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Featured researches published by Lukas A. Mueller.


Nucleic Acids Research | 2003

The Arabidopsis Information Resource (TAIR): a model organism database providing a centralized, curated gateway to Arabidopsis biology, research materials and community

Seung Y. Rhee; William D. Beavis; Tanya Z. Berardini; Guanghong Chen; David A. Dixon; Aisling Doyle; Margarita Garcia-Hernandez; Eva Huala; Gabriel C. Lander; Mary Montoya; Neil Miller; Lukas A. Mueller; Suparna Mundodi; Leonore Reiser; Julie Tacklind; Dan C. Weems; Yihe Wu; Iris Xu; Daniel Yoo; Jungwon Yoon; Peifen Zhang

Arabidopsis thaliana is the most widely-studied plant today. The concerted efforts of over 11 000 researchers and 4000 organizations around the world are generating a rich diversity and quantity of information and materials. This information is made available through a comprehensive on-line resource called the Arabidopsis Information Resource (TAIR) (http://arabidopsis.org), which is accessible via commonly used web browsers and can be searched and downloaded in a number of ways. In the last two years, efforts have been focused on increasing data content and diversity, functionally annotating genes and gene products with controlled vocabularies, and improving data retrieval, analysis and visualization tools. New information include sequence polymorphisms including alleles, germplasms and phenotypes, Gene Ontology annotations, gene families, protein information, metabolic pathways, gene expression data from microarray experiments and seed and DNA stocks. New data visualization and analysis tools include SeqViewer, which interactively displays the genome from the whole chromosome down to 10 kb of nucleotide sequence and AraCyc, a metabolic pathway database and map tool that allows overlaying expression data onto the pathway diagrams. Finally, we have recently incorporated seed and DNA stock information from the Arabidopsis Biological Resource Center (ABRC) and implemented a shopping-cart style on-line ordering system.


Nucleic Acids Research | 2004

MetaCyc: a multiorganism database of metabolic pathways and enzymes.

Cynthia J. Krieger; Peifen Zhang; Lukas A. Mueller; Alfred Wang; Suzanne M. Paley; Martha Arnaud; John Pick; Seung Y. Rhee; Peter D. Karp

The MetaCyc database (see URL http://MetaCyc.org) is a collection of metabolic pathways and enzymes from a wide variety of organisms, primarily microorganisms and plants. The goal of MetaCyc is to contain a representative sample of each experimentally elucidated pathway, and thereby to catalog the universe of metabolism. MetaCyc also describes reactions, chemical compounds and genes. Many of the pathways and enzymes in MetaCyc contain extensive information, including comments and literature citations. SRIs Pathway Tools software supports querying, visualization and curation of MetaCyc. With its wide breadth and depth of metabolic information, MetaCyc is a valuable resource for a variety of applications. MetaCyc is the reference database of pathways and enzymes that is used in conjunction with SRIs metabolic pathway prediction program to create Pathway/Genome Databases that can be augmented with curation from the scientific literature and published on the world wide web. MetaCyc also serves as a readily accessible comprehensive resource on microbial and plant pathways for genome analysis, basic research, education, metabolic engineering and systems biology. In the past 2 years the data content and the Pathway Tools software used to query, visualize and edit MetaCyc have been expanded significantly. These enhancements are described in this paper.


Plant Physiology | 2004

Functional Annotation of the Arabidopsis Genome Using Controlled Vocabularies

Tanya Z. Berardini; Suparna Mundodi; Leonore Reiser; Eva Huala; Margarita Garcia-Hernandez; Peifen Zhang; Lukas A. Mueller; Jungwoon Yoon; Aisling Doyle; Gabriel C. Lander; Nick Moseyko; Danny Yoo; Iris Xu; Brandon Zoeckler; Mary Montoya; Neil Miller; Dan C. Weems; Seung Y. Rhee

