Dataset Information

A systems-genetics approach and data mining tool to assist in the discovery of genes underlying complex traits in Oryza sativa.

ABSTRACT: Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with significant overlap with blast disease resistance.

SUBMITTER: Ficklin SP

PROVIDER: S-EPMC3713027 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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A systems-genetics approach and data mining tool to assist in the discovery of genes underlying complex traits in Oryza sativa.

Ficklin Stephen P SP Feltus Frank Alex FA

PloS one 20130716 7

Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify ...[more]

PMID: 23874666

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Project description:The productivity of rice is greatly affected by the infection of the plant pathogenic fungus Rhizoctonia solani, which causes a significant grain yield reduction globally. There exist a limited number of rice accessions that are available to develop sheath blight resistance (ShB). Our objective was to identify a good source of the ShB resistance, understand the heritability, and trait interactions, and identify the genomic regions for ShB resistance traits by genome-wide association studies (GWAS). In the present study, a set of 330 traditional landraces and improved rice varieties were evaluated for ShB resistance and created a core panel of 192 accessions used in the GWAS. This panel provides a more considerable amount of genetic variance and found a significant phenotypic variation among the panel of rice accessions for all the agro-morphological and disease-resistance traits over the seasons. The infection rate of ShB and disease reaction were calculated as percent disease index (PDI) and area under the disease progress curve (AUDPC). The correlation analysis showed a significant positive association between PDIs and AUPDC and a negative association between PDI and plant height, flag leaf length, and grain yield. The panel was genotyped with 133 SSR microsatellite markers, resulting in a genome coverage of 314.83 Mb, and the average distance between markers is 2.53 Mb. By employing GLM and MLM (Q + K) models, 30 marker-trait associations (MTAs) were identified with targeted traits over the seasons. Among these QTLs, eight were found to be novel and located on 2, 4, 8, 10, and 12 chromosomes, which explained the phenotypic variation ranging from 5% to 15%. With the GWAS approach, six candidate genes were identified. Os05t0566400, Os08t0155900, and Os09t0567300 were found to be associated with defense mechanisms against ShB. These findings provided insights into the novel donors of IC283139, IC 277248, Sivappuchithirai Kar, and Bowalia. The promising genomic regions on 10 of 12 chromosomes associated with ShB would be useful in developing rice varieties with durable disease resistance.

Project description:BackgroundmicroRNAs (miRNAs) are important regulators in plant growth and development. miR159 is a conserved miRNA among different plant species and has various functions in plants. Studies on miR159 are mostly done on model plant, Arabidopsis thaliana. In rice, studies on miR159 were either based upon genome-wide expression analyses focused upon responses to different nitrogen forms and abiotic stress or upon phenotypic studies of transgenic plants overexpressing its precursor. STTM (Short Tandem Target Mimic) is an effective tool to block the activity of endogenous mature miRNA activity in plant. Therefore, specific roles of miR159 in rice could be explored by down regulating miR159 through STTM.ResultsIn this study, expression of mature miR159 was successfully suppressed by STTM which resulted in the increased expressions of its two targets genes, OsGAMYB and OsGAMYBL1 (GAMYB-LIKE 1). Overall, STTM159 plants exhibited short stature along with smaller organ size and reduction in stem diameter, length of flag leaf, main panicle, spikelet hulls and grain size. Histological analysis of stem, leaf and mature spikelet hull showed the reduced number of small vascular bundles (SVB), less number of small veins (SV) between two big veins (LV) and less cell number in outer parenchyma. Gene Ontology (GO) enrichment analysis of differentially expressed genes between wild type plants and STTM159 transgenic plants showed that genes involved in cell division, auxin, cytokinin (CK) and brassinosteroids (BRs) biosynthesis and signaling are significantly down-regulated in STTM159 plants.ConclusionOur data suggests that in rice, miR159 positively regulates organ size, including stem, leaf, and grain size due to the promotion of cell division. Further analysis from the RNA-seq data showed that the decreased cell divisions in STTM159 transgenic plants may result, at least partly from the lower expression of the genes involved in cell cycle and hormone homeostasis, which provides new insights of rice miR159-specific functions.

Dataset Information

A systems-genetics approach and data mining tool to assist in the discovery of genes underlying complex traits in Oryza sativa.

Publications

A systems-genetics approach and data mining tool to assist in the discovery of genes underlying complex traits in Oryza sativa.

Similar Datasets

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