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Differentially expressed genes during the imbibition of dormant and after-ripened seeds - a reverse genetics approach.

ABSTRACT: BACKGROUND:Seed dormancy, defined as the incapability of a viable seed to germinate under favourable conditions, is an important trait in nature and agriculture. Despite extensive research on dormancy and germination, many questions about the molecular mechanisms controlling these traits remain unanswered, likely due to its genetic complexity and the large environmental effects which are characteristic of these quantitative traits. To boost research towards revealing mechanisms in the control of seed dormancy and germination we depend on the identification of genes controlling those traits. METHODS:We used transcriptome analysis combined with a reverse genetics approach to identify genes that are prominent for dormancy maintenance and germination in imbibed seeds of Arabidopsis thaliana. Comparative transcriptomics analysis was employed on freshly harvested (dormant) and after-ripened (AR; non-dormant) 24-h imbibed seeds of four different DELAY OF GERMINATION near isogenic lines (DOGNILs) and the Landsberg erecta (Ler) wild type with varying levels of primary dormancy. T-DNA knock-out lines of the identified genes were phenotypically investigated for their effect on dormancy and AR. RESULTS:We identified conserved sets of 46 and 25 genes which displayed higher expression in seeds of all dormant and all after-ripened DOGNILs and Ler, respectively. Knock-out mutants in these genes showed dormancy and germination related phenotypes. CONCLUSIONS:Most of the identified genes had not been implicated in seed dormancy or germination. This research will be useful to further decipher the molecular mechanisms by which these important ecological and commercial traits are regulated.

SUBMITTER: Yazdanpanah F

PROVIDER: S-EPMC5594490 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Differentially expressed genes during the imbibition of dormant and after-ripened seeds - a reverse genetics approach.

Yazdanpanah Farzaneh F Hanson Johannes J Hilhorst Henk W M HWM Bentsink Leónie L

BMC plant biology 20170911 1

<h4>Background</h4>Seed dormancy, defined as the incapability of a viable seed to germinate under favourable conditions, is an important trait in nature and agriculture. Despite extensive research on dormancy and germination, many questions about the molecular mechanisms controlling these traits remain unanswered, likely due to its genetic complexity and the large environmental effects which are characteristic of these quantitative traits. To boost research towards revealing mechanisms in the co ...[more]

PMID: 28893189

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Project description:Seed dormancy is a genetically controlled block preventing the germination of imbibed seeds in favorable conditions. It requires a period of dry storage (after-ripening) or certain environmental conditions to be overcome. Dormancy is an important seed trait, which is under selective pressure, to control the seasonal timing of seed germination. Dormant and non-dormant (after-ripened) seeds are characterized by large sets of differentially expressed genes. However, little information is available concerning the temporal and spatial transcriptional changes during early stages of rehydration in dormant and non-dormant seeds. We employed genome-wide transcriptome analysis on seeds of the model plant Arabidopsis thaliana to investigate transcriptional changes in dry seeds upon rehydration. We analyzed gene expression of dormant and after-ripened seeds of the Cvi accession over four time points and two seed compartments (the embryo and surrounding single cell layer endosperm), during the first 24 h after sowing. This work provides a global view of gene expression changes in dormant and non-dormant seeds with temporal and spatial detail, and these may be visualized via a web accessible tool (http://www.wageningenseedlab.nl/resources). A large proportion of transcripts change similarly in both dormant and non-dormant seeds upon rehydration, however, the first differences in transcript abundances become visible shortly after the initiation of imbibition, indicating that changes induced by after-ripening are detected and responded to rapidly upon rehydration. We identified several gene expression profiles which contribute to differential gene expression between dormant and non-dormant samples. Genes with enhanced expression in the endosperm of dormant seeds were overrepresented for stress-related Gene Ontology categories, suggesting a protective role for the endosperm against biotic and abiotic stress to support persistence of the dormant seed in its environment.