Controlled vocabularies are increasingly used by databases to describe genes and gene products because they facilitate identification of similar genes within an organism or among different organisms. One of The Arabidopsis Information Resources goals is to associate all Arabidopsis genes with terms developed by the Gene Ontology Consortium that describe the molecular function, biological process, and subcellular location of a gene product. We have also developed terms describing Arabidopsis anatomy and developmental stages and use these to annotate published gene expression data. As of March 2004, we used computational and manual annotation methods to make 85,666 annotations representing 26,624 unique loci. We focus on associating genes to controlled vocabulary terms based on experimental data from the literature and use The Arabidopsis Information Resource-developed PubSearch software to facilitate this process. Each annotation is tagged with a combination of evidence codes, evidence descriptions, and references that provide a robust means to assess data quality. Annotation of all Arabidopsis genes will allow quantitative comparisons between sets of genes derived from sources such as microarray experiments. The Arabidopsis annotation data will also facilitate annotation of newly sequenced plant genomes by using sequence similarity to transfer annotations to homologous genes. In addition, complete and up-to-date annotations will make unknown genes easy to identify and target for experimentation. Here, we describe the process of Arabidopsis functional annotation using a variety of data sources and illustrate several ways in which this information can be accessed and used to infer knowledge about Arabidopsis and other plant species.


Plant Physiology | 2005

The SOL Genomics Network. A Comparative Resource for Solanaceae Biology and Beyond

Lukas A. Mueller; Teri H. Solow; Nicolas L. Taylor; Beth Skwarecki; Robert M. Buels; John Binns; Chenwei Lin; Mark H. Wright; Robert Ahrens; Ying Wang; Evan V. Herbst; Emil Keyder; Naama Menda; Dani Zamir; Steven D. Tanksley

The SOL Genomics Network (SGN; http://sgn.cornell.edu) is a rapidly evolving comparative resource for the plants of the Solanaceae family, which includes important crop and model plants such as potato (Solanum tuberosum), eggplant (Solanum melongena), pepper (Capsicum annuum), and tomato (Solanum lycopersicum). The aim of SGN is to relate these species to one another using a comparative genomics approach and to tie them to the other dicots through the fully sequenced genome of Arabidopsis (Arabidopsis thaliana). SGN currently houses map and marker data for Solanaceae species, a large expressed sequence tag collection with computationally derived unigene sets, an extensive database of phenotypic information for a mutagenized tomato population, and associated tools such as real-time quantitative trait loci. Recently, the International Solanaceae Project (SOL) was formed as an umbrella organization for Solanaceae research in over 30 countries to address important questions in plant biology. The first cornerstone of the SOL project is the sequencing of the entire euchromatic portion of the tomato genome. SGN is collaborating with other bioinformatics centers in building the bioinformatics infrastructure for the tomato sequencing project and implementing the bioinformatics strategy of the larger SOL project. The overarching goal of SGN is to make information available in an intuitive comparative format, thereby facilitating a systems approach to investigations into the basis of adaptation and phenotypic diversity in the Solanaceae family, other species in the Asterid clade such as coffee (Coffea arabica), Rubiaciae, and beyond.


Nature Genetics | 2013

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

Shaogui Guo; Jianguo Zhang; Honghe Sun; Jérôme Salse; William J. Lucas; Haiying Zhang; Yi Zheng; Linyong Mao; Yi Ren; Zhiwen Wang; Jiumeng Min; Xiaosen Guo; Florent Murat; Byung-Kook Ham; Zhaoliang Zhang; Shan Gao; Mingyun Huang; Yimin Xu; Silin Zhong; Aureliano Bombarely; Lukas A. Mueller; Hong Zhao; Hongju He; Zhang Y; Zhonghua Zhang; Sanwen Huang; Tao Tan; Erli Pang; Kui Lin; Qun Hu

Watermelon, Citrullus lanatus, is an important cucurbit crop grown throughout the world. Here we report a high-quality draft genome sequence of the east Asia watermelon cultivar 97103 (2n = 2× = 22) containing 23,440 predicted protein-coding genes. Comparative genomics analysis provided an evolutionary scenario for the origin of the 11 watermelon chromosomes derived from a 7-chromosome paleohexaploid eudicot ancestor. Resequencing of 20 watermelon accessions representing three different C. lanatus subspecies produced numerous haplotypes and identified the extent of genetic diversity and population structure of watermelon germplasm. Genomic regions that were preferentially selected during domestication were identified. Many disease-resistance genes were also found to be lost during domestication. In addition, integrative genomic and transcriptomic analyses yielded important insights into aspects of phloem-based vascular signaling in common between watermelon and cucumber and identified genes crucial to valuable fruit-quality traits, including sugar accumulation and citrulline metabolism.


