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A dataset of egg size and shape from more than 6,700 insect species
Offspring size is a fundamental trait in disparate biological fields of study. This trait can be measured as the size of plant seeds, animal eggs, or live young, and it influences ecological interactions, organism fitness, maternal investment, and embryonic development. Although multiple evolutionar...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6610123/ https://www.ncbi.nlm.nih.gov/pubmed/31270334 http://dx.doi.org/10.1038/s41597-019-0049-y |
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author | Church, Samuel H. Donoughe, Seth de Medeiros, Bruno A. S. Extavour, Cassandra G. |
author_facet | Church, Samuel H. Donoughe, Seth de Medeiros, Bruno A. S. Extavour, Cassandra G. |
author_sort | Church, Samuel H. |
collection | PubMed |
description | Offspring size is a fundamental trait in disparate biological fields of study. This trait can be measured as the size of plant seeds, animal eggs, or live young, and it influences ecological interactions, organism fitness, maternal investment, and embryonic development. Although multiple evolutionary processes have been predicted to drive the evolution of offspring size, the phylogenetic distribution of this trait remains poorly understood, due to the difficulty of reliably collecting and comparing offspring size data from many species. Here we present a dataset of 10,449 morphological descriptions of insect eggs, with records for 6,706 unique insect species and representatives from every extant hexapod order. The dataset includes eggs whose volumes span more than eight orders of magnitude. We created this dataset by partially automating the extraction of egg traits from the primary literature. In the process, we overcame challenges associated with large-scale phenotyping by designing and employing custom bioinformatic solutions to common problems. We matched the taxa in this dataset to the currently accepted scientific names in taxonomic and genetic databases, which will facilitate the use of these data for testing pressing evolutionary hypotheses in offspring size evolution. |
format | Online Article Text |
id | pubmed-6610123 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66101232019-07-05 A dataset of egg size and shape from more than 6,700 insect species Church, Samuel H. Donoughe, Seth de Medeiros, Bruno A. S. Extavour, Cassandra G. Sci Data Data Descriptor Offspring size is a fundamental trait in disparate biological fields of study. This trait can be measured as the size of plant seeds, animal eggs, or live young, and it influences ecological interactions, organism fitness, maternal investment, and embryonic development. Although multiple evolutionary processes have been predicted to drive the evolution of offspring size, the phylogenetic distribution of this trait remains poorly understood, due to the difficulty of reliably collecting and comparing offspring size data from many species. Here we present a dataset of 10,449 morphological descriptions of insect eggs, with records for 6,706 unique insect species and representatives from every extant hexapod order. The dataset includes eggs whose volumes span more than eight orders of magnitude. We created this dataset by partially automating the extraction of egg traits from the primary literature. In the process, we overcame challenges associated with large-scale phenotyping by designing and employing custom bioinformatic solutions to common problems. We matched the taxa in this dataset to the currently accepted scientific names in taxonomic and genetic databases, which will facilitate the use of these data for testing pressing evolutionary hypotheses in offspring size evolution. Nature Publishing Group UK 2019-07-03 /pmc/articles/PMC6610123/ /pubmed/31270334 http://dx.doi.org/10.1038/s41597-019-0049-y Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Church, Samuel H. Donoughe, Seth de Medeiros, Bruno A. S. Extavour, Cassandra G. A dataset of egg size and shape from more than 6,700 insect species |
title | A dataset of egg size and shape from more than 6,700 insect species |
title_full | A dataset of egg size and shape from more than 6,700 insect species |
title_fullStr | A dataset of egg size and shape from more than 6,700 insect species |
title_full_unstemmed | A dataset of egg size and shape from more than 6,700 insect species |
title_short | A dataset of egg size and shape from more than 6,700 insect species |
title_sort | dataset of egg size and shape from more than 6,700 insect species |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6610123/ https://www.ncbi.nlm.nih.gov/pubmed/31270334 http://dx.doi.org/10.1038/s41597-019-0049-y |
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