International journal of plant genomics最新文献

{"title":"Wheat genomics: present status and future prospects.","authors":"P K Gupta,&nbsp;R R Mir,&nbsp;A Mohan,&nbsp;J Kumar","doi":"10.1155/2008/896451","DOIUrl":"https://doi.org/10.1155/2008/896451","url":null,"abstract":"<p><p>Wheat (Triticum aestivum L.), with a large genome (16000 Mb) and high proportion ( approximately 80%) of repetitive sequences, has been a difficult crop for genomics research. However, the availability of extensive cytogenetics stocks has been an asset, which facilitated significant progress in wheat genomic research in recent years. For instance, fairly dense molecular maps (both genetic and physical maps) and a large set of ESTs allowed genome-wide identification of gene-rich and gene-poor regions as well as QTL including eQTL. The availability of markers associated with major economic traits also allowed development of major programs on marker-assisted selection (MAS) in some countries, and facilitated map-based cloning of a number of genes/QTL. Resources for functional genomics including TILLING and RNA interference (RNAi) along with some new approaches like epigenetics and association mapping are also being successfully used for wheat genomics research. BAC/BIBAC libraries for the subgenome D and some individual chromosomes have also been prepared to facilitate sequencing of gene space. In this brief review, we discuss all these advances in some detail, and also describe briefly the available resources, which can be used for future genomics research in this important crop.</p>","PeriodicalId":73471,"journal":{"name":"International journal of plant genomics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2008/896451","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"27480489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recent advances in cotton genomics.","authors":"Hong-Bin Zhang, Yaning Li, Baohua Wang, Peng W Chee","doi":"10.1155/2008/742304","DOIUrl":"10.1155/2008/742304","url":null,"abstract":"<p><p>Genome research promises to promote continued and enhanced plant genetic improvement. As a world's leading crop and a model system for studies of many biological processes, genomics research of cottons has advanced rapidly in the past few years. This article presents a comprehensive review on the recent advances of cotton genomics research. The reviewed areas include DNA markers, genetic maps, mapped genes and QTLs, ESTs, microarrays, gene expression profiling, BAC and BIBAC libraries, physical mapping, genome sequencing, and applications of genomic tools in cotton breeding. Analysis of the current status of each of the genome research areas suggests that the areas of physical mapping, QTL fine mapping, genome sequencing, nonfiber and nonovule EST development, gene expression profiling, and association studies between gene expression and fiber trait performance should be emphasized currently and in near future to accelerate utilization of the genomics research achievements for enhancing cotton genetic improvement.</p>","PeriodicalId":73471,"journal":{"name":"International journal of plant genomics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2233810/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9553155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Brachypodium genomics.","authors":"Bahar Sogutmaz Ozdemir,&nbsp;Pilar Hernandez,&nbsp;Ertugrul Filiz,&nbsp;Hikmet Budak","doi":"10.1155/2008/536104","DOIUrl":"https://doi.org/10.1155/2008/536104","url":null,"abstract":"<p><p>Brachypodium distachyon (L.) Beauv. is a temperate wild grass species; its morphological and genomic characteristics make it a model system when compared to many other grass species. It has a small genome, short growth cycle, self-fertility, many diploid accessions, and simple growth requirements. In addition, it is phylogenetically close to economically important crops, like wheat and barley, and several potential biofuel grasses. It exhibits agricultural traits similar to those of these target crops. For cereal genomes, it is a better model than Arabidopsis thaliana and Oryza sativa (rice), the former used as a model for all flowering plants and the latter hitherto used as model for genomes of all temperate grass species including major cereals like barley and wheat. Increasing interest in this species has resulted in the development of a series of genomics resources, including nuclear sequences and BAC/EST libraries, together with the collection and characterization of other genetic resources. It is expected that the use of this model will allow rapid advances in generation of genomics information for the improvement of all temperate crops, particularly the cereals.