ArticleScientific data2015
High-resolution gene expression data from blastoderm embryos of the scuttle fly Megaselia abdita.
Article in Scientific data, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Genomic resources for the scuttle fly Megaselia abdita: a model organism for comparative developmental studies in flies.Development (Cambridge, England) · 2025Article
- Gap Gene Regulatory Dynamics Evolve along a Genotype Network.Molecular biology and evolution · 2016Article
- Maternal co-ordinate gene regulation and axis polarity in the scuttle fly Megaselia abdita.PLoS genetics · 2015Article
- High-resolution gene expression data from blastoderm embryos of the scuttle fly Megaselia abdita.Scientific data · 2015Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gap genes are involved in segment determination during early development in dipteran insects (flies, midges, and mosquitoes). We carried out a systematic quantitative comparative analysis of the gap gene network across different dipteran species. Our work provides mechanistic insights into the evolution of this pattern-forming network. As a central component of our project, we created a high-resolution quantitative spatio-temporal data set of gap and maternal co-ordinate gene expression in the blastoderm embryo of the non-drosophilid scuttle fly, Megaselia abdita. Our data include expression patterns in both wild-type and RNAi-treated embryos. The data-covering 10 genes, 10 time points, and over 1,000 individual embryos-consist of original embryo images, quantified expression profiles, extracted positions of expression boundaries, and integrated expression patterns, plus metadata and intermediate processing steps. These data provide a valuable resource for researchers interested in the comparative study of gene regulatory networks and pattern formation, an essential step towards a more quantitative and mechanistic understanding of developmental evolution.
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Registered trials
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