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Search Results: 1 - 4 of 4 matches for " Gynheung An "
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Deep sequencing reveals the complex and coordinated transcriptional regulation of genes related to grain quality in rice cultivars
R C Venu, M V Sreerekha, Kan Nobuta, André Beló, Yuese Ning, Gynheung An, Blake C Meyers, Guo-Liang Wang
BMC Genomics , 2011, DOI: 10.1186/1471-2164-12-190
Abstract: The transcriptomes revealed by MPSS and SBS had a high correlation co-efficient (0.81 to 0.90), and about 70% of the transcripts were commonly identified in both types of the libraries. SBS, however, identified 30% more transcripts than MPSS. Among the highly expressed genes in Cypress and Ilpumbyeo, over 100 conserved cis regulatory elements were identified. Numerous specifically expressed transcription factor (TF) genes were identified in Cypress (282), LaGrue (312), Ilpumbyeo (363), YR15965 (260), and Nipponbare (357). Many key grain quality-related genes (i.e., genes involved in starch metabolism, aspartate amino acid metabolism, storage and allergenic protein synthesis, and seed maturation) that were expressed at high levels underwent alternative splicing and produced antisense transcripts either in Cypress or Ilpumbyeo. Further, a time course RT-PCR analysis confirmed a higher expression level of genes involved in starch metabolism such as those encoding ADP glucose pyrophosphorylase (AGPase) and granule bound starch synthase I (GBSS I) in Cypress than that in LaGrue during early seed development.This study represents the most comprehensive analysis of the developing seed transcriptome of rice available to date. Using two high throughput sequencing methods, we identified many differentially expressed genes that may affect milling yield or eating quality in rice. Many of the identified genes are involved in the biosynthesis of starch, aspartate family amino acids, and storage proteins. Some of the differentially expressed genes could be useful for the development of molecular markers if they are located in a known QTL region for milling yield or eating quality in the rice genome. Therefore, our comprehensive and deep survey of the developing seed transcriptome in five rice cultivars has provided a rich genomic resource for further elucidating the molecular basis of grain quality in rice.Rice is the staple food crop of more than 50% of the global population, and
Identification and Functional Analysis of Light-Responsive Unique Genes and Gene Family Members in Rice
Ki-Hong Jung,Jinwon Lee,Chris Dardick,Young-Su Seo,Peijian Cao,Patrick Canlas,Jirapa Phetsom,Xia Xu,Shu Ouyang,Kyungsook An,Yun-Ja Cho,Geun-Cheol Lee,Yoosook Lee,Gynheung An,Pamela C. Ronald
PLOS Genetics , 2008, DOI: 10.1371/journal.pgen.1000164
Abstract: Functional redundancy limits detailed analysis of genes in many organisms. Here, we report a method to efficiently overcome this obstacle by combining gene expression data with analysis of gene-indexed mutants. Using a rice NSF45K oligo-microarray to compare 2-week-old light- and dark-grown rice leaf tissue, we identified 365 genes that showed significant 8-fold or greater induction in the light relative to dark conditions. We then screened collections of rice T-DNA insertional mutants to identify rice lines with mutations in the strongly light-induced genes. From this analysis, we identified 74 different lines comprising two independent mutant lines for each of 37 light-induced genes. This list was further refined by mining gene expression data to exclude genes that had potential functional redundancy due to co-expressed family members (12 genes) and genes that had inconsistent light responses across other publicly available microarray datasets (five genes). We next characterized the phenotypes of rice lines carrying mutations in ten of the remaining candidate genes and then carried out co-expression analysis associated with these genes. This analysis effectively provided candidate functions for two genes of previously unknown function and for one gene not directly linked to the tested biochemical pathways. These data demonstrate the efficiency of combining gene family-based expression profiles with analyses of insertional mutants to identify novel genes and their functions, even among members of multi-gene families.
FSTVAL: a new web tool to validate bulk flanking sequence tags
Joung Sug Kim, Jiye Kim, Tae-Ho Lee, Kyong Mi Jun, Tea Hoon Kim, Yul-Ho Kim, Hyang-Mi Park, Jong-Seong Jeon, Gynheung An, Ung-Han Yoon, Baek Hie Nahm, Yeon-Ki Kim
Plant Methods , 2012, DOI: 10.1186/1746-4811-8-19
Abstract: We present an open access web tool, flanking sequence tags validator (FSTVAL), to manage bulk flanking sequence tags (FSTs). FSTVAL automatically evaluates the FSTs and finds the best mapping positions of the FST against a known genome sequence. The statistics, in terms of genic and intergenic regions, are presented as a table, a distribution map, and a frequency graph along the chromosomes. Currently, 17 plant genome sequences, including Arabidopsis thaliana, Oryza sativa, and Glycine max, are available as reference genomes. We evaluated the utility and accuracy of the tool with 5,144 rice FSTs. The whole process, from uploading the sequences to generating tables of insertions, required a few minutes, with less than 4 clicks in the web environment.Run for 1?year and tested over 1,000 times, we have confirmed FSTVAL efficiently handles bulk FSTs. FSTVAL is freely available without login at http://bioinfo.mju.ac.kr/fstval/ webcite.
Refinement of Light-Responsive Transcript Lists Using Rice Oligonucleotide Arrays: Evaluation of Gene-Redundancy
Ki-Hong Jung, Christopher Dardick, Laura E. Bartley, Peijian Cao, Jirapa Phetsom, Patrick Canlas, Young-Su Seo, Michael Shultz, Shu Ouyang, Qiaoping Yuan, Bryan C. Frank, Eugene Ly, Li Zheng, Yi Jia, An-Ping Hsia, Kyungsook An, Hui-Hsien Chou, David Rocke, Geun Cheol Lee, Patrick S. Schnable, Gynheung An, C. Robin Buell, Pamela C. Ronald
PLOS ONE , 2008, DOI: 10.1371/journal.pone.0003337
Abstract: Studies of gene function are often hampered by gene-redundancy, especially in organisms with large genomes such as rice (Oryza sativa). We present an approach for using transcriptomics data to focus functional studies and address redundancy. To this end, we have constructed and validated an inexpensive and publicly available rice oligonucleotide near-whole genome array, called the rice NSF45K array. We generated expression profiles for light- vs. dark-grown rice leaf tissue and validated the biological significance of the data by analyzing sources of variation and confirming expression trends with reverse transcription polymerase chain reaction. We examined trends in the data by evaluating enrichment of gene ontology terms at multiple false discovery rate thresholds. To compare data generated with the NSF45K array with published results, we developed publicly available, web-based tools (www.ricearray.org). The Oligo and EST Anatomy Viewer enables visualization of EST-based expression profiling data for all genes on the array. The Rice Multi-platform Microarray Search Tool facilitates comparison of gene expression profiles across multiple rice microarray platforms. Finally, we incorporated gene expression and biochemical pathway data to reduce the number of candidate gene products putatively participating in the eight steps of the photorespiration pathway from 52 to 10, based on expression levels of putatively functionally redundant genes. We confirmed the efficacy of this method to cope with redundancy by correctly predicting participation in photorespiration of a gene with five paralogs. Applying these methods will accelerate rice functional genomics.
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