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Annotating New Genes

Annotating New Genes
From in Silico Screening to Experimental Validation

by Shizuka Uchida

  • Publisher : Elsevier
  • Release : 2012-08-06
  • Pages : 196
  • ISBN : 1908818123
  • Language : En, Es, Fr & De
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In recent years, a number of academic and commercial software packages and databases have been developed for the analysis and screening of biological data; however, the usability of these data is compromised by so-called novel genes to which no biological function is assigned. Annotating new genes outlines an approach to the analysis of evolutionary-conserved, heart-enriched genes with unknown functions, offering a step-by-step description of the procedure from screening to validation. The book begins by offering an introduction to the databases and software available, before moving on to cover programming guidelines, including a specific case study on the use of C-It for in silico screening. The second half of the book offers a step-by-step guide to experimental validation concepts and procedures, as well as an overview of additional potential applications of this approach in the field of stem cells and tissue regeneration, before a concluding chapter summarises the concepts and theories presented. Focuses not only on screening but also on biological validations Provides details of databases and software (web interface) products for biologists with minimal computation skills Offers a step-by-step outline of the procedure involved

Development of New Tools and Pipelines for Plant Bioinformatics Applications

Development of New Tools and Pipelines for Plant Bioinformatics Applications
A Book

by Omar M. Darwish

  • Publisher : Unknown Publisher
  • Release : 2014
  • Pages : 140
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Blueberry is an economically and nutritionally important small fruit crop, native to North America. As with many crops, extreme low temperature can affect blueberry crop yield negatively and cause major losses to growers. For this reason, blueberry breeding programs have focused on developing improved cultivars with broader climatic adaptation. To help achieve this goal, the blueberry genomic database (BBGD454) was developed to provide the research community with valuable resources to identify genes that play an important role in flower bud and fruit development, cold acclimation and chilling accumulation in blueberry. The database was developed using SQLServer2008 to house 454 transcript sequences, annotations and gene expression profiles of blueberry genes. BBGD454 can be accessed publically from a web-based interface; this website provides search and browse functionalities to allow scientists to access and search the data in order to correlate gene expression with gene function in different stages of blueberry fruit ripening, at different stages of cold acclimation of flower buds, and in leaves. It can be accessed from: http://bioinformatics.towson.edu/BBGD454. Fragaria vesca, a diploid strawberry species commonly known as the alpine or woodland strawberry, is a versatile experimental plant system and an emerging model for the Rosaceae family. An ancestral F. Vesca genome contributed to the genome of the octoploid dessert strawberry (F. × ananassa), and the extant genome exhibits synteny with other commercially important members of the Rosaceae family such as apple and peach. To provide a molecular description of floral organ and fruit development at the resolution of specific tissues and cell types, RNAs from flowers and early developmental stage fruit tissues of the inbred F. vesca line YW5AF7 were extracted and the resulting cDNA libraries sequenced using an Illumina HiSeq2000. To enable easy access as well as mining of this two-dimensional (stage and tissue) transcriptome dataset, a web-based database, the Strawberry Genomic Resource (SGR), was developed. SGR is a web accessible database that contains sample description, sample statistics, gene annotation, and gene expression analysis. This information can be accessed publicly from a web-based interface at http://bioinformatics.towson.edu/strawberry. The SGR website provides user friendly search and browse capabilities for all the data stored in the database. Users are able to search for genes using a gene ID or description or obtain differentially expressed genes by entering different comparison parameters. Search results can be downloaded in a tabular format compatible with Microsoft excel application. Aligned reads to individual genes and exon/intron structures are displayed using the genome browser, facilitating gene re-annotation by individual users. The SGR database was developed to facilitate dissemination and data mining of extensive floral and fruit transcriptome data in the woodland strawberry. It enables users to mine the data in different ways to study different pathways or biological processes during reproductive development. The F. vesca genome was sequenced in 2010. The current gene models (version 1.1) were developed using GeneMark-ES+, which did not use experimental evidence to partition the DNA sequence into coding and non-coding regions. Taking advantage of the extensive transcriptomic data of fifty different tissue/stage samples of early stage F. vesca fruit development, we re-annotated the F. vesca genome using the MAKER annotation pipeline. This re-annotation significantly improves the accuracy of gene structure and facilitates functional studies of individual strawberry genes. The new annotation described here identifies 33,496 protein-coding genes compared to 32,831 protein-coding genes in the old annotation hosted at the Genome Database of Rosaceae (GDR). The total coding length is 40,815,814 base pair in the new annotation compared to 38,750,535 base pair in the old annotation. Total number of coding regions in the proposed annotation is 176,409 compared to 167,270 in the GeneMark annotation. The total number of newly discovered gene models that were absent in previous annotations is 2286. Using extensive F. vesca RNA-Seq data, we re-annotated F. vesca genome. The number of protein-coding genes and the total coding length across all chromosomes are increased. This increase is due to the discovery of new genes, addition of exons to current genes, extension of current exons and merging of current exons. This complete genome re-annotation is hosted at SGR GBrowse and will significantly benefit the strawberry and Rosaceae research community as a whole.

