http://www.hindawi.comThe latest articles from Hindawi Publishing Corporation© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/387812Plant-parasitic nematodes are important pests of crop plants worldwide, and also among the most difficult animals to identify. Their identification based on nuclear ribosomal DNA (rDNA) cistron (18S, 28S, and 5.8S RNA genes, and internal transcribed spacers, ITS1 and ITS2) is becoming a popular tool. Sequences from nuclear ribosomal RNA repeats have been used to demonstrate the identity of isolates from various hosts and to unravel the relationships of cryptic and complex species. In addition, the availability of RNA sequences allows study of phylogenetic relationships between nematodes, also for more complete understanding of their biology as agricultural pests. PPNEMA is a plant-parasitic nematode bioinformatic resource. It consists of a database of ribosomal cistron sequences from various species grouped according to nematode genera, and a search system allowing data to be extracted according to both text and pattern searching. PPNEMA offers to the scientific community a preprocessed archive of plant parasitic nematode sequences useful for nematologists. It is a tool to retrieve plant nematode multialigned sequences for phylogenetic studies or to recognize a nematode by comparing its rDNA sequence with the PPNEMA available genus specific multialignments.Francesco Rubino, Amalia Voukelatou, Francesca De Luca, Carla De Giorgi, and Marcella Attimonelli© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/496957In 2001 maize became the number one production crop in the world with the Food and Agriculture Organization of the United Nations reporting over 614 million tonnes produced. Its success is due to the high productivity per acre in tandem with a wide variety of commercial uses. Not only is maize an excellent source of food, feed, and fuel, but also its by-products are used in the production of various commercial products. Maize's unparalleled success in agriculture stems from basic research, the outcomes of which drive breeding and product development. In order for basic, translational, and applied researchers to benefit from others' investigations, newly generated data must be made freely and easily accessible. MaizeGDB is the maize research community's central repository for genetics and genomics information. The overall goals of MaizeGDB are to facilitate access to the outcomes of maize research by integrating new maize data into the database and to support the maize research community by coordinating group activities.Carolyn J. Lawrence, Lisa C. Harper, Mary L. Schaeffer, Taner Z. Sen, Trent E. Seigfried, and Darwin A. Campbell© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/412875The Dendrome Project and associated TreeGenes database serve the forest genetics research community through a curated and integrated web-based relational database. The research community is composed of approximately 2 000 members representing over 730 organizations worldwide. The database itself is composed of a wide range of genetic data from many forest trees with focused efforts on commercially important members of the Pinaceae family. The primary data types curated include species, publications, tree and DNA extraction information, genetic maps, molecular markers, ESTs, genotypic, and phenotypic data. There are currently ten main search modules or user access points within this PostgreSQL database. These access points allow users to navigate logically through the related data types. The goals of the Dendrome Project are to (1) provide a comprehensive resource for forest tree genomics data to facilitate gene discovery in related species, (2) develop interfaces that encourage the submission and integration of all genomic data, and to (3) centralize and distribute existing and novel online tools for the research community that both support and ease analysis. Recent developments have focused on increasing data content, functional annotations, data retrieval, and visualization tools. TreeGenes was developed to provide a centralized web resource with analysis and visualization tools to support data storage and exchange.Jill L. Wegrzyn, Jennifer M. Lee, Brandon R. Tearse, and David B. Neale© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/412696Microsatellites 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.Luciano Carlos da Maia, Dario Abel Palmieri, Velci Queiroz de Souza, Mauricio Marini Kopp, Fernando Irajá Félix de Carvalho, and Antonio Costa de Oliveira© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/893941While it is possible to interpret microarray experiments a single gene at a time, most studies generate long lists of differentially expressed genes whose interpretation requires the integration of prior biological knowledge. This prior knowledge is stored in various public and private databases and covers several aspects of gene function and biological information. In this review, we will describe the tools and places where to find prior accurate biological information and how to process and incorporate them to interpret microarray data analyses. Here, we highlight selected tools and resources for gene class level ontology analysis (Section 2), gene coexpression analysis (Section 3), gene