Dataset Information

A high-throughput method for unbiased quantitation and categorization of nuclear morphology†.

ABSTRACT: The physical arrangement of chromatin in the nucleus is cell type and species-specific, a fact particularly evident in sperm, in which most of the cytoplasm has been lost. Analysis of the characteristic falciform ("hook shaped") sperm in mice is important in studies of sperm development, hybrid sterility, infertility, and toxicology. However, quantification of sperm shape differences typically relies on subjective manual assessment, rendering comparisons within and between samples difficult. We have developed an analysis program for morphometric analysis of asymmetric nuclei and characterized the sperm of mice from a range of inbred, outbred, and wild-derived mouse strains. We find that laboratory strains have elevated sperm shape variability both within and between samples in comparison to wild-derived inbred strains, and that sperm shape in F1 offspring from a cross between CBA and C57Bl6J strains is subtly affected by the direction of the cross. We further show that hierarchical clustering can discriminate distinct sperm shapes with greater efficiency and reproducibility than even experienced manual assessors, and is useful both to distinguish between samples and also to identify different morphological classes within a single sample. Our approach allows for the analysis of nuclear shape with unprecedented precision and scale and will be widely applicable to different species and different areas of biology.

SUBMITTER: Skinner BM

PROVIDER: S-EPMC6497523 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

A high-throughput method for unbiased quantitation and categorization of nuclear morphology†.

Skinner Benjamin Matthew BM Rathje Claudia Cattoni CC Bacon Joanne J Johnson Emma Elizabeth Philippa EEP Larson Erica Lee EL Kopania Emily E K EEK Good Jeffrey Martin JM Yousafzai Gullalaii G Affara Nabeel Ahmed NA Ellis Peter James Ivor PJI

Biology of reproduction 20190501 5

The physical arrangement of chromatin in the nucleus is cell type and species-specific, a fact particularly evident in sperm, in which most of the cytoplasm has been lost. Analysis of the characteristic falciform ("hook shaped") sperm in mice is important in studies of sperm development, hybrid sterility, infertility, and toxicology. However, quantification of sperm shape differences typically relies on subjective manual assessment, rendering comparisons within and between samples difficult. We ...[more]

PMID: 30753283

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Project description:BACKGROUND:Biological data that are well-organized by an ontology, such as Gene Ontology, enables high-throughput availability of the semantic web. It can also be used to facilitate high throughput classification of biomedical information. However, to our knowledge, no evaluation has been published on automating classifications of human diseases genes using Gene Ontology. In this study, we evaluate automated classifications of well-defined human disease genes using their Gene Ontology annotations and compared them to a gold standard. This gold standard was independently conceived by Valle's research group, and contains 923 human disease genes organized in 14 categories of protein function. RESULTS:Two automated methods were applied to investigate the classification of human disease genes into independently pre-defined categories of protein function. One method used the structure of Gene Ontology by pre-selecting 74 Gene Ontology terms assigned to 11 protein function categories. The second method was based on the similarity of human disease genes clustered according to the information-theoretic distance of their Gene Ontology annotations. Compared to the categorization of human disease genes found in the gold standard, our automated methods can achieve an overall 56% and 47% precision with 62% and 71% recall respectively. However, approximately 15% of the studied human disease genes remain without GO annotations. CONCLUSION:Automated methods can recapitulate a significant portion of classification of the human disease genes. The method using information-theoretic distance performs slightly better on the precision with some loss in recall. For some protein function categories, such as 'hormone' and 'transcription factor', the automated methods perform particularly well, achieving precision and recall levels above 75%. In summary, this study demonstrates that for semantic webs, methods to automatically classify or analyze a majority of human disease genes require significant progress in both the Gene Ontology annotations and particularly in the utilization of these annotations.

Dataset Information

A high-throughput method for unbiased quantitation and categorization of nuclear morphology†.

Publications

A high-throughput method for unbiased quantitation and categorization of nuclear morphology†.

Similar Datasets

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