Evolutionary dynamics of an Arabidopsis insect resistance quantitative trait locus.
Ontology highlight
ABSTRACT:
SUBMITTER: Kroymann J
PROVIDER: S-EPMC304123 | biostudies-literature | 2003 Nov
REPOSITORIES: biostudies-literature
Publications
Evolutionary dynamics of an Arabidopsis insect resistance quantitative trait locus.
Kroymann Juergen J Donnerhacke Susanne S Schnabelrauch Domenica D Mitchell-Olds Thomas T
Proceedings of the National Academy of Sciences of the United States of America 20030923
Glucosinolate profiles differ among Arabidopsis thaliana ecotypes, caused by the composition of alleles at several glucosinolate biosynthetic loci. One of these, GS-Elong, harbors a family of methylthioalkylmalate synthase (MAM) genes that determine the side chain length of aliphatic glucosinolate structures. Fine mapping reveals that GS-Elong constitutes an insect resistance quantitative trait locus, caused by variation in glucosinolate profiles conferred by polymorphism of MAM alleles in this ...[more]
Similar Datasets
Project description:Quantitative trait loci (QTL) mapping is a powerful tool for investigating the genetic basis of natural variation. QTL can be mapped using a number of different population designs, but recombinant inbred lines (RILs) are among the most effective. Unfortunately, homozygous RIL populations are time consuming to construct, typically requiring at least six generations of selfing starting from a heterozygous F(1). Haploid plants produced from an F(1) combine the two parental genomes and have only one allele at every locus. Converting these sterile haploids into fertile diploids (termed "doubled haploids," DHs) produces immortal homozygous lines in only two steps. Here we describe a unique technique for rapidly creating recombinant doubled haploid populations in Arabidopsis thaliana: centromere-mediated genome elimination. We generated a population of 238 doubled haploid lines that combine two parental genomes and genotyped them by reduced representation Illumina sequencing. The recombination rate and parental allele frequencies in our population are similar to those found in existing RIL sets. We phenotyped this population for traits related to flowering time and for petiole length and successfully mapped QTL controlling each trait. Our work demonstrates that doubled haploid populations offer a rapid, easy alternative to RILs for Arabidopsis genetic analysis.
| S-EPMC3306714 | biostudies-literature
Project description:Genetic variation for seed dormancy in nature is a typical quantitative trait controlled by multiple loci on which environmental factors have a strong effect. Finding the genes underlying dormancy quantitative trait loci is a major scientific challenge, which also has relevance for agriculture and ecology. In this study we describe the identification of the DELAY OF GERMINATION 1 (DOG1) gene previously identified as a quantitative trait locus involved in the control of seed dormancy. This gene was isolated by a combination of positional cloning and mutant analysis and is absolutely required for the induction of seed dormancy. DOG1 is a member of a small gene family of unknown molecular function, with five members in Arabidopsis. The functional natural allelic variation present in Arabidopsis is caused by polymorphisms in the cis-regulatory region of the DOG1 gene and results in considerable expression differences between the DOG1 alleles of the accessions analyzed.
| S-EPMC1636575 | biostudies-literature
Project description:Soil salinity limits agricultural production and is a major obstacle for feeding the growing world population. We used natural genetic variation in salt tolerance among different Arabidopsis accessions to map a major quantitative trait locus (QTL) for salt tolerance and abscisic acid (ABA) sensitivity during seed germination and early seedling growth. A recombinant inbred population derived from Landsberg erecta (Ler; salt and ABA sensitive) x Shakdara (Sha; salt and ABA resistant) was used for QTL mapping. High-resolution mapping and cloning of this QTL, Response to ABA and Salt 1 (RAS1), revealed that it is an ABA- and salt stress-inducible gene and encodes a previously undescribed plant-specific protein. A premature stop codon results in a truncated RAS1 protein in Sha. Reducing the expression of RAS1 by transfer-DNA insertion in Col or RNA interference in Ler leads to decreased salt and ABA sensitivity, whereas overexpression of the Ler allele but not the Sha allele causes increased salt and ABA sensitivity. Our results suggest that RAS1 functions as a negative regulator of salt tolerance during seed germination and early seedling growth by enhancing ABA sensitivity and that its loss of function contributes to the increased salt tolerance of Sha.
