithelial cells. We identified an enrichment of novel putatively functional variants in genes related to cilia structure and function in resistant smokers. Ciliary function abnormalities are known to be associated with both smoking and reduced mucociliary clearance in patients with COPD. We suggest that genetic influences on the development or function of cilia in the bronchial

Genome-scale model guided design of Propionibacterium for enhanced propionic acid production

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Laura Navone

2018-06-01

Full Text Available Production of propionic acid by fermentation of propionibacteria has gained increasing attention in the past few years. However, biomanufacturing of propionic acid cannot compete with the current oxo-petrochemical synthesis process due to its well-established infrastructure, low oil prices and the high downstream purification costs of microbial production. Strain improvement to increase propionic acid yield is the best alternative to reduce downstream purification costs. The recent generation of genome-scale models for a number of Propionibacterium species facilitates the rational design of metabolic engineering strategies and provides a new opportunity to explore the metabolic potential of the Wood-Werkman cycle. Previous strategies for strain improvement have individually targeted acid tolerance, rate of propionate production or minimisation of by-products. Here we used the P. freudenreichii subsp. shermanii and the pan-Propionibacterium genome-scale metabolic models (GEMs to simultaneously target these combined issues. This was achieved by focussing on strategies which yield higher energies and directly suppress acetate formation. Using P. freudenreichii subsp. shermanii, two strategies were assessed. The first tested the ability to manipulate the redox balance to favour propionate production by over-expressing the first two enzymes of the pentose-phosphate pathway (PPP, Zwf (glucose-6-phosphate 1-dehydrogenase and Pgl (6-phosphogluconolactonase. Results showed a 4-fold increase in propionate to acetate ratio during the exponential growth phase. Secondly, the ability to enhance the energy yield from propionate production by over-expressing an ATP-dependent phosphoenolpyruvate carboxykinase (PEPCK and sodium-pumping methylmalonyl-CoA decarboxylase (MMD was tested, which extended the exponential growth phase. Together, these strategies demonstrate that in silico design strategies are predictive and can be used to reduce by-product formation in

Savant Genome Browser 2: visualization and analysis for population-scale genomics.

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Fiume, Marc; Smith, Eric J M; Brook, Andrew; Strbenac, Dario; Turner, Brian; Mezlini, Aziz M; Robinson, Mark D; Wodak, Shoshana J; Brudno, Michael

2012-07-01

High-throughput sequencing (HTS) technologies are providing an unprecedented capacity for data generation, and there is a corresponding need for efficient data exploration and analysis capabilities. Although most existing tools for HTS data analysis are developed for either automated (e.g. genotyping) or visualization (e.g. genome browsing) purposes, such tools are most powerful when combined. For example, integration of visualization and computation allows users to iteratively refine their analyses by updating computational parameters within the visual framework in real-time. Here we introduce the second version of the Savant Genome Browser, a standalone program for visual and computational analysis of HTS data. Savant substantially improves upon its predecessor and existing tools by introducing innovative visualization modes and navigation interfaces for several genomic datatypes, and synergizing visual and automated analyses in a way that is powerful yet easy even for non-expert users. We also present a number of plugins that were developed by the Savant Community, which demonstrate the power of integrating visual and automated analyses using Savant. The Savant Genome Browser is freely available (open source) at www.savantbrowser.com.

The genome and transcriptome of Phalaenopsis yield insights into floral organ development and flowering regulation

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Jian-Zhi Huang

2016-05-01

Full Text Available The Phalaenopsis orchid is an important potted flower of high economic value around the world. We report the 3.1 Gb draft genome assembly of an important winter flowering Phalaenopsis ‘KHM190’ cultivar. We generated 89.5 Gb RNA-seq and 113 million sRNA-seq reads to use these data to identify 41,153 protein-coding genes and 188 miRNA families. We also generated a draft genome for Phalaenopsis pulcherrima ‘B8802,’ a summer flowering species, via resequencing. Comparison of genome data between the two Phalaenopsis cultivars allowed the identification of 691,532 single-nucleotide polymorphisms. In this study, we reveal that the key role of PhAGL6b in the regulation of labellum organ development involves alternative splicing in the big lip mutant. Petal or sepal overexpressing PhAGL6b leads to the conversion into a lip-like structure. We also discovered that the gibberellin pathway that regulates the expression of flowering time genes during the reproductive phase change is induced by cool temperature. Our work thus depicted a valuable resource for the flowering control, flower architecture development, and breeding of the Phalaenopsis orchids.

Birth of scale-free molecular networks and the number of distinct DNA and protein domains per genome.

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Rzhetsky, A; Gomez, S M

2001-10-01

Current growth in the field of genomics has provided a number of exciting approaches to the modeling of evolutionary mechanisms within the genome. Separately, dynamical and statistical analyses of networks such as the World Wide Web and the social interactions existing between humans have shown that these networks can exhibit common fractal properties-including the property of being scale-free. This work attempts to bridge these two fields and demonstrate that the fractal properties of molecular networks are linked to the fractal properties of their underlying genomes. We suggest a stochastic model capable of describing the evolutionary growth of metabolic or signal-transduction networks. This model generates networks that share important statistical properties (so-called scale-free behavior) with real molecular networks. In particular, the frequency of vertices connected to exactly k other vertices follows a power-law distribution. The shape of this distribution remains invariant to changes in network scale: a small subgraph has the same distribution as the complete graph from which it is derived. Furthermore, the model correctly predicts that the frequencies of distinct DNA and protein domains also follow a power-law distribution. Finally, the model leads to a simple equation linking the total number of different DNA and protein domains in a genome with both the total number of genes and the overall network topology. MatLab (MathWorks, Inc.) programs described in this manuscript are available on request from the authors. ar345@columbia.edu.

Genome-scale metabolic models applied to human health and disease.

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Cook, Daniel J; Nielsen, Jens

2017-11-01

Advances in genome sequencing, high throughput measurement of gene and protein expression levels, data accessibility, and computational power have allowed genome-scale metabolic models (GEMs) to become a useful tool for understanding metabolic alterations associated with many different diseases. Despite the proven utility of GEMs, researchers confront multiple challenges in the use of GEMs, their application to human health and disease, and their construction and simulation in an organ-specific and disease-specific manner. Several approaches that researchers are taking to address these challenges include using proteomic and transcriptomic-informed methods to build GEMs for individual organs, diseases, and patients and using constraints on model behavior during simulation to match observed metabolic fluxes. We review the challenges facing researchers in the use of GEMs, review the approaches used to address these challenges, and describe advances that are on the horizon and could lead to a better understanding of human metabolism. WIREs Syst Biol Med 2017, 9:e1393. doi: 10.1002/wsbm.1393 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

The Sequenced Angiosperm Genomes and Genome Databases.

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

2018-01-01

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

Mitotic evolution of Plasmodium falciparum shows a stable core genome but recombination in antigen families.

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Selina E R Bopp

Full Text Available Malaria parasites elude eradication attempts both within the human host and across nations. At the individual level, parasites evade the host immune responses through antigenic variation. At the global level, parasites escape drug pressure through single nucleotide variants and gene copy amplification events conferring drug resistance. Despite their importance to global health, the rates at which these genomic alterations emerge have not been determined. We studied the complete genomes of different Plasmodium falciparum clones that had been propagated asexually over one year in the presence and absence of drug pressure. A combination of whole-genome microarray analysis and next-generation deep resequencing (totaling 14 terabases revealed a stable core genome with only 38 novel single nucleotide variants appearing in seventeen evolved clones (avg. 5.4 per clone. In clones exposed to atovaquone, we found cytochrome b mutations as well as an amplification event encompassing the P. falciparum multidrug resistance associated protein (mrp1 on chromosome 1. We observed 18 large-scale (>1 kb on average deletions of telomere-proximal regions encoding multigene families, involved in immune evasion (9.5×10(-6 structural variants per base pair per generation. Six of these deletions were associated with chromosomal crossovers generated during mitosis. We found only minor differences in rates between genetically distinct strains and between parasites cultured in the presence or absence of drug. Using these derived mutation rates for P. falciparum (1.0-9.7×10(-9 mutations per base pair per generation, we can now model the frequency at which drug or immune resistance alleles will emerge under a well-defined set of assumptions. Further, the detection of mitotic recombination events in var gene families illustrates how multigene families can arise and change over time in P. falciparum. These results will help improve our understanding of how P. falciparum

Mitotic Evolution of Plasmodium falciparum Shows a Stable Core Genome but Recombination in Antigen Families

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Bopp, Selina E. R.; Manary, Micah J.; Bright, A. Taylor; Johnston, Geoffrey L.; Dharia, Neekesh V.; Luna, Fabio L.; McCormack, Susan; Plouffe, David; McNamara, Case W.; Walker, John R.; Fidock, David A.; Denchi, Eros Lazzerini; Winzeler, Elizabeth A.

2013-01-01

Malaria parasites elude eradication attempts both within the human host and across nations. At the individual level, parasites evade the host immune responses through antigenic variation. At the global level, parasites escape drug pressure through single nucleotide variants and gene copy amplification events conferring drug resistance. Despite their importance to global health, the rates at which these genomic alterations emerge have not been determined. We studied the complete genomes of different Plasmodium falciparum clones that had been propagated asexually over one year in the presence and absence of drug pressure. A combination of whole-genome microarray analysis and next-generation deep resequencing (totaling 14 terabases) revealed a stable core genome with only 38 novel single nucleotide variants appearing in seventeen evolved clones (avg. 5.4 per clone). In clones exposed to atovaquone, we found cytochrome b mutations as well as an amplification event encompassing the P. falciparum multidrug resistance associated protein (mrp1) on chromosome 1. We observed 18 large-scale (>1 kb on average) deletions of telomere-proximal regions encoding multigene families, involved in immune evasion (9.5×10−6 structural variants per base pair per generation). Six of these deletions were associated with chromosomal crossovers generated during mitosis. We found only minor differences in rates between genetically distinct strains and between parasites cultured in the presence or absence of drug. Using these derived mutation rates for P. falciparum (1.0–9.7×10−9 mutations per base pair per generation), we can now model the frequency at which drug or immune resistance alleles will emerge under a well-defined set of assumptions. Further, the detection of mitotic recombination events in var gene families illustrates how multigene families can arise and change over time in P. falciparum. These results will help improve our understanding of how P. falciparum evolves to

Genome-wide analysis reveals signatures of selection for important traits in domestic sheep from different ecoregions.

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Liu, Zhaohua; Ji, Zhibin; Wang, Guizhi; Chao, Tianle; Hou, Lei; Wang, Jianmin

2016-11-03

Throughout a long period of adaptation and selection, sheep have thrived in a diverse range of ecological environments. Mongolian sheep is the common ancestor of the Chinese short fat-tailed sheep. Migration to different ecoregions leads to changes in selection pressures and results in microevolution. Mongolian sheep and its subspecies differ in a number of important traits, especially reproductive traits. Genome-wide intraspecific variation is required to dissect the genetic basis of these traits. This research resequenced 3 short fat-tailed sheep breeds with a 43.2-fold coverage of the sheep genome. We report more than 17 million single nucleotide polymorphisms and 2.9 million indels and identify 143 genomic regions with reduced pooled heterozygosity or increased genetic distance to each other breed that represent likely targets for selection during the migration. These regions harbor genes related to developmental processes, cellular processes, multicellular organismal processes, biological regulation, metabolic processes, reproduction, localization, growth and various components of the stress responses. Furthermore, we examined the haplotype diversity of 3 genomic regions involved in reproduction and found significant differences in TSHR and PRL gene regions among 8 sheep breeds. Our results provide useful genomic information for identifying genes or causal mutations associated with important economic traits in sheep and for understanding the genetic basis of adaptation to different ecological environments.

Ascertainment bias in studies of human genome-wide polymorphism

DEFF Research Database (Denmark)

Clark, Andrew G.; Hubisz, Melissa J.; Bustamente, Carlos D.

2005-01-01

of the SNPs that are found are influenced by the discovery sampling effort. The International HapMap project relied on nearly any piece of information available to identify SNPs-including BAC end sequences, shotgun reads, and differences between public and private sequences-and even made use of chimpanzee...... was a resequencing-by-hybridization effort using the 24 people of diverse origin in the Polymorphism Discovery Resource. Here we take these two data sets and contrast two basic summary statistics, heterozygosity and FST, as well as the site frequency spectra, for 500-kb windows spanning the genome. The magnitude...... of disparity between these samples in these measures of variability indicates that population genetic analysis on the raw genotype data is ill advised. Given the knowledge of the discovery samples, we perform an ascertainment correction and show how the post-correction data are more consistent across...

Whole-genome sequencing approaches for conservation biology: Advantages, limitations and practical recommendations.

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Fuentes-Pardo, Angela P; Ruzzante, Daniel E

2017-10-01

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.

