Timing of meristem initiation and maintenance determines the morphology of fern gametophytes.

Ceratopteris richardii Pteris vittata Apical initial cell division cell size fern gametophyte lateral meristem live imaging multicellular meristem seed-free plants

Journal

Journal of experimental botany
ISSN: 1460-2431
Titre abrégé: J Exp Bot
Pays: England
ID NLM: 9882906

Informations de publication

Date de publication:
26 10 2021
Historique:
received: 17 03 2021
accepted: 25 06 2021
pubmed: 29 6 2021
medline: 25 11 2021
entrez: 28 6 2021
Statut: ppublish

Résumé

The alternation of generations in land plants occurs between the sporophyte phase and the gametophyte phase. The sporophytes of seed plants develop self-maintained, multicellular meristems, and these meristems determine plant architecture. The gametophytes of seed plants lack meristems and are heterotrophic. In contrast, the gametophytes of seed-free vascular plants, including ferns, are autotrophic and free-living, developing meristems to sustain their independent growth and proliferation. Compared with meristems in the sporophytes of seed plants, the cellular mechanisms underlying meristem development in fern gametophytes remain largely unknown. Here, using confocal time-lapse live imaging and computational segmentation and quantification, we determined different patterns of cell divisions associated with the initiation and proliferation of two distinct types of meristems in gametophytes of two closely related Pteridaceae ferns, Pteris vittata and Ceratopteris richardii. Our results reveal how the simple timing of a switch between two meristems has considerable consequences for the divergent gametophyte morphologies of the two ferns. They further provide evolutionary insight into the function and regulation of gametophyte meristems in seed-free vascular plants.

Identifiants

pubmed: 34181730
pii: 6310841
doi: 10.1093/jxb/erab307
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

6990-7001

Informations de copyright

© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Auteurs

Xiao Wu (X)

Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN, USA.
Purdue Center for Plant Biology, Purdue University, West Lafayette, IN, USA.
Center of Pear Engineering Technology Research, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, Jiangsu, China.

An Yan (A)

Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
Howard Hughes Medical Institute, California Institute of Technology, Pasadena, CA, USA.

Scott A M McAdam (SAM)

Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN, USA.
Purdue Center for Plant Biology, Purdue University, West Lafayette, IN, USA.

Jo Ann Banks (JA)

Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN, USA.
Purdue Center for Plant Biology, Purdue University, West Lafayette, IN, USA.

Shaoling Zhang (S)

Center of Pear Engineering Technology Research, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, Jiangsu, China.

Yun Zhou (Y)

Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN, USA.
Purdue Center for Plant Biology, Purdue University, West Lafayette, IN, USA.

Articles similaires

A scenario for an evolutionary selection of ageing.

Tristan Roget, Claire Macmurray, Pierre Jolivet et al.
1.00
Aging Selection, Genetic Biological Evolution Animals Fertility
Biological Evolution History, 20th Century Selection, Genetic History, 19th Century Biology
Animals Biological Evolution Amphibians Fossils Wyoming

Constructing stability: optimal learning in noisy ecological niches.

Edward D Lee, Jessica C Flack, David C Krakauer
1.00
Learning Ecosystem Animals Models, Biological Game Theory

Classifications MeSH