Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Samarth

PROVIDER: S-EPMC6693765 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

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

Samarth Lee Robyn R Song Jiancheng J Macknight Richard C RC Jameson Paula E PE

PloS one 20190814 8

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 c ...[more]

PMID: 31412034

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Project description:BackgroundGarlic (Allium sativum L.) is the second most widely cultivated Allium which is mainly grown in temperate regions and used as a flavoring agent in a wide variety of foods. Garlic contains various bioactive compounds whose metabolic pathways, plant-pathogen interactions, defensive genes, identify interaction networks, and functional genomics were not previously predicted in the garlic at the genomic level. To address this issue, we constructed two garlic Illumina 2000 libraries from tissues of garlic clove and leaf.ResultsApproximately 43 million 125 bp paired-end reads were obtained in the two libraries. A total of 239,973 contigs were generated by de novo assembly of both samples and were compared with the sequences in the NCBI non-redundant protein database (Nr). In total, 42% of contigs were matched to known proteins in public databases including Nr, Gene Ontology (GO), and Cluster Orthologous Gene Database (COG), and then, contigs were mapped to 138 via functional annotation against the Kyoto Encyclopedia of Genes and Genomes pathway database (KEGG). In addition, a number of regulatory genes including the CCHC (Zn) family, followed by WD40, bromodomain, bZIP, AP2-EREBP, BED-type (Zn) proteins, and defense response proteins related to different conserved domains, such as RGA3, NBS-LRR, TIR-NBS-LRR, LRR, NBS-ARC, and CC-NBS-LRR were discovered based on the transcriptome dataset. We compared the ortholog gene family of the A. sativum transcriptome to A. thaliana, O. sativa, and Z. mays and found that 12,077 orthologous gene families are specific to A. sativum L. Furthermore, we identified genes involved in plant defense mechanisms, their protein-protein interaction network, and plant-pathogen interaction pathways.ConclusionsOur study contains an extensive sequencing and functional gene-annotation analysis of A. sativum L. The findings provide insights into the molecular basis of TFs, defensive genes, and a reference for future studies on the genetics and breeding of A. sativum L.

Dataset Information

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

Publications

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

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