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Whole Genome Mapping with Feature Sets from High-Throughput Sequencing Data
A good physical map is essential to guide sequence assembly in de novo whole genome sequencing, especially when sequences are produced by high-throughput sequencing such as next-generation-sequencing (NGS) technology. We here present a novel method, Feature sets-based Genome Mapping (FGM). With FGM,...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5017645/ https://www.ncbi.nlm.nih.gov/pubmed/27611682 http://dx.doi.org/10.1371/journal.pone.0161583 |
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author | Pan, Yonglong Wang, Xiaoming Liu, Lin Wang, Hao Luo, Meizhong |
author_facet | Pan, Yonglong Wang, Xiaoming Liu, Lin Wang, Hao Luo, Meizhong |
author_sort | Pan, Yonglong |
collection | PubMed |
description | A good physical map is essential to guide sequence assembly in de novo whole genome sequencing, especially when sequences are produced by high-throughput sequencing such as next-generation-sequencing (NGS) technology. We here present a novel method, Feature sets-based Genome Mapping (FGM). With FGM, physical map and draft whole genome sequences can be generated, anchored and integrated using the same data set of NGS sequences, independent of restriction digestion. Method model was created and parameters were inspected by simulations using the Arabidopsis genome sequence. In the simulations, when ~4.8X genome BAC library including 4,096 clones was used to sequence the whole genome, ~90% of clones were successfully connected to physical contigs, and 91.58% of genome sequences were mapped and connected to chromosomes. This method was experimentally verified using the existing physical map and genome sequence of rice. Of 4,064 clones covering 115 Mb sequence selected from ~3 tiles of 3 chromosomes of a rice draft physical map, 3,364 clones were reconstructed into physical contigs and 98 Mb sequences were integrated into the 3 chromosomes. The physical map-integrated draft genome sequences can provide permanent frameworks for eventually obtaining high-quality reference sequences by targeted sequencing, gap filling and combining other sequences. |
format | Online Article Text |
id | pubmed-5017645 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-50176452016-09-27 Whole Genome Mapping with Feature Sets from High-Throughput Sequencing Data Pan, Yonglong Wang, Xiaoming Liu, Lin Wang, Hao Luo, Meizhong PLoS One Research Article A good physical map is essential to guide sequence assembly in de novo whole genome sequencing, especially when sequences are produced by high-throughput sequencing such as next-generation-sequencing (NGS) technology. We here present a novel method, Feature sets-based Genome Mapping (FGM). With FGM, physical map and draft whole genome sequences can be generated, anchored and integrated using the same data set of NGS sequences, independent of restriction digestion. Method model was created and parameters were inspected by simulations using the Arabidopsis genome sequence. In the simulations, when ~4.8X genome BAC library including 4,096 clones was used to sequence the whole genome, ~90% of clones were successfully connected to physical contigs, and 91.58% of genome sequences were mapped and connected to chromosomes. This method was experimentally verified using the existing physical map and genome sequence of rice. Of 4,064 clones covering 115 Mb sequence selected from ~3 tiles of 3 chromosomes of a rice draft physical map, 3,364 clones were reconstructed into physical contigs and 98 Mb sequences were integrated into the 3 chromosomes. The physical map-integrated draft genome sequences can provide permanent frameworks for eventually obtaining high-quality reference sequences by targeted sequencing, gap filling and combining other sequences. Public Library of Science 2016-09-09 /pmc/articles/PMC5017645/ /pubmed/27611682 http://dx.doi.org/10.1371/journal.pone.0161583 Text en © 2016 Pan et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Pan, Yonglong Wang, Xiaoming Liu, Lin Wang, Hao Luo, Meizhong Whole Genome Mapping with Feature Sets from High-Throughput Sequencing Data |
title | Whole Genome Mapping with Feature Sets from High-Throughput Sequencing Data |
title_full | Whole Genome Mapping with Feature Sets from High-Throughput Sequencing Data |
title_fullStr | Whole Genome Mapping with Feature Sets from High-Throughput Sequencing Data |
title_full_unstemmed | Whole Genome Mapping with Feature Sets from High-Throughput Sequencing Data |
title_short | Whole Genome Mapping with Feature Sets from High-Throughput Sequencing Data |
title_sort | whole genome mapping with feature sets from high-throughput sequencing data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5017645/ https://www.ncbi.nlm.nih.gov/pubmed/27611682 http://dx.doi.org/10.1371/journal.pone.0161583 |
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