IMG ER

IMG ER
A System for Microbial Genome Annotation Expert Review and Curation

by Anonim

  • Publisher : Unknown Publisher
  • Release : 2009
  • Pages : 129
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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A rapidly increasing number of microbial genomes are sequenced by organizations worldwide and are eventually included into various public genome data resources. The quality of the annotations depends largely on the original dataset providers, with erroneous or incomplete annotations often carried over into the public resources and difficult to correct. We have developed an Expert Review (ER) version of the Integrated Microbial Genomes (IMG) system, with the goal of supporting systematic and efficient revision of microbial genome annotations. IMG ER provides tools for the review and curation of annotations of both new and publicly available microbial genomes within IMG's rich integrated genome framework. New genome datasets are included into IMG ER prior to their public release either with their native annotations or with annotations generated by IMG ER's annotation pipeline. IMG ER tools allow addressing annotation problems detected with IMG's comparative analysis tools, such as genes missed by gene prediction pipelines or genes without an associated function. Over the past year, IMG ER was used for improving the annotations of about 150 microbial genomes.

An Integrated Approach to Enhancing Functional Annotation of Sequences for Data Analysis of a Transcriptome

An Integrated Approach to Enhancing Functional Annotation of Sequences for Data Analysis of a Transcriptome
A Book

by Matthew Morritt Hindle

  • Publisher : Unknown Publisher
  • Release : 2012
  • Pages : 129
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Given the ever increasing quantity of sequence data, functional annotation of new gene sequences persists as being a significant challenge for bioinformatics. This is a particular problem for transcriptomics studies in crop plants where large genomes and evolutionarily distant model organisms, means that identifying the function of a given gene used on a microarray, is often a non-trivial task. Information pertinent to gene annotations is spread across technically and semantically heterogeneous biological databases. Combining and exploiting these data in a consistent way has the potential to improve our ability to assign functions to new or uncharacterised genes. Methods: The Ondex data integration framework was further developed to integrate databases pertinent to plant gene annotation, and provide data inference tools. The CoPSA annotation pipeline was created to provide automated annotation of novel plant genes using this knowledgebase. CoPSA was used to derive annotations for Affymetrix GeneChips available for plant species. A conjoint approach was used to align GeneChip sequences to orthologous proteins, and identify protein domain regions. These proteins and domains were used together with multiple evidences to predict functional annotations for sequences on the GeneChip. Quality was assessed with reference to other annotation pipelines. These improved gene annotations were used in the analysis of a time-series transcriptomics study of the differential responses of durum wheat varieties to water stress. Results and Conclusions: The integration of plant databases using the Ondex showed that it was possible to increase the overall quantity and quality of information available, and thereby improve the resulting annotation. Direct data aggregation benefits were observed, as well as new information derived from inference across databases. The CoPSA pipeline was shown to improve coverage of the wheat microarray compared to the NetAffx and BLAST2GO pipelines. Leverage of these annotations during the analysis of data from a transcriptomics study of the durum wheat water stress responses, yielded new biological insights into water stress and highlighted potential candidate genes that could be used by breeders to improve drought response.