network analysis (Section 4), biological pathway analysis (Section 5), analysis of transcriptional regulation (Section 6), and omics data integration (Section 7). The overall goal of this review is to provide researchers with tools and information to facilitate the interpretation of microarray data.Issa Coulibaly and Grier P. Page© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/584360Experimental designs that efficiently embed a fixed effects treatment structure within a random effects design structure typically require a mixed-model approach to data analyses. Although mixed model software tailored for the analysis of two-color microarray data is increasingly available, much of this software is generally not capable of correctly analyzing the elaborate incomplete block designs that are being increasingly proposed and used for factorial treatment structures. That is, optimized designs are generally unbalanced as it pertains to various treatment comparisons, with different specifications of experimental variability often required for different treatment factors. This paper uses a publicly available microarray dataset, as based upon an efficient experimental design, to demonstrate a proper mixed model analysis of a typical unbalanced factorial design characterized by incomplete blocks and hierarchical levels of variability.Robert J. Tempelman© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/348621Rice is one of the most important crops in the world. Although genetic improvement is a key technology for the acceleration of rice breeding, a lack of genome information had restricted efforts in molecular-based breeding until the completion of the high-quality rice genome sequence, which opened new opportunities for research in various areas of genomics. The syntenic relationship of the rice genome to other cereal genomes makes the rice genome invaluable for understanding how cereal genomes function. Producing an accurate genome sequence is not an easy task, and it is becoming more important as sequence deviations among, and even within, species highlight functional or evolutionary implications for comparative genomics.Takashi Matsumoto, Jianzhong Wu, Baltazar A. Antonio, and Takuji Sasaki© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/360874We 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.David Kuykendall, Jonathan Shao, and Kenneth Trimmer© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/286561Since Lander and Botstein proposed the interval mapping method for QTL mapping data analysis in 1989, tremendous progress has been made in the last many years to advance new and powerful statistical methods for QTL analysis. Recent research progress has been focused on statistical methods and issues for mapping multiple QTL together. In this article, we review this progress. We focus the discussion on the statistical methods for mapping multiple QTL by maximum likelihood and Bayesian methods and also on determining appropriate thresholds for the analysis.Wei Zou and Zhao-Bang Zeng© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/574927Compared to the conventional linkage mapping, linkage disequilibrium (LD)-mapping, using the nonrandom associations of loci in haplotypes, is a powerful high-resolution mapping tool for complex quantitative traits. The recent advances in the development of unbiased association mapping approaches for plant population with their successful applications in dissecting a number of simple to complex traits in many crop species demonstrate a flourish of the approach as a “powerful gene tagging” tool for crops in the plant genomics era of 21st century. The goal of this review is to provide nonexpert readers of crop breeding community with (1) the basic concept, merits, and simple description of existing methodologies for an association mapping with the recent improvements for plant populations, and (2) the details of some of pioneer and recent studies on association mapping in various crop species to demonstrate the feasibility, success, problems, and future perspectives of the efforts in plants. This should be helpful for interested readers of international plant research community as a guideline for the basic understanding, choosing the appropriate methods, and its application.Ibrokhim Y. Abdurakhmonov and Abdusattor Abdukarimov© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/147563Microarrays are a very powerful tool for quantifying the amount of RNA in samples; however, their ability to query essentially every gene in a genome, which can number in the tens of thousands, presents analytical and interpretative problems. As a result, a variety of software and web-based tools have been developed to help with these issues. This article highlights and reviews some of the tools for the first steps in the analysis of a microarray study. We have tried for a balance between free and commercial systems. We have organized the tools by topics including image processing tools (Section 2), power analysis tools (Section 3), image analysis tools (Section 4), database tools (Section 5), databases of functional information (Section 6), annotation tools (Section 7), statistical and data mining tools (Section 8), and dissemination tools (Section 9).Grier P. Page and Issa Coulibaly© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/524847Using 