</p>","PeriodicalId":73471,"journal":{"name":"International journal of plant genomics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2008/536104","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"27294423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SSR Locator: Tool for Simple Sequence Repeat Discovery Integrated with Primer Design and PCR Simulation.","authors":"Luciano Carlos da Maia,&nbsp;Dario Abel Palmieri,&nbsp;Velci Queiroz de Souza,&nbsp;Mauricio Marini Kopp,&nbsp;Fernando Irajá Félix de Carvalho,&nbsp;Antonio Costa de Oliveira","doi":"10.1155/2008/412696","DOIUrl":"https://doi.org/10.1155/2008/412696","url":null,"abstract":"<p><p>Microsatellites or SSRs (simple sequence repeats) are ubiquitous short tandem duplications occurring in eukaryotic organisms. These sequences are among the best marker technologies applied in plant genetics and breeding. The abundant genomic, BAC, and EST sequences available in databases allow the survey regarding presence and location of SSR loci. Additional information concerning primer sequences is also the target of plant geneticists and breeders. In this paper, we describe a utility that integrates SSR searches, frequency of occurrence of motifs and arrangements, primer design, and PCR simulation against other databases. This simulation allows the performance of global alignments and identity and homology searches between different amplified sequences, that is, amplicons. In order to validate the tool functions, SSR discovery searches were performed in a database containing 28 469 nonredundant rice cDNA sequences.</p>","PeriodicalId":73471,"journal":{"name":"International journal of plant genomics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2008/412696","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"27570512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The generation challenge programme platform: semantic standards and workbench for crop science.","authors":"Richard Bruskiewich,&nbsp;Martin Senger,&nbsp;Guy Davenport,&nbsp;Manuel Ruiz,&nbsp;Mathieu Rouard,&nbsp;Tom Hazekamp,&nbsp;Masaru Takeya,&nbsp;Koji Doi,&nbsp;Kouji Satoh,&nbsp;Marcos Costa,&nbsp;Reinhard Simon,&nbsp;Jayashree Balaji,&nbsp;Akinnola Akintunde,&nbsp;Ramil Mauleon,&nbsp;Samart Wanchana,&nbsp;Trushar Shah,&nbsp;Mylah Anacleto,&nbsp;Arllet Portugal,&nbsp;Victor Jun Ulat,&nbsp;Supat Thongjuea,&nbsp;Kyle Braak,&nbsp;Sebastian Ritter,&nbsp;Alexis Dereeper,&nbsp;Milko Skofic,&nbsp;Edwin Rojas,&nbsp;Natalia Martins,&nbsp;Georgios Pappas,&nbsp;Ryan Alamban,&nbsp;Roque Almodiel,&nbsp;Lord Hendrix Barboza,&nbsp;Jeffrey Detras,&nbsp;Kevin Manansala,&nbsp;Michael Jonathan Mendoza,&nbsp;Jeffrey Morales,&nbsp;Barry Peralta,&nbsp;Rowena Valerio,&nbsp;Yi Zhang,&nbsp;Sergio Gregorio,&nbsp;Joseph Hermocilla,&nbsp;Michael Echavez,&nbsp;Jan Michael Yap,&nbsp;Andrew Farmer,&nbsp;Gary Schiltz,&nbsp;Jennifer Lee,&nbsp;Terry Casstevens,&nbsp;Pankaj Jaiswal,&nbsp;Ayton Meintjes,&nbsp;Mark Wilkinson,&nbsp;Benjamin Good,&nbsp;James Wagner,&nbsp;Jane Morris,&nbsp;David Marshall,&nbsp;Anthony Collins,&nbsp;Shoshi Kikuchi,&nbsp;Thomas Metz,&nbsp;Graham McLaren,&nbsp;Theo van Hintum","doi":"10.1155/2008/369601","DOIUrl":"https://doi.org/10.1155/2008/369601","url":null,"abstract":"<p><p>The Generation Challenge programme (GCP) is a global crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. A key consortium research activity is the development of a GCP crop bioinformatics platform to support GCP research. This platform includes the following: (i) shared, public platform-independent domain models, ontology, and data formats to enable interoperability of data and analysis flows within the platform; (ii) web service and registry technologies to identify, share, and integrate information across diverse, globally dispersed data sources, as well as to access high-performance computational (HPC) facilities for computationally intensive, high-throughput analyses of project data; (iii) platform-specific middleware reference implementations of the domain model integrating a suite of public (largely open-access/-source) databases and software tools into a workbench to facilitate biodiversity analysis, comparative analysis of crop genomic data, and plant breeding decision making.</p>","PeriodicalId":73471,"journal":{"name":"International journal of plant genomics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2375972/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"27444592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phylogenetic analyses: A toolbox expanding towards Bayesian methods.","authors":"Stéphane Aris-Brosou,&nbsp;Xuhua Xia","doi":"10.1155/2008/683509","DOIUrl":"https://doi.org/10.1155/2008/683509","url":null,"abstract":"<p><p>The reconstruction of phylogenies is becoming an increasingly simple activity. This is mainly due to two reasons: the democratization of computing power and the increased availability of sophisticated yet user-friendly software. This review describes some of the latest additions to the phylogenetic toolbox, along with some of their theoretical and practical limitations. It is shown that Bayesian methods are under heavy development, as they offer the possibility to solve a number of long-standing issues and to integrate several steps of the phylogenetic analyses into a single framework. Specific topics include not only phylogenetic reconstruction, but also the comparison of phylogenies, the detection of adaptive evolution, and the estimation of divergence times between species.