Project description:Soybean is a major source of protein and oil and a primary feedstock for biodiesel production. Research on soybean seed composition and yield has revealed that protein, oil and yield are controlled quantitatively and quantitative trait loci (QTL) have been identified for each of these traits. However, very limited information is available regarding the genetic mechanisms controlling seed composition and yield. To help address this deficiency, we used Affymetrix Soybean GeneChips® to identify genes that are differentially expressed between developing seeds of the Minsoy and Archer soybean cultivars, which differ in seed weight, yield, protein content and oil content. A total of 700 probe sets were found to be expressed at significantly different (defined as having an adjusted p-value below or equal to 0.05 and an at least 2-fold difference) levels between the two cultivars at one or more of the three developmental stages and in at least one of the two years assayed. Comparison of data from soybeans collected in two different years revealed that 97 probe sets were expressed at significantly different levels in both years. Functional annotations were assigned to 78% of these 97 probe sets based on the SoyBase Affymetrix™ GeneChip® Soybean Genome Array Annotation. Genes involved in receptor binding/activity and protein binding are overrepresented among the group of 97 probe sets that were differentially expressed in both years assayed. Probe sets involved in growth/development, signal transduction, transcription, defense/stress response and protein and lipid metabolism were also identified among the 97 probe sets and their possible implications in the regulation of agronomic traits are discussed. As the Minsoy and Archer soybean cultivars differ with respect to seed size, yield, protein content and lipid content, some of the differentially expressed probe sets identified in this study may thus play important roles in controlling these traits. Others of these probe sets may be involved in regulation of general seed development or metabolism. All microarray data and expression values after GCRMA are available at the Gene Expression Omnibus (GEO) at NCBI (http://www.ncbi.nlm.nih.gov/geo), under accession number GSE21598.

Project description:BackgroundIdentifying differentially expressed genes (DEG) is a fundamental step in studies that perform genome wide expression profiling. Typically, DEG are identified by univariate approaches such as Significance Analysis of Microarrays (SAM) or Linear Models for Microarray Data (LIMMA) for processing cDNA microarrays, and differential gene expression analysis based on the negative binomial distribution (DESeq) or Empirical analysis of Digital Gene Expression data in R (edgeR) for RNA-seq profiling.ResultsHere we present a new geometrical multivariate approach to identify DEG called the Characteristic Direction. We demonstrate that the Characteristic Direction method is significantly more sensitive than existing methods for identifying DEG in the context of transcription factor (TF) and drug perturbation responses over a large number of microarray experiments. We also benchmarked the Characteristic Direction method using synthetic data, as well as RNA-Seq data. A large collection of microarray expression data from TF perturbations (73 experiments) and drug perturbations (130 experiments) extracted from the Gene Expression Omnibus (GEO), as well as an RNA-Seq study that profiled genome-wide gene expression and STAT3 DNA binding in two subtypes of diffuse large B-cell Lymphoma, were used for benchmarking the method using real data. ChIP-Seq data identifying DNA binding sites of the perturbed TFs, as well as known drug targets of the perturbing drugs, were used as prior knowledge silver-standard for validation. In all cases the Characteristic Direction DEG calling method outperformed other methods. We find that when drugs are applied to cells in various contexts, the proteins that interact with the drug-targets are differentially expressed and more of the corresponding genes are discovered by the Characteristic Direction method. In addition, we show that the Characteristic Direction conceptualization can be used to perform improved gene set enrichment analyses when compared with the gene-set enrichment analysis (GSEA) and the hypergeometric test.ConclusionsThe application of the Characteristic Direction method may shed new light on relevant biological mechanisms that would have remained undiscovered by the current state-of-the-art DEG methods. The method is freely accessible via various open source code implementations using four popular programming languages: R, Python, MATLAB and Mathematica, all available at: http://www.maayanlab.net/CD.

Dataset Information

Differentially expressed genes during the imbibition of dormant and after-ripened seeds - a reverse genetics approach.

Publications

Differentially expressed genes during the imbibition of dormant and after-ripened seeds - a reverse genetics approach.

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