Genome-scale analysis of positional clustering of mouse testis-specific genes

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Lee Bernett TK

2005-01-01

Full Text Available Abstract Background Genes are not randomly distributed on a chromosome as they were thought even after removal of tandem repeats. The positional clustering of co-expressed genes is known in prokaryotes and recently reported in several eukaryotic organisms such as Caenorhabditis elegans, Drosophila melanogaster, and Homo sapiens. In order to further investigate the mode of tissue-specific gene clustering in higher eukaryotes, we have performed a genome-scale analysis of positional clustering of the mouse testis-specific genes. Results Our computational analysis shows that a large proportion of testis-specific genes are clustered in groups of 2 to 5 genes in the mouse genome. The number of clusters is much higher than expected by chance even after removal of tandem repeats. Conclusion Our result suggests that testis-specific genes tend to cluster on the mouse chromosomes. This provides another piece of evidence for the hypothesis that clusters of tissue-specific genes do exist.

Genome-scale modeling using flux ratio constraints to enable metabolic engineering of clostridial metabolism in silico.

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McAnulty, Michael J; Yen, Jiun Y; Freedman, Benjamin G; Senger, Ryan S

2012-05-14

Genome-scale metabolic networks and flux models are an effective platform for linking an organism genotype to its phenotype. However, few modeling approaches offer predictive capabilities to evaluate potential metabolic engineering strategies in silico. A new method called "flux balance analysis with flux ratios (FBrAtio)" was developed in this research and applied to a new genome-scale model of Clostridium acetobutylicum ATCC 824 (iCAC490) that contains 707 metabolites and 794 reactions. FBrAtio was used to model wild-type metabolism and metabolically engineered strains of C. acetobutylicum where only flux ratio constraints and thermodynamic reversibility of reactions were required. The FBrAtio approach allowed solutions to be found through standard linear programming. Five flux ratio constraints were required to achieve a qualitative picture of wild-type metabolism for C. acetobutylicum for the production of: (i) acetate, (ii) lactate, (iii) butyrate, (iv) acetone, (v) butanol, (vi) ethanol, (vii) CO2 and (viii) H2. Results of this simulation study coincide with published experimental results and show the knockdown of the acetoacetyl-CoA transferase increases butanol to acetone selectivity, while the simultaneous over-expression of the aldehyde/alcohol dehydrogenase greatly increases ethanol production. FBrAtio is a promising new method for constraining genome-scale models using internal flux ratios. The method was effective for modeling wild-type and engineered strains of C. acetobutylicum.

ReseqChip: Automated integration of multiple local context probe data from the MitoChip array in mitochondrial DNA sequence assembly

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Spang Rainer

2009-12-01

Full Text Available Abstract Background The Affymetrix MitoChip v2.0 is an oligonucleotide tiling array for the resequencing of the human mitochondrial (mt genome. For each of 16,569 nucleotide positions of the mt genome it holds two sets of four 25-mer probes each that match the heavy and the light strand of a reference mt genome and vary only at their central position to interrogate all four possible alleles. In addition, the MitoChip v2.0 carries alternative local context probes to account for known mtDNA variants. These probes have been neglected in most studies due to the lack of software for their automated analysis. Results We provide ReseqChip, a free software that automates the process of resequencing mtDNA using multiple local context probes on the MitoChip v2.0. ReseqChip significantly improves base call rate and sequence accuracy. ReseqChip is available at http://code.open-bio.org/svnweb/index.cgi/bioperl/browse/bioperl-live/trunk/Bio/Microarray/Tools/. Conclusions ReseqChip allows for the automated consolidation of base calls from alternative local mt genome context probes. It thereby improves the accuracy of resequencing, while reducing the number of non-called bases.

Efficient genome-wide genotyping strategies and data integration in crop plants.

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Torkamaneh, Davoud; Boyle, Brian; Belzile, François

2018-03-01

Next-generation sequencing (NGS) has revolutionized plant and animal research by providing powerful genotyping methods. This review describes and discusses the advantages, challenges and, most importantly, solutions to facilitate data processing, the handling of missing data, and cross-platform data integration. Next-generation sequencing technologies provide powerful and flexible genotyping methods to plant breeders and researchers. These methods offer a wide range of applications from genome-wide analysis to routine screening with a high level of accuracy and reproducibility. Furthermore, they provide a straightforward workflow to identify, validate, and screen genetic variants in a short time with a low cost. NGS-based genotyping methods include whole-genome re-sequencing, SNP arrays, and reduced representation sequencing, which are widely applied in crops. The main challenges facing breeders and geneticists today is how to choose an appropriate genotyping method and how to integrate genotyping data sets obtained from various sources. Here, we review and discuss the advantages and challenges of several NGS methods for genome-wide genetic marker development and genotyping in crop plants. We also discuss how imputation methods can be used to both fill in missing data in genotypic data sets and to integrate data sets obtained using different genotyping tools. It is our hope that this synthetic view of genotyping methods will help geneticists and breeders to integrate these NGS-based methods in crop plant breeding and research.

Predicting growth of the healthy infant using a genome scale metabolic model.

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Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens

2017-01-01

An estimated 165 million children globally have stunted growth, and extensive growth data are available. Genome scale metabolic models allow the simulation of molecular flux over each metabolic enzyme, and are well adapted to analyze biological systems. We used a human genome scale metabolic model to simulate the mechanisms of growth and integrate data about breast-milk intake and composition with the infant's biomass and energy expenditure of major organs. The model predicted daily metabolic fluxes from birth to age 6 months, and accurately reproduced standard growth curves and changes in body composition. The model corroborates the finding that essential amino and fatty acids do not limit growth, but that energy is the main growth limiting factor. Disruptions to the supply and demand of energy markedly affected the predicted growth, indicating that elevated energy expenditure may be detrimental. The model was used to simulate the metabolic effect of mineral deficiencies, and showed the greatest growth reduction for deficiencies in copper, iron, and magnesium ions which affect energy production through oxidative phosphorylation. The model and simulation method were integrated to a platform and shared with the research community. The growth model constitutes another step towards the complete representation of human metabolism, and may further help improve the understanding of the mechanisms underlying stunting.

Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling

DEFF Research Database (Denmark)

Ghaffari, Pouyan; Mardinoglu, Adil; Asplund, Anna

2015-01-01

Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines...... based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted...... for inhibition of cell growth may provide leads for the development of efficient cancer treatment strategies....

Rapid Increase in Genome Size as a Consequence of Transposable Element Hyperactivity in Wood-White (Leptidea) Butterflies.

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Talla, Venkat; Suh, Alexander; Kalsoom, Faheema; Dinca, Vlad; Vila, Roger; Friberg, Magne; Wiklund, Christer; Backström, Niclas

2017-10-01

Characterizing and quantifying genome size variation among organisms and understanding if genome size evolves as a consequence of adaptive or stochastic processes have been long-standing goals in evolutionary biology. Here, we investigate genome size variation and association with transposable elements (TEs) across lepidopteran lineages using a novel genome assembly of the common wood-white (Leptidea sinapis) and population re-sequencing data from both L. sinapis and the closely related L. reali and L. juvernica together with 12 previously available lepidopteran genome assemblies. A phylogenetic analysis confirms established relationships among species, but identifies previously unknown intraspecific structure within Leptidea lineages. The genome assembly of L. sinapis is one of the largest of any lepidopteran taxon so far (643 Mb) and genome size is correlated with abundance of TEs, both in Lepidoptera in general and within Leptidea where L. juvernica from Kazakhstan has considerably larger genome size than any other Leptidea population. Specific TE subclasses have been active in different Lepidoptera lineages with a pronounced expansion of predominantly LINEs, DNA elements, and unclassified TEs in the Leptidea lineage after the split from other Pieridae. The rate of genome expansion in Leptidea in general has been in the range of four Mb/Million year (My), with an increase in a particular L. juvernica population to 72 Mb/My. The considerable differences in accumulation rates of specific TE classes in different lineages indicate that TE activity plays a major role in genome size evolution in butterflies and moths. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Multidimensional scaling for large genomic data sets

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Lu Henry

2008-04-01

Full Text Available Abstract Background Multi-dimensional scaling (MDS is aimed to represent high dimensional data in a low dimensional space with preservation of the similarities between data points. This reduction in dimensionality is crucial for analyzing and revealing the genuine structure hidden in the data. For noisy data, dimension reduction can effectively reduce the effect of noise on the embedded structure. For large data set, dimension reduction can effectively reduce information retrieval complexity. Thus, MDS techniques are used in many applications of data mining and gene network research. However, although there have been a number of studies that applied MDS techniques to genomics research, the number of analyzed data points was restricted by the high computational complexity of MDS. In general, a non-metric MDS method is faster than a metric MDS, but it does not preserve the true relationships. The computational complexity of most metric MDS methods is over O(N2, so that it is difficult to process a data set of a large number of genes N, such as in the case of whole genome microarray data. Results We developed a new rapid metric MDS method with a low computational complexity, making metric MDS applicable for large data sets. Computer simulation showed that the new method of split-and-combine MDS (SC-MDS is fast, accurate and efficient. Our empirical studies using microarray data on the yeast cell cycle showed that the performance of K-means in the reduced dimensional space is similar to or slightly better than that of K-means in the original space, but about three times faster to obtain the clustering results. Our clustering results using SC-MDS are more stable than those in the original space. Hence, the proposed SC-MDS is useful for analyzing whole genome data. Conclusion Our new method reduces the computational complexity from O(N3 to O(N when the dimension of the feature space is far less than the number of genes N, and it successfully

Network Thermodynamic Curation of Human and Yeast Genome-Scale Metabolic Models

Science.gov (United States)

Martínez, Verónica S.; Quek, Lake-Ee; Nielsen, Lars K.

2014-01-01

Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. PMID:25028891

De Novo Assembly of Complete Chloroplast Genomes from Non-model Species Based on a K-mer Frequency-Based Selection of Chloroplast Reads from Total DNA Sequences

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Shairul Izan

2017-08-01

Full Text Available Whole Genome Shotgun (WGS sequences of plant species often contain an abundance of reads that are derived from the chloroplast genome. Up to now these reads have generally been identified and assembled into chloroplast genomes based on homology to chloroplasts from related species. This re-sequencing approach may select against structural differences between the genomes especially in non-model species for which no close relatives have been sequenced before. The alternative approach is to de novo assemble the chloroplast genome from total genomic DNA sequences. In this study, we used k-mer frequency tables to identify and extract the chloroplast reads from the WGS reads and assemble these using a highly integrated and automated custom pipeline. Our strategy includes steps aimed at optimizing assemblies and filling gaps which are left due to coverage variation in the WGS dataset. We have successfully de novo assembled three complete chloroplast genomes from plant species with a range of nuclear genome sizes to demonstrate the universality of our approach: Solanum lycopersicum (0.9 Gb, Aegilops tauschii (4 Gb and Paphiopedilum henryanum (25 Gb. We also highlight the need to optimize the choice of k and the amount of data used. This new and cost-effective method for de novo short read assembly will facilitate the study of complete chloroplast genomes with more accurate analyses and inferences, especially in non-model plant genomes.

The draft genome and transcriptome of Cannabis sativa.

Science.gov (United States)

van Bakel, Harm; Stout, Jake M; Cote, Atina G; Tallon, Carling M; Sharpe, Andrew G; Hughes, Timothy R; Page, Jonathan E

2011-10-20

Cannabis sativa has been cultivated throughout human history as a source of fiber, oil and food, and for its medicinal and intoxicating properties. Selective breeding has produced cannabis plants for specific uses, including high-potency marijuana strains and hemp cultivars for fiber and seed production. The molecular biology underlying cannabinoid biosynthesis and other traits of interest is largely unexplored. We sequenced genomic DNA and RNA from the marijuana strain Purple Kush using shortread approaches. We report a draft haploid genome sequence of 534 Mb and a transcriptome of 30,000 genes. Comparison of the transcriptome of Purple Kush with that of the hemp cultivar 'Finola' revealed that many genes encoding proteins involved in cannabinoid and precursor pathways are more highly expressed in Purple Kush than in 'Finola'. The exclusive occurrence of Δ9-tetrahydrocannabinolic acid synthase in the Purple Kush transcriptome, and its replacement by cannabidiolic acid synthase in 'Finola', may explain why the psychoactive cannabinoid Δ9-tetrahydrocannabinol (THC) is produced in marijuana but not in hemp. Resequencing the hemp cultivars 'Finola' and 'USO-31' showed little difference in gene copy numbers of cannabinoid pathway enzymes. However, single nucleotide variant analysis uncovered a relatively high level of variation among four cannabis types, and supported a separation of marijuana and hemp. The availability of the Cannabis sativa genome enables the study of a multifunctional plant that occupies a unique role in human culture. Its availability will aid the development of therapeutic marijuana strains with tailored cannabinoid profiles and provide a basis for the breeding of hemp with improved agronomic characteristics.