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.Bert C. Y. Collard, Casiana M. Vera Cruz, Kenneth L. McNally, Parminder S. Virk, and David J. Mackill© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/528361Citrus is one of the most widespread fruit crops globally, with great economic and health value. It is among the most difficult plants to improve through traditional breeding approaches. Currently, there is risk of devastation by diseases threatening to limit production and future availability to the human population. As technologies rapidly advance in genomic science, they are quickly adapted to address the biological challenges of the citrus plant system and the world's industries. The historical developments of linkage mapping, markers and breeding, EST projects, physical mapping, an international citrus genome sequencing project, and critical functional analysis are described. Despite the challenges of working with citrus, there has been substantial progress. Citrus researchers engaged in international collaborations provide optimism about future productivity and contributions to the benefit of citrus industries worldwide and to the human population who can rely on future widespread availability of this health-promoting and aesthetically pleasing fruit crop.Manuel Talon and Fred G. Gmitter Jr.© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/896451Wheat (Triticum aestivum L.), with a large genome (16000 Mb) and high proportion (∼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. K. Gupta, R. R. Mir, A. Mohan, and J. Kumar© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/369601The 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.Richard Bruskiewich, Martin Senger, Guy Davenport, Manuel Ruiz, Mathieu Rouard, Tom Hazekamp, Masaru Takeya, Koji Doi, Kouji Satoh, Marcos Costa, Reinhard Simon, Jayashree Balaji, Akinnola Akintunde, Ramil Mauleon, Samart Wanchana, Trushar Shah, Mylah Anacleto, Arllet Portugal, Victor Jun Ulat, Supat Thongjuea, Kyle Braak, Sebastian Ritter, Alexis Dereeper, Milko Skofic, Edwin Rojas, Natalia Martins, Georgios Pappas, Ryan Alamban, Roque Almodiel, Lord Hendrix Barboza, Jeffrey Detras, Kevin Manansala, Michael Jonathan Mendoza, Jeffrey Morales, Barry Peralta, Rowena Valerio, Yi Zhang, Sergio Gregorio, Joseph Hermocilla, Michael Echavez, Jan Michael Yap, Andrew Farmer, Gary Schiltz, Jennifer Lee, Terry Casstevens, Pankaj Jaiswal, Ayton Meintjes, Mark Wilkinson, Benjamin Good, James Wagner, Jane Morris, David Marshall, Anthony Collins, Shoshi Kikuchi, Thomas Metz, Graham McLaren, and Theo van Hintum© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/619832Functional annotation of novel sequence data is a primary requirement for the utilization of functional genomics approaches in plant research. In this paper, we describe the Blast2GO suite as a comprehensive bioinformatics tool for functional annotation of sequences and data mining on the resulting annotations, primarily based on the gene ontology (GO) vocabulary. Blast2GO optimizes function transfer from homologous sequences through an elaborate algorithm that considers similarity, the extension of the homology, the database of choice, the GO hierarchy, and the quality of the original annotations. The tool includes numerous functions for the visualization, management, and statistical analysis of annotation results, including gene set enrichment analysis. The application supports InterPro, enzyme codes, KEGG pathways, GO direct acyclic graphs (DAGs), and GOSlim. Blast2GO is a suitable tool for plant genomics research because of its versatility, easy installation, and friendly use.Ana Conesa and Stefan Götz© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/683509The 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.Stéphane Aris-Brosou and Xuhua Xia© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/362451Sorghum (Sorghum bicolor (L.) Moench) is a subject of plant genomics research based on its importance as one of the world's leading cereal crops, a biofuels crop of high and growing importance, a progenitor of one of the world's most noxious weeds, and a botanical model for many tropical grasses with complex genomes. A rich history of genome analysis, culminating in the recent complete sequencing of the genome of a leading inbred, provides a foundation for invigorating progress toward relating sorghum genes to their functions. Further characterization of the genomes other than Saccharinae cereals may shed light on mechanisms, levels, and patterns of evolution of genome size and structure, laying the foundation for further study of sugarcane and other economically important members of the group.Andrew H. Paterson© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/793158Legume 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) ~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 2,408 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 provides 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.David A. Lightfoot© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/231897We propose a Bayesian procedure to cluster temporal gene expression microarray profiles, based on a mixed-effect smoothing-spline model, and design a Gibbs sampler to sample from the desired posterior