Dataset Information

An image database of Drosophila melanogaster wings for phenomic and biometric analysis.

ABSTRACT: BACKGROUND:Extracting important descriptors and features from images of biological specimens is an ongoing challenge. Features are often defined using landmarks and semi-landmarks that are determined a priori based on criteria such as homology or some other measure of biological significance. An alternative, widely used strategy uses computational pattern recognition, in which features are acquired from the image de novo. Subsets of these features are then selected based on objective criteria. Computational pattern recognition has been extensively developed primarily for the classification of samples into groups, whereas landmark methods have been broadly applied to biological inference. RESULTS:To compare these approaches and to provide a general community resource, we have constructed an image database of Drosophila melanogaster wings - individually identifiable and organized by sex, genotype and replicate imaging system - for the development and testing of measurement and classification tools for biological images. We have used this database to evaluate the relative performance of current classification strategies. Several supervised parametric and nonparametric machine learning algorithms were used on principal components extracted from geometric morphometric shape data (landmarks and semi-landmarks). For comparison, we also classified phenotypes based on de novo features extracted from wing images using several computer vision and pattern recognition methods as implemented in the Bioimage Classification and Annotation Tool (BioCAT). CONCLUSIONS:Because we were able to thoroughly evaluate these strategies using the publicly available Drosophila wing database, we believe that this resource will facilitate the development and testing of new tools for the measurement and classification of complex biological phenotypes.

SUBMITTER: Sonnenschein A

PROVIDER: S-EPMC4942975 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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An image database of Drosophila melanogaster wings for phenomic and biometric analysis.

Sonnenschein Anne A VanderZee David D Pitchers William R WR Chari Sudarshan S Dworkin Ian I

GigaScience 20150522

<h4>Background</h4>Extracting important descriptors and features from images of biological specimens is an ongoing challenge. Features are often defined using landmarks and semi-landmarks that are determined a priori based on criteria such as homology or some other measure of biological significance. An alternative, widely used strategy uses computational pattern recognition, in which features are acquired from the image de novo. Subsets of these features are then selected based on objective cri ...[more]

PMID: 27390931

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Project description:BackgroundThe formation of matured and individual sperm involves a series of molecular and spectacular morphological changes of the developing cysts in Drosophila melanogaster testis. Recent advances in RNA Sequencing (RNA-Seq) technology help us to understand the complexity of eukaryotic transcriptomes by dissecting different tissues and developmental stages of organisms. To gain a better understanding of cellular differentiation of spermatogenesis, we applied RNA-Seq to analyse the testis-specific transcriptome, including coding and non-coding genes.ResultsWe isolated three different parts of the wild-type testis by dissecting and cutting the different regions: 1.) the apical region, which contains stem cells and developing spermatocytes 2.) the middle region, with enrichment of meiotic cysts 3.) the basal region, which contains elongated post-meiotic cysts with spermatids. Total RNA was isolated from each region and analysed by next-generation sequencing. We collected data from the annotated 17412 Drosophila genes and identified 5381 genes with significant transcript accumulation differences between the regions, representing the main stages of spermatogenesis. We demonstrated for the first time the presence and region specific distribution of 2061 lncRNAs in testis, with 203 significant differences. Using the available modENCODE RNA-Seq data, we determined the tissue specificity indices of Drosophila genes. Combining the indices with our results, we identified genes with region-specific enrichment in testis.ConclusionBy multiple analyses of our results and integrating existing knowledge about Drosophila melanogaster spermatogenesis to our dataset, we were able to describe transcript composition of different regions of Drosophila testis, including several stage-specific transcripts. We present searchable visualizations that can facilitate the identification of new components that play role in the organisation and composition of different stages of spermatogenesis, including the less known, but complex regulation of post-meiotic stages.

Dataset Information

An image database of Drosophila melanogaster wings for phenomic and biometric analysis.

Publications

An image database of Drosophila melanogaster wings for phenomic and biometric analysis.

Similar Datasets

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