Acorn: A grid computing system for constraint based modeling and visualization of the genome scale metabolic reaction networks via a web interface

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Bushell Michael E

2011-05-01

Full Text Available Abstract Background Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the genome. Recently, genome annotations have been used to reconstruct genome scale metabolic reaction networks for numerous species, including Homo sapiens, which allow simulations that provide valuable insights into topics, including predictions of gene essentiality of pathogens, interpretation of genetic polymorphism in metabolic disease syndromes and suggestions for novel approaches to microbial metabolic engineering. These constraint-based simulations are being integrated with the functional genomics portals, an activity that requires efficient implementation of the constraint-based simulations in the web-based environment. Results Here, we present Acorn, an open source (GNU GPL grid computing system for constraint-based simulations of genome scale metabolic reaction networks within an interactive web environment. The grid-based architecture allows efficient execution of computationally intensive, iterative protocols such as Flux Variability Analysis, which can be readily scaled up as the numbers of models (and users increase. The web interface uses AJAX, which facilitates efficient model browsing and other search functions, and intuitive implementation of appropriate simulation conditions. Research groups can install Acorn locally and create user accounts. Users can also import models in the familiar SBML format and link reaction formulas to major functional genomics portals of choice. Selected models and simulation results can be shared between different users and made publically available. Users can construct pathway map layouts and import them into the server using a desktop editor integrated within the system. Pathway maps are then used to visualise numerical results within the web environment. To illustrate these features we have deployed Acorn and created a

SWAP-Assembler 2: Optimization of De Novo Genome Assembler at Large Scale

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Meng, Jintao; Seo, Sangmin; Balaji, Pavan; Wei, Yanjie; Wang, Bingqiang; Feng, Shengzhong

2016-08-16

In this paper, we analyze and optimize the most time-consuming steps of the SWAP-Assembler, a parallel genome assembler, so that it can scale to a large number of cores for huge genomes with the size of sequencing data ranging from terabyes to petabytes. According to the performance analysis results, the most time-consuming steps are input parallelization, k-mer graph construction, and graph simplification (edge merging). For the input parallelization, the input data is divided into virtual fragments with nearly equal size, and the start position and end position of each fragment are automatically separated at the beginning of the reads. In k-mer graph construction, in order to improve the communication efficiency, the message size is kept constant between any two processes by proportionally increasing the number of nucleotides to the number of processes in the input parallelization step for each round. The memory usage is also decreased because only a small part of the input data is processed in each round. With graph simplification, the communication protocol reduces the number of communication loops from four to two loops and decreases the idle communication time. The optimized assembler is denoted as SWAP-Assembler 2 (SWAP2). In our experiments using a 1000 Genomes project dataset of 4 terabytes (the largest dataset ever used for assembling) on the supercomputer Mira, the results show that SWAP2 scales to 131,072 cores with an efficiency of 40%. We also compared our work with both the HipMER assembler and the SWAP-Assembler. On the Yanhuang dataset of 300 gigabytes, SWAP2 shows a 3X speedup and 4X better scalability compared with the HipMer assembler and is 45 times faster than the SWAP-Assembler. The SWAP2 software is available at https://sourceforge.net/projects/swapassembler.

Subgenome parallel selection is associated with morphotype diversification and convergent crop domestication in Brassica rapa and Brassica oleracea

NARCIS (Netherlands)

Cheng, Feng; Sun, Rifei; Hou, Xilin; Zheng, Hongkun; Zhang, Fenglan; Zhang, Yangyong; Liu, Bo; Liang, Jianli; Zhuang, Mu; Liu, Yunxia; Liu, Dongyuan; Wang, Xiaobo; Li, Pingxia; Liu, Yumei; Lin, Ke; Bucher, Johan; Zhang, Ningwen; Wang, Yan; Wang, Hui; Deng, Jie; Liao, Yongcui; Wei, Keyun; Zhang, Xueming; Fu, Lixia; Hu, Yunyan; Liu, Jisheng; Cai, Chengcheng; Zhang, Shujiang; Zhang, Shifan; Li, Fei; Zhang, Hui; Zhang, Jifang; Guo, Ning; Liu, Zhiyuan; Liu, Jin; Sun, Chao; Ma, Yuan; Zhang, Haijiao; Cui, Yang; Freeling, Micheal R.; Borm, Theo; Bonnema, Guusje; Wu, Jian; Wang, Xiaowu

2016-01-01

Brassica species, including crops such as cabbage, turnip and oilseed, display enormous phenotypic variation. Brassica genomes have all undergone a whole-genome triplication (WGT) event with unknown effects on phenotype diversification. We resequenced 199 Brassica rapa and 119 Brassica oleracea

A genome-wide analysis of lentivector integration sites using targeted sequence capture and next generation sequencing technology.

Science.gov (United States)

Ustek, Duran; Sirma, Sema; Gumus, Ergun; Arikan, Muzaffer; Cakiris, Aris; Abaci, Neslihan; Mathew, Jaicy; Emrence, Zeliha; Azakli, Hulya; Cosan, Fulya; Cakar, Atilla; Parlak, Mahmut; Kursun, Olcay

2012-10-01

One application of next-generation sequencing (NGS) is the targeted resequencing of interested genes which has not been used in viral integration site analysis of gene therapy applications. Here, we combined targeted sequence capture array and next generation sequencing to address the whole genome profiling of viral integration sites. Human 293T and K562 cells were transduced with a HIV-1 derived vector. A custom made DNA probe sets targeted pLVTHM vector used to capture lentiviral vector/human genome junctions. The captured DNA was sequenced using GS FLX platform. Seven thousand four hundred and eighty four human genome sequences flanking the long terminal repeats (LTR) of pLVTHM fragment sequences matched with an identity of at least 98% and minimum 50 bp criteria in both cells. In total, 203 unique integration sites were identified. The integrations in both cell lines were totally distant from the CpG islands and from the transcription start sites and preferentially located in introns. A comparison between the two cell lines showed that the lentiviral-transduced DNA does not have the same preferred regions in the two different cell lines. Copyright © 2012 Elsevier B.V. All rights reserved.

An Exon-Based Comparative Variant Analysis Pipeline to Study the Scale and Role of Frameshift and Nonsense Mutation in the Human-Chimpanzee Divergence

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GongXin Yu

2009-01-01

important biological processes such as T cell lineage development, the pathogenesis of inflammatory diseases, and antigen induced cell death. A “less-is-more” model was previously established to illustrate the role of the gene inactivation and disruptions during human evolution. Here this analysis suggested a different model where the chimpanzee-specific exon-disrupting mutations may act as additional evolutionary force that drove the human-chimpanzee divergence. Finally, the analysis revealed a number of sequencing errors in the chimpanzee and human genome sequences and further illustrated that they could be corrected without resequencing.

Genomic innovations, transcriptional plasticity and gene loss underlying the evolution and divergence of two highly polyphagous and invasive Helicoverpa pest species

DEFF Research Database (Denmark)

Pearce, S L; Clarke, D F; East, P D

2017-01-01

BACKGROUND: Helicoverpa armigera and Helicoverpa zea are major caterpillar pests of Old and New World agriculture, respectively. Both, particularly H. armigera, are extremely polyphagous, and H. armigera has developed resistance to many insecticides. Here we use comparative genomics, transcriptom......BACKGROUND: Helicoverpa armigera and Helicoverpa zea are major caterpillar pests of Old and New World agriculture, respectively. Both, particularly H. armigera, are extremely polyphagous, and H. armigera has developed resistance to many insecticides. Here we use comparative genomics......, transcriptomics and resequencing to elucidate the genetic basis for their properties as pests. RESULTS: We find that, prior to their divergence about 1.5 Mya, the H. armigera/H. zea lineage had accumulated up to more than 100 more members of specific detoxification and digestion gene families and more than 100...... lacks certain genes and alleles conferring insecticide resistance found in H. armigera. Non-synonymous sites in the expanded gene families above are rapidly diverging, both between paralogues and between orthologues in the two species. Whole genome transcriptomic analyses of H. armigera larvae show...

Genome-scale reconstruction of metabolic networks of Lactobacillus casei ATCC 334 and 12A.

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Elena Vinay-Lara

Full Text Available Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications.

In Silico Genome-Scale Reconstruction and Validation of the Corynebacterium glutamicum Metabolic Network

DEFF Research Database (Denmark)

Kjeldsen, Kjeld Raunkjær; Nielsen, J.

2009-01-01

A genome-scale metabolic model of the Gram-positive bacteria Corynebacterium glutamicum ATCC 13032 was constructed comprising 446 reactions and 411 metabolite, based on the annotated genome and available biochemical information. The network was analyzed using constraint based methods. The model...... was extensively validated against published flux data, and flux distribution values were found to correlate well between simulations and experiments. The split pathway of the lysine synthesis pathway of C. glutamicum was investigated, and it was found that the direct dehydrogenase variant gave a higher lysine...... yield than the alternative succinyl pathway at high lysine production rates. The NADPH demand of the network was not found to be critical for lysine production until lysine yields exceeded 55% (mmol lysine (mmol glucose)(-1)). The model was validated during growth on the organic acids acetate...

Network-assisted crop systems genetics: network inference and integrative analysis.

Science.gov (United States)

Lee, Tak; Kim, Hyojin; Lee, Insuk

2015-04-01

Although next-generation sequencing (NGS) technology has enabled the decoding of many crop species genomes, most of the underlying genetic components for economically important crop traits remain to be determined. Network approaches have proven useful for the study of the reference plant, Arabidopsis thaliana, and the success of network-based crop genetics will also require the availability of a genome-scale functional networks for crop species. In this review, we discuss how to construct functional networks and elucidate the holistic view of a crop system. The crop gene network then can be used for gene prioritization and the analysis of resequencing-based genome-wide association study (GWAS) data, the amount of which will rapidly grow in the field of crop science in the coming years. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

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Adina J Renz

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

Genome-scale modelling of microbial metabolism with temporal and spatial resolution.

Science.gov (United States)

Henson, Michael A

2015-12-01

Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated. © 2015 Authors; published by Portland Press Limited.

A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism

KAUST Repository

Hefzi, Hooman

2016-11-23

Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess optimization, we reconstructed the metabolic pathways in CHO and associated them with >1,700 genes in the Cricetulus griseus genome. The genome-scale metabolic model based on this reconstruction, iCHO1766, and cell-line-specific models for CHO-K1, CHO-S, and CHO-DG44 cells provide the biochemical basis of growth and recombinant protein production. The models accurately predict growth phenotypes and known auxotrophies in CHO cells. With the models, we quantify the protein synthesis capacity of CHO cells and demonstrate that common bioprocess treatments, such as histone deacetylase inhibitors, inefficiently increase product yield. However, our simulations show that the metabolic resources in CHO are more than three times more efficiently utilized for growth or recombinant protein synthesis following targeted efforts to engineer the CHO secretory pathway. This model will further accelerate CHO cell engineering and help optimize bioprocesses.

Genome-scale comparison and constraint-based metabolic reconstruction of the facultative anaerobic Fe(III-reducer Rhodoferax ferrireducens

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Daugherty Sean

2009-09-01

Full Text Available Abstract Background Rhodoferax ferrireducens is a metabolically versatile, Fe(III-reducing, subsurface microorganism that is likely to play an important role in the carbon and metal cycles in the subsurface. It also has the unique ability to convert sugars to electricity, oxidizing the sugars to carbon dioxide with quantitative electron transfer to graphite electrodes in microbial fuel cells. In order to expand our limited knowledge about R. ferrireducens, the complete genome sequence of this organism was further annotated and then the physiology of R. ferrireducens was investigated with a constraint-based, genome-scale in silico metabolic model and laboratory studies. Results The iterative modeling and experimental approach unveiled exciting, previously unknown physiological features, including an expanded range of substrates that support growth, such as cellobiose and citrate, and provided additional insights into important features such as the stoichiometry of the electron transport chain and the ability to grow via fumarate dismutation. Further analysis explained why R. ferrireducens is unable to grow via photosynthesis or fermentation of sugars like other members of this genus and uncovered novel genes for benzoate metabolism. The genome also revealed that R. ferrireducens is well-adapted for growth in the subsurface because it appears to be capable of dealing with a number of environmental insults, including heavy metals, aromatic compounds, nutrient limitation and oxidative stress. Conclusion This study demonstrates that combining genome-scale modeling with the annotation of a new genome sequence can guide experimental studies and accelerate the understanding of the physiology of under-studied yet environmentally relevant microorganisms.

Integrative genomics approaches validate PpYUC11-like as candidate gene for the stony hard trait in peach (P. persica L. Batsch).

