Project description:Genetic analysis of interspecific populations derived from crosses between the wild tomato species Solanum habrochaites f glabratum, which synthesizes and accumulates insecticidal methylketones (MKs) such as 2-undecanone and 2-tridecanone in glandular trichomes, and Solanum lycopersicum (cultivated tomato), which does not, demonstrated that MK metabolism in the wild species can be attributed to several loci. Comparative trascriptome analysis of the glandular trichomes of F2 segregants bulked into low- and high-MK plants identified several genes whose transcripts were either more or less abundant in the high-MK plants.
Project description:In this study, we describe the impact of genetic variation on transcript abundance in an F2 population of Arabidopsis thaliana. The RNA-seq resource generated by this study is suitable for expression quantitative trait locus (eQTL) mapping. From the aligned RNA-seq reads, and available genomic data for each of the parents of the cross, we imputed the genomes of each F2 individual (to allow genetic mapping of RNA abundance traits; briefly, genetic differences in aligned RNA-seq reads were used to impute each F2 genome). Our results show that heritable differences on gene expression can be detected using F2 populations (that is, single F2 plants), and shed light on the control of expression differences among strains of this reference plant.
Project description:Mapping the genetic architecture of RNA transcript abundances has potential for revealing molecular mechanisms underlying complex traits like disease. Gene expression microarrays allow monitoring genetic control on a whole transcriptome level, but validity and reproducibility of microarray data is a subject of ongoing scientific debate. Here we demonstrate how combining genetic and gene expression data provide a basis for biologically relevant assessment of the current state of microarray technology. We profile liver samples from a murine F2 intercross population using Agilent microarrays. Tissue profiling in a mouse F2 cross. We analyzed 298 Liver samples.
Project description:Summary Mapping the genetic architecture of RNA transcript abundances has potential for revealing molecular mechanisms underlying complex traits like disease. Gene expression microarrays allow monitoring genetic control on a whole transcriptome level, but validity and reproducibility of microarray data is a subject of ongoing scientific debate. Here we demonstrate how combining genetic and gene expression data provide a basis for biologically relevant assessment of the current state of microarray technology. We profile liver samples from a murine F2 intercross population using Affymetrix microarrays. Tissue profiling in a mouse F2 cross. We analyzed 294 Liver samples.
Project description:The aim of this study was to conduct a genome-wide analysis for constituent tuber carotenoid QTL. Using a genetical genomics approach samples from clones with similar carotenoid traits were bulked and patterns of gene expression were measured for each bulk by microarray analysis. Variation of gene expression within these bulks may be due to either polymorphisms located near to or within the gene (cis-eQTL) or indirectly from a distant location on the genome (trans-eQTL). Differentially expressed clones from bulks with contrasting carotenoid traits were genetically mapped in order to re-enforce the QTL analysis, and provide a rapid means of developing gene markers closely associated with the target traits.
Project description:Summary Mapping the genetic architecture of RNA transcript abundances has potential for revealing molecular mechanisms underlying complex traits like disease. Gene expression microarrays allow monitoring genetic control on a whole transcriptome level, but validity and reproducibility of microarray data is a subject of ongoing scientific debate. Here we demonstrate how combining genetic and gene expression data provide a basis for biologically relevant assessment of the current state of microarray technology. We profile liver samples from a murine F2 intercross population using Affymetrix microarrays.
Project description:Mapping the genetic architecture of RNA transcript abundances has potential for revealing molecular mechanisms underlying complex traits like disease. Gene expression microarrays allow monitoring genetic control on a whole transcriptome level, but validity and reproducibility of microarray data is a subject of ongoing scientific debate. Here we demonstrate how combining genetic and gene expression data provide a basis for biologically relevant assessment of the current state of microarray technology. We profile liver samples from a murine F2 intercross population using Agilent microarrays.
Project description:To identify biological processes as well as molecular markers for drip loss, the transcriptomes of logissimus dorsi from 6 sib pair of F2 animals Experiment Overall Design: 12 F2 animals of a resource population based on the breeds Duroc and Pietrain known to differ in meat quality and quantity traits were hybridized to Affymetrix Porcine Genome Arrays
Project description:Coordinated regulation of gene expression levels across a series of experimental conditions provides valuable information about the functions of correlated transcripts. To map gene regulatory pathways, we used microarray-derived gene expression measurements in 60 individuals of an F2 sample segregating for diabetes. We performed correlation analysis among ~40,000 expression traits. By combining correlation among expression traits and linkage mapping information, we were able to identify regulatory networks, make functional predictions to uncharacterized genes, and characterize novel members of known pathways. Using 36 seed traits, we found evidence of coordinate regulation of 160 G-protein coupled receptor (GPCR) pathway expression traits. Of the 160 traits, 50 had their major LOD peak within 8 cM of a locus on chromosome 2, and 81 others had a secondary peak in this region. A previously uncharacterized Riken cDNA clone, which showed strong correlation with stearoyl CoA desaturase 1 expression, was experimentally validated to be responsive to conditions that regulate lipid metabolism. Using linkage mapping, we identified multiple genes whose expression is under the control of transcription regulatory loci. Trait-correlation combined with linkage mapping can reveal regulatory networks that would otherwise be missed if we only studied mRNA traits with statistically significant linkages in this small cross. The combined analysis is more sensitive compared with linkage mapping only. References: ; Kendziorski C., M. Chen, M. Yuan, H. Lan, and A.D. Attie. Statistical Methods for Expression Quantitative Trait Loci (eQTL) Mapping. Biometrics, to appear, 2005. Lan H, Chen M, Flowers JB, Yandell BS, Stapleton DS, et al. (2006) Combined Expression Trait Correlations and Expression Quantitative Trait Locus Mapping. PLoS Genet 2(1): e6. Experiment Overall Design: The F2-ob/ob mice were chosen from a mapping panel that we created to map diabetes related physiological phenotypes (Stoehr et al. 2000). About 110 of these F2-ob/ob mice were also used to map mRNA abundance traits derived by quantitative real-time RT-PCR (Lan et al. 2003). The sixty F2-ob/ob mice that were used to generate microarray-derived mRNA abundance traits were selected from the 110 mice based on a selective phenotyping algorithm (Jin et al. 2004). The F2-ob/ob mice were housed at weaning at the University of Wisconsin-Madison animal care facility on a 12-h light/dark cycle. Mice were provided Purina Formulab Chow 5008 (6.5% fat) and acidified water ad libitum. Mice were killed at 14 weeks of age by CO2 asphyxiation after a 4-hour fast. The livers, along with other tissues, were immediately foil wrapped and frozen in liquid nitrogen, and subsequently transferred to -80 °C freezers for storage. Liver samples were taken from 29 male and 31 females. Total RNA was isolated with RNAzol Reagent (Tel-Test, Inc.) using a modification of the single-step acid guanidinium isothiocyanate phenol-chloroform extraction method according to the manufacturer's protocol. The extracted RNA was purified using RNeasy (Qiagen, Inc.). RNA samples were evaluated by UV spectroscopy for concentration. RNA quality was monitored by visualization on an ethidium bromide-stained denaturing formaldehyde agarose gel. RNA samples were converted to cDNA, and then biotin-labeled cRNA according to Affymetrix Expression Analysis Technical Manual. The labeled samples were hybridized to the M430A, and subsequently the M430B array. The hybridization, washing and scanning steps were carried out by Hong Lan using the Affymetrix core facility at the Gene Expression Center of University of Wisconsin-Madison.