</p>","PeriodicalId":73471,"journal":{"name":"International journal of plant genomics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2008/683509","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"27446567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coe1 in Beta vulgaris L. Has a Tnp2-Domain DNA Transposase Gene within Putative LTRs and Other Retroelement-Like Features.","authors":"David Kuykendall,&nbsp;Jonathan Shao,&nbsp;Kenneth Trimmer","doi":"10.1155/2008/360874","DOIUrl":"https://doi.org/10.1155/2008/360874","url":null,"abstract":"<p><p>We describe discovery in Beta vulgaris L. of Coe1, a DNA transposase gene within putative long terminal repeats (LTRs), and other retrotransposon-like features including both a retroviral-like hypothetical gene and an Rvt2-domain reverse transcriptase pseudogene. The central DNA transposase gene encodes, in eight exons, a predicted 160-KDa protein producing BLAST alignments with En/Spm-type transposons. Except for a stop signal, another ORF encodes a Ty1-copia-like reverse transcriptase with amino acid sequence domain YVDDIIL. Outside apparent LTRs, an 8-mer nucleotide sequence motif CACTATAA, near or within inverted repeat sequences, is hypothetical extreme termini. A genome scan of Arabidopsis thaliana found another example of a Tnp2-domain transposase gene within an apparent LTR-retrotransposon on chromosome 4.</p>","PeriodicalId":73471,"journal":{"name":"International journal of plant genomics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2008/360874","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"27510156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soybean genomics: Developments through the use of cultivar \"Forrest\".","authors":"David A Lightfoot","doi":"10.1155/2008/793158","DOIUrl":"https://doi.org/10.1155/2008/793158","url":null,"abstract":"<p><p>Legume crops are particularly important due to their ability to support symbiotic nitrogen fixation, a key to sustainable crop production and reduced carbon emissions. Soybean (Glycine max) has a special position as a major source of increased protein and oil production in the common grass-legume rotation. The cultivar \"Forrest\" has saved US growers billions of dollars in crop losses due to resistances programmed into the genome. Moreover, since Forrest grows well in the north-south transition zone, breeders have used this cultivar as a bridge between the southern and northern US gene pools. Investment in Forrest genomics resulted in the development of the following research tools: (i) a genetic map, (ii) three RIL populations (96 > n > 975), (iii) approximately 200 NILs, (iv) 115 220 BACs and BIBACs, (v) a physical map, (vi) 4 different minimum tiling path (MTP) sets, (vii) 25 123 BAC end sequences (BESs) that encompass 18.5 Mbp spaced out from the MTPs, and 2 000 microsatellite markers within them (viii) a map of 2408 regions each found at a single position in the genome and 2104 regions found in 2 or 4 similar copies at different genomic locations (each of >150 kbp), (ix) a map of homoeologous regions among both sets of regions, (x) a set of transcript abundance measurements that address biotic stress resistance, (xi) methods for transformation, (xii) methods for RNAi, (xiii) a TILLING resource for directed mutant isolation, and (xiv) analyses of conserved synteny with other sequenced genomes. The SoyGD portal at sprovides access to the data. To date these resources assisted in the genomic analysis of soybean nodulation and disease resistance. This review summarizes the resources and their uses.</p>","PeriodicalId":73471,"journal":{"name":"International journal of plant genomics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2008/793158","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9253304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rice molecular breeding laboratories in the genomics era: Current status and future considerations.","authors":"Bert C Y Collard,&nbsp;Casiana M Vera Cruz,&nbsp;Kenneth L McNally,&nbsp;Parminder S Virk,&nbsp;David J Mackill","doi":"10.1155/2008/524847","DOIUrl":"https://doi.org/10.1155/2008/524847","url":null,"abstract":"<p><p>Using DNA markers in plant breeding with marker-assisted selection (MAS) could greatly improve the precision and efficiency of selection, leading to the accelerated development of new crop varieties. The numerous examples of MAS in rice have prompted many breeding institutes to establish molecular breeding labs. The last decade has produced an enormous amount of genomics research in rice, including the identification of thousands of QTLs for agronomically