| S-EPMC2851765 | biostudies-literature
Project description:Insect hosts and parasitoids are engaged in an intense struggle of antagonistic coevolution. Infection with heritable bacterial endosymbionts can substantially increase the resistance of aphids to parasitoid wasps, which exerts selection on parasitoids to overcome this symbiont-conferred protection (counteradaptation). Experimental evolution in the laboratory has produced counteradapted populations of the parasitoid wasp Lysiphlebus fabarum. These populations can parasitize black bean aphids (Aphis fabae) protected by the bacterial endosymbiont Hamiltonella defensa, which confers high resistance against L. fabarum. We used two experimentally evolved parasitoid populations to study the genetic architecture of the counteradaptation to symbiont-conferred resistance by QTL analysis. With simple crossing experiments, we showed that the counteradaptation is a recessive trait depending on the maternal genotype. Based on these results, we designed a customized crossing scheme to genotype a mapping population phenotyped for the ability to parasitize Hamiltonella-protected aphids. Using 1835 SNP markers obtained by ddRAD sequencing, we constructed a high-density linkage map consisting of six linkage groups (LGs) with an overall length of 828.3 cM and an average marker spacing of 0.45 cM. We identified a single QTL associated with the counteradaptation to Hamiltonella in L. fabarum on linkage group 2. Out of 120 genes located in this QTL, several genes encoding putative venoms may represent candidates for counteradaptation, as parasitoid wasps inject venoms into their hosts during oviposition.
| S-EPMC8322320 | biostudies-literature
Project description:BackgroundQuantitative Trait Locus (QTL) analysis and Genome-Wide Association Studies (GWAS) have the power to identify variants that capture significant levels of phenotypic variance in complex traits. However, effort and time are required to select the best methods and optimize parameters and pre-processing steps. Although machine learning approaches have been shown to greatly assist in optimization and data processing, applying them to QTL analysis and GWAS is challenging due to the complexity of large, heterogenous datasets. Here, we describe proof-of-concept for an automated machine learning approach, AutoQTL, with the ability to automate many complicated decisions related to analysis of complex traits and generate solutions to describe relationships that exist in genetic data.ResultsUsing a publicly available dataset of 18 putative QTL from a large-scale GWAS of body mass index in the laboratory rat, Rattus norvegicus, AutoQTL captures the phenotypic variance explained under a standard additive model. AutoQTL also detects evidence of non-additive effects including deviations from additivity and 2-way epistatic interactions in simulated data via multiple optimal solutions. Additionally, feature importance metrics provide different insights into the inheritance models and predictive power of multiple GWAS-derived putative QTL.ConclusionsThis proof-of-concept illustrates that automated machine learning techniques can complement standard approaches and have the potential to detect both additive and non-additive effects via various optimal solutions and feature importance metrics. In the future, we aim to expand AutoQTL to accommodate omics-level datasets with intelligent feature selection and feature engineering strategies.
| S-EPMC10088184 | biostudies-literature
Project description:BackgroundBacterial grain rot (BGR), caused by the bacterial pathogen Burkholderia glumae, is a destructive disease of rice. Because BGR tends to be highly affected by environmental conditions such as temperature and humidity, it is difficult to evaluate BGR resistance of diverse cultivars with different heading dates by using field inoculation. Molecular tagging of genes involved in BGR is an important objective for rice breeding.ResultsIn this study, we mapped a quantitative trait locus (QTL) for BGR resistance by a modified cut-panicle inoculation method. First, we assessed the levels of BGR resistance in 84 cultivars by a standard cut-panicle inoculation technique, in which panicles are harvested and inoculated in the laboratory under controlled conditions. For the genetic analysis, we selected two cultivars: Kele, a resistant traditional lowland cultivar (indica) that originated in India, and Hitomebore, a susceptible modern lowland cultivar (temperate japonica) from Japan. Second, by comparing the susceptibility of Kele and Hitomebore spikelets before and up to 3 days after anthesis, we found a dramatic decline in susceptibility at 1 day after anthesis in Kele but not in Hitomebore. Thus, we applied a modified method by inoculating spikelets at 1 day after anthesis for further analysis. To search for QTLs associated with BGR resistance, we measured the ratio of diseased spikelets (RDS, an index reflecting both quantity and severity of infection) and the ratio of diseased spikelet area (RDSA) in 110 backcrossed inbred lines (BILs) derived from a cross between Kele and Hitomebore. One major QTL associated with both RDS and RDSA was detected on the long arm of chromosome 1. This QTL explained 25.7% and 12.1% of the total phenotypic variance in RDS and RDSA in the BILs, respectively, and the Kele allele increased BGR resistance.ConclusionsWe mapped a major QTL for BGR resistance on the long arm of chromosome 1. These results clearly demonstrated that genetic analysis of BGR resistance in rice can be effectively performed and that this trait could be a target of marker-assisted selection in rice breeding programs.
