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Featured researches published by Kevin L. Childs.


Nucleic Acids Research | 2007

The TIGR Rice Genome Annotation Resource: improvements and new features

Shu Ouyang; Wei Zhu; John A. Hamilton; Haining Lin; Matthew Campbell; Kevin L. Childs; Françoise Thibaud-Nissen; Renae L. Malek; Yuandan Lee; Li Zheng; Joshua Orvis; Brian J. Haas; Jennifer R. Wortman; C. Robin Buell

In The Institute for Genomic Research Rice Genome Annotation project (), we have continued to update the rice genome sequence with new data and improve the quality of the annotation. In our current release of annotation (Release 4.0; January 12, 2006), we have identified 42 653 non-transposable element-related genes encoding 49 472 gene models as a result of the detection of alternative splicing. We have refined our identification methods for transposable element-related genes resulting in 13 237 genes that are related to transposable elements. Through incorporation of multiple transcript and proteomic expression data sets, we have been able to annotate 24 799 genes (31 739 gene models), representing ∼50% of the total gene models, as expressed in the rice genome. All structural and functional annotation is viewable through our Rice Genome Browser which currently supports 59 tracks. Enhanced data access is available through web interfaces, FTP downloads and a Data Extractor tool developed in order to support discrete dataset downloads.


Rice | 2013

Improvement of the Oryza sativa Nipponbare reference genome using next generation sequence and optical map data

Yoshihiro Kawahara; Melissa de la Bastide; John P. Hamilton; Hiroyuki Kanamori; W. Richard McCombie; Shu Ouyang; David C. Schwartz; Tsuyoshi Tanaka; Jianzhong Wu; Shiguo Zhou; Kevin L. Childs; Rebecca M. Davidson; Haining Lin; L. M. Quesada-Ocampo; Brieanne Vaillancourt; Hiroaki Sakai; Sung Shin Lee; Jungsok Kim; Hisataka Numa; Takeshi Itoh; C. Robin Buell; Takashi Matsumoto

BackgroundRice research has been enabled by access to the high quality reference genome sequence generated in 2005 by the International Rice Genome Sequencing Project (IRGSP). To further facilitate genomic-enabled research, we have updated and validated the genome assembly and sequence for the Nipponbare cultivar of Oryza sativa (japonica group).ResultsThe Nipponbare genome assembly was updated by revising and validating the minimal tiling path of clones with the optical map for rice. Sequencing errors in the revised genome assembly were identified by re-sequencing the genome of two different Nipponbare individuals using the Illumina Genome Analyzer II/IIx platform. A total of 4,886 sequencing errors were identified in 321 Mb of the assembled genome indicating an error rate in the original IRGSP assembly of only 0.15 per 10,000 nucleotides. A small number (five) of insertions/deletions were identified using longer reads generated using the Roche 454 pyrosequencing platform. As the re-sequencing data were generated from two different individuals, we were able to identify a number of allelic differences between the original individual used in the IRGSP effort and the two individuals used in the re-sequencing effort. The revised assembly, termed Os-Nipponbare-Reference-IRGSP-1.0, is now being used in updated releases of the Rice Annotation Project and the Michigan State University Rice Genome Annotation Project, thereby providing a unified set of pseudomolecules for the rice community.ConclusionsA revised, error-corrected, and validated assembly of the Nipponbare cultivar of rice was generated using optical map data, re-sequencing data, and manual curation that will facilitate on-going and future research in rice. Detection of polymorphisms between three different Nipponbare individuals highlights that allelic differences between individuals should be considered in diversity studies.


Proceedings of the National Academy of Sciences of the United States of America | 2009

Genomewide SNP variation reveals relationships among landraces and modern varieties of rice.

