Decoding the complete organelle genomic architecture of Stewartia gemmata: an early-diverging species in Theaceae.

Chloroplast genome Mitochondrial genome Phylogenetics Stewartia gemmate

Journal

BMC genomics
ISSN: 1471-2164
Titre abrégé: BMC Genomics
Pays: England
ID NLM: 100965258

Informations de publication

Date de publication:
25 Jan 2024
Historique:
received: 02 09 2023
accepted: 15 01 2024
medline: 26 1 2024
pubmed: 26 1 2024
entrez: 25 1 2024
Statut: epublish

Résumé

Theaceae, comprising 300 + species, holds significance in biodiversity, economics, and culture, notably including the globally consumed tea plant. Stewartia gemmata, a species of the earliest diverging tribe Stewartieae, is critical to offer insights into Theaceae's origin and evolutionary history. We sequenced the complete organelle genomes of Stewartia gemmata using short/long reads sequencing technologies. The chloroplast genome (158,406 bp) exhibited a quadripartite structure including the large single-copy region (LSC), a small single-copy region (SSC), and a pair of inverted repeat regions (IRs); 114 genes encoded 80 proteins, 30 tRNAs, and four rRNAs. The mitochondrial genome (681,203 bp) exhibited alternative conformations alongside a monocyclic structure: 61 genes encoding 38 proteins, 20 tRNAs, three rRNAs, and RNA editing-impacting genes, including ATP6, RPL16, COX2, NAD4L, NAD5, NAD7, and RPS1. Comparative analyses revealed frequent recombination events and apparent rRNA gene gains and losses in the mitochondrial genome of Theaceae. In organelle genomes, the protein-coding genes exhibited a strong A/U bias at codon endings; ENC-GC3 analysis implies selection-driven codon bias. Transposable elements might facilitate interorganelle sequence transfer. Phylogenetic analysis confirmed Stewartieae's early divergence within Theaceae, shedding light on organelle genome characteristics and evolution in Theaceae. We studied the detailed characterization of organelle genomes, including genome structure, composition, and repeated sequences, along with the identification of lateral gene transfer (LGT) events and complexities. The discovery of a large number of repetitive sequences and simple sequence repeats (SSRs) has led to new insights into molecular phylogenetic markers. Decoding the Stewartia gemmata organellar genome provides valuable genomic resources for further studies in tea plant phylogenomics and evolutionary biology.

Sections du résumé

BACKGROUND BACKGROUND
Theaceae, comprising 300 + species, holds significance in biodiversity, economics, and culture, notably including the globally consumed tea plant. Stewartia gemmata, a species of the earliest diverging tribe Stewartieae, is critical to offer insights into Theaceae's origin and evolutionary history.
RESULT RESULTS
We sequenced the complete organelle genomes of Stewartia gemmata using short/long reads sequencing technologies. The chloroplast genome (158,406 bp) exhibited a quadripartite structure including the large single-copy region (LSC), a small single-copy region (SSC), and a pair of inverted repeat regions (IRs); 114 genes encoded 80 proteins, 30 tRNAs, and four rRNAs. The mitochondrial genome (681,203 bp) exhibited alternative conformations alongside a monocyclic structure: 61 genes encoding 38 proteins, 20 tRNAs, three rRNAs, and RNA editing-impacting genes, including ATP6, RPL16, COX2, NAD4L, NAD5, NAD7, and RPS1. Comparative analyses revealed frequent recombination events and apparent rRNA gene gains and losses in the mitochondrial genome of Theaceae. In organelle genomes, the protein-coding genes exhibited a strong A/U bias at codon endings; ENC-GC3 analysis implies selection-driven codon bias. Transposable elements might facilitate interorganelle sequence transfer. Phylogenetic analysis confirmed Stewartieae's early divergence within Theaceae, shedding light on organelle genome characteristics and evolution in Theaceae.
CONCLUSIONS CONCLUSIONS
We studied the detailed characterization of organelle genomes, including genome structure, composition, and repeated sequences, along with the identification of lateral gene transfer (LGT) events and complexities. The discovery of a large number of repetitive sequences and simple sequence repeats (SSRs) has led to new insights into molecular phylogenetic markers. Decoding the Stewartia gemmata organellar genome provides valuable genomic resources for further studies in tea plant phylogenomics and evolutionary biology.

Identifiants

DOI: 10.1186/s12864-024-10016-8 PMID: 38273225
pubmed: 38273225
doi: 10.1186/s12864-024-10016-8
pii: 10.1186/s12864-024-10016-8
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

114

Subventions

Organisme : Program for Science & Technology Innovation Talents in Universities of Henan Province
ID : 21HASTIT040
Organisme : Program for Science & Technology Innovation Talents in Universities of Henan Province
ID : 21HASTIT040
Organisme : Scientific and Technological Project in Henan Province
ID : 212102110447
Organisme : Scientific and Technological Project in Henan Province
ID : 212102110447
Organisme : Key Laboratory of Functional Agriculture within Guizhou Province's Higher Education Institutions
ID : Qian-Jiao-Ji [2023]007
Organisme : Key Laboratory of Functional Agriculture within Guizhou Province's Higher Education Institutions
ID : Qian-Jiao-Ji [2023]007

Informations de copyright

© 2024. The Author(s).

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Auteurs

Daliang Liu (D)

Henan International Joint Laboratory of Tea-Oil Tree Biology and High-Value Utilization, College of Life Sciences, Xinyang Normal University, Xinyang, 464000, China.
Key Laboratory of Functional Agriculture in Higher Education of Guizhou Province, College of Agriculture, Guizhou University, Guiyang, 550025, China.
State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025, China.

Zhihan Zhang (Z)

Key Laboratory of Functional Agriculture in Higher Education of Guizhou Province, College of Agriculture, Guizhou University, Guiyang, 550025, China.
State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025, China.
College of Engineering and Technology, Northeast Forestry University, Harbin, 150040, China.

Yanlin Hao (Y)

Henan International Joint Laboratory of Tea-Oil Tree Biology and High-Value Utilization, College of Life Sciences, Xinyang Normal University, Xinyang, 464000, China.

Mengge Li (M)

Henan International Joint Laboratory of Tea-Oil Tree Biology and High-Value Utilization, College of Life Sciences, Xinyang Normal University, Xinyang, 464000, China.

Houlin Yu (H)

Department of Biochemistry and Molecular Biology, University of Massachusetts Amherst, Amherst, MA, 01003, USA.
Present address: Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.

Xingruo Zhang (X)

Department of Public Health Sciences, University of Chicago, Chicago, IL, 60637, USA.

Haoyang Mi (H)

Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA.

Lin Cheng (L)

Henan International Joint Laboratory of Tea-Oil Tree Biology and High-Value Utilization, College of Life Sciences, Xinyang Normal University, Xinyang, 464000, China. lzc5569@xynu.edu.cn.

Yiyong Zhao (Y)

Key Laboratory of Functional Agriculture in Higher Education of Guizhou Province, College of Agriculture, Guizhou University, Guiyang, 550025, China. yiyongzhao1991@gmail.com.
State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025, China. yiyongzhao1991@gmail.com.

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