Drosophila melanogaster
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA389281 | ENA |
REPOSITORIES: ENA
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Project description:The aim was to profile the small RNA population in females. We observed that a very abundant rRNA fragment was present in the AB sample, but not in the HT sample.
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Project description:Quantitative comparation of the tagmata of body and head using iTRAQ based on HCD Fragmentation. The 8-plex iTRAQ Multiplex Buffer Kit (AB SCIEX, Foster City, CA) was used to label different peptide fractions, in which iTRAQ reagents dissolved in isopropyl alcohol. Another internal standard of D.melanogaster body and head mixed with 1:1 (B+H) was also used when doing iTRAQ labeling. Therefore the same amount of B (body), H1 (head), H2 (head), B+H (internal standard) peptide fractions prepared as described above were labeled by equal but different iTRAQ reagents and incubated for 5 h at room temperature. The four different labeled peptide fractions (B:113, H1:114, H2:115, B+H:116 ) were then mixed with 1:1 and dried in a speedvac followed by desalting purification using stage tip. All prepared peptides were further analyzed on an LTQ-Orbitrap Velos hybrid mass spectrometer (Thermo Electron, San Jose, CA) coupled with UPLC (nano Acquity Ultra Performance LC, Waters). For HCD raw files, the profile data was firstly centralized by ReAdW.exe in TPP and then deisotoped and deconvoluted using in-house made scripts to improve the identification rate of spectra. All MGF files were searched using Mascot 2.3 against a Drosophila melanogaster database with 24,043 entries (http://flybase.org/, release 5.4, 24,043 entries). The target-decoy based strategy was used to control the peptide false discovery rate (FDR).
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Project description:Understanding the genotype-phenotype map and how variation at different levels of biological organization is associated are central topics in modern biology. Fast developments in sequencing technologies and other molecular omic tools enable researchers to obtain detailed information on variation at DNA level and on intermediate endophenotypes, such as RNA, proteins and metabolites. This can facilitate our understanding of the link between genotypes and molecular and functional organismal phenotypes. Here, we use the Drosophila melanogaster Genetic Reference Panel and nuclear magnetic resonance (NMR) metabolomics to investigate the ability of the metabolome to predict organismal phenotypes. We performed NMR metabolomics on four replicate pools of male flies from each of 170 different isogenic lines. Our results show that metabolite profiles are variable among the investigated lines and that this variation is highly heritable. Second, we identify genes associated with metabolome variation. Third, using the metabolome gave better prediction accuracies than genomic information for four of five quantitative traits analyzed. Our comprehensive characterization of population-scale diversity of metabolomes and its genetic basis illustrates that metabolites have large potential as predictors of organismal phenotypes. This finding is of great importance, e.g., in human medicine, evolutionary biology and animal and plant breeding.
2021-08-05 | MTBLS2060 | MetaboLights