Science.gov (United States)

Cirilli, Marco; Giovannini, Daniela; Ciacciulli, Angelo; Chiozzotto, Remo; Gattolin, Stefano; Rossini, Laura; Liverani, Alessandro; Bassi, Daniele

2018-05-18

Texture is one of the most important fruit quality attributes. In peach, stony hard (SH) is a recessive monogenic trait (hd/hd) that confers exceptionally prolonged firm flesh to fully ripe fruit. Previous studies have shown that the SH mutation affects the fruit ability to synthesize appropriate amounts of indol-3-acetic acid (IAA), which orchestrates the ripening processes through the activation of system 2 ethylene pathway. Allelic variation in a TC microsatellite located within the first intron of PpYUC11-like (a YUCCA-like auxin-biosynthesis gene) has been recently proposed as the causal mutation of the SH phenotype. The simple genetic determinism of the SH trait has been clarified through genome-wide association and LD analyses in a diverse set of accessions, restricting the hd locus to an interval of about 1.8 Mbp in chromosome 6. The comparison of fruit transcriptome data from non-SH (melting flesh) and SH accessions provided an expression patterns overview of the annotated transcripts within the hd locus, confirming the absence of PpYUC11-like expression in SH fruits. To explore further possible associations between genomic variants at the hd locus and the SH phenotype, re-sequencing data of the SH accession 'D41-62' were compared with several SH and non-SH accessions with different genetic backgrounds. A further step of validation was provided through the evaluation of variant-trait association in two bi-parental F 2 populations issued from the SH accession 'D41-62' and a panel of advanced breeding selections, showing perfect co-segregation of the PpYUC11-like intron TC 20 allele and the SH phenotype. In this study, we provide a multi-level validation of the genetic control of the SH trait through the integration of genome-wide association mapping, transcriptome analysis and whole-genome resequencing data for SH and non-SH accessions, and marker-trait association in a panel of advanced breeding selections and segregating progenies. Collectively, our data

The large-scale blast score ratio (LS-BSR pipeline: a method to rapidly compare genetic content between bacterial genomes

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Jason W. Sahl

2014-04-01

Full Text Available Background. As whole genome sequence data from bacterial isolates becomes cheaper to generate, computational methods are needed to correlate sequence data with biological observations. Here we present the large-scale BLAST score ratio (LS-BSR pipeline, which rapidly compares the genetic content of hundreds to thousands of bacterial genomes, and returns a matrix that describes the relatedness of all coding sequences (CDSs in all genomes surveyed. This matrix can be easily parsed in order to identify genetic relationships between bacterial genomes. Although pipelines have been published that group peptides by sequence similarity, no other software performs the rapid, large-scale, full-genome comparative analyses carried out by LS-BSR.Results. To demonstrate the utility of the method, the LS-BSR pipeline was tested on 96 Escherichia coli and Shigella genomes; the pipeline ran in 163 min using 16 processors, which is a greater than 7-fold speedup compared to using a single processor. The BSR values for each CDS, which indicate a relative level of relatedness, were then mapped to each genome on an independent core genome single nucleotide polymorphism (SNP based phylogeny. Comparisons were then used to identify clade specific CDS markers and validate the LS-BSR pipeline based on molecular markers that delineate between classical E. coli pathogenic variant (pathovar designations. Scalability tests demonstrated that the LS-BSR pipeline can process 1,000 E. coli genomes in 27–57 h, depending upon the alignment method, using 16 processors.Conclusions. LS-BSR is an open-source, parallel implementation of the BSR algorithm, enabling rapid comparison of the genetic content of large numbers of genomes. The results of the pipeline can be used to identify specific markers between user-defined phylogenetic groups, and to identify the loss and/or acquisition of genetic information between bacterial isolates. Taxa-specific genetic markers can then be translated

Genome-wide massively parallel sequencing of formaldehyde fixed-paraffin embedded (FFPE tumor tissues for copy-number- and mutation-analysis.

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Michal R Schweiger

Full Text Available BACKGROUND: Cancer re-sequencing programs rely on DNA isolated from fresh snap frozen tissues, the preparation of which is combined with additional preservation efforts. Tissue samples at pathology departments are routinely stored as formalin-fixed and paraffin-embedded (FFPE samples and their use would open up access to a variety of clinical trials. However, FFPE preparation is incompatible with many down-stream molecular biology techniques such as PCR based amplification methods and gene expression studies. METHODOLOGY/PRINCIPAL FINDINGS: Here we investigated the sample quality requirements of FFPE tissues for massively parallel short-read sequencing approaches. We evaluated key variables of pre-fixation, fixation related and post-fixation processes that occur in routine medical service (e.g. degree of autolysis, duration of fixation and of storage. We also investigated the influence of tissue storage time on sequencing quality by using material that was up to 18 years old. Finally, we analyzed normal and tumor breast tissues using the Sequencing by Synthesis technique (Illumina Genome Analyzer, Solexa to simultaneously localize genome-wide copy number alterations and to detect genomic variations such as substitutions and point-deletions and/or insertions in FFPE tissue samples. CONCLUSIONS/SIGNIFICANCE: The application of second generation sequencing techniques on small amounts of FFPE material opens up the possibility to analyze tissue samples which have been collected during routine clinical work as well as in the context of clinical trials. This is in particular important since FFPE samples are amply available from surgical tumor resections and histopathological diagnosis, and comprise tissue from precursor lesions, primary tumors, lymphogenic and/or hematogenic metastases. Large-scale studies using this tissue material will result in a better prediction of the prognosis of cancer patients and the early identification of patients which

Network thermodynamic curation of human and yeast genome-scale metabolic models.

Science.gov (United States)

Martínez, Verónica S; Quek, Lake-Ee; Nielsen, Lars K

2014-07-15

Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

CoVaCS: a consensus variant calling system.

Science.gov (United States)

Chiara, Matteo; Gioiosa, Silvia; Chillemi, Giovanni; D'Antonio, Mattia; Flati, Tiziano; Picardi, Ernesto; Zambelli, Federico; Horner, David Stephen; Pesole, Graziano; Castrignanò, Tiziana

2018-02-05

The advent and ongoing development of next generation sequencing technologies (NGS) has led to a rapid increase in the rate of human genome re-sequencing data, paving the way for personalized genomics and precision medicine. The body of genome resequencing data is progressively increasing underlining the need for accurate and time-effective bioinformatics systems for genotyping - a crucial prerequisite for identification of candidate causal mutations in diagnostic screens. Here we present CoVaCS, a fully automated, highly accurate system with a web based graphical interface for genotyping and variant annotation. Extensive tests on a gold standard benchmark data-set -the NA12878 Illumina platinum genome- confirm that call-sets based on our consensus strategy are completely in line with those attained by similar command line based approaches, and far more accurate than call-sets from any individual tool. Importantly our system exhibits better sensitivity and higher specificity than equivalent commercial software. CoVaCS offers optimized pipelines integrating state of the art tools for variant calling and annotation for whole genome sequencing (WGS), whole-exome sequencing (WES) and target-gene sequencing (TGS) data. The system is currently hosted at Cineca, and offers the speed of a HPC computing facility, a crucial consideration when large numbers of samples must be analysed. Importantly, all the analyses are performed automatically allowing high reproducibility of the results. As such, we believe that CoVaCS can be a valuable tool for the analysis of human genome resequencing studies. CoVaCS is available at: https://bioinformatics.cineca.it/covacs .

Genome-wide SNP detection, validation, and development of an 8K SNP array for apple.

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David Chagné

Full Text Available As high-throughput genetic marker screening systems are essential for a range of genetics studies and plant breeding applications, the International RosBREED SNP Consortium (IRSC has utilized the Illumina Infinium® II system to develop a medium- to high-throughput SNP screening tool for genome-wide evaluation of allelic variation in apple (Malus×domestica breeding germplasm. For genome-wide SNP discovery, 27 apple cultivars were chosen to represent worldwide breeding germplasm and re-sequenced at low coverage with the Illumina Genome Analyzer II. Following alignment of these sequences to the whole genome sequence of 'Golden Delicious', SNPs were identified using SoapSNP. A total of 2,113,120 SNPs were detected, corresponding to one SNP to every 288 bp of the genome. The Illumina GoldenGate® assay was then used to validate a subset of 144 SNPs with a range of characteristics, using a set of 160 apple accessions. This validation assay enabled fine-tuning of the final subset of SNPs for the Illumina Infinium® II system. The set of stringent filtering criteria developed allowed choice of a set of SNPs that not only exhibited an even distribution across the apple genome and a range of minor allele frequencies to ensure utility across germplasm, but also were located in putative exonic regions to maximize genotyping success rate. A total of 7867 apple SNPs was established for the IRSC apple 8K SNP array v1, of which 5554 were polymorphic after evaluation in segregating families and a germplasm collection. This publicly available genomics resource will provide an unprecedented resolution of SNP haplotypes, which will enable marker-locus-trait association discovery, description of the genetic architecture of quantitative traits, investigation of genetic variation (neutral and functional, and genomic selection in apple.

Genome-Wide SNP Detection, Validation, and Development of an 8K SNP Array for Apple

Science.gov (United States)

Chagné, David; Crowhurst, Ross N.; Troggio, Michela; Davey, Mark W.; Gilmore, Barbara; Lawley, Cindy; Vanderzande, Stijn; Hellens, Roger P.; Kumar, Satish; Cestaro, Alessandro; Velasco, Riccardo; Main, Dorrie; Rees, Jasper D.; Iezzoni, Amy; Mockler, Todd; Wilhelm, Larry; Van de Weg, Eric; Gardiner, Susan E.; Bassil, Nahla; Peace, Cameron

2012-01-01

As high-throughput genetic marker screening systems are essential for a range of genetics studies and plant breeding applications, the International RosBREED SNP Consortium (IRSC) has utilized the Illumina Infinium® II system to develop a medium- to high-throughput SNP screening tool for genome-wide evaluation of allelic variation in apple (Malus×domestica) breeding germplasm. For genome-wide SNP discovery, 27 apple cultivars were chosen to represent worldwide breeding germplasm and re-sequenced at low coverage with the Illumina Genome Analyzer II. Following alignment of these sequences to the whole genome sequence of ‘Golden Delicious’, SNPs were identified using SoapSNP. A total of 2,113,120 SNPs were detected, corresponding to one SNP to every 288 bp of the genome. The Illumina GoldenGate® assay was then used to validate a subset of 144 SNPs with a range of characteristics, using a set of 160 apple accessions. This validation assay enabled fine-tuning of the final subset of SNPs for the Illumina Infinium® II system. The set of stringent filtering criteria developed allowed choice of a set of SNPs that not only exhibited an even distribution across the apple genome and a range of minor allele frequencies to ensure utility across germplasm, but also were located in putative exonic regions to maximize genotyping success rate. A total of 7867 apple SNPs was established for the IRSC apple 8K SNP array v1, of which 5554 were polymorphic after evaluation in segregating families and a germplasm collection. This publicly available genomics resource will provide an unprecedented resolution of SNP haplotypes, which will enable marker-locus-trait association discovery, description of the genetic architecture of quantitative traits, investigation of genetic variation (neutral and functional), and genomic selection in apple. PMID:22363718

Fast evolution from precast bricks: genomics of young freshwater populations of threespine stickleback Gasterosteus aculeatus.

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Nadezhda V Terekhanova

2014-10-01

Full Text Available Adaptation is driven by natural selection; however, many adaptations are caused by weak selection acting over large timescales, complicating its study. Therefore, it is rarely possible to study selection comprehensively in natural environments. The threespine stickleback (Gasterosteus aculeatus is a well-studied model organism with a short generation time, small genome size, and many genetic and genomic tools available. Within this originally marine species, populations have recurrently adapted to freshwater all over its range. This evolution involved extensive parallelism: pre-existing alleles that adapt sticklebacks to freshwater habitats, but are also present at low frequencies in marine populations, have been recruited repeatedly. While a number of genomic regions responsible for this adaptation have been identified, the details of selection remain poorly understood. Using whole-genome resequencing, we compare pooled genomic samples from marine and freshwater populations of the White Sea basin, and identify 19 short genomic regions that are highly divergent between them, including three known inversions. 17 of these regions overlap protein-coding genes, including a number of genes with predicted functions that are relevant for adaptation to the freshwater environment. We then analyze four additional independently derived young freshwater populations of known ages, two natural and two artificially established, and use the observed shifts of allelic frequencies to estimate the strength of positive selection. Adaptation turns out to be quite rapid, indicating strong selection acting simultaneously at multiple regions of the genome, with selection coefficients of up to 0.27. High divergence between marine and freshwater genotypes, lack of reduction in polymorphism in regions responsible for adaptation, and high frequencies of freshwater alleles observed even in young freshwater populations are all consistent with rapid assembly of G. aculeatus

Fast evolution from precast bricks: genomics of young freshwater populations of threespine stickleback Gasterosteus aculeatus.

