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Construction of a de novo assembly pipeline using multiple transcriptome data sets from Cypripedium macranthos (Orchidaceae)
The family Orchidaceae comprises the most species of any monocotyledonous family and has interesting characteristics such as seed germination induced by mycorrhizal fungi and flower morphology that co-adapted with pollinators. In orchid species, genomes have been decoded for only a few horticultural...
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Published in: | PloS one 2023-06, Vol.18 (6), p.e0286804-e0286804 |
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description | The family Orchidaceae comprises the most species of any monocotyledonous family and has interesting characteristics such as seed germination induced by mycorrhizal fungi and flower morphology that co-adapted with pollinators. In orchid species, genomes have been decoded for only a few horticultural species, and there is little genetic information available. Generally, for species lacking sequenced genomes, gene sequences are predicted by de novo assembly of transcriptome data. Here, we devised a de novo assembly pipeline for transcriptome data from the wild orchid Cypripedium (lady slipper orchid) in Japan by mixing multiple data sets and integrating assemblies to create a more complete and less redundant contig set. Among the assemblies generated by combining various assemblers, Trinity and IDBA-Tran yielded good assembly with higher mapping rates and percentages of BLAST hit contigs and complete BUSCO. Using this contig set as a reference, we analyzed differential gene expression between protocorms grown aseptically or with mycorrhizal fungi to detect gene expressions required for mycorrhizal interaction. A pipeline proposed in this study can construct a highly reliable contig set with little redundancy even when multiple transcriptome data are mixed, and can provide a reference that is adaptable to DEG analysis and other downstream analysis in RNA-seq. |
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In orchid species, genomes have been decoded for only a few horticultural species, and there is little genetic information available. Generally, for species lacking sequenced genomes, gene sequences are predicted by de novo assembly of transcriptome data. Here, we devised a de novo assembly pipeline for transcriptome data from the wild orchid Cypripedium (lady slipper orchid) in Japan by mixing multiple data sets and integrating assemblies to create a more complete and less redundant contig set. Among the assemblies generated by combining various assemblers, Trinity and IDBA-Tran yielded good assembly with higher mapping rates and percentages of BLAST hit contigs and complete BUSCO. Using this contig set as a reference, we analyzed differential gene expression between protocorms grown aseptically or with mycorrhizal fungi to detect gene expressions required for mycorrhizal interaction. A pipeline proposed in this study can construct a highly reliable contig set with little redundancy even when multiple transcriptome data are mixed, and can provide a reference that is adaptable to DEG analysis and other downstream analysis in RNA-seq.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0286804</identifier><identifier>PMID: 37279244</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Assemblies ; Assembly ; Biology and Life Sciences ; Cypripedium ; Datasets ; Design and construction ; Fungi ; Gene expression ; Gene mapping ; Gene sequencing ; Genes ; Genomes ; Genomics ; Germination ; Orchidaceae ; Pipe lines ; Pipelines ; Pollinators ; Redundancy ; Research and Analysis Methods ; RNA ; Seed germination ; Seeds ; Symbiosis ; Transcription factors ; Transcriptomes</subject><ispartof>PloS one, 2023-06, Vol.18 (6), p.e0286804-e0286804</ispartof><rights>Copyright: © 2023 Kambara et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2023 Public Library of Science</rights><rights>2023 Kambara 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.</rights><rights>2023 Kambara et al 2023 Kambara et al</rights><rights>2023 Kambara 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. 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In orchid species, genomes have been decoded for only a few horticultural species, and there is little genetic information available. Generally, for species lacking sequenced genomes, gene sequences are predicted by de novo assembly of transcriptome data. Here, we devised a de novo assembly pipeline for transcriptome data from the wild orchid Cypripedium (lady slipper orchid) in Japan by mixing multiple data sets and integrating assemblies to create a more complete and less redundant contig set. Among the assemblies generated by combining various assemblers, Trinity and IDBA-Tran yielded good assembly with higher mapping rates and percentages of BLAST hit contigs and complete BUSCO. Using this contig set as a reference, we analyzed differential gene expression between protocorms grown aseptically or with mycorrhizal fungi to detect gene expressions required for mycorrhizal interaction. 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subjects | Analysis Assemblies Assembly Biology and Life Sciences Cypripedium Datasets Design and construction Fungi Gene expression Gene mapping Gene sequencing Genes Genomes Genomics Germination Orchidaceae Pipe lines Pipelines Pollinators Redundancy Research and Analysis Methods RNA Seed germination Seeds Symbiosis Transcription factors Transcriptomes |
title | Construction of a de novo assembly pipeline using multiple transcriptome data sets from Cypripedium macranthos (Orchidaceae) |
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