important traits, the generation of large amounts of gene expression data, and cloning and characterization of new genes, including the detection of single nucleotide polymorphisms. The pinnacle of genomics research has been the completion and annotation of genome sequences for indica and japonica rice. This information-coupled with the development of new genotyping methodologies and platforms, and the development of bioinformatics databases and software tools-provides even more exciting opportunities for rice molecular breeding in the 21st century. However, the great challenge for molecular breeders is to apply genomics data in actual breeding programs. Here, we review the current status of MAS in rice, current genomics projects and promising new genotyping methodologies, and evaluate the probable impact of genomics research. We also identify critical research areas to \"bridge the application gap\" between QTL identification and applied breeding that need to be addressed to realize the full potential of MAS, and propose ideas and guidelines for establishing rice molecular breeding labs in the postgenome sequence era to integrate molecular breeding within the context of overall rice breeding and research programs.</p>","PeriodicalId":73471,"journal":{"name":"International journal of plant genomics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2008/524847","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9253307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioinformatics tools for plant genomics.","authors":"Gary R Skuse,&nbsp;Chunguang Du","doi":"10.1155/2008/910474","DOIUrl":"https://doi.org/10.1155/2008/910474","url":null,"abstract":"The articles in this special issue reflect a convergence of developments in the fields of bioinformatics and plant genomics. Bioinformatics has its roots vaguely seated in the early 1980s, a time when personal computers began appearing in research laboratories and researchers began recognizing that those computers could be used as tools to organize, analyze and visualize their data. In the ensuing years bioinformatics tools began appearing at various sites including the European Molecular Biology Laboratory, the Molecular Biology Research Resource at the Dana-Farber Cancer Institute in the mid 1980s, the National Center for Biotechnology Information (NCBI) in 1988, the Genome Database Project at Johns Hopkins University in early 1989, and in countless laboratories throughout the world. These last efforts resulted in the development of many of the tools described in this special issue. \u0000 \u0000Progress and interest in plant genomics have been accelerating since the time in late 2000 when the genome of Arabidopsis thaliana was published. Since then many genome sequencing projects have been undertaken that include poplar (Populus), grape (Vitis), the moss Physcomitrella, the biflagellate algae Chlamydomonas and several globally crucial crop plants such as corn (Maize) and rice (Oryza). However, as we have witnessed on numerous occasions, determining the sequence of a genome is only the first step toward understanding genome organization, gene structure, gene expression patterns, disease pathogenesis and a host of other features of both scientific and commercial interests. Computational tools of genomic annotation and comparative genomics must be applied to gain a useful understanding of any genome. \u0000 \u0000In this special issue we present a collection of papers that together describe a powerful and impactful toolbox of applications and resources for plant genomic analysis. Among those articles you will find a description of research performed by the Mexican headquartered Generation Challenge Programme (GCP) which led to the GCP Platform (Bruskiewich et al.). This research support tool supports a number of data formats and web services and provides access to high performance computing facilities and platform-specific middleware collectively designed to support crop science research. \u0000 \u0000Probably one of the most promising empirical tools for investigating gene expression developed in the last 15 or so years is that of microarray technology. While the technology has become commonplace, with tools for generating and hybridizing arrays available to all, the analysis of microarray-derived data has been challenging. Many laboratories have struggled not only with this challenge but also with the task of sorting through the plethora of analytical tools available in an effort to find the ones that may be best suited to their own work. In this issue there are two reviews by Page and Coulibaly which examine and describe bioinformatics tools for inferring functional inform","PeriodicalId":73471,"journal":{"name":"International journal of plant genomics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2008/910474","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"28474005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}