distribution. Our method can determine the cluster number automatically based on the Bayesian information criterion, and handle missing data easily. When applied to a microarray dataset on the budding yeast, our clustering algorithm provides biologically meaningful gene clusters according to a functional enrichment analysis.Ping Ma, Wenxuan Zhong, Yang Feng, and Jun S. Liu© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/892927Control-treatment design is widely used in microarray gene expression experiments. The purpose of such a design is to detect genes that express differentially between the control and the treatment. Many statistical procedures have been developed to detect differentially expressed genes, but all have pros and cons and room is still open for improvement. In this study, we propose a Bayesian mixture model approach to classifying genes into one of three clusters, corresponding to clusters of downregulated, neutral, and upregulated genes, respectively. The Bayesian method is implemented via the Markov chain Monte Carlo (MCMC) algorithm. The cluster means of down- and upregulated genes are sampled from truncated normal distributions whereas the cluster mean of the neutral genes is set to zero. Using simulated data as well as data from a real microarray experiment, we demonstrate that the new method outperforms all methods commonly used in differential expression analysis. Zhenyu Jia and Shizhong Xu© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/817210Detection of differentially expressed genes from expressed sequence tags (ESTs) data has received much attention. An empirical Bayesian method is introduced in which gene expression patterns are estimated and used to define detection statistics. Significantly differentially expressed genes can be declared given detection statistics. Simulation is done to evaluate the performance of proposed method. Two real applications are studied.Na You, Junmei Liu, and Chang Xuan Mao© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/486258Barley (Hordeum vulgare), first domesticated in the Near East, is a well-studied crop in terms of genetics, genomics, and breeding and qualifies as a model plant for Triticeae research. Recent advances made in barley genomics mainly include the following: (i) rapid accumulation of EST sequence data, (ii) growing number of studies on transcriptome, proteome, and metabolome, (iii) new modeling techniques, (iv) availability of genome-wide knockout collections as well as efficient transformation techniques, and (v) the recently started genome sequencing effort. These developments pave the way for a comprehensive functional analysis and understanding of gene expression networks linked to agronomically important traits. Here, we selectively review important technological developments in barley genomics and related fields and discuss the relevance for understanding genotype-phenotype relationships by using approaches such as genetical genomics and association studies. High-throughput genotyping platforms that have recently become available will allow the construction of high-density genetic maps that will further promote marker-assisted selection as well as physical map construction. Systems biology approaches will further enhance our knowledge and largely increase our abilities to design refined breeding strategies on the basis of detailed molecular physiological knowledge.Nese Sreenivasulu, Andreas Graner, and Ulrich Wobus© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2007/97386The purpose of this study was to determine whether the rates of tomato seed germination under different stress and nonstress conditions were under common genetic controls by examining quantitative trait loci (QTL) affecting such traits. Seeds of BC1 progeny of a cross between a slow-germinating tomato breeding line and a rapid-germinating tomato wild accession were evaluated for germination under nonstress as well as cold, salt, and drought stress conditions. In each treatment, the most rapidly-germinating seeds were selected, grown to maturity, and subjected to molecular marker analysis. A selective genotyping approach detected between 6 and 9 QTL affecting germination rate under each of the four conditions, with a total of 14 QTL identified. Ten QTL affected germination rate under 2 or 3 conditions, which were considered germination-related common QTL. Four QTL affected germination rate only in one treatment, which were considered germination-related, condition-specific QTL . The results indicated that mostly the same QTL affected seed germination under different stress and nonstress conditions, supporting a previous suggestion that similar physiological mechanisms contribute to rapid seed germination under different conditions. Marker-assisted selection for the common QTL may result in progeny with rapid seed germinability under different conditions.Majid R. Foolad, Prakash Subbiah, and Liping Zhang© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/536104Brachypodium 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.Bahar Sogutmaz Ozdemir, Pilar Hernandez, Ertugrul Filiz, and Hikmet Budak© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/820274Tomato (Solanum lycopersicum L.) is the most intensively investigated Solanaceous species both in genetic and