Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Dissecting the developmental transcriptomes of rice

ABSTRACT: Transcriptional programs are important for the development of complex eukaryotic organisms. Suites of genes expressed with temporal and spatial controls by regulatory networks in response to environmental cues are the cornerstone for achieving the specification of morphology and physiology of the tissue or organ systems. Thus, an important issue of developmental biology is to define the subsets of expressed genes and their expression patterns that are related to the organ or tissue system. Rice is a model plant for cereal genome research. Although large amounts of data of whole genome expression have been generated in recent years in rice, the majority of the studies were designed to identify differentially expressed genes between controls and treatments with certain experimental conditions such as biotic, abiotic or light, or to investigate the comparative expression patterns between wild type and mutants of certain genes. Only in a few cases were the datasets designed for studying the transcriptomes of a limited number of organs and cell types. Thus, there is still insufficiency in the available datasets that would allow for the establishment of expression patterns for suits of genes during the developmental processes of rice. In this study, we collected 39 tissues/organs covering the life cycle of the rice from two indica varieties Minghui 63 and Zhenshan 97, and the Affymetrix GeneChip Rice Genome Array was used to investigate the transcriptomes of these organs. The objective was to develop a genomic resource of genome-wide dynamic transcriptome of the rice plant, which could be used as the reference gene expression map for rice and other cereals. Also, the dataset is used to identify the candidates of genes with potential functions in regulating the development of rice or breeding practice. Keywords: rice, expression profiling, life cycle, development, inflorescence To dissect the developmental transcriptomes of rice, a total of 39 tissues covering the entire tissue culture process and life cycle were sampled from two indica varieties Minghui 63 and Zhenshan 97. And the Affymetrix Genechip rice Genome Array was used to investigate their dynamic transcriptomes. Two independent biological replicates were sampled from most tissues, except two seedling and three panicle tissues, for which three independent biological replicates each with two technical replicates were sampled, resulting in a dataset of 190 microarrays.

ORGANISM(S): Oryza sativa Indica Group

SUBMITTER: Weibo Xie

PROVIDER: E-GEOD-19024 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

A dynamic gene expression atlas covering the entire life cycle of rice.

Wang Lei L Xie Weibo W Chen Ying Y Tang Weijiang W Yang Jiangyi J Ye Rongjian R Liu Li L Lin Yongjun Y Xu Caiguo C Xiao Jinghua J Zhang Qifa Q

The Plant journal : for cell and molecular biology 20091209 5

Growth and development of a plant are controlled by programmed expression of suits of genes at the appropriate time, tissue and abundance. Although genomic resources have been developed rapidly in recent years in rice, a model plant for cereal genome research, data of gene expression profiling are still insufficient to relate the developmental processes to transcriptomes, leaving a large gap between the genome sequence and phenotype. In this study, we generated genome-wide expression data by hyb ...[more]

PMID: 20003165

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Project description:Analyses of QTLs for expression levels (eQTLs) of the genes reveal genetic relationship between expression variation and the regulator, thus unlocking the information for identifying the regulatory network. Oligo-nucleotide expression microarrays hybridized with RNA can simultaneously provide data for molecular markers and transcript abundance. In this study, we used Affymetrix GeneChip Rice Genome Array to analyze eQTLs in rice shoots at 72 h after germination from 110 recombinant inbred lines (RILs) derived from a cross between Zhenshan 97 and Minghui 63. Totally 1,632 single feature polymorphisms (SFPs) plus 23 PCR markers were identified and placed into 601 recombinant bins, spanning 1,459 cM in length, which were used as markers to genotype the RILs. We obtained 16,372 expression traits (e-traits) each with at least one eQTL, resulting in 26,051 eQTLs in total, including both cis- and trans-eQTLs. We also identified 171 eQTL hotspots among rice genome, each of which controls transcript variations of many e-traits. Gene Ontology analysis revealed enrichment of certain functional categories of genes in some of the eQTL hotspots. In particular, eQTLs for e-traits involving DNA metabolic process was significantly enriched in several eQTL hotspots on chromosomes 3, 5 and 10. Several transcription factors colocalizing with cis-eQTLs showed significant correlations with hundreds of e-traits, indicating possible co-regulation. We also detected correlations between the QTLs for shoot dry weight and eQTLs, revealing possible candidate genes for the trait. These results provided the clues for identification and characterization of regulatory network in the whole genome at the transcriptional level. To dissect the genetic variation between the two rice indica varieties Minghui 63 and Zhenshan 97, a total of 110 RILs from Minghui 63 and Zhenshan 97 and parents were sampled. And the Affymetrix Genechip rice Genome Array was used to investigate their dynamic transcript levels. Two independent biological replicates were sampled from each RIL, and three replicates for each parent.resulting in a dataset of 226 microarrays.

Dataset Information

Dissecting the developmental transcriptomes of rice

Publications

A dynamic gene expression atlas covering the entire life cycle of rice.

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