Modern Genome Annotation

Modern Genome Annotation
The Biosapiens Network

by D. Frishman,Alfonso Valencia

  • Publisher : Springer Science & Business Media
  • Release : 2009-10-02
  • Pages : 490
  • ISBN : 3211751238
  • Language : En, Es, Fr & De
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An accurate description of current scientific developments in the field of bioinformatics and computational implementation is presented by research of the BioSapiens Network of Excellence. Bioinformatics is essential for annotating the structure and function of genes, proteins and the analysis of complete genomes and to molecular biology and biochemistry. Included is an overview of bioinformatics, the full spectrum of genome annotation approaches including; genome analysis and gene prediction, gene regulation analysis and expression, genome variation and QTL analysis, large scale protein annotation of function and structure, annotation and prediction of protein interactions, and the organization and annotation of molecular networks and biochemical pathways. Also covered is a technical framework to organize and represent genome data using the DAS technology and work in the annotation of two large genomic sets: HIV/HCV viral genomes and splicing alternatives potentially encoded in 1% of the human genome.

Database Annotation in Molecular Biology

Database Annotation in Molecular Biology
Principles and Practice

by Arthur M. Lesk

  • Publisher : John Wiley & Sons
  • Release : 2005-09-01
  • Pages : 266
  • ISBN : 0470856858
  • Language : En, Es, Fr & De
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Two factors dominate current molecular biology: the amount of raw data is increasing very rapidly and successful applications in biomedical research require carefully curated and annotated databases. The quality of the experimental data -- especially nucleic acid sequences -- is satisfactory; however, annotations depend on features inferred from the data rather than measured directly, for instance the identification of genes in genome sequences. It is essential that these inferences are as accurate as possible and this requires human intervention. With the recognition of the importance of accurate database annotation and the requirement for individuals with particular constellations of skills to carry it out, annotators are emerging as specialists within the profession of bioinformatics. This book compiles information about annotation -- its current status, what is required to improve it, what skills must be brought to bear on database curation and hence what is the proper training for annotators. The book should be essential reading for all people working on biological databases, both biologists and computer scientists. It will also be of interest to all users of such databases, including molecular biologists, geneticists, protein chemists, clinicians and drug developers.

Automatic Annotation of Multigene Families, the Case of Peroxidases

Automatic Annotation of Multigene Families, the Case of Peroxidases
A Book

by Nizar Fawal

  • Publisher : Unknown Publisher
  • Release : 2013
  • Pages : 155
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Gene families are groups of homologous genes with a common ancestor that are likely to have highly similar sequences and functions. In our team, we are mainly interested in one of these families, the peroxidase superfamily. Peroxidases are universal enzymes present in all organisms where they typically catalyze the reduction of peroxides, such as hydrogen peroxide and the oxidation of a variety of organic and inorganic compounds. However, with the continually reducing cost and time of genome sequencing, expert manual annotation became a cumbersome task. Therefore, in order to handle the flood of data in an expert manner, the first step was to update the peroxidases database, the PeroxiBase. For this first aim, several tools and pipelines were set in place to facilitate and accelerate the annotation process of peroxidases all while maintaining a high quality of annotations. First of all, two new automatic pipelines, " proteome_filter " et " EST_filter ", for the annotation of multigene families were developed. They are based on a BLAST homology search in order to detect sequences that may be related to the families in question. Plus, a new tool named GECA, was developed for comparing exon/intron organization and therefore to help detecting gene structure variations. Furthermore, this gene structure information can be used as means to validate the annotation of multigene families. The new pipelines and GECA were implemented and tested with the family of ligninases. The choice for this family is supported by the massive annotation of fungi genomes due to the increased industrial interest in ligninases. These enzymes belong to the class II peroxidase, found essentially in fungi and responsible of degrading lignin (a high molecular compound found in the cell wall of land plants). Having a specialized databank on peroxidases, I started classifying, analyzing and studying the evolution of these ligninases. Finally, in addition to my work I was implicated in several side projects, such as designing a semi-automatic annotation workflows, constructing a pipeline for a complete phylogenic study and finally, studying of the evolution of eight gene families in Eucalyptus.

