Semantic Assembly and Annotation of Draft RNAseq Transcripts without a Reference Genome
Transcriptomes are one of the first sources of high-throughput genomic data that have benefitted from the introduction of Next-Gen Sequencing. As sequencing technology becomes more accessible, transcriptome sequencing is applicable to multiple organisms for which genome sequences are unavailable. Cu...
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Published in | PloS one Vol. 10; no. 9; p. e0138006 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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Public Library of Science
22.09.2015
Public Library of Science (PLoS) |
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Abstract | Transcriptomes are one of the first sources of high-throughput genomic data that have benefitted from the introduction of Next-Gen Sequencing. As sequencing technology becomes more accessible, transcriptome sequencing is applicable to multiple organisms for which genome sequences are unavailable. Currently all methods for de novo assembly are based on the concept of matching the nucleotide context overlapping between short fragments-reads. However, even short reads may still contain biologically relevant information which can be used as hints in guiding the assembly process. We propose a computational workflow for the reconstruction and functional annotation of expressed gene transcripts that does not require a reference genome sequence and can be tolerant to low coverage, high error rates and other issues that often lead to poor results of de novo assembly in studies of non-model organisms. We start with either raw sequences or the output of a context-based de novo transcriptome assembly. Instead of mapping reads to a reference genome or creating a completely unsupervised clustering of reads, we assemble the unknown transcriptome using nearest homologs from a public database as seeds. We consider even distant relations, indirectly linking protein-coding fragments to entire gene families in multiple distantly related genomes. The intended application of the proposed method is an additional step of semantic (based on relations between protein-coding fragments) scaffolding following traditional (i.e. based on sequence overlap) de novo assembly. The method we developed was effective in analysis of the jellyfish Cyanea capillata transcriptome and may be applicable in other studies of gene expression in species lacking a high quality reference genome sequence. Our algorithms are implemented in C and designed for parallel computation using a high-performance computer. The software is available free of charge via an open source license. |
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AbstractList | Transcriptomes are one of the first sources of high-throughput genomic data that have benefitted from the introduction of Next-Gen Sequencing. As sequencing technology becomes more accessible, transcriptome sequencing is applicable to multiple organisms for which genome sequences are unavailable. Currently all methods for de novo assembly are based on the concept of matching the nucleotide context overlapping between short fragments-reads. However, even short reads may still contain biologically relevant information which can be used as hints in guiding the assembly process. We propose a computational workflow for the reconstruction and functional annotation of expressed gene transcripts that does not require a reference genome sequence and can be tolerant to low coverage, high error rates and other issues that often lead to poor results of de novo assembly in studies of non-model organisms. We start with either raw sequences or the output of a context-based de novo transcriptome assembly. Instead of mapping reads to a reference genome or creating a completely unsupervised clustering of reads, we assemble the unknown transcriptome using nearest homologs from a public database as seeds. We consider even distant relations, indirectly linking protein-coding fragments to entire gene families in multiple distantly related genomes. The intended application of the proposed method is an additional step of semantic (based on relations between protein-coding fragments) scaffolding following traditional (i.e. based on sequence overlap) de novo assembly. The method we developed was effective in analysis of the jellyfish Cyanea capillata transcriptome and may be applicable in other studies of gene expression in species lacking a high quality reference genome sequence. Our algorithms are implemented in C and designed for parallel computation using a high-performance computer. The software is available free of charge via an open source license. Transcriptomes are one of the first sources of high-throughput genomic data that have benefitted from the introduction of Next-Gen Sequencing. As sequencing technology becomes more accessible, transcriptome sequencing is applicable to multiple organisms for which genome sequences are unavailable. Currently all methods for de novo assembly are based on the concept of matching the nucleotide context overlapping between short fragments-reads. However, even short reads may still contain