Picea engelmannii x Picea glauca
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ABSTRACT:
PROVIDER: PRJNA138431 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:White pine weevil is a major pest of conifers in North America, especially for Spruce trees. Constitutive defenses are important in understanding defense mechanisms because they constitute the initial barrier to attacks by weevils and other pests. Resistant and susceptible trees exhibit constitutive differences in spruce. To improve our knowledge of their genetic basis, we compared the constitutive expression levels of 17,825 genes between 20 resistant and 20 susceptible trees in interior spruce (Picea glauca).
2011-11-28 | GSE27476 | GEO
Project description:White pine weevil is a major pest of conifers in North America, especially for Spruce trees. Constitutive defenses are important in understanding defense mechanisms because they constitute the initial barrier to attacks by weevils and other pests. Resistant and susceptible trees exhibit constitutive differences in spruce. To improve our knowledge of their genetic basis, we compared the constitutive expression levels of 17,825 genes between 20 resistant and 20 susceptible trees in interior spruce (Picea glauca). Twenty hybridizations were performed to compare untreated bark of resistant and susceptible trees.RNA isolated from each of the 20 individual untreated resistant trees was compared directly against the 20 individual untreated susceptble trees using two hybridizations with a dye flip for each tree pair.
2011-11-28 | E-GEOD-27476 | biostudies-arrayexpress
Project description:We performed a transcriptome analysis of interior spruce (Picea glauca x engelmannii) bark response to weevil (Pissodes strobi) feeding using 21.8K spruce microarray (that contains 21.8 thousand unique transcripts). This microarray study revealed a large rearrangement of the interior spruce bark transcriptome in response to weevil feeding involving differential expression of close to 20% of the studied transcriptome.
2012-12-01 | GSE23715 | GEO
Project description:Picea engelmannii x Picea glauca overview
| PRJNA155393 | ENA
Project description:Inferring the heritability of gene expression is one of the main areas of the field of genetical genomics. With the possibility to treat the abundances of gene transcripts as a suite of quantitative traits, genetical genomics can make an extensive use of the microarray technology. Here we extended a major method for estimating the heritability of a quantitative trait, single parent-offspring regression, to assess the heritability of the expression of genes with two-channel microarrays. In a series of maternal parent-offspring pairs of Interior spruce (Picea glauca x engelmannii, our focus in the outer stem tissues is the expression of defense-related genes, the heritability of which can affect fitness and necessary for evolution by natural selection.
2010-07-15 | GSE22921 | GEO
Project description:Heritability of the expression of defense-related genes in the outer stem of Interior spruce (Picea glauca x engelmannii)
| PRJNA127981 | ENA
Project description:We performed a transcriptome analysis of interior spruce (Picea glauca x engelmannii) bark response to weevil (Pissodes strobi) feeding using 21.8K spruce microarray (that contains 21.8 thousand unique transcripts). This microarray study revealed a large rearrangement of the interior spruce bark transcriptome in response to weevil feeding involving differential expression of close to 20% of the studied transcriptome. RNA was isolated from the bark of interior spruce exposed to weevil feeding and from the bark of untreated trees at three time points (6 hours, 2 days and 2 weeks). Four independent biological replicates were included for treatment and control at each time point. Four hybridizations were performed for treatment and control comparison within each time point (6 hours, 2 days, 2 weeks) and one hybridization was performed for each comparison between time points for both treatment and control (total 18 hybridizations/slides).
2012-12-01 | E-GEOD-23715 | biostudies-arrayexpress
Project description:Inferring the heritability of gene expression is one of the main areas of the field of genetical genomics. With the possibility to treat the abundances of gene transcripts as a suite of quantitative traits, genetical genomics can make an extensive use of the microarray technology. Here we extended a major method for estimating the heritability of a quantitative trait, single parent-offspring regression, to assess the heritability of the expression of genes with two-channel microarrays. In a series of maternal parent-offspring pairs of Interior spruce (Picea glauca x engelmannii, our focus in the outer stem tissues is the expression of defense-related genes, the heritability of which can affect fitness and necessary for evolution by natural selection. Parent-offspring pairs of Interior spruce planted as a part of Tree Breeding and Improvement Program of the Forest Genetics Section, British Columbia Ministry of Forests and Range, Prince George, BC, Canada (http://www.for.gov.bc.ca/hre/forgen/interior/spruce.htm#1) were used. A total of 30 trees, comprising 15 parent-offpsring pairs were sampled. These include15 offsprings and 15 maternal parents (grafts), which were planted within ~ 1Km range west (122º 42’ 43’’W, 53º 45’41’’N) of the offsprings, hence grown in a relatively similar environment. The bark and the attached phloem were separated from inner layers in the mid-morning hours of June 25, 2008, flash-frozen in liquid nitrogen, and transferred into separate containers. A chain design was decided for gene expression profiling (a total of 45 slides) using the Treenomix third generation cDNA microarray platform (GEO accession #: GPL5423). Array350 kit (Genisphere, Hatfield, USA) was chosen for the microarray hybridizations. The slides were scanned with a ProScanArray scanner (PerkinElmer, Downers Grove, IL, USA), and the scanned TIF images were processed by ImaGene software (BioDiscovery, Inc., El Segundo, CA, USA) to quantify spot signals. Normalization was done between arrays using variance stabilizing (VSN) method for ratio based analysis of the expression data.
2010-07-15 | E-GEOD-22921 | biostudies-arrayexpress