Genetics | 2006

Combining Bioinformatics and Phylogenetics to Identify Large Sets of Single-Copy Orthologous Genes (COSII) for Comparative, Evolutionary and Systematic Studies: A Test Case in the Euasterid Plant Clade

Feinan Wu; Lukas A. Mueller; Dominique Crouzillat; Vincent Petiard; Steven D. Tanksley

We report herein the application of a set of algorithms to identify a large number (2869) of single-copy orthologs (COSII), which are shared by most, if not all, euasterid plant species as well as the model species Arabidopsis. Alignments of the orthologous sequences across multiple species enabled the design of “universal PCR primers,” which can be used to amplify the corresponding orthologs from a broad range of taxa, including those lacking any sequence databases. Functional annotation revealed that these conserved, single-copy orthologs encode a higher-than-expected frequency of proteins transported and utilized in organelles and a paucity of proteins associated with cell walls, protein kinases, transcription factors, and signal transduction. The enabling power of this new ortholog resource was demonstrated in phylogenetic studies, as well as in comparative mapping across the plant families tomato (family Solanaceae) and coffee (family Rubiaceae). The combined results of these studies provide compelling evidence that (1) the ancestral species that gave rise to the core euasterid families Solanaceae and Rubiaceae had a basic chromosome number of x = 11 or 12.2) No whole-genome duplication event (i.e., polyploidization) occurred immediately prior to or after the radiation of either Solanaceae or Rubiaceae as has been recently suggested.


Plant Physiology | 2005

MetaCyc and AraCyc. Metabolic Pathway Databases for Plant Research

Peifen Zhang; Hartmut Foerster; Christophe Tissier; Lukas A. Mueller; Suzanne M. Paley; Peter D. Karp; Seung Y. Rhee

MetaCyc (http://metacyc.org) contains experimentally determined biochemical pathways to be used as a reference database for metabolism. In conjunction with the Pathway Tools software, MetaCyc can be used to computationally predict the metabolic pathway complement of an annotated genome. To increase the breadth of pathways and enzymes, more than 60 plant-specific pathways have been added or updated in MetaCyc recently. In contrast to MetaCyc, which contains metabolic data for a wide range of organisms, AraCyc is a species-specific database containing only enzymes and pathways found in the model plant Arabidopsis (Arabidopsis thaliana). AraCyc (http://arabidopsis.org/tools/aracyc/) was the first computationally predicted plant metabolism database derived from MetaCyc. Since its initial computational build, AraCyc has been under continued curation to enhance data quality and to increase breadth of pathway coverage. Twenty-eight pathways have been manually curated from the literature recently. Pathway predictions in AraCyc have also been recently updated with the latest functional annotations of Arabidopsis genes that use controlled vocabulary and literature evidence. AraCyc currently features 1,418 unique genes mapped onto 204 pathways with 1,156 literature citations. The Omics Viewer, a user data visualization and analysis tool, allows a list of genes, enzymes, or metabolites with experimental values to be painted on a diagram of the full pathway map of AraCyc. Other recent enhancements to both MetaCyc and AraCyc include implementation of an evidence ontology, which has been used to provide information on data quality, expansion of the secondary metabolism node of the pathway ontology to accommodate curation of secondary metabolic pathways, and enhancement of the cellular component ontology for storing and displaying enzyme and pathway locations within subcellular compartments.