Kenneth L. McNally; Kevin L. Childs; Regina Bohnert; Rebecca M. Davidson; Keyan Zhao; Victor Jun Ulat; Georg Zeller; Richard M. Clark; Douglas R. Hoen; Thomas E. Bureau; Renee Stokowski; Dennis G. Ballinger; Kelly A. Frazer; D. R. Cox; Badri Padhukasahasram; Carlos Bustamante; Detlef Weigel; David J. Mackill; Richard Bruskiewich; Gunnar Rätsch; C. Robin Buell; Hei Leung; Jan E. Leach

Rice, the primary source of dietary calories for half of humanity, is the first crop plant for which a high-quality reference genome sequence from a single variety was produced. We used resequencing microarrays to interrogate 100 Mb of the unique fraction of the reference genome for 20 diverse varieties and landraces that capture the impressive genotypic and phenotypic diversity of domesticated rice. Here, we report the distribution of 160,000 nonredundant SNPs. Introgression patterns of shared SNPs revealed the breeding history and relationships among the 20 varieties; some introgressed regions are associated with agronomic traits that mark major milestones in rice improvement. These comprehensive SNP data provide a foundation for deep exploration of rice diversity and gene–trait relationships and their use for future rice improvement.


Plant Journal | 2011

Genome-wide atlas of transcription during maize development

Rajandeep S. Sekhon; Haining Lin; Kevin L. Childs; Candice N. Hansey; C. Robin Buell; Natalia de Leon; Shawn M. Kaeppler

Maize is an important model species and a major constituent of human and animal diets. It has also emerged as a potential feedstock and model system for bioenergy research due to recent worldwide interest in developing plant biomass-based, carbon-neutral liquid fuels. To understand how the underlying genome sequence results in specific plant phenotypes, information on the temporal and spatial transcription patterns of genes is crucial. Here we present a comprehensive atlas of global transcription profiles across developmental stages and plant organs. We used a NimbleGen microarray containing 80,301 probe sets to profile transcription patterns in 60 distinct tissues representing 11 major organ systems of inbred line B73. Of the 30,892 probe sets representing the filtered B73 gene models, 91.4% were expressed in at least one tissue. Interestingly, 44.5% of the probe sets were expressed in all tissues, indicating a substantial overlap of gene expression among plant organs. Clustering of maize tissues based on global gene expression profiles resulted in formation of groups of biologically related tissues. We utilized this dataset to examine the expression of genes that encode enzymes in the lignin biosynthetic pathway, and found that expansion of distinct gene families was accompanied by divergent, tissue-specific transcription patterns of the paralogs. This comprehensive expression atlas represents a valuable resource for gene discovery and functional characterization in maize.


PLOS Genetics | 2012

Genome, Functional Gene Annotation, and Nuclear Transformation of the Heterokont Oleaginous Alga Nannochloropsis oceanica CCMP1779

Astrid Vieler; Guangxi Wu; Chia Hong Tsai; Blair Bullard; Adam J. Cornish; Christopher M. Harvey; Ida Barbara Reca; Chelsea K. Thornburg; Rujira Achawanantakun; Christopher J. Buehl; Michael S. Campbell; David Cavalier; Kevin L. Childs; Teresa J. Clark; Rahul R. Deshpande; Erika Erickson; Ann A. Ferguson; Witawas Handee; Que Kong; Xiaobo Li; Bensheng Liu; Steven Lundback; Cheng Peng; Rebecca L. Roston; Sanjaya; Jeffrey P. Simpson; Allan D. TerBush; Jaruswan Warakanont; Simone Zäuner; Eva M. Farré

Unicellular marine algae have promise for providing sustainable and scalable biofuel feedstocks, although no single species has emerged as a preferred organism. Moreover, adequate molecular and genetic resources prerequisite for the rational engineering of marine algal feedstocks are lacking for most candidate species. Heterokonts of the genus Nannochloropsis naturally have high cellular oil content and are already in use for industrial production of high-value lipid products. First success in applying reverse genetics by targeted gene replacement makes Nannochloropsis oceanica an attractive model to investigate the cell and molecular biology and biochemistry of this fascinating organism group. Here we present the assembly of the 28.7 Mb genome of N. oceanica CCMP1779. RNA sequencing data from nitrogen-replete and nitrogen-depleted growth conditions support a total of 11,973 genes, of which in addition to automatic annotation some were manually inspected to predict the biochemical repertoire for this organism. Among others, more than 100 genes putatively related to lipid metabolism, 114 predicted transcription factors, and 109 transcriptional regulators were annotated. Comparison of the N. oceanica CCMP1779 gene repertoire with the recently published N. gaditana genome identified 2,649 genes likely specific to N. oceanica CCMP1779. Many of these N. oceanica–specific genes have putative orthologs in other species or are supported by transcriptional evidence. However, because similarity-based annotations are limited, functions of most of these species-specific genes remain unknown. Aside from the genome sequence and its analysis, protocols for the transformation of N. oceanica CCMP1779 are provided. The availability of genomic and transcriptomic data for Nannochloropsis oceanica CCMP1779, along with efficient transformation protocols, provides a blueprint for future detailed gene functional analysis and genetic engineering of Nannochloropsis species by a growing academic community focused on this genus.