Transcription of Human-specific Duplicate Genes

Transcription of Human-specific Duplicate Genes
A Book

by Max L. Dougherty

  • Publisher : Unknown Publisher
  • Release : 2018
  • Pages : 162
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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In this work, I set out to characterize new genes contained specifically within the human genome but absent from any other, including our closest evolutionary cousins. Our interest in these genes is twofold: First, gene duplication is a fundamental process by which evolutionary innovations at the organismal level arise; and second, we believe that variation in these new genes is an important and unappreciated source of phenotypic differences between individuals, both normal and pathogenic. The ability to interpret observed variation in a gene, such as to determine if a mutation in that gene is likely to be impactful, requires quality annotation. This includes an understanding of gene structure: how the gene is transcribed, processed, and which base pairs code for protein or have other specific roles. The major challenge presented by this category of genes is that they are highly identical to other parts of the genome, and as such, most methods of investigation struggle to tell them apart. As will be expanded upon, this annotation is currently absent or insufficient for genes that are specific to the human genome. Combined with evolutionary and expression analysis, solving this annotation problem enables us to understand how new genes are created in the human genome at the very earliest stages. Combined with surveys of natural occurring and pathogenic variation, it enables us to understand which new genes are functional and which are not, and among those with function, which harbor deleterious variants that can cause disease. With these goals in mind, I set out to solve the annotation of human-specific duplicate genes most promising for functional status. I performed a close study of one such gene, HYDIN2, where I present an evolutionary analysis that gives insight into gene creation and associated disease mechanism, present a survey of naturally occurring variation, and describe the complex transcriptional pattern of a gene that serves as a case study in how duplication and rearrangement of genome segments can lead to rapid gene innovation. Next, I present a technique to more rapidly and rigorously study the transcription of any recently created duplicate gene. I apply this technique to the body of human-specific duplicate genes as well as other expanded gene families. I show that by improving upon current annotations we gain insight into the structural history, expression pattern, and functional status of such genes. I conclude with logical next steps and promising future directions. Ultimately, this work increments our understanding of how gene duplication leads to evolutionary innovation specifically in human, the functional impact of these species-specific differences, and how variation in these genes can contribute to disease.

Gene Annotation and Disease Gene Prediction from an Integrated Functional Linkage Gene Network

Gene Annotation and Disease Gene Prediction from an Integrated Functional Linkage Gene Network
A Book

by Bolan Linghu

  • Publisher : Unknown Publisher
  • Release : 2009
  • Pages : 290
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Abstract: In the postgenomic era, it remains a challenging task to understand the cellular functions of genes and how the dysfunction of a gene relates to a disease. Since genes work cooperatively for particular cellular tasks, a functional linkage network (FLN) can be used for function-related studies. In this network, the nodes represent genes and the weighted edges represent the degree of their functional association. Here I explore the FLN construction, FLN-based gene-function prediction, and FLN-based new-disease-gene prediction. In the first part of the dissertation, aiming to provide precise functional annotation for as many genes as possible, I explore and propose a two-step framework: (i) construction of a high-coverage and reliable FLN via data integration, and (ii) development of a reliable decision rule for functional annotation. This framework is tested in yeast and E. coli . In step one, I demonstrate that commonly used machine learning methods such as Linear SVM and Naïve Bayes all combine heterogeneous data to produce reliable and high-coverage FLNs. In step two, empirical tuning of an adjustable decision rule on the FLN reveals that basing annotation on maximum edge weight results in the most precise annotation at high coverages. In the second part of the dissertation, I build and validate a human genome-scale FLN by data integration using a Naïve Bayes classifier. This FLN is then used to predict new candidate disease genes associated with 110 diseases. In particular I hypothesize that the neighborhood of known disease genes tends to be enriched in genes that are also associated with the same disease. This is based on the observation that disease genes underlying common diseases tend to occur in distinct functional modules. The network thus enables one to identify previously unimplicated genes, and to rank them by the likelihood of their involvement. I show that this FLN is able to predict new disease genes for diverse diseases and outperforms networks based solely on protein-protein physical interactions. Additionally, based on the observation that disease genes underlying similar or related diseases tend to be functionally related, I illustrate that the FLN can also help to assess disease-disease associations.