Science.gov (United States)

Terekhanova, Nadezhda V; Logacheva, Maria D; Penin, Aleksey A; Neretina, Tatiana V; Barmintseva, Anna E; Bazykin, Georgii A; Kondrashov, Alexey S; Mugue, Nikolai S

2014-10-01

Adaptation is driven by natural selection; however, many adaptations are caused by weak selection acting over large timescales, complicating its study. Therefore, it is rarely possible to study selection comprehensively in natural environments. The threespine stickleback (Gasterosteus aculeatus) is a well-studied model organism with a short generation time, small genome size, and many genetic and genomic tools available. Within this originally marine species, populations have recurrently adapted to freshwater all over its range. This evolution involved extensive parallelism: pre-existing alleles that adapt sticklebacks to freshwater habitats, but are also present at low frequencies in marine populations, have been recruited repeatedly. While a number of genomic regions responsible for this adaptation have been identified, the details of selection remain poorly understood. Using whole-genome resequencing, we compare pooled genomic samples from marine and freshwater populations of the White Sea basin, and identify 19 short genomic regions that are highly divergent between them, including three known inversions. 17 of these regions overlap protein-coding genes, including a number of genes with predicted functions that are relevant for adaptation to the freshwater environment. We then analyze four additional independently derived young freshwater populations of known ages, two natural and two artificially established, and use the observed shifts of allelic frequencies to estimate the strength of positive selection. Adaptation turns out to be quite rapid, indicating strong selection acting simultaneously at multiple regions of the genome, with selection coefficients of up to 0.27. High divergence between marine and freshwater genotypes, lack of reduction in polymorphism in regions responsible for adaptation, and high frequencies of freshwater alleles observed even in young freshwater populations are all consistent with rapid assembly of G. aculeatus freshwater genotypes

Targeted exonic sequencing of GWAS loci in the high extremes of the plasma lipids distribution

NARCIS (Netherlands)

Patel, Aniruddh P.; Peloso, Gina M.; Pirruccello, James P.; Johansen, Christopher T.; Dubé, Joseph B.; Larach, Daniel B.; Ban, Matthew R.; Dallinge-Thie, Geesje M.; Gupta, Namrata; Boehnke, Michael; Abecasis, Gonçalo R.; Kastelein, John J. P.; Hovingh, G. Kees; Hegele, Robert A.; Rader, Daniel J.; Kathiresan, Sekar

2016-01-01

Genome-wide association studies (GWAS) for plasma lipid levels have mapped numerous genomic loci, with each region often containing many protein-coding genes. Targeted re-sequencing of exons is a strategy to pinpoint causal variants and genes. We performed solution-based hybrid selection of 9008

Genome scale metabolic network reconstruction of Spirochaeta cellobiosiphila

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Bharat Manna

2017-10-01

Full Text Available Substantial rise in the global energy demand is one of the biggest challenges in this century. Environmental pollution due to rapid depletion of the fossil fuel resources and its alarming impact on the climate change and Global Warming have motivated researchers to look for non-petroleum-based sustainable, eco-friendly, renewable, low-cost energy alternatives, such as biofuel. Lignocellulosic biomass is one of the most promising bio-resources with huge potential to contribute to this worldwide energy demand. However, the complex organization of the Cellulose, Hemicellulose and Lignin in the Lignocellulosic biomass requires extensive pre-treatment and enzymatic hydrolysis followed by fermentation, raising overall production cost of biofuel. This encourages researchers to design cost-effective approaches for the production of second generation biofuels. The products from enzymatic hydrolysis of cellulose are mostly glucose monomer or cellobiose unit that are subjected to fermentation. Spirochaeta genus is a well-known group of obligate or facultative anaerobes, living primarily on carbohydrate metabolism. Spirochaeta cellobiosiphila sp. is a facultative anaerobe under this genus, which uses a variety of monosaccharides and disaccharides as energy sources. However, most rapid growth occurs on cellobiose and fermentation yields significant amount of ethanol, acetate, CO2, H2 and small amounts of formate. It is predicted to be promising microbial machinery for industrial fermentation processes for biofuel production. The metabolic pathways that govern cellobiose metabolism in Spirochaeta cellobiosiphila are yet to be explored. The function annotation of the genome sequence of Spirochaeta cellobiosiphila is in progress. In this work we aim to map all the metabolic activities for reconstruction of genome-scale metabolic model of Spirochaeta cellobiosiphila.

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

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

2016-06-01

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

The architecture of ArgR-DNA complexes at the genome-scale in Escherichia coli

DEFF Research Database (Denmark)

Cho, Suhyung; Cho, Yoo-Bok; Kang, Taek Jin

2015-01-01

DNA-binding motifs that are recognized by transcription factors (TFs) have been well studied; however, challenges remain in determining the in vivo architecture of TF-DNA complexes on a genome-scale. Here, we determined the in vivo architecture of Escherichia coli arginine repressor (ArgR)-DNA co...

Genome-scale portrait and evolutionary significance of human-specific core promoter tri- and tetranucleotide short tandem repeats.

Science.gov (United States)

Nazaripanah, N; Adelirad, F; Delbari, A; Sahaf, R; Abbasi-Asl, T; Ohadi, M

2018-04-05

While there is an ongoing trend to identify single nucleotide substitutions (SNSs) that are linked to inter/intra-species differences and disease phenotypes, short tandem repeats (STRs)/microsatellites may be of equal (if not more) importance in the above processes. Genes that contain STRs in their promoters have higher expression divergence compared to genes with fixed or no STRs in the gene promoters. In line with the above, recent reports indicate a role of repetitive sequences in the rise of young transcription start sites (TSSs) in human evolution. Following a comparative genomics study of all human protein-coding genes annotated in the GeneCards database, here we provide a genome-scale portrait of human-specific short- and medium-size (≥ 3-repeats) tri- and tetranucleotide STRs and STR motifs in the critical core promoter region between - 120 and + 1 to the TSS and evidence of skewing of this compartment in reference to the STRs that are not human-specific (Levene's test p human-specific transcripts was detected in the tri and tetra human-specific compartments (mid-p genome-scale skewing of STRs at a specific region of the human genome and a link between a number of these STRs and TSS selection/transcript specificity. The STRs and genes listed here may have a role in the evolution and development of characteristics and phenotypes that are unique to the human species.

Contribution of FKBP5 genetic variation to gemcitabine treatment and survival in pancreatic adenocarcinoma.

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Katarzyna A Ellsworth

Full Text Available FKBP51, (FKBP5, is a negative regulator of Akt. Variability in FKBP5 expression level is a major factor contributing to variation in response to chemotherapeutic agents including gemcitabine, a first line treatment for pancreatic cancer. Genetic variation in FKBP5 could influence its function and, ultimately, treatment response of pancreatic cancer.We set out to comprehensively study the role of genetic variation in FKBP5 identified by Next Generation DNA resequencing on response to gemcitabine treatment of pancreatic cancer by utilizing both tumor and germline DNA samples from 43 pancreatic cancer patients, including 19 paired normal-tumor samples. Next, genotype-phenotype association studies were performed with overall survival as well as with FKBP5 gene expression in tumor using the same samples in which resequencing had been performed, followed by functional genomics studies.In-depth resequencing identified 404 FKBP5 single nucleotide polymorphisms (SNPs in normal and tumor DNA. SNPs with the strongest associations with survival or FKBP5 expression were subjected to functional genomic study. Electromobility shift assay showed that the rs73748206 "A(T" SNP altered DNA-protein binding patterns, consistent with significantly increased reporter gene activity, possibly through its increased binding to Glucocorticoid Receptor (GR. The effect of rs73748206 was confirmed on the basis of its association with FKBP5 expression by affecting the binding to GR in lymphoblastoid cell lines derived from the same patients for whom DNA was used for resequencing.This comprehensive FKBP5 resequencing study provides insights into the role of genetic variation in variation of gemcitabine response.

Genome-scale metabolic analysis of Clostridium thermocellum for bioethanol production

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Brooks J Paul

2010-03-01

Full Text Available Abstract Background Microorganisms possess diverse metabolic capabilities that can potentially be leveraged for efficient production of biofuels. Clostridium thermocellum (ATCC 27405 is a thermophilic anaerobe that is both cellulolytic and ethanologenic, meaning that it can directly use the plant sugar, cellulose, and biochemically convert it to ethanol. A major challenge in using microorganisms for chemical production is the need to modify the organism to increase production efficiency. The process of properly engineering an organism is typically arduous. Results Here we present a genome-scale model of C. thermocellum metabolism, iSR432, for the purpose of establishing a computational tool to study the metabolic network of C. thermocellum and facilitate efforts to engineer C. thermocellum for biofuel production. The model consists of 577 reactions involving 525 intracellular metabolites, 432 genes, and a proteomic-based representation of a cellulosome. The process of constructing this metabolic model led to suggested annotation refinements for 27 genes and identification of areas of metabolism requiring further study. The accuracy of the iSR432 model was tested using experimental growth and by-product secretion data for growth on cellobiose and fructose. Analysis using this model captures the relationship between the reduction-oxidation state of the cell and ethanol secretion and allowed for prediction of gene deletions and environmental conditions that would increase ethanol production. Conclusions By incorporating genomic sequence data, network topology, and experimental measurements of enzyme activities and metabolite fluxes, we have generated a model that is reasonably accurate at predicting the cellular phenotype of C. thermocellum and establish a strong foundation for rational strain design. In addition, we are able to draw some important conclusions regarding the underlying metabolic mechanisms for observed behaviors of C. thermocellum

Analysis of Aspergillus nidulans metabolism at the genome-scale

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David, Helga; Ozcelik, İlknur Ş; Hofmann, Gerald

2008-01-01

of relevant secondary metabolites, was reconstructed based on detailed metabolic reconstructions available for A. niger and Saccharomyces cerevisiae, and information on the genetics, biochemistry and physiology of A. nidulans. Thereby, it was possible to identify metabolic functions without a gene associated...... a function. Results: In this work, we have manually assigned functions to 472 orphan genes in the metabolism of A. nidulans, by using a pathway-driven approach and by employing comparative genomics tools based on sequence similarity. The central metabolism of A. nidulans, as well as biosynthetic pathways......, in an objective and systematic manner. The functional assignments served as a basis to develop a mathematical model, linking 666 genes (both previously and newly annotated) to metabolic roles. The model was used to simulate metabolic behavior and additionally to integrate, analyze and interpret large-scale gene...

Development and validation of an rDNA operon based primer walking strategy applicable to de novo bacterial genome finishing.

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Alexander William Eastman

2015-01-01

Full Text Available Advances in sequencing technology have drastically increased the depth and feasibility of bacterial genome sequencing. However, little information is available that details the specific techniques and procedures employed during genome sequencing despite the large numbers of published genomes. Shotgun approaches employed by second-generation sequencing platforms has necessitated the development of robust bioinformatics tools for in silico assembly, and complete assembly is limited by the presence of repetitive DNA sequences and multi-copy operons. Typically, re-sequencing with multiple platforms and laborious, targeted Sanger sequencing are employed to finish a draft bacterial genome. Here we describe a novel strategy based on the identification and targeted sequencing of repetitive rDNA operons to expedite bacterial genome assembly and finishing. Our strategy was validated by finishing the genome of Paenibacillus polymyxa strain CR1, a bacterium with potential in sustainable agriculture and bio-based processes. An analysis of the 38 contigs contained in the P. polymyxa strain CR1 draft genome revealed 12 repetitive rDNA operons with varied intragenic and flanking regions of variable length, unanimously located at contig boundaries and within contig gaps. These highly similar but not identical rDNA operons were experimentally verified and sequenced simultaneously with multiple, specially designed primer sets. This approach also identified and corrected significant sequence rearrangement generated during the initial in silico assembly of sequencing reads. Our approach reduces the required effort associated with blind primer walking for contig assembly, increasing both the speed and feasibility of genome finishing. Our study further reinforces the notion that repetitive DNA elements are major limiting factors for genome finishing. Moreover, we provided a step-by-step workflow for genome finishing, which may guide future bacterial genome finishing

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

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Sheina B. Sim

2017-06-01

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

Molecular mapping and genomics of soybean seed protein: a review and perspective for the future.

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Patil, Gunvant; Mian, Rouf; Vuong, Tri; Pantalone, Vince; Song, Qijian; Chen, Pengyin; Shannon, Grover J; Carter, Tommy C; Nguyen, Henry T

2017-10-01

Genetic improvement of soybean protein meal is a complex process because of negative correlation with oil, yield, and temperature. This review describes the progress in mapping and genomics, identifies knowledge gaps, and highlights the need of integrated approaches. Meal protein derived from soybean [Glycine max (L) Merr.] seed is the primary source of protein in poultry and livestock feed. Protein is a key factor that determines the nutritional and economical value of soybean. Genetic improvement of soybean seed protein content is highly desirable, and major quantitative trait loci (QTL) for soybean protein have been detected and repeatedly mapped on chromosomes (Chr.) 20 (LG-I), and 15 (LG-E). However, practical breeding progress is challenging because of seed protein content's negative genetic correlation with seed yield, other seed components such as oil and sucrose, and interaction with environmental effects such as temperature during seed development. In this review, we discuss rate-limiting factors related to soybean protein content and nutritional quality, and potential control factors regulating seed storage protein. In addition, we describe advances in next-generation sequencing technologies for precise detection of natural variants and their integration with conventional and high-throughput genotyping technologies. A syntenic analysis of QTL on Chr. 15 and 20 was performed. Finally, we discuss comprehensive approaches for integrating protein and amino acid QTL, genome-wide association studies, whole-genome resequencing, and transcriptome data to accelerate identification of genomic hot spots for allele introgression and soybean meal protein improvement.

