A global analysis of QTLs for expression variations in rice flag leaf at heading date
Ontology highlight
ABSTRACT:
ORGANISM(S): Oryza sativa
PROVIDER: GSE49020 | GEO | 2014/02/05
SECONDARY ACCESSION(S): PRJNA212700
REPOSITORIES: GEO
Similar Datasets
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.
2014-02-05 | E-GEOD-49020 | biostudies-arrayexpress
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.
2011-06-24 | GSE22564 | GEO
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. To dissect the genetic variation between the two rice indica varieties Minghui 63 and Zhenshan 97, a total of 110 RILs from Minghui 63 and Zhenshan 97 and parents were sampled. And the Affymetrix Genechip rice Genome Array was used to investigate their dynamic transcript levels. Two independent biological replicates were sampled from each RIL, and three replicates for each parent.resulting in a dataset of 226 microarrays.
2011-06-24 | E-GEOD-22564 | biostudies-arrayexpress
Project description:The study of natural genetic variation for plant disease resistance responses is a complementary approach to utilizing mutants to elucidate genetic pathways. While some key genes involved in pathways controlling disease resistance, and signaling intermediates such as salicylic acid (SA) and jasmonic acid (JA), have been identified through mutational analyses, the use of genetic variation in natural populations permits the identification of change-of-function alleles, which likely act in a quantitative manner. Whole genome microarrays, such as Affymetrix GeneChips, allow for molecular characterization of the disease response at a genomics level and characterization of differences in gene expression due to natural variation. Differences in the level of gene expression, or expression level polymorphisms (ELPs), can be mapped in a segregating population to identify regulatory quantitative trait loci (expression QTLs, eQTLs) affecting host resistance responses. We surveyed recombinant inbred lines (RILs) from a population derived from a cross of inbred Arabidopsis accessions Bayreuth-0 (Bay-0) and Shahdara (Sha) in order to map eQTLs controlling ELPs. We treated vegetatively grown plants with either SA or a control solution (Silwet), and harvested the plants 28 hours after chemical treatment. We present Affymetrix GeneChip microarray expression data for 2 biological replications of the control (Silwet) samples for 63 RILs, plus replicated Bay-0 and Sha control samples grown at the same time as the RILs. These GeneChips representing 63 RILs, along with the GeneChips in Accession E-TABM-62 which represent an additional 148 RILs, form a 211 RIL dataset from which we mapped eQTLs.
2007-04-11 | E-TABM-126 | biostudies-arrayexpress
Project description:2 Recombinant Inbred Lines (RILs) per array, 40 arrays per Temperature, 2 Temperatures(16C,24C) Keywords: genetical genomics experiment
2006-11-29 | GSE5395 | GEO
Project description:We advance a three gene model of arsenate tolerance in rice based on testing root growth of 108 recombinant inbred lines (RILs) of the Bala x Azucena population. Marker genotype at 3 loci determined arsenate tolerance in 99% of RILs tested. Interestingly, plants must inherit 2, but any two alleles from the tolerant parent (Bala) to have the tolerant phenotype. Challenging the Affymetrix GeneChip Rice Genome array with Azucena and Bala RNA isolated from control and arsenate treated plants revealed 592 genes 2 fold-upregulated by arsenate and 696 downregulated. The array data was also used to identify which genes are expressed within the three target loci. We used microarrays to detail the gene expression at three locations in the rice genome termed AsTol6.1, AsTol6.2 and AsTol10 in response to 1ppm arsenate. The data was also used to study the global gene expression of the two varieties of rice, Azucena and Bala, in the presence of 1ppm arsenate. Keywords: Hydroponics, 0 and 1ppm sodium arsenate, Rice varieties Azucena and Bala
2006-03-16 | GSE4471 | GEO
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
2009-06-05 | GSE16393 | GEO
Project description:Heading date is a critical trait for adaptation of rice to different cultivation areas and cropping seasons. We evaluated the heading dates of 1,123 chromosome segments substitution lines (CSSLs) in the genetic background of an elite rice variety Huajingxian74 (HJX74). A CSSL with the substituted segments from Zihui100 exhibited late heading under both natural long-day (NLD) and natural short-day (NSD) conditions, and the late heading phenotype was controlled by two novel epistatic loci on chromosome 8 and chromosome 3, respectively, termed LH8 and EH3. The function of EH3 was dependent on the LH8 genotype through epistatic interaction between EH3(Zihui100) and LH8(Zihui100) alleles. Genetic and molecular characterization revealed LH8 encodes a CCAAT-box-binding transcription factor with Heading date1 (Hd1)-binding activity and may delay flowering by repressing the expression of Early heading date1 (Ehd1). Our work provides a solid foundation for further study on gene interaction in heading date and has application in breeding rice with greater adaptability.
| S-EPMC3939452 | biostudies-literature
Project description:The aim of this study was to minimize the number of candidate genes responsible for salt tolerance between a pair of rice varieties (CSR27 and MI48) with contrasting level of salt tolerance by bulked segregant analysis of their recombinant inbred lines. Microarray analysis of RNA extracted from the tolerant and susceptible parents without and with stress showed 798 and 2407 differentially expressed genes, respectively. The number of differentially expressed genes was drastically reduced to 70 and 30, by pooling the RNAs from ten extreme tolerant and ten extreme susceptible RILs due to normalization of irrelevant differentially expressed genes between the parents.
2010-04-20 | GSE16108 | GEO
Project description:The study of natural genetic variation for plant disease resistance responses is a complementary approach to utilizing mutants to elucidate genetic pathways. While some key genes involved in pathways controlling disease resistance, and signaling intermediates such as salicylic acid (SA) and jasmonic acid (JA), have been identified through mutational analyses, the use of genetic variation in natural populations permits the identification of change-of-function alleles, which likely act in a quantitative manner. Whole genome microarrays, such as Affymetrix GeneChips, allow for molecular characterization of the disease response at a genomics level and characterization of differences in gene expression due to natural variation. Differences in the level of gene expression, or expression level polymorphisms (ELPs), can be mapped in a segregating population to identify regulatory quantitative trait loci (expression QTLs, e-QTLs) affecting host resistance responses. We surveyed recombinant inbred lines (RILs) from a population derived from a cross of inbred Arabidopsis accessions Bayreuth-0 (Bay-0) and Shahdara (Sha) in order to map e-QTLs controlling ELPs. We treated vegetatively grown plants with either SA or a control solution (Silwet), and harvested the plants 28 hours after chemical treatment. We present Affymetrix GeneChip microarray expression data for 2 biological replications of the SA-treated samples for 211 RILs, plus replicated Bay-0 and Sha control samples grown at the same time as the RILs. The control (Silwet-treated) samples were submitted as E-TABM-126. Normalized data is not provided here as the normalization step was included in the data statistical analsyses - for more information please contact the experiment provider.
2009-07-17 | E-TABM-518 | biostudies-arrayexpress