Genome Annotation

Genome Annotation
A Book

by Jung Soh,Paul M.K. Gordon,Christoph W. Sensen

  • Publisher : CRC Press
  • Release : 2016-04-19
  • Pages : 270
  • ISBN : 1439841187
  • Language : En, Es, Fr & De
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The success of individualized medicine, advanced crops, and new and sustainable energy sources requires thoroughly annotated genomic information and the integration of this information into a coherent model. A thorough overview of this field, Genome Annotation explores automated genome analysis and annotation from its origins to the challenges of next-generation sequencing data analysis. The book initially takes you through the last 16 years since the sequencing of the first complete microbial genome. It explains how current analysis strategies were developed, including sequencing strategies, statistical models, and early annotation systems. The authors then present visualization techniques for displaying integrated results as well as state-of-the-art annotation tools, including MAGPIE, Ensembl, Bluejay, and Galaxy. They also discuss the pipelines for the analysis and annotation of complex, next-generation DNA sequencing data. Each chapter includes references and pointers to relevant tools. As very few existing genome annotation pipelines are capable of dealing with the staggering amount of DNA sequence information, new strategies must be developed to accommodate the needs of today’s genome researchers. Covering this topic in detail, Genome Annotation provides you with the foundation and tools to tackle this challenging and evolving area. Suitable for both students new to the field and professionals who deal with genomic information in their work, the book offers two genome annotation systems on an accompanying CD-ROM.

Reannotation and Extended Community Resources for the Genome of the Non-seed Plant Physcomitrella Patens Provide Insights Into the Evolution of Plant Gene Structures and Functions

Reannotation and Extended Community Resources for the Genome of the Non-seed Plant Physcomitrella Patens Provide Insights Into the Evolution of Plant Gene Structures and Functions
A Book

by Andreas D. Zimmer,Daniel Lang,Karol Buchta,Stefan A. Rensing,Ralf Reski

  • Publisher : Unknown Publisher
  • Release : 2013
  • Pages : 129
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Algal Functional Annotation Tool

Algal Functional Annotation Tool
A Book

by Anonim

  • Publisher : Unknown Publisher
  • Release : 2012
  • Pages : 129
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Abstract BACKGROUND: Progress in genome sequencing is proceeding at an exponential pace, and several new algal genomes are becoming available every year. One of the challenges facing the community is the association of protein sequences encoded in the genomes with biological function. While most genome assembly projects generate annotations for predicted protein sequences, they are usually limited and integrate functional terms from a limited number of databases. Another challenge is the use of annotations to interpret large lists of 'interesting' genes generated by genome-scale datasets. Previously, these gene lists had to be analyzed across several independent biological databases, often on a gene-by-gene basis. In contrast, several annotation databases, such as DAVID, integrate data from multiple functional databases and reveal underlying biological themes of large gene lists. While several such databases have been constructed for animals, none is currently available for the study of algae. Due to renewed interest in algae as potential sources of biofuels and the emergence of multiple algal genome sequences, a significant need has arisen for such a database to process the growing compendiums of algal genomic data. DESCRIPTION: The Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of genes on KEGG pathway maps and batch gene identifier conversion. CONCLUSIONS: The Algal Functional Annotation Tool aims to provide an integrated data-mining environment for algal genomics by combining data from multiple annotation databases into a centralized tool. This site is designed to expedite the process of functional annotation and the interpretation of gene lists, such as those derived from high-throughput RNA-seq experiments. The tool is publicly available at http://pathways.mcdb.ucla.edu.

