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Gene expression profiles in rice gametes and zygotes: identification of gamete-enriched genes and up- or down-regulated genes in zygotes after fertilization.

ABSTRACT: In angiosperms, fertilization and subsequent zygotic development occur in embryo sacs deeply embedded in the ovaries; therefore, these processes are poorly elucidated. In this study, microarray-based transcriptome analyses were conducted on rice sperm cells, egg cells, and zygotes isolated from flowers to identify candidate genes involved in gametic and/or early zygotic development. Cell type-specific transcriptomes were obtained, and up- or down-regulated genes in zygotes after fertilization were identified, in addition to genes enriched in male and female gametes. A total of 325 putatively up-regulated and 94 putatively down-regulated genes in zygotes were obtained. Interestingly, several genes encoding homeobox proteins or transcription factors were identified as highly up-regulated genes after fertilization, and the gene ontology for up-regulated genes was highly enriched in functions related to chromatin/DNA organization and assembly. Because a gene encoding methyltransferase 1 was identified as a highly up-regulated gene in zygotes after fertilization, the effect of an inhibitor of this enzyme on zygote development was monitored. The inhibitor appeared partially to affect polarity or division asymmetry in rice zygotes, but it did not block normal embryo generation.

SUBMITTER: Abiko M

PROVIDER: S-EPMC3638821 | biostudies-other | 2013 Apr

REPOSITORIES: biostudies-other

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Gene expression profiles in rice gametes and zygotes: identification of gamete-enriched genes and up- or down-regulated genes in zygotes after fertilization.

Abiko Mafumi M Maeda Hiroki H Tamura Kentaro K Hara-Nishimura Ikuko I Okamoto Takashi T

Journal of experimental botany 20130409 7

In angiosperms, fertilization and subsequent zygotic development occur in embryo sacs deeply embedded in the ovaries; therefore, these processes are poorly elucidated. In this study, microarray-based transcriptome analyses were conducted on rice sperm cells, egg cells, and zygotes isolated from flowers to identify candidate genes involved in gametic and/or early zygotic development. Cell type-specific transcriptomes were obtained, and up- or down-regulated genes in zygotes after fertilization we ...[more]

PMID: 23570690

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Project description:BackgroundA common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software.ResultsThis method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes.ConclusionOur results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.

Dataset Information

Gene expression profiles in rice gametes and zygotes: identification of gamete-enriched genes and up- or down-regulated genes in zygotes after fertilization.

Publications

Gene expression profiles in rice gametes and zygotes: identification of gamete-enriched genes and up- or down-regulated genes in zygotes after fertilization.

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