Nucleic Acids Research | 2007

The TIGR Plant Transcript Assemblies database

Kevin L. Childs; John P. Hamilton; Wei Zhu; Eugene Ly; Foo Cheung; Hank Wu; Pablo D. Rabinowicz; Christopher D. Town; C. Robin Buell; Agnes P. Chan

The TIGR Plant Transcript Assemblies (TA) database () uses expressed sequences collected from the NCBI GenBank Nucleotide database for the construction of transcript assemblies. The sequences collected include expressed sequence tags (ESTs) and full-length and partial cDNAs, but exclude computationally predicted gene sequences. The TA database includes all plant species for which more than 1000 EST or cDNA sequences are publicly available. The EST and cDNA sequences are first clustered based on an all-versus-all pairwise sequence comparison, followed by the generation of consensus sequences (TAs) from individual clusters. The clustering and assembly procedures use the TGICL tool, Megablast and the CAP3 assembler. The UniProt Reference Clusters (UniRef100) protein database is used as the reference database for the functional annotation of the assemblies. The transcription orientation of each TA is determined based on the orientation of the alignment with the best protein hit. The TA sequences and annotation are available via web interfaces and FTP downloads. Assemblies can be retrieved by a text-based keyword search or a sequence-based BLAST search. The current version of the TA database is Release 2 (July 17, 2006) and includes a total of 215 plant species.


Plant Physiology | 1997

The Sorghum Photoperiod Sensitivity Gene, Ma3, Encodes a Phytochrome B'

Kevin L. Childs; Frederick Miller; Marie Michèle Cordonnier-Pratt; Lee H. Pratt; Page W. Morgan; John E. Mullet

The Ma3 gene is one of six genes that regulate the photoperiodic sensitivity of flowering in sorghum (Sorghum bicolor [L.] Moench). The ma3R mutation of this gene causes a phenotype that is similar to plants that are known to lack phytochrome B, and ma3R sorghum lacks a 123-kD phytochrome that predominates in light-grown plants and that is present in non-ma3R plants. A population segregating for Ma3 and ma3R was created and used to identify two randomly amplified polymorphic DNA markers linked to Ma3. These two markers were cloned and mapped in a recombinant inbred population as restriction fragment length polymorphisms. cDNA clones of PHYA and PHYC were cloned and sequenced from a cDNA library prepared from green sorghum leaves. Using a genome-walking technique, a 7941-bp partial sequence of PHYB was determined from genomic DNA from ma3R sorghum. PHYA, PHYB, and PHYC all mapped to the same linkage group. The Ma3- linked markers mapped with PHYB more than 121 centimorgans from PHYA and PHYC. A frameshift mutation resulting in a premature stop codon was found in the PHYB sequence from ma3R sorghum. Therefore, we conclude that the Ma3 locus in sorghum is a PHYB gene that encodes a 123-kD phytochrome.


Nucleic Acids Research | 2011

Hymenoptera Genome Database: integrated community resources for insect species of the order Hymenoptera

Monica Munoz-Torres; Justin T. Reese; Christopher P. Childers; Anna K. Bennett; Jaideep P. Sundaram; Kevin L. Childs; Juan M. Anzola; Natalia V. Milshina; Christine G. Elsik

The Hymenoptera Genome Database (HGD) is a comprehensive model organism database that caters to the needs of scientists working on insect species of the order Hymenoptera. This system implements open-source software and relational databases providing access to curated data contributed by an extensive, active research community. HGD contains data from 9 different species across ∼200 million years in the phylogeny of Hymenoptera, allowing researchers to leverage genetic, genome sequence and gene expression data, as well as the biological knowledge of related model organisms. The availability of resources across an order greatly facilitates comparative genomics and enhances our understanding of the biology of agriculturally important Hymenoptera species through genomics. Curated data at HGD includes predicted and annotated gene sets supported with evidence tracks such as ESTs/cDNAs, small RNA sequences and GC composition domains. Data at HGD can be queried using genome browsers and/or BLAST/PSI-BLAST servers, and it may also be downloaded to perform local searches. We encourage the public to access and contribute data to HGD at: http://HymenopteraGenome.org.