Draft Sequencing of the Heterozygous Diploid Genome of Satsuma (Citrus unshiu Marc. Using a Hybrid Assembly Approach

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Tokurou Shimizu

2017-12-01

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.

Genome-scale metabolic model of the fission yeast Schizosaccharomyces pombe and the reconciliation of in silico/in vivo mutant growth

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2012-01-01

Background Over the last decade, the genome-scale metabolic models have been playing increasingly important roles in elucidating metabolic characteristics of biological systems for a wide range of applications including, but not limited to, system-wide identification of drug targets and production of high value biochemical compounds. However, these genome-scale metabolic models must be able to first predict known in vivo phenotypes before it is applied towards these applications with high confidence. One benchmark for measuring the in silico capability in predicting in vivo phenotypes is the use of single-gene mutant libraries to measure the accuracy of knockout simulations in predicting mutant growth phenotypes. Results Here we employed a systematic and iterative process, designated as Reconciling In silico/in vivo mutaNt Growth (RING), to settle discrepancies between in silico prediction and in vivo observations to a newly reconstructed genome-scale metabolic model of the fission yeast, Schizosaccharomyces pombe, SpoMBEL1693. The predictive capabilities of the genome-scale metabolic model in predicting single-gene mutant growth phenotypes were measured against the single-gene mutant library of S. pombe. The use of RING resulted in improving the overall predictive capability of SpoMBEL1693 by 21.5%, from 61.2% to 82.7% (92.5% of the negative predictions matched the observed growth phenotype and 79.7% the positive predictions matched the observed growth phenotype). Conclusion This study presents validation and refinement of a newly reconstructed metabolic model of the yeast S. pombe, through improving the metabolic model’s predictive capabilities by reconciling the in silico predicted growth phenotypes of single-gene knockout mutants, with experimental in vivo growth data. PMID:22631437

Short-term genome evolution of Listeria monocytogenes in a non-controlled environment

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Ivy Reid A

2008-11-01

Full Text Available Abstract Background While increasing data on bacterial evolution in controlled environments are available, our understanding of bacterial genome evolution in natural environments is limited. We thus performed full genome analyses on four Listeria monocytogenes, including human and food isolates from both a 1988 case of sporadic listeriosis and a 2000 listeriosis outbreak, which had been linked to contaminated food from a single processing facility. All four isolates had been shown to have identical subtypes, suggesting that a specific L. monocytogenes strain persisted in this processing plant over at least 12 years. While a genome sequence for the 1988 food isolate has been reported, we sequenced the genomes of the 1988 human isolate as well as a human and a food isolate from the 2000 outbreak to allow for comparative genome analyses. Results The two L. monocytogenes isolates from 1988 and the two isolates from 2000 had highly similar genome backbone sequences with very few single nucleotide (nt polymorphisms (1 – 8 SNPs/isolate; confirmed by re-sequencing. While no genome rearrangements were identified in the backbone genome of the four isolates, a 42 kb prophage inserted in the chromosomal comK gene showed evidence for major genome rearrangements. The human-food isolate pair from each 1988 and 2000 had identical prophage sequence; however, there were significant differences in the prophage sequences between the 1988 and 2000 isolates. Diversification of this prophage appears to have been caused by multiple homologous recombination events or possibly prophage replacement. In addition, only the 2000 human isolate contained a plasmid, suggesting plasmid loss or acquisition events. Surprisingly, besides the polymorphisms found in the comK prophage, a single SNP in the tRNA Thr-4 prophage represents the only SNP that differentiates the 1988 isolates from the 2000 isolates. Conclusion Our data support the hypothesis that the 2000 human listeriosis

Identifying all moiety conservation laws in genome-scale metabolic networks.

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De Martino, Andrea; De Martino, Daniele; Mulet, Roberto; Pagnani, Andrea

2014-01-01

The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell's metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative integer solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation.

Identifying all moiety conservation laws in genome-scale metabolic networks.

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Andrea De Martino

Full Text Available The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell's metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative integer solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation.

Genome-scale metabolic network validation of Shewanella oneidensis using transposon insertion frequency analysis.

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Hong Yang

2014-09-01

Full Text Available Transposon mutagenesis, in combination with parallel sequencing, is becoming a powerful tool for en-masse mutant analysis. A probability generating function was used to explain observed miniHimar transposon insertion patterns, and gene essentiality calls were made by transposon insertion frequency analysis (TIFA. TIFA incorporated the observed genome and sequence motif bias of the miniHimar transposon. The gene essentiality calls were compared to: 1 previous genome-wide direct gene-essentiality assignments; and, 2 flux balance analysis (FBA predictions from an existing genome-scale metabolic model of Shewanella oneidensis MR-1. A three-way comparison between FBA, TIFA, and the direct essentiality calls was made to validate the TIFA approach. The refinement in the interpretation of observed transposon insertions demonstrated that genes without insertions are not necessarily essential, and that genes that contain insertions are not always nonessential. The TIFA calls were in reasonable agreement with direct essentiality calls for S. oneidensis, but agreed more closely with E. coli essentiality calls for orthologs. The TIFA gene essentiality calls were in good agreement with the MR-1 FBA essentiality predictions, and the agreement between TIFA and FBA predictions was substantially better than between the FBA and the direct gene essentiality predictions.

Comprehensive Mapping of Pluripotent Stem Cell Metabolism Using Dynamic Genome-Scale Network Modeling

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Sriram Chandrasekaran

2017-12-01

Full Text Available Summary: Metabolism is an emerging stem cell hallmark tied to cell fate, pluripotency, and self-renewal, yet systems-level understanding of stem cell metabolism has been limited by the lack of genome-scale network models. Here, we develop a systems approach to integrate time-course metabolomics data with a computational model of metabolism to analyze the metabolic state of naive and primed murine pluripotent stem cells. Using this approach, we find that one-carbon metabolism involving phosphoglycerate dehydrogenase, folate synthesis, and nucleotide synthesis is a key pathway that differs between the two states, resulting in differential sensitivity to anti-folates. The model also predicts that the pluripotency factor Lin28 regulates this one-carbon metabolic pathway, which we validate using metabolomics data from Lin28-deficient cells. Moreover, we identify and validate metabolic reactions related to S-adenosyl-methionine production that can differentially impact histone methylation in naive and primed cells. Our network-based approach provides a framework for characterizing metabolic changes influencing pluripotency and cell fate. : Chandrasekaran et al. use computational modeling, metabolomics, and metabolic inhibitors to discover metabolic differences between various pluripotent stem cell states and infer their impact on stem cell fate decisions. Keywords: systems biology, stem cell biology, metabolism, genome-scale modeling, pluripotency, histone methylation, naive (ground state, primed state, cell fate, metabolic network

The genome sequence of Barbarea vulgaris facilitates the study of ecological biochemistry

DEFF Research Database (Denmark)

Byrne, Stephen L.; Erthmann, Pernille Østerbye; Agerbirk, Niels

2017-01-01

The genus Barbarea has emerged as a model for evolution and ecology of plant defense compounds, due to its unusual glucosinolate profile and production of saponins, unique to the Brassicaceae. One species, B. vulgaris, includes two ‘types’, G-type and P-type that differ in trichome density......, and their glucosinolate and saponin profiles. A key difference is the stereochemistry of hydroxylation of their common phenethylglucosinolate backbone, leading to epimeric glucobarbarins. Here we report a draft genome sequence of the G-type, and re-sequencing of the P-type for comparison. This enables us to identify...... candidate genes underlying glucosinolate diversity, trichome density, and study the genetics of biochemical variation for glucosinolate and saponins. B. vulgaris is resistant to the diamondback moth, and may be exploited for “dead-end” trap cropping where glucosinolates stimulate oviposition and saponins...

Pigs in sequence space: A 0.66X coverage pig genome survey based on shotgun sequencing

Directory of Open Access Journals (Sweden)

Li Wei

2005-05-01

Full Text Available Abstract Background Comparative whole genome analysis of Mammalia can benefit from the addition of more species. The pig is an obvious choice due to its economic and medical importance as well as its evolutionary position in the artiodactyls. Results We have generated ~3.84 million shotgun sequences (0.66X coverage from the pig genome. The data are hereby released (NCBI Trace repository with center name "SDJVP", and project name "Sino-Danish Pig Genome Project" together with an initial evolutionary analysis. The non-repetitive fraction of the sequences was aligned to the UCSC human-mouse alignment and the resulting three-species alignments were annotated using the human genome annotation. Ultra-conserved elements and miRNAs were identified. The results show that for each of these types of orthologous data, pig is much closer to human than mouse is. Purifying selection has been more efficient in pig compared to human, but not as efficient as in mouse, and pig seems to have an isochore structure most similar to the structure in human. Conclusion The addition of the pig to the set of species sequenced at low coverage adds to the understanding of selective pressures that have acted on the human genome by bisecting the evolutionary branch between human and mouse with the mouse branch being approximately 3 times as long as the human branch. Additionally, the joint alignment of the shot-gun sequences to the human-mouse alignment offers the investigator a rapid way to defining specific regions for analysis and resequencing.

Genomic Prediction of Sunflower Hybrids Oil Content

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Brigitte Mangin

2017-09-01

Full Text Available Prediction of hybrid performance using incomplete factorial mating designs is widely used in breeding programs including different heterotic groups. Based on the general combining ability (GCA of the parents, predictions are accurate only if the genetic variance resulting from the specific combining ability is small and both parents have phenotyped descendants. Genomic selection (GS can predict performance using a model trained on both phenotyped and genotyped hybrids that do not necessarily include all hybrid parents. Therefore, GS could overcome the issue of unknown parent GCA. Here, we compared the accuracy of classical GCA-based and genomic predictions for oil content of sunflower seeds using several GS models. Our study involved 452 sunflower hybrids from an incomplete factorial design of 36 female and 36 male lines. Re-sequencing of parental lines allowed to identify 468,194 non-redundant SNPs and to infer the hybrid genotypes. Oil content was observed in a multi-environment trial (MET over 3 years, leading to nine different environments. We compared GCA-based model to different GS models including female and male genomic kinships with the addition of the female-by-male interaction genomic kinship, the use of functional knowledge as SNPs in genes of oil metabolic pathways, and with epistasis modeling. When both parents have descendants in the training set, the predictive ability was high even for GCA-based prediction, with an average MET value of 0.782. GS performed slightly better (+0.2%. Neither the inclusion of the female-by-male interaction, nor functional knowledge of oil metabolism, nor epistasis modeling improved the GS accuracy. GS greatly improved predictive ability when one or both parents were untested in the training set, increasing GCA-based predictive ability by 10.4% from 0.575 to 0.635 in the MET. In this scenario, performing GS only considering SNPs in oil metabolic pathways did not improve whole genome GS prediction but

Natural selection affects multiple aspects of genetic variation at putatively neutral sites across the human genome.

Science.gov (United States)

Lohmueller, Kirk E; Albrechtsen, Anders; Li, Yingrui; Kim, Su Yeon; Korneliussen, Thorfinn; Vinckenbosch, Nicolas; Tian, Geng; Huerta-Sanchez, Emilia; Feder, Alison F; Grarup, Niels; Jørgensen, Torben; Jiang, Tao; Witte, Daniel R; Sandbæk, Annelli; Hellmann, Ines; Lauritzen, Torsten; Hansen, Torben; Pedersen, Oluf; Wang, Jun; Nielsen, Rasmus

2011-10-01

A major question in evolutionary biology is how natural selection has shaped patterns of genetic variation across the human genome. Previous work has documented a reduction in genetic diversity in regions of the genome with low recombination rates. However, it is unclear whether other summaries of genetic variation, like allele frequencies, are also correlated with recombination rate and whether these correlations can be explained solely by negative selection against deleterious mutations or whether positive selection acting on favorable alleles is also required. Here we attempt to address these questions by analyzing three different genome-wide resequencing datasets from European individuals. We document several significant correlations between different genomic features. In particular, we find that average minor allele frequency and diversity are reduced in regions of low recombination and that human diversity, human-chimp divergence, and average minor allele frequency are reduced near genes. Population genetic simulations show that either positive natural selection acting on favorable mutations or negative natural selection acting against deleterious mutations can explain these correlations. However, models with strong positive selection on nonsynonymous mutations and little negative selection predict a stronger negative correlation between neutral diversity and nonsynonymous divergence than observed in the actual data, supporting the importance of negative, rather than positive, selection throughout the genome. Further, we show that the widespread presence of weakly deleterious alleles, rather than a small number of strongly positively selected mutations, is responsible for the correlation between neutral genetic diversity and recombination rate. This work suggests that natural selection has affected multiple aspects of linked neutral variation throughout the human genome and that positive selection is not required to explain these observations.

