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Analysis of local genome rearrangement improves resolution of ancestral genomic maps in plants
BACKGROUND: Computationally inferred ancestral genomes play an important role in many areas of genome research. We present an improved workflow for the reconstruction from highly diverged genomes such as those of plants. RESULTS: Our work relies on an established workflow in the reconstruction of an...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7160886/ https://www.ncbi.nlm.nih.gov/pubmed/32299356 http://dx.doi.org/10.1186/s12864-020-6609-x |
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author | Rubert, Diego P. Martinez, Fábio V. Stoye, Jens Doerr, Daniel |
author_facet | Rubert, Diego P. Martinez, Fábio V. Stoye, Jens Doerr, Daniel |
author_sort | Rubert, Diego P. |
collection | PubMed |
description | BACKGROUND: Computationally inferred ancestral genomes play an important role in many areas of genome research. We present an improved workflow for the reconstruction from highly diverged genomes such as those of plants. RESULTS: Our work relies on an established workflow in the reconstruction of ancestral plants, but improves several steps of this process. Instead of using gene annotations for inferring the genome content of the ancestral sequence, we identify genomic markers through a process called genome segmentation. This enables us to reconstruct the ancestral genome from hundreds of thousands of markers rather than the tens of thousands of annotated genes. We also introduce the concept of local genome rearrangement, through which we refine syntenic blocks before they are used in the reconstruction of contiguous ancestral regions. With the enhanced workflow at hand, we reconstruct the ancestral genome of eudicots, a major sub-clade of flowering plants, using whole genome sequences of five modern plants. CONCLUSIONS: Our reconstructed genome is highly detailed, yet its layout agrees well with that reported in Badouin et al. (2017). Using local genome rearrangement, not only the marker-based, but also the gene-based reconstruction of the eudicot ancestor exhibited increased genome content, evidencing the power of this novel concept. |
format | Online Article Text |
id | pubmed-7160886 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-71608862020-04-21 Analysis of local genome rearrangement improves resolution of ancestral genomic maps in plants Rubert, Diego P. Martinez, Fábio V. Stoye, Jens Doerr, Daniel BMC Genomics Research BACKGROUND: Computationally inferred ancestral genomes play an important role in many areas of genome research. We present an improved workflow for the reconstruction from highly diverged genomes such as those of plants. RESULTS: Our work relies on an established workflow in the reconstruction of ancestral plants, but improves several steps of this process. Instead of using gene annotations for inferring the genome content of the ancestral sequence, we identify genomic markers through a process called genome segmentation. This enables us to reconstruct the ancestral genome from hundreds of thousands of markers rather than the tens of thousands of annotated genes. We also introduce the concept of local genome rearrangement, through which we refine syntenic blocks before they are used in the reconstruction of contiguous ancestral regions. With the enhanced workflow at hand, we reconstruct the ancestral genome of eudicots, a major sub-clade of flowering plants, using whole genome sequences of five modern plants. CONCLUSIONS: Our reconstructed genome is highly detailed, yet its layout agrees well with that reported in Badouin et al. (2017). Using local genome rearrangement, not only the marker-based, but also the gene-based reconstruction of the eudicot ancestor exhibited increased genome content, evidencing the power of this novel concept. BioMed Central 2020-04-16 /pmc/articles/PMC7160886/ /pubmed/32299356 http://dx.doi.org/10.1186/s12864-020-6609-x 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, 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 data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Rubert, Diego P. Martinez, Fábio V. Stoye, Jens Doerr, Daniel Analysis of local genome rearrangement improves resolution of ancestral genomic maps in plants |
title | Analysis of local genome rearrangement improves resolution of ancestral genomic maps in plants |
title_full | Analysis of local genome rearrangement improves resolution of ancestral genomic maps in plants |
title_fullStr | Analysis of local genome rearrangement improves resolution of ancestral genomic maps in plants |
title_full_unstemmed | Analysis of local genome rearrangement improves resolution of ancestral genomic maps in plants |
title_short | Analysis of local genome rearrangement improves resolution of ancestral genomic maps in plants |
title_sort | analysis of local genome rearrangement improves resolution of ancestral genomic maps in plants |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7160886/ https://www.ncbi.nlm.nih.gov/pubmed/32299356 http://dx.doi.org/10.1186/s12864-020-6609-x |
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