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SSRome: an integrated database and pipelines for exploring microsatellites in all organisms

Over the past decade, many databases focusing on microsatellite mining on a genomic scale were released online with at least one of the following major deficiencies: (i) lacking the classification of microsatellites as genic or non-genic, (ii) not comparing microsatellite motifs at both genic and no...

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Autores principales: Mokhtar, Morad M, Atia, Mohamed A M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323889/
https://www.ncbi.nlm.nih.gov/pubmed/30365025
http://dx.doi.org/10.1093/nar/gky998
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author Mokhtar, Morad M
Atia, Mohamed A M
author_facet Mokhtar, Morad M
Atia, Mohamed A M
author_sort Mokhtar, Morad M
collection PubMed
description Over the past decade, many databases focusing on microsatellite mining on a genomic scale were released online with at least one of the following major deficiencies: (i) lacking the classification of microsatellites as genic or non-genic, (ii) not comparing microsatellite motifs at both genic and non-genic levels in order to identify unique motifs for each class or (iii) missing SSR marker development. In this study, we have developed ‘SSRome’ as a web-based, user-friendly, comprehensive and dynamic database with pipelines for exploring microsatellites in 6533 organisms. In the SSRome database, 158 million microsatellite motifs are identified across all taxa, in addition to all the mitochondrial and chloroplast genomes and expressed sequence tags available from NCBI. Moreover, 45.1 million microsatellite markers were developed and classified as genic or non-genic. All the stored motif and marker datasets can be downloaded freely. In addition, SSRome provides three user-friendly tools to identify, classify and compare motifs on either a genome- or transcriptome-wide scale. With the implementation of PHP, HTML and JavaScript, users can upload their data for analysis via a user-friendly GUI. SSRome represents a powerful database and mega-tool that will assist researchers in developing and dissecting microsatellite markers on a high-throughput scale.
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spelling pubmed-63238892019-01-10 SSRome: an integrated database and pipelines for exploring microsatellites in all organisms Mokhtar, Morad M Atia, Mohamed A M Nucleic Acids Res Database Issue Over the past decade, many databases focusing on microsatellite mining on a genomic scale were released online with at least one of the following major deficiencies: (i) lacking the classification of microsatellites as genic or non-genic, (ii) not comparing microsatellite motifs at both genic and non-genic levels in order to identify unique motifs for each class or (iii) missing SSR marker development. In this study, we have developed ‘SSRome’ as a web-based, user-friendly, comprehensive and dynamic database with pipelines for exploring microsatellites in 6533 organisms. In the SSRome database, 158 million microsatellite motifs are identified across all taxa, in addition to all the mitochondrial and chloroplast genomes and expressed sequence tags available from NCBI. Moreover, 45.1 million microsatellite markers were developed and classified as genic or non-genic. All the stored motif and marker datasets can be downloaded freely. In addition, SSRome provides three user-friendly tools to identify, classify and compare motifs on either a genome- or transcriptome-wide scale. With the implementation of PHP, HTML and JavaScript, users can upload their data for analysis via a user-friendly GUI. SSRome represents a powerful database and mega-tool that will assist researchers in developing and dissecting microsatellite markers on a high-throughput scale. Oxford University Press 2019-01-08 2018-10-26 /pmc/articles/PMC6323889/ /pubmed/30365025 http://dx.doi.org/10.1093/nar/gky998 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Database Issue
Mokhtar, Morad M
Atia, Mohamed A M
SSRome: an integrated database and pipelines for exploring microsatellites in all organisms
title SSRome: an integrated database and pipelines for exploring microsatellites in all organisms
title_full SSRome: an integrated database and pipelines for exploring microsatellites in all organisms
title_fullStr SSRome: an integrated database and pipelines for exploring microsatellites in all organisms
title_full_unstemmed SSRome: an integrated database and pipelines for exploring microsatellites in all organisms
title_short SSRome: an integrated database and pipelines for exploring microsatellites in all organisms
title_sort ssrome: an integrated database and pipelines for exploring microsatellites in all organisms
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323889/
https://www.ncbi.nlm.nih.gov/pubmed/30365025
http://dx.doi.org/10.1093/nar/gky998
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