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

Science.gov (United States)

2016-03-15

RESEARCH ARTICLE Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism Francisco G...jaques.reifman.civ@mail.mil Abstract A hallmark of Pseudomonas aeruginosa is its ability to establish biofilm -based infections that are difficult to...eradicate. Biofilms are less susceptible to host inflammatory and immune responses and have higher antibiotic tolerance than free-living planktonic

Quantitative Assessment of Thermodynamic Constraints on the Solution Space of Genome-Scale Metabolic Models

Science.gov (United States)

Hamilton, Joshua J.; Dwivedi, Vivek; Reed, Jennifer L.

2013-01-01

Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. PMID:23870272

Targeted and genome-scale methylomics reveals gene body signatures in human cell lines

Science.gov (United States)

Ball, Madeleine Price; Li, Jin Billy; Gao, Yuan; Lee, Je-Hyuk; LeProust, Emily; Park, In-Hyun; Xie, Bin; Daley, George Q.; Church, George M.

2012-01-01

Cytosine methylation, an epigenetic modification of DNA, is a target of growing interest for developing high throughput profiling technologies. Here we introduce two new, complementary techniques for cytosine methylation profiling utilizing next generation sequencing technology: bisulfite padlock probes (BSPPs) and methyl sensitive cut counting (MSCC). In the first method, we designed a set of ~10,000 BSPPs distributed over the ENCODE pilot project regions to take advantage of existing expression and chromatin immunoprecipitation data. We observed a pattern of low promoter methylation coupled with high gene body methylation in highly expressed genes. Using the second method, MSCC, we gathered genome-scale data for 1.4 million HpaII sites and confirmed that gene body methylation in highly expressed genes is a consistent phenomenon over the entire genome. Our observations highlight the usefulness of techniques which are not inherently or intentionally biased in favor of only profiling particular subsets like CpG islands or promoter regions. PMID:19329998

Whole-genome in-silico subtractive hybridization (WISH - using massive sequencing for the identification of unique and repetitive sex-specific sequences: the example of Schistosoma mansoni

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Parrinello Hugues

2010-06-01

Full Text Available Abstract Background Emerging methods of massive sequencing that allow for rapid re-sequencing of entire genomes at comparably low cost are changing the way biological questions are addressed in many domains. Here we propose a novel method to compare two genomes (genome-to-genome comparison. We used this method to identify sex-specific sequences of the human blood fluke Schistosoma mansoni. Results Genomic DNA was extracted from male and female (heterogametic S. mansoni adults and sequenced with a Genome Analyzer (Illumina. Sequences are available at the NCBI sequence read archive http://www.ncbi.nlm.nih.gov/Traces/sra/ under study accession number SRA012151.6. Sequencing reads were aligned to the genome, and a pseudogenome composed of known repeats. Straightforward comparative bioinformatics analysis was performed to compare male and female schistosome genomes and identify female-specific sequences. We found that the S. mansoni female W chromosome contains only few specific unique sequences (950 Kb i.e. about 0.2% of the genome. The majority of W-specific sequences are repeats (10.5 Mb i.e. about 2.5% of the genome. Arbitrarily selected W-specific sequences were confirmed by PCR. Primers designed for unique and repetitive sequences allowed to reliably identify the sex of both larval and adult stages of the parasite. Conclusion Our genome-to-genome comparison method that we call "whole-genome in-silico subtractive hybridization" (WISH allows for rapid identification of sequences that are specific for a certain genotype (e.g. the heterogametic sex. It can in principle be used for the detection of any sequence differences between isolates (e.g. strains, pathovars or even closely related species.

In silico analysis of human metabolism: Reconstruction, contextualization and application of genome-scale models

DEFF Research Database (Denmark)

Geng, Jun; Nielsen, Jens

2017-01-01

The arising prevalence of metabolic diseases calls for a holistic approach for analysis of the underlying nature of abnormalities in cellular functions. Through mathematic representation and topological analysis of cellular metabolism, GEnome scale metabolic Models (GEMs) provide a promising fram...... that correctly describe interactions between cells or tissues, and we therefore discuss how GEMs can be integrated with blood circulation models. Finally, we end the review with proposing some possible future research directions....

Reconstruction of genome-scale human metabolic models using omics data

DEFF Research Database (Denmark)

Ryu, Jae Yong; Kim, Hyun Uk; Lee, Sang Yup

2015-01-01

used to describe metabolic phenotypes of healthy and diseased human tissues and cells, and to predict therapeutic targets. Here we review recent trends in genome-scale human metabolic modeling, including various generic and tissue/cell type-specific human metabolic models developed to date, and methods......, databases and platforms used to construct them. For generic human metabolic models, we pay attention to Recon 2 and HMR 2.0 with emphasis on data sources used to construct them. Draft and high-quality tissue/cell type-specific human metabolic models have been generated using these generic human metabolic...... refined through gap filling, reaction directionality assignment and the subcellular localization of metabolic reactions. We review relevant tools for this model refinement procedure as well. Finally, we suggest the direction of further studies on reconstructing an improved human metabolic model....

Large-scale parallel genome assembler over cloud computing environment.

Science.gov (United States)

Das, Arghya Kusum; Koppa, Praveen Kumar; Goswami, Sayan; Platania, Richard; Park, Seung-Jong

2017-06-01

The size of high throughput DNA sequencing data has already reached the terabyte scale. To manage this huge volume of data, many downstream sequencing applications started using locality-based computing over different cloud infrastructures to take advantage of elastic (pay as you go) resources at a lower cost. However, the locality-based programming model (e.g. MapReduce) is relatively new. Consequently, developing scalable data-intensive bioinformatics applications using this model and understanding the hardware environment that these applications require for good performance, both require further research. In this paper, we present a de Bruijn graph oriented Parallel Giraph-based Genome Assembler (GiGA), as well as the hardware platform required for its optimal performance. GiGA uses the power of Hadoop (MapReduce) and Giraph (large-scale graph analysis) to achieve high scalability over hundreds of compute nodes by collocating the computation and data. GiGA achieves significantly higher scalability with competitive assembly quality compared to contemporary parallel assemblers (e.g. ABySS and Contrail) over traditional HPC cluster. Moreover, we show that the performance of GiGA is significantly improved by using an SSD-based private cloud infrastructure over traditional HPC cluster. We observe that the performance of GiGA on 256 cores of this SSD-based cloud infrastructure closely matches that of 512 cores of traditional HPC cluster.

The RAVEN Toolbox and Its Use for Generating a Genome-scale Metabolic Model for Penicillium chrysogenum

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Agren, Rasmus; Liu, Liming; Shoaie, Saeed; Vongsangnak, Wanwipa; Nookaew, Intawat; Nielsen, Jens

2013-01-01

We present the RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox: a software suite that allows for semi-automated reconstruction of genome-scale models. It makes use of published models and/or the KEGG database, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology. The RAVEN Toolbox workflow was applied in order to reconstruct a genome-scale metabolic model for the important microbial cell factory Penicillium chrysogenum Wisconsin54-1255. The model was validated in a bibliomic study of in total 440 references, and it comprises 1471 unique biochemical reactions and 1006 ORFs. It was then used to study the roles of ATP and NADPH in the biosynthesis of penicillin, and to identify potential metabolic engineering targets for maximization of penicillin production. PMID:23555215

SNPdetector: a software tool for sensitive and accurate SNP detection.

Directory of Open Access Journals (Sweden)

Jinghui Zhang

2005-10-01

Full Text Available Identification of single nucleotide polymorphisms (SNPs and mutations is important for the discovery of genetic predisposition to complex diseases. PCR resequencing is the method of choice for de novo SNP discovery. However, manual curation of putative SNPs has been a major bottleneck in the application of this method to high-throughput screening. Therefore it is critical to develop a more sensitive and accurate computational method for automated SNP detection. We developed a software tool, SNPdetector, for automated identification of SNPs and mutations in fluorescence-based resequencing reads. SNPdetector was designed to model the process of human visual inspection and has a very low false positive and false negative rate. We demonstrate the superior performance of SNPdetector in SNP and mutation analysis by comparing its results with those derived by human inspection, PolyPhred (a popular SNP detection tool, and independent genotype assays in three large-scale investigations. The first study identified and validated inter- and intra-subspecies variations in 4,650 traces of 25 inbred mouse strains that belong to either the Mus musculus species or the M. spretus species. Unexpected heterozygosity in CAST/Ei strain was observed in two out of 1,167 mouse SNPs. The second study identified 11,241 candidate SNPs in five ENCODE regions of the human genome covering 2.5 Mb of genomic sequence. Approximately 50% of the candidate SNPs were selected for experimental genotyping; the validation rate exceeded 95%. The third study detected ENU-induced mutations (at 0.04% allele frequency in 64,896 traces of 1,236 zebra fish. Our analysis of three large and diverse test datasets demonstrated that SNPdetector is an effective tool for genome-scale research and for large-sample clinical studies. SNPdetector runs on Unix/Linux platform and is available publicly (http://lpg.nci.nih.gov.

Use of an uncertainty analysis for genome-scale models as a prediction tool for microbial growth processes in subsurface environments.

Science.gov (United States)

Klier, Christine

2012-03-06

The integration of genome-scale, constraint-based models of microbial cell function into simulations of contaminant transport and fate in complex groundwater systems is a promising approach to help characterize the metabolic activities of microorganisms in natural environments. In constraint-based modeling, the specific uptake flux rates of external metabolites are usually determined by Michaelis-Menten kinetic theory. However, extensive data sets based on experimentally measured values are not always available. In this study, a genome-scale model of Pseudomonas putida was used to study the key issue of uncertainty arising from the parametrization of the influx of two growth-limiting substrates: oxygen and toluene. The results showed that simulated growth rates are highly sensitive to substrate affinity constants and that uncertainties in specific substrate uptake rates have a significant influence on the variability of simulated microbial growth. Michaelis-Menten kinetic theory does not, therefore, seem to be appropriate for descriptions of substrate uptake processes in the genome-scale model of P. putida. Microbial growth rates of P. putida in subsurface environments can only be accurately predicted if the processes of complex substrate transport and microbial uptake regulation are sufficiently understood in natural environments and if data-driven uptake flux constraints can be applied.

LipidSeq: a next-generation clinical resequencing panel for monogenic dyslipidemias[S

Science.gov (United States)

Johansen, Christopher T.; Dubé, Joseph B.; Loyzer, Melissa N.; MacDonald, Austin; Carter, David E.; McIntyre, Adam D.; Cao, Henian; Wang, Jian; Robinson, John F.; Hegele, Robert A.

2014-01-01

We report the design of a targeted resequencing panel for monogenic dyslipidemias, LipidSeq, for the purpose of replacing Sanger sequencing in the clinical detection of dyslipidemia-causing variants. We also evaluate the performance of the LipidSeq approach versus Sanger sequencing in 84 patients with a range of phenotypes including extreme blood lipid concentrations as well as additional dyslipidemias and related metabolic disorders. The panel performs well, with high concordance (95.2%) in samples with known mutations based on Sanger sequencing and a high detection rate (57.9%) of mutations likely to be causative for disease in samples not previously sequenced. Clinical implementation of LipidSeq has the potential to aid in the molecular diagnosis of patients with monogenic dyslipidemias with a high degree of speed and accuracy and at lower cost than either Sanger sequencing or whole exome sequencing. Furthermore, LipidSeq will help to provide a more focused picture of monogenic and polygenic contributors that underlie dyslipidemia while excluding the discovery of incidental pathogenic clinically actionable variants in nonmetabolism-related genes, such as oncogenes, that would otherwise be identified by a whole exome approach, thus minimizing potential ethical issues. PMID:24503134

Variation in Linked Selection and Recombination Drive Genomic Divergence during Allopatric Speciation of European and American Aspens.

Science.gov (United States)

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

2016-07-01

Despite the global economic and ecological importance of forest trees, the genomic basis of differential adaptation and speciation in tree species is still poorly understood. Populus tremula and Populus tremuloides are two of the most widespread tree species in the Northern Hemisphere. Using whole-genome re-sequencing data of 24 P. tremula and 22 P. tremuloides individuals, we find that the two species diverged ∼2.2-3.1 million years ago, coinciding with the severing of the Bering land bridge and the onset of dramatic climatic oscillations during the Pleistocene. Both species have experienced substantial population expansions following long-term declines after species divergence. We detect widespread and heterogeneous genomic differentiation between species, and in accordance with the expectation of allopatric speciation, coalescent simulations suggest that neutral evolutionary processes can account for most of the observed patterns of genetic differentiation. However, there is an excess of regions exhibiting extreme differentiation relative to those expected under demographic simulations, which is indicative of the action of natural selection. Overall genetic differentiation is negatively associated with recombination rate in both species, providing strong support for a role of linked selection in generating the heterogeneous genomic landscape of differentiation between species. Finally, we identify a number of candidate regions and genes that may have been subject to positive and/or balancing selection during the speciation process. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Exploring Networks at the genome scale

NARCIS (Netherlands)

Lam, M.C.; Puchalka, J.; Diez, M.S.; Martins Dos Santos, V.A.P.