Comparative Annotation Toolkit (CAT) - Simultaneous Clade and Personal Genome Annotation

Comparative Annotation Toolkit (CAT) - Simultaneous Clade and Personal Genome Annotation
A Book

by Ian Fiddes

  • Publisher : Unknown Publisher
  • Release : 2017
  • Pages : 214
  • ISBN : 9780355671698
  • Language : En, Es, Fr & De
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The recent introductions of low-cost, long-read and read-cloud sequencing technologies coupled with intense efforts to develop efficient algorithms have made affordable, high-quality de-novo sequence assembly a realistic proposition. The result is an explosion of new, ultra contiguous genome assemblies. To compare these genomes we need robust methods for genome annotation. I describe the fully open source Comparative Annotation Toolkit (CAT), which provides a flexible way to simultaneously annotate entire clades and identify orthology relationships. I show that CAT can be used to improve annotations on the rat genome, annotate the great apes, annotate a diverse set of mammals, and annotate personal, diploid human genomes. I demonstrate the resulting discovery of novel genes, isoforms and structural variants, even in genomes as well studied as the rat and great apes, and how these annotations improve cross-species RNA expression experiments.

Genesmith

Genesmith
Implementing Customized Gene Finding to Assess the Landscape of Genome Annotation

by Ravi Dandekar

  • Publisher : Unknown Publisher
  • Release : 2016
  • Pages : 129
  • ISBN : 9781369311747
  • Language : En, Es, Fr & De
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Modern gene prediction, otherwise known as ab initio gene annotation, has yet to progress to a level of accuracy where it can replace the more costly process of manual curation through laboratory experiments. Gene annotation software utilizes machine learning approaches to model genes using Hidden Markov Models (HMMs) in order to accurately predict the location and structure of genes in a given genome. To gain a more cohesive understanding of which components can be improved in gene prediction algorithms, we developed flexible gene annotation software, Genesmith, in order to experiment with different HMM structures. Our results show that reducing the complexity of gene HMMs may reduce the overall accuracy of gene prediction, but there are certain features, such as donor and acceptor splice sites in introns, which remain highly predictive. In addition to our findings, we also introduce a new decoding algorithm, the Stochastic Viterbi, for extracting gene structure from genomic sequence. Our results point out holes in the current ab initio gene annotation process and suggest potential avenues for improvement.

Challenges in Whole-Genome Annotation of Pyrosequenced Eukaryotic Genomes

Challenges in Whole-Genome Annotation of Pyrosequenced Eukaryotic Genomes
A Book

by Anonim

  • Publisher : Unknown Publisher
  • Release : 2009
  • Pages : 129
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Pyrosequencing technologies such as 454/Roche and Solexa/Illumina vastly lower the cost of nucleotide sequencing compared to the traditional Sanger method, and thus promise to greatly expand the number of sequenced eukaryotic genomes. However, the new technologies also bring new challenges such as shorter reads and new kinds and higher rates of sequencing errors, which complicate genome assembly and gene prediction. At JGI we are deploying 454 technology for the sequencing and assembly of ever-larger eukaryotic genomes. Here we describe our first whole-genome annotation of a purely 454-sequenced fungal genome that is larger than a yeast (>30 Mbp). The pezizomycotine (filamentous ascomycote) Aspergillus carbonarius belongs to the Aspergillus section Nigri species complex, members of which are significant as platforms for bioenergy and bioindustrial technology, as members of soil microbial communities and players in the global carbon cycle, and as agricultural toxigens. Application of a modified version of the standard JGI Annotation Pipeline has so far predicted ~;;10k genes. ~;;12percent of these preliminary annotations suffer a potential frameshift error, which is somewhat higher than the ~;;9percent rate in the Sanger-sequenced and conventionally assembled and annotated genome of fellow Aspergillus section Nigri member A. niger. Also,>90percent of A. niger genes have potential homologs in the A. carbonarius preliminary annotation. Weconclude, and with further annotation and comparative analysis expect to confirm, that 454 sequencing strategies provide a promising substrate for annotation of modestly sized eukaryotic genomes. We will also present results of annotation of a number of other pyrosequenced fungal genomes of bioenergy interest.