Plant Physiology | 2014

MAKER-P: A Tool Kit for the Rapid Creation, Management, and Quality Control of Plant Genome Annotations

Michael S. Campbell; MeiYee Law; Carson Holt; Joshua C. Stein; Gaurav D. Moghe; David E. Hufnagel; Jikai Lei; Rujira Achawanantakun; Dian Jiao; Carolyn J. Lawrence; Doreen Ware; Shin Han Shiu; Kevin L. Childs; Yanni Sun; Ning Jiang; Mark Yandell

MAKER-P annotates the entire Arabidopsis and maize genomes in less than 3 h with comparable quality to the current TAIR10 and maize V2 annotation builds. We have optimized and extended the widely used annotation engine MAKER in order to better support plant genome annotation efforts. New features include better parallelization for large repeat-rich plant genomes, noncoding RNA annotation capabilities, and support for pseudogene identification. We have benchmarked the resulting software tool kit, MAKER-P, using the Arabidopsis (Arabidopsis thaliana) and maize (Zea mays) genomes. Here, we demonstrate the ability of the MAKER-P tool kit to automatically update, extend, and revise the Arabidopsis annotations in light of newly available data and to annotate pseudogenes and noncoding RNAs absent from The Arabidopsis Informatics Resource 10 build. Our results demonstrate that MAKER-P can be used to manage and improve the annotations of even Arabidopsis, perhaps the best-annotated plant genome. We have also installed and benchmarked MAKER-P on the Texas Advanced Computing Center. We show that this public resource can de novo annotate the entire Arabidopsis and maize genomes in less than 3 h and produce annotations of comparable quality to those of the current The Arabidopsis Information Resource 10 and maize V2 annotation builds.


PLOS ONE | 2012

Development of transcriptomic resources for interrogating the biosynthesis of monoterpene indole alkaloids in medicinal plant species.

Elsa Góngora-Castillo; Kevin L. Childs; Greg Fedewa; John P. Hamilton; David K. Liscombe; Maria Magallanes-Lundback; Kranthi K. Mandadi; Ezekiel Nims; Weerawat Runguphan; Brieanne Vaillancourt; Marina Varbanova-Herde; Dean DellaPenna; Thomas D. McKnight; Sarah E. O’Connor; C. Robin Buell

The natural diversity of plant metabolism has long been a source for human medicines. One group of plant-derived compounds, the monoterpene indole alkaloids (MIAs), includes well-documented therapeutic agents used in the treatment of cancer (vinblastine, vincristine, camptothecin), hypertension (reserpine, ajmalicine), malaria (quinine), and as analgesics (7-hydroxymitragynine). Our understanding of the biochemical pathways that synthesize these commercially relevant compounds is incomplete due in part to a lack of molecular, genetic, and genomic resources for the identification of the genes involved in these specialized metabolic pathways. To address these limitations, we generated large-scale transcriptome sequence and expression profiles for three species of Asterids that produce medicinally important MIAs: Camptotheca acuminata, Catharanthus roseus, and Rauvolfia serpentina. Using next generation sequencing technology, we sampled the transcriptomes of these species across a diverse set of developmental tissues, and in the case of C. roseus, in cultured cells and roots following elicitor treatment. Through an iterative assembly process, we generated robust transcriptome assemblies for all three species with a substantial number of the assembled transcripts being full or near-full length. The majority of transcripts had a related sequence in either UniRef100, the Arabidopsis thaliana predicted proteome, or the Pfam protein domain database; however, we also identified transcripts that lacked similarity with entries in either database and thereby lack a known function. Representation of known genes within the MIA biosynthetic pathway was robust. As a diverse set of tissues and treatments were surveyed, expression abundances of transcripts in the three species could be estimated to reveal transcripts associated with development and response to elicitor treatment. Together, these transcriptomes and expression abundance matrices provide a rich resource for understanding plant specialized metabolism, and promotes realization of innovative production systems for plant-derived pharmaceuticals.

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C. Robin Buell

Michigan State University

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Shawn M. Kaeppler

University of Wisconsin-Madison

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Haining Lin

Michigan State University

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Robert R. Klein

Agricultural Research Service

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