Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Genome-wide gene expression profiling of rice Indica cultivar Zhongxian 3037 and mutant phoenix (pho) panicle

ABSTRACT: phoenix (pho) is a naturally occurring rice (Oryza sativa L.) mutant that exhibits stable inflorescence reversion. Genetic analysis showed that it was not a simple mendelian mutant. In order to find the major genes contributed to the formation of pho, microarray experiments were carried out to analyze and compare the transcriptional profiles between pho and wild-type panicles. We generated gene expression profiles of rice Indica cultivar Zhongxian 3037 and mutant phoenix (pho) by using 57K Affymetrix rice whole genome array.

ORGANISM(S): Oryza sativa

SUBMITTER: Wenying Xu

PROVIDER: E-GEOD-17194 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

DEP and AFO regulate reproductive habit in rice.

Wang Kejian K Tang Ding D Hong Lilan L Xu Wenying W Huang Jian J Li Ming M Gu Minghong M Xue Yongbiao Y Cheng Zhukuan Z

PLoS genetics 20100122 1

Sexual reproduction is essential for the life cycle of most angiosperms. However, pseudovivipary is an important reproductive strategy in some grasses. In this mode of reproduction, asexual propagules are produced in place of sexual reproductive structures. However, the molecular mechanism of pseudovivipary still remains a mystery. In this work, we found three naturally occurring mutants in rice, namely, phoenix (pho), degenerative palea (dep), and abnormal floral organs (afo). Genetic analysis ...[more]

PMID: 20107517

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Project description:Plant diurnal oscillation is a 24-hour period based variation. The correlation between diurnal genes and biological pathways was widely revealed by microarray analysis in different species. Rice (Oryza sativa) is the major food staple for about half of the world's population. The rice flag leaf is essential in providing photosynthates to the grain filling. However, there is still no comprehensive view about the diurnal transcriptome for rice leaves. In this study, we applied rice microarray to monitor the rhythmically expressed genes in rice seedling and flag leaves. We developed a new computational analysis approach and identified 6,266 (10.96%) diurnal probe sets in seedling leaves, 13,773 (24.08%) diurnal probe sets in flag leaves. About 65% of overall transcription factors were identified as flag leaf preferred. In seedling leaves, the peak of phase distribution was from 2:00am to 4:00am, whereas in flag leaves, the peak was from 8:00pm to 2:00am. The diurnal phase distribution analysis of gene ontology (GO) and cis-element enrichment indicated that, some important processes were waken by the light, such as photosynthesis and abiotic stimulus, while some genes related to the nuclear and ribosome involved processes were active mostly during the switch time of light to dark. The starch and sucrose metabolism pathway genes also showed diurnal phase. We conducted comparison analysis between Arabidopsis and rice leaf transcriptome throughout the diurnal cycle. In summary, our analysis approach is feasible for relatively unbiased identification of diurnal transcripts, efficiently detecting some special periodic patterns with non-sinusoidal periodic patterns. Compared to the rice flag leaves, the gene transcription levels of seedling leaves were relatively limited to the diurnal rhythm. Our comprehensive microarray analysis of seedling and flag leaves of rice provided an overview of the rice diurnal transcriptome and indicated some diurnal regulated biological processes and key functional pathways in rice. we generate rice diurnal gene expression profiles of seedling leaves and flag leaves using 57K Affymetrix rice whole genome array. keywords: rice (Oryza sativa L.), seedling leaves, flag leaves, diurnal, molecular functions, microarray

Dataset Information

Genome-wide gene expression profiling of rice Indica cultivar Zhongxian 3037 and mutant phoenix (pho) panicle

Publications

DEP and AFO regulate reproductive habit in rice.

Similar Datasets

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