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Identification of flowering-time genes in mast flowering plants using De Novo transcriptomic analysis

Mast flowering is synchronised highly variable flowering by a population of perennial plants over a wide geographical area. High seeding years are seen as a threat to native and endangered species due to high predator density caused by the abundance of seed. An understanding of the molecular pathway...

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Autores principales: Samarth, Lee, Robyn, Song, Jiancheng, Macknight, Richard C., Jameson, Paula E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6693765/
https://www.ncbi.nlm.nih.gov/pubmed/31412034
http://dx.doi.org/10.1371/journal.pone.0216267
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author Samarth,
Lee, Robyn
Song, Jiancheng
Macknight, Richard C.
Jameson, Paula E.
author_facet Samarth,
Lee, Robyn
Song, Jiancheng
Macknight, Richard C.
Jameson, Paula E.
author_sort Samarth,
collection PubMed
description Mast flowering is synchronised highly variable flowering by a population of perennial plants over a wide geographical area. High seeding years are seen as a threat to native and endangered species due to high predator density caused by the abundance of seed. An understanding of the molecular pathways that influence masting behaviour in plants could provide better prediction of a forthcoming masting season and enable conservation strategies to be deployed. The goal of this study was to identify candidate flowering genes that might be involved in regulating mast flowering. To achieve this, high-throughput large-scale RNA-sequencing was performed on two masting plant species, Celmisia lyallii (Asteraceae), and Chionochloa pallens (Poaceae) to develop a reference transcriptome for functional and molecular analysis. An average total of 33 million 150 base-paired reads, for both species, were assembled using the Trinity pipeline, resulting in 151,803 and 348,649 transcripts respectively for C. lyallii and C. pallens. For both species, about 56% of the unigenes were annotated with gene descriptions to known proteins followed by Gene Ontology analysis, categorising them on the basis of putative biological processes, molecular function, and cellular localization. A total of 543 transcripts from C. lyallii and 470 transcripts from C. pallens were also mapped to unique flowering-time proteins identified in Arabidopsis thaliana, suggesting the conservation of the flowering network in these wild alpine plants growing in natural field conditions. Expression analysis of several selected homologous flowering-pathway genes showed seasonal and photoperiodic variations. These genes can further be analysed to understand why seasonal cues, such as the increasing photoperiod in spring, that triggers the annual flowering of most plants, are insufficient to always trigger flowering in masting plants and to uncover the molecular basis of how additional cues (such as temperature during the previous growing seasons) then determines flowering in mast years.
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spelling pubmed-66937652019-08-16 Identification of flowering-time genes in mast flowering plants using De Novo transcriptomic analysis Samarth, Lee, Robyn Song, Jiancheng Macknight, Richard C. Jameson, Paula E. PLoS One Research Article Mast flowering is synchronised highly variable flowering by a population of perennial plants over a wide geographical area. High seeding years are seen as a threat to native and endangered species due to high predator density caused by the abundance of seed. An understanding of the molecular pathways that influence masting behaviour in plants could provide better prediction of a forthcoming masting season and enable conservation strategies to be deployed. The goal of this study was to identify candidate flowering genes that might be involved in regulating mast flowering. To achieve this, high-throughput large-scale RNA-sequencing was performed on two masting plant species, Celmisia lyallii (Asteraceae), and Chionochloa pallens (Poaceae) to develop a reference transcriptome for functional and molecular analysis. An average total of 33 million 150 base-paired reads, for both species, were assembled using the Trinity pipeline, resulting in 151,803 and 348,649 transcripts respectively for C. lyallii and C. pallens. For both species, about 56% of the unigenes were annotated with gene descriptions to known proteins followed by Gene Ontology analysis, categorising them on the basis of putative biological processes, molecular function, and cellular localization. A total of 543 transcripts from C. lyallii and 470 transcripts from C. pallens were also mapped to unique flowering-time proteins identified in Arabidopsis thaliana, suggesting the conservation of the flowering network in these wild alpine plants growing in natural field conditions. Expression analysis of several selected homologous flowering-pathway genes showed seasonal and photoperiodic variations. These genes can further be analysed to understand why seasonal cues, such as the increasing photoperiod in spring, that triggers the annual flowering of most plants, are insufficient to always trigger flowering in masting plants and to uncover the molecular basis of how additional cues (such as temperature during the previous growing seasons) then determines flowering in mast years. Public Library of Science 2019-08-14 /pmc/articles/PMC6693765/ /pubmed/31412034 http://dx.doi.org/10.1371/journal.pone.0216267 Text en © 2019 Samarth 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
Samarth,
Lee, Robyn
Song, Jiancheng
Macknight, Richard C.
Jameson, Paula E.
Identification of flowering-time genes in mast flowering plants using De Novo transcriptomic analysis
title Identification of flowering-time genes in mast flowering plants using De Novo transcriptomic analysis
title_full Identification of flowering-time genes in mast flowering plants using De Novo transcriptomic analysis
title_fullStr Identification of flowering-time genes in mast flowering plants using De Novo transcriptomic analysis
title_full_unstemmed Identification of flowering-time genes in mast flowering plants using De Novo transcriptomic analysis
title_short Identification of flowering-time genes in mast flowering plants using De Novo transcriptomic analysis
title_sort identification of flowering-time genes in mast flowering plants using de novo transcriptomic analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6693765/
https://www.ncbi.nlm.nih.gov/pubmed/31412034
http://dx.doi.org/10.1371/journal.pone.0216267
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