genomics studies. It is a diploid species with a haploid set of 12 chromosomes and a small genome (950 Mb). Based on the detailed knowledge on tomato structural genomics, the sequencing of the euchromatic regions started in the year 2005 as a common effort of different countries. The manuscript focuses on markers used for tomato, on mapping efforts mainly based on exploitation of natural biodiversity, and it gives an updated report on the international sequencing activities. The principal tools developed to explore the function of tomato genes are also summarized, including mutagenesis, genetic transformation, and transcriptome analysis. The current progress in bioinformatic strategies available to manage the overwhelming amount of data generated from different tomato “omics” approaches is reported, and emphasis is given to the effort of producing a computational workbench for the analysis of the organization, as well as the functionality and evolution of the Solanaceae family.Amalia Barone, Maria Luisa Chiusano, Maria Raffaella Ercolano, Giovanni Giuliano, Silvana Grandillo, and Luigi Frusciante© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/582837Brassica rapa, which is closely related to Arabidopsis thaliana, is an important crop and a model plant for studying genome evolution via polyploidization. We report the current understanding of the genome structure of B. rapa and efforts for the whole-genome sequencing of the species. The tribe Brassicaceae, which comprises ca. 240 species, descended from a common hexaploid ancestor with a basic genome similar to that of Arabidopsis. Chromosome rearrangements, including fusions and/or fissions, resulted in the present-day “diploid” Brassica species with variation in chromosome number and phenotype. Triplicated genomic segments of B. rapa are collinear to those of A. thaliana with InDels. The genome triplication has led to an approximately 1.7-fold increase in the B. rapa gene number compared to that of A. thaliana. Repetitive DNA of B. rapa has also been extensively amplified and has diverged from that of A. thaliana. For its whole-genome sequencing, the Brassica rapa Genome Sequencing Project (BrGSP) consortium has developed suitable genomic resources and constructed genetic and physical maps. Ten chromosomes of B. rapa are being allocated to BrGSP consortium participants, and each chromosome will be sequenced by a BAC-by-BAC approach. Genome sequencing of B. rapa will offer a new perspective for plant biology and evolution in the context of polyploidization.Chang Pyo Hong, Soo-Jin Kwon, Jung Sun Kim, Tae-Jin Yang, Beom-Seok Park, and Yong Pyo Lim© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/742304Genome 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.Hong-Bin Zhang, Yaning Li, Baohua Wang, and Peng W. Chee© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/458732Sugarcane is a highly productive crop used for centuries as the main source of sugar and recently to produce ethanol, a renewable bio-fuel energy source. There is increased interest in this crop due to the impending need to decrease fossil fuel usage. Sugarcane has a highly polyploid genome. Expressed sequence tag (EST) sequencing has significantly contributed to gene discovery and expression studies used to associate function with sugarcane genes. A significant amount of data exists on regulatory events controlling responses to herbivory, drought, and phosphate deficiency, which cause important constraints on yield and on endophytic bacteria, which are highly beneficial. The means to reduce drought, phosphate deficiency, and herbivory by the sugarcane borer have a negative impact on the environment. Improved tolerance for these constraints is being sought. Sugarcane's ability to accumulate sucrose up to 16% of its culm dry weight is a challenge for genetic manipulation. Genome-based technology such as cDNA microarray data indicates genes associated with sugar content that may be used to develop new varieties improved for sucrose content or for traits that restrict the expansion of the cultivated land. The genes can also be used as molecular markers of agronomic traits in traditional breeding programs.M. Menossi, M. C. Silva-Filho, M. Vincentz, M.-A. Van-Sluys, and G. M. Souza© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/256597Legume rotation has allowed a consistent increase in crop yield and consequently in human population since the antiquity. Legumes will also be instrumental in our ability to maintain the sustainability of our agriculture while facing the challenges of increasing food and biofuel demand. Medicago truncatula and Lotus japonicus have emerged during the last decade as two major model systems for legume biology. Initially developed to dissect plant-microbe symbiotic interactions and especially legume nodulation, these two models are now widely used in a variety of biological fields from plant physiology and development to population genetics and structural genomics. This review highlights the genetic and genomic tools available to the M. truncatula community. Comparative genomic approaches to transfer biological information between model systems and legume crops are also discussed.Jean-Michel Ané, Hongyan Zhu, and Julia Frugoli© 2008, Hindawi Publishing Corporation. All rights reserved.