| S-EPMC4883728 | biostudies-literature
Project description:Coordinated regulation of gene expression levels across a series of experimental conditions provides valuable information about the functions of correlated transcripts. The consideration of gene expression correlation over a time or tissue dimension has proved valuable in predicting gene function. Here, we consider correlations over a genetic dimension. In addition to identifying coregulated genes, the genetic dimension also supplies us with information about the genomic locations of putative regulatory loci. We calculated correlations among approximately 45,000 expression traits derived from 60 individuals in an F2 sample segregating for obesity and diabetes. By combining the correlation results with linkage mapping information, we were able to identify regulatory networks, make functional predictions for uncharacterized genes, and characterize novel members of known pathways. We found evidence of coordinate regulation of 174 G protein-coupled receptor protein signaling pathway expression traits. Of the 174 traits, 50 had their major LOD peak within 10 cM of a locus on Chromosome 2, and 81 others had a secondary peak in this region. We also characterized a Riken cDNA clone that showed strong correlation with stearoyl-CoA desaturase 1 expression. Experimental validation confirmed that this clone is involved in the regulation of lipid metabolism. We conclude that trait correlation combined with linkage mapping can reveal regulatory networks that would otherwise be missed if we studied only mRNA traits with statistically significant linkages in this small cross. The combined analysis is more sensitive compared with linkage mapping alone.
| S-EPMC1331977 | biostudies-literature
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. Keywords: Genetics of gene expression
2005-09-21 | GSE3330 | GEO
Project description:Soil mechanical impedance precludes root penetration, confining root system development to shallow soil horizons where mobile nutrients are scarce. Using a two-phase-agar system, we characterized Arabidopsis responses to low and high mechanical impedance at three root penetration stages. We found that seedlings whose roots fail to penetrate agar barriers show a significant reduction in leaf area, root length, and elongation zone and an increment in root diameter, while those capable of penetrating show only minor morphological effects. Analyses using different auxin-responsive reporter lines, exogenous auxins, and inhibitor treatments suggest that auxin responsiveness and PIN-mediated auxin distribution play an important role in regulating root responses to mechanical impedance. The assessment of 21 Arabidopsis accessions revealed that primary root penetrability varies widely among accessions. To search for quantitative trait loci (QTLs) associated to root system penetrability, we evaluated a recombinant inbred population derived from Landsberg erecta (Ler-0, with a high primary root penetrability) and Shahdara (Sha, with a low primary root penetrability) accessions. QTL analysis revealed a major-effect QTL localized in chromosome 3, ROOT PENETRATION INDEX 3 (q-RPI3), which accounted for 29.98% (logarithm of odds=8.82) of the total phenotypic variation. Employing an introgression line (IL-321) with a homozygous q-RPI3 region from Sha in the Ler-0 genetic background, we demonstrated that q-RPI3 plays a crucial role in root penetrability. This multiscale study reveals new insights into root plasticity during the penetration process in hard agar layers, natural variation, and genetic architecture behind primary root penetrability in Arabidopsis.
| S-EPMC9366324 | biostudies-literature
Project description:BackgroundRice blast is a destructive disease caused by Magnaporthe oryzae, and it has a large impact on rice production worldwide. Compared with leaf blast resistance, our understanding of panicle blast resistance is limited, with only one panicle blast resistance gene, Pb1, isolated so far. The japonica cultivar Miyazakimochi shows resistance to panicle blast, yet the genetic components accounting for this resistance remain to be determined.ResultsIn this study, we evaluated the panicle blast resistance of populations derived from a cross between Miyazakimochi and the Bikei 22 cultivar, which is susceptible to both leaf and panicle blast. The phenotypic analyses revealed no correlation between panicle blast resistance and leaf blast resistance. Quantitative trait locus (QTL) analysis of 158 recombinant inbred lines using 112 developed genome-wide and 35 previously reported polymerase chain reaction (PCR) markers revealed the presence of two QTLs conferring panicle blast resistance in Miyazakimochi: a major QTL, qPbm11, on chromosome 11; and a minor QTL, qPbm9, on chromosome 9. To clarify the contribution of these QTLs to panicle blast resistance, 24 lines homozygous for each QTL were selected from 2,818 progeny of a BC2F7 backcrossed population, and characterized for disease phenotypes. The panicle blast resistance of the lines harboring qPbm11 was very similar to the resistant donor parental cultivar Miyazakimochi, whereas the contribution of qPbm9 to the resistance was small. Genotyping of the BC2F7 individuals highlighted the overlap between the qPbm11 region and a locus of the panicle blast resistance gene, Pb1. Reverse transcriptase PCR analysis revealed that the Pb1 transcript was absent in the panicles of Miyazakimochi, demonstrating that qPbm11 is a novel genetic component of panicle blast resistance.ConclusionsThis study revealed that Miyazakimochi harbors a novel panicle blast resistance controlled mainly by the major QTL qPbm11. qPbm11 is distinct from Pb1 and could be a genetic source for breeding panicle blast resistance, and will improve understanding of the molecular basis of host resistance to panicle blast.
| S-EPMC4052777 | biostudies-literature