INCISE Mutational Data Subset
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ABSTRACT:
PROVIDER: PRJEB91741 | ENA |
REPOSITORIES: ENA
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Project description:Transcript abundance was measured in whole-body virgin male Drosophila serrata from 41 inbred lines that had diverged through 27 generations of mutation accumulation. Pleiotropic mutations are the ultimate source of genetic variation in complex traits, including many human diseases. However, the nature and extent of mutational pleiotropy remain largely unknown. Here, we investigate the variation in 11,604 gene expression traits among 41 mutation accumulation lines of Drosophila serrata, which had diverged for 27 generations. We detected significant mutational variance in 4.6% of ESTs, but 70% of ESTs were invariant among lines, allowing us to reject a null hypothesis of phenome-wide universal pleiotropy. Mutational covariance among ESTs was detected at a frequency of only 1 in 193 random pairs of variable EST, bu t was detected among random combinations of five ESTs in 1 in 5 cases, revealing that mutational covariance among multiple ESTs was common. The observed frequency of significant multivariate covariance among random ESTs implied that a substantial number of ESTs (>70) must be pleiotropically affected by at least some mutations. We measured gene expression of male Drosophila serrata from 41 mutation accumulation lines (whole-body). Data from two replicates for each line are presented.
2013-09-01 | E-GEOD-49815 | biostudies-arrayexpress
Project description:RawTools is a software that provides parsing and quantification of raw Thermo Orbitrap mass spectrometer data. RawTools software was used to process a subset of injections (n = 10) from a prepared HeLa digest that were analyzed on an Orbitrap Velos to get instrument performance metrics.
2018-09-18 | PXD011070 | Pride
Project description:Transcript abundance was measured in whole-body virgin male Drosophila serrata from 41 inbred lines that had diverged through 27 generations of mutation accumulation that were sexually selected Sexual selection is predicted to have widespread effects on the genetic variation generated by new mutations as a consequence of the genic capture of condition by male sexual traits. We manipulated the opportunity for sexual selection on males during 27 generations of mutation accumulation in inbred lines of Drosophila serrata, and used a microarray platform to investigate the effect of sexual selection on the expression of 2685 genes, representing a broad coverage of biological function. Sexual selection had little effect on mean gene expression levels, with only 4 genes diverging significantly at a false discovery rate of 5% . In contrast, sexual selection impacted on both the magnitude and nature of mutational variance accumulating in these genes. The magnitude of mutational variance increased under sexual selection by an average of 29%. Mutational variance was less commonly generated by extreme phenotypes less commonly under sexual selection. Furthermore, analysis of random sets of five genes revealed that the mutational variance that accumulated under sexual selection was less pleiotropic in nature than that found in the absence of sexual selection. The generation of greater mutational variance without a general concomitant change in mean expression under sexual selection suggested that gene expression traits were be under apparent rather than direct sexual selection. We discuss two main explanations for the broad-based increase in mutational variance under sexual selection that both require extensive pleiotropy between traits affecting male mating success, standard metric traits represented here by gene expression traits, and general fitness. We measured gene expression of male Drosophila serrata from 41 mutation accumulation lines (whole-body) that were sexually selected. Data from two replicates for each line are presented.
2014-03-01 | E-GEOD-54777 | biostudies-arrayexpress
Project description:P. aeruginosa mutational resistome
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Project description:Deep mutational scanning is a powerful method for exploring the mutational fitness landscape of proteins. Its adaptation to anti-CRISPR proteins, which are natural CRISPR-Cas inhibitors and key players in the co-evolution of microbes and phages, facilitates their characterization and optimization. Here, we developed a robust anti-CRISPR deep mutational scanning pipeline in Escherichia coli that combines synthetic gene circuits based on CRISPR interference with flow cytometry coupled sequencing and mathematical modeling. Using this pipeline, we characterized comprehensive single point mutation libraries for AcrIIA4 and AcrIIA5, two potent inhibitors of CRISPR-Cas9. The resulting mutational fitness landscapes revealed considerable mutational tolerance for both Acrs, suggesting an intrinsic redundancy with respect to Cas9 inhibitory features, and – for AcrIIA5 – indicated mutations that boost Cas9 inhibition. Subsequent in vitro characterization suggested that the observed differences in inhibitory potency between mutant inhibitors were mostly due to changes in binding affinity rather than protein expression levels. Finally, to demonstrate that our pipeline can inform Acrs-based genome editing applications, we employed a selected subset of mutant inhibitors to increase CRISPR-Cas9 target specificity by modulating Cas9 activity. Taken together, our work establishes deep mutational scanning as a powerful method for anti-CRISPR protein characterization and optimization.
2024-03-01 | GSE254101 | GEO
Project description:Gene expression data from formalin-fixed paraffin-embedded (FFPE) human uveal melanoma tumors subset early metastasis vs subset no metastasis
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