2010-01-01

Systems biology is aimed at achieving a holistic understanding of living organisms, while synthetic biology seeks to design and construct new living organisms with targeted functionalities. Genome sequencing and the fields of ‘omics’ technology have proven a goldmine of information for scientists

Mapping copy number variation by population-scale genome sequencing

DEFF Research Database (Denmark)

Mills, Ryan E.; Walter, Klaudia; Stewart, Chip

2011-01-01

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...

[Genome editing of industrial microorganism].

Science.gov (United States)

Zhu, Linjiang; Li, Qi

2015-03-01

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

Genome-scale reconstruction of the metabolic network in Yersinia pestis, strain 91001

Energy Technology Data Exchange (ETDEWEB)

Navid, A; Almaas, E

2009-01-13

The gram-negative bacterium Yersinia pestis, the aetiological agent of bubonic plague, is one the deadliest pathogens known to man. Despite its historical reputation, plague is a modern disease which annually afflicts thousands of people. Public safety considerations greatly limit clinical experimentation on this organism and thus development of theoretical tools to analyze the capabilities of this pathogen is of utmost importance. Here, we report the first genome-scale metabolic model of Yersinia pestis biovar Mediaevalis based both on its recently annotated genome, and physiological and biochemical data from literature. Our model demonstrates excellent agreement with Y. pestis known metabolic needs and capabilities. Since Y. pestis is a meiotrophic organism, we have developed CryptFind, a systematic approach to identify all candidate cryptic genes responsible for known and theoretical meiotrophic phenomena. In addition to uncovering every known cryptic gene for Y. pestis, our analysis of the rhamnose fermentation pathway suggests that betB is the responsible cryptic gene. Despite all of our medical advances, we still do not have a vaccine for bubonic plague. Recent discoveries of antibiotic resistant strains of Yersinia pestis coupled with the threat of plague being used as a bioterrorism weapon compel us to develop new tools for studying the physiology of this deadly pathogen. Using our theoretical model, we can study the cell's phenotypic behavior under different circumstances and identify metabolic weaknesses which may be harnessed for the development of therapeutics. Additionally, the automatic identification of cryptic genes expands the usage of genomic data for pharmaceutical purposes.

Microarray analysis of serum mRNA in patients with head and neck squamous cell carcinoma at whole-genome scale

Czech Academy of Sciences Publication Activity Database

Čapková, M.; Šáchová, Jana; Strnad, Hynek; Kolář, Michal; Hroudová, Miluše; Chovanec, M.; Čada, Z.; Štefl, M.; Valach, J.; Kastner, J.; Smetana, K. Jr.; Plzák, J.

-, April 23 (2014) ISSN 2314-6141 R&D Projects: GA MZd(CZ) NT13488 Institutional support: RVO:68378050 Keywords : Microarray Analysis * Head and Neck Squamous Cell Carcinoma * whole-genome scale Subject RIV: EB - Genetics ; Molecular Biology

Data partitioning enables the use of standard SOAP Web Services in genome-scale workflows.

Science.gov (United States)

Sztromwasser, Pawel; Puntervoll, Pål; Petersen, Kjell

2011-07-26

Biological databases and computational biology tools are provided by research groups around the world, and made accessible on the Web. Combining these resources is a common practice in bioinformatics, but integration of heterogeneous and often distributed tools and datasets can be challenging. To date, this challenge has been commonly addressed in a pragmatic way, by tedious and error-prone scripting. Recently however a more reliable technique has been identified and proposed as the platform that would tie together bioinformatics resources, namely Web Services. In the last decade the Web Services have spread wide in bioinformatics, and earned the title of recommended technology. However, in the era of high-throughput experimentation, a major concern regarding Web Services is their ability to handle large-scale data traffic. We propose a stream-like communication pattern for standard SOAP Web Services, that enables efficient flow of large data traffic between a workflow orchestrator and Web Services. We evaluated the data-partitioning strategy by comparing it with typical communication patterns on an example pipeline for genomic sequence annotation. The results show that data-partitioning lowers resource demands of services and increases their throughput, which in consequence allows to execute in-silico experiments on genome-scale, using standard SOAP Web Services and workflows. As a proof-of-principle we annotated an RNA-seq dataset using a plain BPEL workflow engine.

Data partitioning enables the use of standard SOAP Web Services in genome-scale workflows

Directory of Open Access Journals (Sweden)

Sztromwasser Paweł

2011-06-01

Full Text Available Biological databases and computational biology tools are provided by research groups around the world, and made accessible on the Web. Combining these resources is a common practice in bioinformatics, but integration of heterogeneous and often distributed tools and datasets can be challenging. To date, this challenge has been commonly addressed in a pragmatic way, by tedious and error-prone scripting. Recently however a more reliable technique has been identified and proposed as the platform that would tie together bioinformatics resources, namely Web Services. In the last decade the Web Services have spread wide in bioinformatics, and earned the title of recommended technology. However, in the era of high-throughput experimentation, a major concern regarding Web Services is their ability to handle large-scale data traffic. We propose a stream-like communication pattern for standard SOAP Web Services, that enables efficient flow of large data traffic between a workflow orchestrator and Web Services. We evaluated the data-partitioning strategy by comparing it with typical communication patterns on an example pipeline for genomic sequence annotation. The results show that data-partitioning lowers resource demands of services and increases their throughput, which in consequence allows to execute in-silico experiments on genome-scale, using standard SOAP Web Services and workflows. As a proof-of-principle we annotated an RNA-seq dataset using a plain BPEL workflow engine.

Quantitative assessment of thermodynamic constraints on the solution space of genome-scale metabolic models.

Science.gov (United States)

Hamilton, Joshua J; Dwivedi, Vivek; Reed, Jennifer L

2013-07-16

Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets

NARCIS (Netherlands)

Levering, J.; Fiedler, T.; Sieg, A.; van Grinsven, K.W.A.; Hering, S.; Veith, N.; Olivier, B.G.; Klett, L.; Hugenholtz, J.; Teusink, B.; Kreikemeyer, B.; Kummer, U.

2016-01-01

Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes

Evolutionary origin of Rosaceae-specific active non-autonomous hAT elements and their contribution to gene regulation and genomic structural variation.

Science.gov (United States)

Wang, Lu; Peng, Qian; Zhao, Jianbo; Ren, Fei; Zhou, Hui; Wang, Wei; Liao, Liao; Owiti, Albert; Jiang, Quan; Han, Yuepeng

2016-05-01

Transposable elements account for approximately 30 % of the Prunus genome; however, their evolutionary origin and functionality remain largely unclear. In this study, we identified a hAT transposon family, termed Moshan, in Prunus. The Moshan elements consist of three types, aMoshan, tMoshan, and mMoshan. The aMoshan and tMoshan types contain intact or truncated transposase genes, respectively, while the mMoshan type is miniature inverted-repeat transposable element (MITE). The Moshan transposons are unique to Rosaceae, and the copy numbers of different Moshan types are significantly correlated. Sequence homology analysis reveals that the mMoshan MITEs are direct deletion derivatives of the tMoshan progenitors, and one kind of mMoshan containing a MuDR-derived fragment were amplified predominately in the peach genome. The mMoshan sequences contain cis-regulatory elements that can enhance gene expression up to 100-fold. The mMoshan MITEs can serve as potential sources of micro and long noncoding RNAs. Whole-genome re-sequencing analysis indicates that mMoshan elements are highly active, and an insertion into S-haplotype-specific F-box gene was reported to cause the breakdown of self-incompatibility in sour cherry. Taken together, all these results suggest that the mMoshan elements play important roles in regulating gene expression and driving genomic structural variation in Prunus.

Ultrafast comparison of personal genomes

OpenAIRE

Mauldin, Denise; Hood, Leroy; Robinson, Max; Glusman, Gustavo

2017-01-01

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...

Genome-scale metabolic model of Pichia pastoris with native and humanized glycosylation of recombinant proteins.

Science.gov (United States)

Irani, Zahra Azimzadeh; Kerkhoven, Eduard J; Shojaosadati, Seyed Abbas; Nielsen, Jens

2016-05-01

Pichia pastoris is used for commercial production of human therapeutic proteins, and genome-scale models of P. pastoris metabolism have been generated in the past to study the metabolism and associated protein production by this yeast. A major challenge with clinical usage of recombinant proteins produced by P. pastoris is the difference in N-glycosylation of proteins produced by humans and this yeast. However, through metabolic engineering, a P. pastoris strain capable of producing humanized N-glycosylated proteins was constructed. The current genome-scale models of P. pastoris do not address native nor humanized N-glycosylation, and we therefore developed ihGlycopastoris, an extension to the iLC915 model with both native and humanized N-glycosylation for recombinant protein production, but also an estimation of N-glycosylation of P. pastoris native proteins. This new model gives a better prediction of protein yield, demonstrates the effect of the different types of N-glycosylation of protein yield, and can be used to predict potential targets for strain improvement. The model represents a step towards a more complete description of protein production in P. pastoris, which is required for using these models to understand and optimize protein production processes. © 2015 Wiley Periodicals, Inc.

Genomic tools for evolution and conservation in the chimpanzee: Pan troglodytes ellioti is a genetically distinct population.

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Rory Bowden

Full Text Available In spite of its evolutionary significance and conservation importance, the population structure of the common chimpanzee, Pan troglodytes, is still poorly understood. An issue of particular controversy is whether the proposed fourth subspecies of chimpanzee, Pan troglodytes ellioti, from parts of Nigeria and Cameroon, is genetically distinct. Although modern high-throughput SNP genotyping has had a major impact on our understanding of human population structure and demographic history, its application to ecological, demographic, or conservation questions in non-human species has been extremely limited. Here we apply these tools to chimpanzee population structure, using ∼700 autosomal SNPs derived from chimpanzee genomic data and a further ∼100 SNPs from targeted re-sequencing. We demonstrate conclusively the existence of P. t. ellioti as a genetically distinct subgroup. We show that there is clear differentiation between the verus, troglodytes, and ellioti populations at the SNP and haplotype level, on a scale that is greater than that separating continental human populations. Further, we show that only a small set of SNPs (10-20 is needed to successfully assign individuals to these populations. Tellingly, use of only mitochondrial DNA variation to classify individuals is erroneous in 4 of 54 cases, reinforcing the dangers of basing demographic inference on a single locus and implying that the demographic history of the species is more complicated than that suggested analyses based solely on mtDNA. In this study we demonstrate the feasibility of developing economical and robust tests of individual chimpanzee origin as well as in-depth studies of population structure. These findings have important implications for conservation strategies and our understanding of the evolution of chimpanzees. They also act as a proof-of-principle for the use of cheap high-throughput genomic methods for ecological questions.

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

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

2014-01-01

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

Genome-scale reconstruction and in silico analysis of the Ralstonia eutropha H16 for polyhydroxyalkanoate synthesis, lithoautotrophic growth, and 2-methyl citric acid production

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Kim Tae

2011-06-01

Full Text Available Abstract Background Ralstonia eutropha H16, found in both soil and water, is a Gram-negative lithoautotrophic bacterium that can utillize CO2 and H2 as its sources of carbon and energy in the absence of organic substrates. R. eutropha H16 can reach high cell densities either under lithoautotrophic or heterotrophic conditions, which makes it suitable for a number of biotechnological applications. It is the best known and most promising producer of polyhydroxyalkanoates (PHAs from various carbon substrates and is an environmentally important bacterium that can degrade aromatic compounds. In order to make R. eutropha H16 a more efficient and robust biofactory, system-wide metabolic engineering to improve its metabolic performance is essential. Thus, it is necessary to analyze its metabolic characteristics systematically and optimize the entire metabolic network at systems level. Results We present the lithoautotrophic genome-scale metabolic model of R. eutropha H16 based on the annotated genome with biochemical and physiological information. The stoichiometic model, RehMBEL1391, is composed of 1391 reactions including 229 transport reactions and 1171 metabolites. Constraints-based flux analyses were performed to refine and validate the genome-scale metabolic model under environmental and genetic perturbations. First, the lithoautotrophic growth characteristics of R. eutropha H16 were investigated under varying feeding ratios of gas mixture. Second, the genome-scale metabolic model was used to design the strategies for the production of poly[R-(--3hydroxybutyrate] (PHB under different pH values and carbon/nitrogen source uptake ratios. It was also used to analyze the metabolic characteristics of R. eutropha when the phosphofructokinase gene was expressed. Finally, in silico gene knockout simulations were performed to identify targets for metabolic engineering essential for the production of 2-methylcitric acid in R. eutropha H16. Conclusion The

Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model