ABSTRACT: eQTL analysis - Extracting genotype information of recombinant inbred lines from transcript profiles established with high-density oligonucleotide arrays
Project description:gnp3_tri33-arabidoseed - eqtl analysis (random pair design) - WP3 : Biodiversity of seed traits : state of the art - Comparison of the developping seed transcriptome in 160 Bay0/Sha Recombinant Inbred Lines (RILs) at 10 days after pollinisation. Keywords: genotype and ecotype comparison
Project description:gnp3_tri33-arabidoseed - eqtl analysis (random pair design) - WP3 : Biodiversity of seed traits : state of the art - Comparison of the developping seed transcriptome in 160 Bay0/Sha Recombinant Inbred Lines (RILs) at 10 days after pollinisation. Keywords: genotype and ecotype comparison 80 dye-swap - CATMA arrays
Project description:gnp07_rilkit - rilkit-eqtl analysis (random pair design). To provide quantitative geneticists studying natural variation in our RIL populations with information and resources necessary to speed up QTL cloning and candidate genes identification. This articulates around the creation of two major resources and their integration into databases to make the information accessible to users: A. Whole transcriptome survey, B. Production of complementary material. Comparison of 164 Cvi/Col(8RV) Recombinant Inbred Lines (RILs) and 164 Bur/Col (20RV) RILs. 162 dye-swaps. Genotype and ecotype comparison.
Project description:Analyses of QTLs for expression levels (eQTLs) of the genes reveal genetic relationship between expression variation and the regulator, thus unlocking the information for identifying the regulatory network. In this study, we used Affymetrix GeneChip Rice Genome Array to analyze eQTLs in rice flag leaf at heading date from 210 recombinant inbred lines (RILs) derived from a cross between Zhenshan 97 and Minghui 63. In the study, we attempted to construct the regulatory network by identifying putative regulators and the respective targets using an eQTL guided co-expression analysis with a recombinant inbred line population of rice.
Project description:gnp07_rilkit - rilkit-eqtl analysis (random pair design). To provide quantitative geneticists studying natural variation in our RIL populations with information and resources necessary to speed up QTL cloning and candidate genes identification. This articulates around the creation of two major resources and their integration into databases to make the information accessible to users: A. Whole transcriptome survey, B. Production of complementary material. Comparison of 164 Cvi/Col(8RV) Recombinant Inbred Lines (RILs) and 164 Bur/Col (20RV) RILs.
Project description:We mapped quantitative trait loci for genome-wide gene expression (eQTL) in juvenile, reproductive and senescent C. elegans recombinant inbred lines, to determine heritable transcript dynamics
Project description:In order to identify eQTL in developing seeds of Arabidopsis thaliana 116 Arabidopsis thaliana recombinant inbred lines (C24/Col 0 and Col 0/C24, Törjék et al. 2006) were analysed.
Project description:Analyses of QTLs for expression levels (eQTLs) of the genes reveal genetic relationship between expression variation and the regulator, thus unlocking the information for identifying the regulatory network. Oligo-nucleotide expression microarrays hybridized with RNA can simultaneously provide data for molecular markers and transcript abundance. In this study, we used Affymetrix GeneChip Rice Genome Array to analyze eQTLs in rice shoots at 72 h after germination from 110 recombinant inbred lines (RILs) derived from a cross between Zhenshan 97 and Minghui 63. Totally 1,632 single feature polymorphisms (SFPs) plus 23 PCR markers were identified and placed into 601 recombinant bins, spanning 1,459 cM in length, which were used as markers to genotype the RILs. We obtained 16,372 expression traits (e-traits) each with at least one eQTL, resulting in 26,051 eQTLs in total, including both cis- and trans-eQTLs. We also identified 171 eQTL hotspots among rice genome, each of which controls transcript variations of many e-traits. Gene Ontology analysis revealed enrichment of certain functional categories of genes in some of the eQTL hotspots. In particular, eQTLs for e-traits involving DNA metabolic process was significantly enriched in several eQTL hotspots on chromosomes 3, 5 and 10. Several transcription factors colocalizing with cis-eQTLs showed significant correlations with hundreds of e-traits, indicating possible co-regulation. We also detected correlations between the QTLs for shoot dry weight and eQTLs, revealing possible candidate genes for the trait. These results provided the clues for identification and characterization of regulatory network in the whole genome at the transcriptional level.
Project description:Analyses of QTLs for expression levels (eQTLs) of the genes reveal genetic relationship between expression variation and the regulator, thus unlocking the information for identifying the regulatory network. In this study, we used Affymetrix GeneChip Rice Genome Array to analyze eQTLs in rice flag leaf at heading date from 210 recombinant inbred lines (RILs) derived from a cross between Zhenshan 97 and Minghui 63. In the study, we attempted to construct the regulatory network by identifying putative regulators and the respective targets using an eQTL guided co-expression analysis with a recombinant inbred line population of rice. The ability to reveal the regulatory architecture of the genes at the whole genome level by constructing the regulatory network is critical for understanding the biological processes and developmental programs of the organism. Here we conducted an eQTL guided function-related co-expression analysis for identifying the putative regulators and constructing gene regulatory network. The Affymetrix Genechip rice Genome Array was used to investigate their dynamic transcript levels. one replicates were sampled from each RIL, three for parents, and three replicates for each parent resulting in a dataset of 216 microarrays.
Project description:The aim of this study was to identify eQTL in Brassica rapa grown under altered soil phosphorus (P) supply, to understand better the genetic architecture of P-use efficiency (PUE) in plants. Recombinant inbred lines (RILs) of the BraIRRI mapping population were grown at adequate and growth-limiting soil P. Variation in leaf gene expression was quantified using an Agilent Brassica 95k oligonucleotide array. Informative gene expression markers (GEMs) were used to map eQTL and PUE-related QTL. Gene expression was highly dependent on soil P supply. However, the altered expression of many genes, including known P-responsive genes, was highly heritable. Interval mapping using P supply as a covariate revealed 18,876 eQTL, representing 15,912 unique probes. Notable trans-eQTL hotspots occurred on chromosomes A06 and A01; these were enriched with protein modification and phosphorus metabolism-related (A06), as well as chloroplast and photosynthesis-related (A01) transcripts. Regulatory loci and genes associated with P-use efficiency identified through eQTL analysis are potential targets for further characterisation and may have potential for crop improvement. Availability of the annotated B. rapa genome sequence will facilitate their study, including the separation of cis- and trans- effects.