Genome Annotation and Finding Repetitive DNA Elements

Genome Annotation and Finding Repetitive DNA Elements
A Book

by Renu Rawat

  • Publisher : Unknown Publisher
  • Release : 2014-06-03
  • Pages : 44
  • ISBN : 9783656659815
  • Language : En, Es, Fr & De
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Bachelor Thesis from the year 2014 in the subject Computer Science - Bioinformatics, grade: 8.26, Lovely Professional University, course: b.tech honors biotechnology, language: English, abstract: As the number of genomes sequenced is increasing at high rate, there is a need of gene prediction method which is quick, reliable, inexpensive. In such conditions, the computations tool will serve as an alternative to wet lab methods. The confidence level of annotation by the tool can be enhanced by preparing exhaustive training data sets. The aim is to develop a tool which will read data from a DNA sequence file in the fasta format and will annotate it. For this purpose Genome Database was used to retrieve the input data. PERL programming has been put to develop this tool for annotation. To increase the confidence level of annotation the data was validated from multiple sources. Perl script was written to find the promoter region, repeats, transcription factor binding site, base periodicity, and nucleotide frequency. The program written was also executed to identify repeats, poly (A) signals, CpG islands, ARS. The tool will annotate the DNA by predicting the gene structure based on the consensus sequences of important regulatory elements. The confidence level of annotation of the predicted gene, non-coding region, ARS, repeats etc. were checked by running test dataset. This test dataset was annotated data as reported by genome database and computational tools. Gene prediction of the non-coding regions as reported by genome database (SGD) were performed by existing tools; the regions identified as non-coding by these tools were then analyzed for presence of repeats. The BLAST was used to annotate on the basis of sequence similarity with the already annotated genes. GeneMark.hmm and FGENESH were used for gene prediction. In order to validate the predicted results, annotations of genome of Saccharomyces cerevisiae from SGD Database, and output of different computational

A Case Study of Oryza sativa. Annotation of Plant Genome

A Case Study of Oryza sativa. Annotation of Plant Genome
A Book

by IDSAsr Study

  • Publisher : GRIN Verlag
  • Release : 2020-09-29
  • Pages : 60
  • ISBN : 3346256359
  • Language : En, Es, Fr & De
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Scientific Study from the year 2020 in the subject Computer Science - Bioinformatics, , language: English, abstract: Using Insilco analysis mode, the present study is an attempt to examine various characteristics conformation of senescence causing gene in rice. The two gene chosen were HCP and RR because, the interaction in between these two led to the onset of senescence in rice. Two gene that is HCP (Histidine-containing phosphor transfer protein 1) and RR (Two-component response regulator) are responsible for attaining the stage of senescence in rice. Understanding their molecular and structural property will be going to let us closer to perform successful adjustments. Moreover, their specific property is also responsible for their specific interaction which led to generation of such signals that triggers senescence. Therefore, this analysis was aimed to understand the features of the two genes as well as their interaction by the means of computational technique. Understanding the features, function and flow of gene will lead us to stabilized effective measure in order to get a beneficiary outcome while going for alteration in its characters. As the pure data for the structure conformation of the selected genes are not available so, we have at first, searched the most similar homolog of the query sequence and the search was based on similar sequence homology on the platform of local alignment tool. And further analysis was carried out on the base conformation of the most relevant homologs (structure/sequence) found. We have analysed the query gene sequence by various dry lab analysis tool to explore its structural and molecular features with the motive to contribute a little knowledge for the sake of further studies to delay senescence in rice plant in order to increase grain productivity. Rice is a perennial claim crop of the world. Besides satisfying the eager of energy rice, has also been known to support worlds trade economy. Hence, being a crop of such crucial importance its examinational study at genome level will serve in multiplying its production and quality to irrigate the burning crave of humanity. Likewise, the senescence gene of rice is responsible for its age duration. Hence, understanding its property at 360° will help us to modify or to alter its function in positive portion.