Nucleic Acids Research | 2011

The Sol Genomics Network (solgenomics.net): growing tomatoes using Perl

Aureliano Bombarely; Naama Menda; Isaak Y. Tecle; Robert M. Buels; Susan R. Strickler; Thomas Fischer-York; Anuradha Pujar; Jonathan Leto; Joseph Gosselin; Lukas A. Mueller

The Sol Genomics Network (SGN; http://solgenomics.net/) is a clade-oriented database (COD) containing biological data for species in the Solanaceae and their close relatives, with data types ranging from chromosomes and genes to phenotypes and accessions. SGN hosts several genome maps and sequences, including a pre-release of the tomato (Solanum lycopersicum cv Heinz 1706) reference genome. A new transcriptome component has been added to store RNA-seq and microarray data. SGN is also an open source software project, continuously developing and improving a complex system for storing, integrating and analyzing data. All code and development work is publicly visible on GitHub (http://github.com). The database architecture combines SGN-specific schemas and the community-developed Chado schema (http://gmod.org/wiki/Chado) for compatibility with other genome databases. The SGN curation model is community-driven, allowing researchers to add and edit information using simple web tools. Currently, over a hundred community annotators help curate the database. SGN can be accessed at http://solgenomics.net/.


Molecular Plant-microbe Interactions | 2012

A Draft Genome Sequence of Nicotiana benthamiana to Enhance Molecular Plant-Microbe Biology Research

Aureliano Bombarely; Hernan G. Rosli; Julia Vrebalov; Peter Moffett; Lukas A. Mueller; Gregory B. Martin

Nicotiana benthamiana is a widely used model plant species for the study of fundamental questions in molecular plant-microbe interactions and other areas of plant biology. This popularity derives from its well-characterized susceptibility to diverse pathogens and, especially, its amenability to virus-induced gene silencing and transient protein expression methods. Here, we report the generation of a 63-fold coverage draft genome sequence of N. benthamiana and its availability on the Sol Genomics Network for both BLAST searches and for downloading to local servers. The estimated genome size of N. benthamiana is 3 Gb (gigabases). The current assembly consists of approximately 141,000 scaffolds, spanning 2.6 Gb with 50% of the genome sequence contained within scaffolds >89 kilobases. Of the approximately 16,000 N. benthamiana unigenes available in GenBank, >90% are represented in the assembly. The usefulness of the sequence was demonstrated by the retrieval of N. benthamiana orthologs for 24 immunity-associated genes from other species including Ago2, Ago7, Bak1, Bik1, Crt1, Fls2, Pto, Prf, Rar1, and mitogen-activated protein kinases. The sequence will also be useful for comparative genomics in the Solanaceae family as shown here by the discovery of microsynteny between N. benthamiana and tomato in the region encompassing the Pto and Prf genes.


Nucleic Acids Research | 2015

The Sol Genomics Network (SGN)—from genotype to phenotype to breeding

Noe Fernandez-Pozo; Naama Menda; Jeremy D. Edwards; Surya Saha; Isaak Y. Tecle; Susan R. Strickler; Aureliano Bombarely; Thomas Fisher-York; Anuradha Pujar; Hartmut Foerster; Aimin Yan; Lukas A. Mueller

The Sol Genomics Network (SGN, http://solgenomics.net) is a web portal with genomic and phenotypic data, and analysis tools for the Solanaceae family and close relatives. SGN hosts whole genome data for an increasing number of Solanaceae family members including tomato, potato, pepper, eggplant, tobacco and Nicotiana benthamiana. The database also stores loci and phenotype data, which researchers can upload and edit with user-friendly web interfaces. Tools such as BLAST, GBrowse and JBrowse for browsing genomes, expression and map data viewers, a locus community annotation system and a QTL analysis tools are available. A new tool was recently implemented to improve Virus-Induced Gene Silencing (VIGS) constructs called the SGN VIGS tool. With the growing genomic and phenotypic data in the database, SGN is now advancing to develop new web-based breeding tools and implement the code and database structure for other species or clade-specific databases.

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Naama Menda

Boyce Thompson Institute for Plant Research

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Susan R. Strickler

Boyce Thompson Institute for Plant Research

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Noe Fernandez-Pozo

Boyce Thompson Institute for Plant Research

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Seung Y. Rhee

Carnegie Institution for Science

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James J. Giovannoni

Boyce Thompson Institute for Plant Research

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Peifen Zhang

Carnegie Institution for Science

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