Arabinogalactan proteins in plant sexual reproduction

PROTOPLASMA ◽  
1999 ◽  
Vol 208 (1-4) ◽  
pp. 87-98 ◽  
Author(s):  
A. Y. Cheung ◽  
H. -M. Wu
Keyword(s):  
Sexual Reproduction ◽  
Arabinogalactan Proteins ◽  
Plant Sexual Reproduction

The role of UV-B radiation in plant sexual reproduction

2015 ◽  
Vol 17 (3) ◽  
pp. 243-254 ◽  
Author(s):  
Laura Llorens ◽  
Francisco Rubén Badenes-Pérez ◽  
Riitta Julkunen-Tiitto ◽  
Christian Zidorn ◽  
Alberto Fereres ◽  
...  
Keyword(s):  
Sexual Reproduction ◽  
Plant Sexual Reproduction

scholarly journals Temperature stress and plant sexual reproduction: uncovering the weakest links

2010 ◽  
Vol 61 (7) ◽  
pp. 1959-1968 ◽  
Author(s):  
K. E. Zinn ◽  
M. Tunc-Ozdemir ◽  
J. F. Harper
Keyword(s):  
Sexual Reproduction ◽  
Temperature Stress ◽  
Plant Sexual Reproduction

Cell–cell communications and molecular mechanisms in plant sexual reproduction

2017 ◽  
Vol 131 (1) ◽  
pp. 37-47 ◽  
Author(s):  
Masahiro M. Kanaoka
Keyword(s):  
Sexual Reproduction ◽  
Molecular Mechanisms ◽  
Plant Sexual Reproduction ◽  
Cell Cell

scholarly journals Chromatin dynamics during plant sexual reproduction

2014 ◽  
Vol 5 ◽  
Author(s):  
Wenjing She ◽  
Célia Baroux
Keyword(s):  
Sexual Reproduction ◽  
Chromatin Dynamics ◽  
Plant Sexual Reproduction

scholarly journals Arabinogalactan proteins as molecular markers in Arabidopsis thaliana sexual reproduction

2007 ◽  
Vol 58 (15-16) ◽  
pp. 4027-4035 ◽  
Author(s):  
S. Coimbra ◽  
J. Almeida ◽  
V. Junqueira ◽  
M. L. Costa ◽  
L. G. Pereira
Keyword(s):  
Arabidopsis Thaliana ◽  
Molecular Markers ◽  
Sexual Reproduction ◽  
Arabinogalactan Proteins

scholarly journals Plant Sexual Reproduction: Perhaps the current plant two-sex model should be replaced with three- and four-sex models?

2020 ◽  
Author(s):  
Scott Meissner
Keyword(s):  
Life Cycle ◽  
Sexual Reproduction ◽  
The Other ◽  
Male And Female ◽  
Sexual Determination ◽  
New Models ◽  
Plant Sexual Reproduction ◽  
Alternation Of Generations

The current plant two-sex model makes the assumption that there are only two sexual reproductive states: male and female. However, the application of this model to the plant alternation of generations requires the subtle redefinition of several common terms related to sexual reproduction, which also seems to obscure aspects of one or the other plant generation: For instance, the homosporous sporophytic plant is treated as being “asexual,” and the gametophytes of angiosperms treated like mere gametes. In contrast, the proposal is made that the sporophytes of homosporous plants are indeed sexual reproductive organisms, as are the gametophytes of heterosporous plants. This view requires the expansion of the number of sexual reproductive states we accept for plants, therefore a three-sex model for homosporous plants and a four-sex model for heterosporous plants are described and then contrasted with the current two-sex model. These new models allow the use of sexual reproductive terms in a manner largely similar to that seen in animals, and may better accommodate the plant alternation of generations life cycle than does the current plant two-sex model. These new three-sex and four-sex models may also help stimulate new lines of research, and examples of how they might alter our view of the flower, and may lead to new perspectives in terms of sexual determination, are presented. Thus it is suggested that plants have more than merely two sexual reproductive states, and that recognition of this may promote our study and understanding of plants.

scholarly journals MCRiceRepGP: a framework for identification of sexual reproduction associated coding and lincRNA genes in rice

2018 ◽  
Author(s):  
Agnieszka A. Golicz ◽  
Prem L. Bhalla ◽  
Mohan B. Singh
Keyword(s):  
Machine Learning ◽  
Decision Analysis ◽  
Sexual Reproduction ◽  
Web Application ◽  
Molecular Mechanisms ◽  
Rice Genome ◽  
Protein Coding ◽  
Genome Wide ◽  
Plant Sexual Reproduction ◽  
Global Food

AbstractSexual reproduction in plants underpins global food production and evolution. It is a complex process, requiring intricate signalling pathways integrating a multitude of internal and external cues. However, key players and especially non-coding genes controlling plant sexual reproduction remain elusive. We report the development of MCRiceRepGP a novel machine learning framework, which integrates genomic, transcriptomic, homology and available phenotypic evidence and employs multi-criteria decision analysis and machine learning to predict coding and non-coding genes involved in rice sexual reproduction.The rice genome was re-annotated using deep sequencing transcriptomic data from reproduction-associated tissues/cell types identifying novel putative protein coding genes, transcript isoforms and long intergenic non-coding RNAs (lincRNAs). MCRiceRepGP was used for genome-wide discovery of sexual reproduction associated genes in rice; 2,275 protein-coding and 748 lincRNA genes were predicted to be involved in sexual reproduction. The annotation performed and the genes identified, especially the ones for which mutant lines with phenotypes are available provide a valuable resource. The analysis of genes identified gives insights into the genetic architecture of plant sexual reproduction. MCRiceRepGP can be used in combination with other genome-wide studies, like GWAS, giving more confidence that the genes identified are associated with the biological process of interest. As more data, especially about mutant plant phenotypes will become available, the power of MCRiceRepGP with grow providing researchers with a tool to identify candidate genes for future experiments. MCRiceRepGP is available as a web application (http://mcgplannotator.com/MCRiceRepGP/)Significance statementRice is a staple food crop plant for over half of the world’s population and sexual reproduction resulting in grain formation is a key process underpinning global food security. Despite considerable research efforts, much remains to be learned about the molecular mechanisms involved in rice sexual reproduction. We have developed MCRiceRepGP, a novel framework which allows prediction of sexual reproduction associated genes using multi-omics data, multicriteria decision analysis and machine learning. The genes identified and the methodology developed will become a significant resource for the plant research community.

scholarly journals Callose in Plant Sexual Reproduction

10.5772/53001 ◽  
2013 ◽  
Author(s):  
Meral nal ◽  
Filiz Vardar ◽  
zlem Ayturk
Keyword(s):  
Sexual Reproduction ◽  
Plant Sexual Reproduction
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