Detection of Frameshifts and Improving Genome Annotation

Detection of Frameshifts and Improving Genome Annotation
A Book

by Ivan Valentinovich Antonov

  • Publisher : Unknown Publisher
  • Release : 2012
  • Pages : 129
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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We developed a new program called GeneTack for ab initio frameshift detection in intronless protein-coding nucleotide sequences. The GeneTack program uses\r : a hidden Markov model (HMM) of a genomic sequence with possibly frameshifted\r : protein-coding regions. The Viterbi algorithm nds the maximum likelihood path\r : that discriminates between true adjacent genes and a single gene with a frameshift.\r : We tested GeneTack as well as two other earlier developed programs FrameD and\r : FSFind on 17 prokaryotic genomes with frameshifts introduced randomly into known\r : genes. We observed that the average frameshift prediction accuracy of GeneTack, in\r : terms of (Sn+Sp)/2 values, was higher by a signicant margin than the accuracy of\r : the other two programs.\r : GeneTack was used to screen 1,106 complete prokaryotic genomes and 206,991\r : genes with frameshifts (fs-genes) were identifed. Our goal was to determine if a\r : frameshift transition was due to (i) a sequencing error, (ii) an indel mutation or (iii)\r : a recoding event. We grouped 102,731 genes with frameshifts (fs-genes) into 19,430\r : clusters based on sequence similarity between their protein products (fs-proteins), \r : conservation of predicted frameshift position, and its direction. While fs-genes in\r.

Comparative Reannotation of 21 Aspergillus Genomes

Comparative Reannotation of 21 Aspergillus Genomes
A Book

by Anonim

  • Publisher : Unknown Publisher
  • Release : 2013
  • Pages : 129
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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We used comparative gene modeling to reannotate 21 Aspergillus genomes. Initial automatic annotation of individual genomes may contain some errors of different nature, e.g. missing genes, incorrect exon-intron structures, 'chimeras', which fuse 2 or more real genes or alternatively splitting some real genes into 2 or more models. The main premise behind the comparative modeling approach is that for closely related genomes most orthologous families have the same conserved gene structure. The algorithm maps all gene models predicted in each individual Aspergillus genome to the other genomes and, for each locus, selects from potentially many competing models, the one which most closely resembles the orthologous genes from other genomes. This procedure is iterated until no further change in gene models is observed. For Aspergillus genomes we predicted in total 4503 new gene models (~;;2percent per genome), supported by comparative analysis, additionally correcting ~;;18percent of old gene models. This resulted in a total of 4065 more genes with annotated PFAM domains (~;;3percent increase per genome). Analysis of a few genomes with EST/transcriptomics data shows that the new annotation sets also have a higher number of EST-supported splice sites at exon-intron boundaries.

Discovery and Annotation of Small Proteins Using Genomics, Proteomics and Computational Approaches

Discovery and Annotation of Small Proteins Using Genomics, Proteomics and Computational Approaches
A Book

by Anonim

  • Publisher : Unknown Publisher
  • Release : 2011
  • Pages : 129
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Small proteins (10 200 amino acids aa in length) encoded by short open reading frames (sORF) play important regulatory roles in various biological processes, including tumor progression, stress response, flowering, and hormone signaling. However, ab initio discovery of small proteins has been relatively overlooked. Recent advances in deep transcriptome sequencing make it possible to efficiently identify sORFs at the genome level. In this study, we obtained 2.6 million expressed sequence tag (EST) reads from Populus deltoides leaf transcriptome and reconstructed full-length transcripts from the EST sequences. We identified an initial set of 12,852 sORFs encoding proteins of 10 200 aa in length. Three computational approaches were then used to enrich for bona fide protein-coding sORFs from the initial sORF set: (1) codingpotential prediction, (2) evolutionary conservation between P. deltoides and other plant species, and (3) gene family clustering within P. deltoides. As a result, a high-confidence sORF candidate set containing 1469 genes was obtained. Analysis of the protein domains, non-protein-coding RNA motifs, sequence length distribution, and protein mass spectrometry data supported this high-confidence sORF set. In the high-confidence sORF candidate set, known protein domains were identified in 1282 genes (higher-confidence sORF candidate set), out of which 611 genes, designated as highest-confidence candidate sORF set, were supported by proteomics data. Of the 611 highest-confidence candidate sORF genes, 56 were new to the current Populus genome annotation. This study not only demonstrates that there are potential sORF candidates to be annotated in sequenced genomes, but also presents an efficient strategy for discovery of sORFs in species with no genome annotation yet available.