biologically relevant information which can be used as hints in guiding the assembly process. We propose a computational workflow for the reconstruction and functional annotation of expressed gene transcripts that does not require a reference genome sequence and can be tolerant to low coverage, high error rates and other issues that often lead to poor results of de novo assembly in studies of non-model organisms. We start with either raw sequences or the output of a context-based de novo transcriptome assembly. Instead of mapping reads to a reference genome or creating a completely unsupervised clustering of reads, we assemble the unknown transcriptome using nearest homologs from a public database as seeds. We consider even distant relations, indirectly linking protein-coding fragments to entire gene families in multiple distantly related genomes. The intended application of the proposed method is an additional step of semantic (based on relations between protein-coding fragments) scaffolding following traditional (i.e. based on sequence overlap) de novo assembly. The method we developed was effective in analysis of the jellyfish Cyanea capillata transcriptome and may be applicable in other studies of gene expression in species lacking a high quality reference genome sequence. Our algorithms are implemented in C and designed for parallel computation using a high-performance computer. The software is available free of charge via an open source license. |
Audience | Academic |
Author | Bouchard, Christelle Anderson, Peter A V Temanni, Ramzi Ptitsyn, Andrey |
AuthorAffiliation | 2 University of South Florida Sarasota-Manatee, 8350 N. Tamiami Trail, Sarasota, FL, 34243, United States of America University of North Carolina at Charlotte, UNITED STATES 1 Sidra Medical and Research Center, P.O. Box, 26999, Doha, Qatar 4 Department of Physiology and Functional Genomics, University of Florida; 9505 Ocean Shore Blvd, Saint Augustine, FL, 32080, United States of America 3 Whitney Laboratory for Marine Biosciences, University of Florida; 9505 Ocean Shore Blvd, Saint Augustine, FL, 32080, United States of America |
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Author_xml | – sequence: 1 givenname: Andrey surname: Ptitsyn fullname: Ptitsyn, Andrey organization: Sidra Medical and Research Center, P.O. Box, 26999, Doha, Qatar – sequence: 2 givenname: Ramzi surname: Temanni fullname: Temanni, Ramzi organization: Sidra Medical and Research Center, P.O. Box, 26999, Doha, Qatar – sequence: 3 givenname: Christelle surname: Bouchard fullname: Bouchard, Christelle organization: University of South Florida Sarasota-Manatee, 8350 N. Tamiami Trail, Sarasota, FL, 34243, United States of America – sequence: 4 givenname: Peter A V surname: Anderson fullname: Anderson, Peter A V organization: Whitney Laboratory for Marine Biosciences, University of Florida; 9505 Ocean Shore Blvd, Saint Augustine, FL, 32080, United States of America; Department of Physiology and Functional Genomics, University of Florida; 9505 Ocean Shore Blvd, Saint Augustine, FL, 32080, United States of America |
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CitedBy_id | crossref_primary_10_1093_bioinformatics_bty378 crossref_primary_10_1371_journal_pone_0218806 crossref_primary_10_3390_metabo13030388 |
Cites_doi | 10.1007/s11427-011-4255-x 10.1155/2010/853916 10.2307/1541225 10.1093/bib/5.1.39 10.1093/database/bar009 10.1242/jeb.133.1.231 10.1186/gb-2009-10-3-r25 10.1038/nprot.2008.211 10.1093/nar/gks804 10.1101/gr.103846.109 10.1101/gr.074492.107 10.1007/s00018-009-0180-6 10.1126/science.1080339 10.1093/bioinformatics/btp336 10.1093/nar/gkj123 10.1016/S0022-2836(05)80360-2 10.1152/jn.1985.53.3.821 10.1093/bioinformatics/bts094 10.1152/jn.1983.50.3.671 10.1038/nbt.1883 10.1038/nmeth.2251 |
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Copyright | COPYRIGHT 2015 Public Library of Science 2015 Ptitsyn et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2015 Ptitsyn et al 2015 Ptitsyn et al |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Competing Interests: The authors have declared that no competing interests exist. Conceived and designed the experiments: PAA CB. Performed the experiments: CB. Analyzed the data: AP RT. Contributed reagents/materials/analysis tools: AP. Wrote the paper: AP PAA. Designed the algorithm and implemented the software: AP. Performed additional case studies described in Supplemental Materials: RT. |
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SubjectTerms | Algorithms Annotations Assembly Bioinformatics Biology Clustering Computer applications Cyanea capillata Data processing Evolution Fragmentation Fragments Freeware Gene expression Gene families Gene mapping Gene sequencing Genes Genome Genomes Genomics Homology Nervous system Neurons Nucleotide sequence Organisms Parallel processing Physiology Proteins RNA - genetics RNA sequencing Scaffolding Scyphozoa Seeds Sequence Analysis, RNA - methods Transcriptome Workflow Workflow software |
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Title | Semantic Assembly and Annotation of Draft RNAseq Transcripts without a Reference Genome |
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