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De novo transcriptome assembly and annotation for gene discovery in avocado, macadamia and mango
Avocado (Persea americana Mill.), macadamia (Macadamia integrifolia L.) and mango (Mangifera indica L.) are important subtropical tree species grown for their edible fruits and nuts. Despite their commercial and nutritional importance, the genomic information for these species is largely lacking. He...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6949230/ https://www.ncbi.nlm.nih.gov/pubmed/31913298 http://dx.doi.org/10.1038/s41597-019-0350-9 |
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author | Chabikwa, Tinashe G. Barbier, Francois F. Tanurdzic, Milos Beveridge, Christine A. |
author_facet | Chabikwa, Tinashe G. Barbier, Francois F. Tanurdzic, Milos Beveridge, Christine A. |
author_sort | Chabikwa, Tinashe G. |
collection | PubMed |
description | Avocado (Persea americana Mill.), macadamia (Macadamia integrifolia L.) and mango (Mangifera indica L.) are important subtropical tree species grown for their edible fruits and nuts. Despite their commercial and nutritional importance, the genomic information for these species is largely lacking. Here we report the generation of avocado, macadamia and mango transcriptome assemblies from pooled leaf, stem, bud, root, floral and fruit/nut tissue. Using normalized cDNA libraries, we generated comprehensive RNA-Seq datasets from which we assembled 63420, 78871 and 82198 unigenes of avocado, macadamia and mango, respectively using a combination of de novo transcriptome assembly and redundancy reduction. These unigenes were functionally annotated using Basic Local Alignment Search Tool (BLAST) to query the Universal Protein Resource Knowledgebase (UniProtKB). A workflow encompassing RNA extraction, library preparation, transcriptome assembly, redundancy reduction, assembly validation and annotation is provided. This study provides avocado, macadamia and mango transcriptome and annotation data, which is valuable for gene discovery and gene expression profiling experiments as well as ongoing and future genome annotation and marker development applications. |
format | Online Article Text |
id | pubmed-6949230 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-69492302020-01-13 De novo transcriptome assembly and annotation for gene discovery in avocado, macadamia and mango Chabikwa, Tinashe G. Barbier, Francois F. Tanurdzic, Milos Beveridge, Christine A. Sci Data Data Descriptor Avocado (Persea americana Mill.), macadamia (Macadamia integrifolia L.) and mango (Mangifera indica L.) are important subtropical tree species grown for their edible fruits and nuts. Despite their commercial and nutritional importance, the genomic information for these species is largely lacking. Here we report the generation of avocado, macadamia and mango transcriptome assemblies from pooled leaf, stem, bud, root, floral and fruit/nut tissue. Using normalized cDNA libraries, we generated comprehensive RNA-Seq datasets from which we assembled 63420, 78871 and 82198 unigenes of avocado, macadamia and mango, respectively using a combination of de novo transcriptome assembly and redundancy reduction. These unigenes were functionally annotated using Basic Local Alignment Search Tool (BLAST) to query the Universal Protein Resource Knowledgebase (UniProtKB). A workflow encompassing RNA extraction, library preparation, transcriptome assembly, redundancy reduction, assembly validation and annotation is provided. This study provides avocado, macadamia and mango transcriptome and annotation data, which is valuable for gene discovery and gene expression profiling experiments as well as ongoing and future genome annotation and marker development applications. Nature Publishing Group UK 2020-01-08 /pmc/articles/PMC6949230/ /pubmed/31913298 http://dx.doi.org/10.1038/s41597-019-0350-9 Text en © The Author(s) 2020 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 Chabikwa, Tinashe G. Barbier, Francois F. Tanurdzic, Milos Beveridge, Christine A. De novo transcriptome assembly and annotation for gene discovery in avocado, macadamia and mango |
title | De novo transcriptome assembly and annotation for gene discovery in avocado, macadamia and mango |
title_full | De novo transcriptome assembly and annotation for gene discovery in avocado, macadamia and mango |
title_fullStr | De novo transcriptome assembly and annotation for gene discovery in avocado, macadamia and mango |
title_full_unstemmed | De novo transcriptome assembly and annotation for gene discovery in avocado, macadamia and mango |
title_short | De novo transcriptome assembly and annotation for gene discovery in avocado, macadamia and mango |
title_sort | de novo transcriptome assembly and annotation for gene discovery in avocado, macadamia and mango |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6949230/ https://www.ncbi.nlm.nih.gov/pubmed/31913298 http://dx.doi.org/10.1038/s41597-019-0350-9 |
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