Literature DB >> 12146788

Plant functional genomics.

Hauke Holtorf1, Marie-Christine Guitton, Ralf Reski.   

Abstract

Functional genome analysis of plants has entered the high-throughput stage. The complete genome information from key species such as Arabidopsis thaliana and rice is now available and will further boost the application of a range of new technologies to functional plant gene analysis. To broadly assign functions to unknown genes, different fast and multiparallel approaches are currently used and developed. These new technologies are based on known methods but are adapted and improved to accommodate for comprehensive, large-scale gene analysis, i.e. such techniques are novel in the sense that their design allows researchers to analyse many genes at the same time and at an unprecedented pace. Such methods allow analysis of the different constituents of the cell that help to deduce gene function, namely the transcripts, proteins and metabolites. Similarly the phenotypic variations of entire mutant collections can now be analysed in a much faster and more efficient way than before. The different methodologies have developed to form their own fields within the functional genomics technological platform and are termed transcriptomics, proteomics, metabolomics and phenomics. Gene function, however, cannot solely be inferred by using only one such approach. Rather, it is only by bringing together all the information collected by different functional genomic tools that one will be able to unequivocally assign functions to unknown plant genes. This review focuses on current technical developments and their impact on the field of plant functional genomics. The lower plant Physcomitrella is introduced as a new model system for gene function analysis, owing to its high rate of homologous recombination.

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Year:  2002        PMID: 12146788     DOI: 10.1007/s00114-002-0321-3

Source DB:  PubMed          Journal:  Naturwissenschaften        ISSN: 0028-1042


  14 in total

1.  Cyclin D-knockout uncouples developmental progression from sugar availability.

Authors:  Stefan Lorenz; Stefanie Tintelnot; Ralf Reski; Eva L Decker
Journal:  Plant Mol Biol       Date:  2003-09       Impact factor: 4.076

2.  Understanding DNA repair and recombination in higher plant genome: information from genome-wide screens in Arabidopsis and rice.

Authors:  Sanjay Kumar Singh; Swarup Roy Choudhury; Sujit Roy; Dibyendu N Sengupta
Journal:  Plant Signal Behav       Date:  2011-01-01

3.  A novel approach for nontargeted data analysis for metabolomics. Large-scale profiling of tomato fruit volatiles.

Authors:  Yury Tikunov; Arjen Lommen; C H Ric de Vos; Harrie A Verhoeven; Raoul J Bino; Robert D Hall; Arnaud G Bovy
Journal:  Plant Physiol       Date:  2005-11       Impact factor: 8.340

Review 4.  Natural and artificial mutants as valuable resources for functional genomics and molecular breeding.

Authors:  Shu-Ye Jiang; Srinivasan Ramachandran
Journal:  Int J Biol Sci       Date:  2010-04-28       Impact factor: 6.580

5.  An improved and highly standardised transformation procedure allows efficient production of single and multiple targeted gene-knockouts in a moss, Physcomitrella patens.

Authors:  Annette Hohe; Tanja Egener; Jan M Lucht; Hauke Holtorf; Christina Reinhard; Gabriele Schween; Ralf Reski
Journal:  Curr Genet       Date:  2003-10-29       Impact factor: 3.886

6.  Cisgenics - a sustainable approach for crop improvement.

Authors:  R S Telem; Shabir H Wani; N B Singh; R Nandini; R Sadhukhan; S Bhattacharya; N Mandal
Journal:  Curr Genomics       Date:  2013-11       Impact factor: 2.236

7.  Quantitative promoter analysis in Physcomitrella patens: a set of plant vectors activating gene expression within three orders of magnitude.

Authors:  Verena Horstmann; Claudia M Huether; Wolfgang Jost; Ralf Reski; Eva L Decker
Journal:  BMC Biotechnol       Date:  2004-07-07       Impact factor: 2.563

Review 8.  Advanced phenotyping and phenotype data analysis for the study of plant growth and development.

Authors:  Md Matiur Rahaman; Dijun Chen; Zeeshan Gillani; Christian Klukas; Ming Chen
Journal:  Front Plant Sci       Date:  2015-08-10       Impact factor: 5.753

9.  A bacterial quercetin oxidoreductase QuoA-mediated perturbation in the phenylpropanoid metabolic network increases lignification with a concomitant decrease in phenolamides in Arabidopsis.

Authors:  Sheela Reuben; Amit Rai; Bhinu V S Pillai; Amrith Rodrigues; Sanjay Swarup
Journal:  J Exp Bot       Date:  2013-10-01       Impact factor: 6.992

10.  Ascribing Functions to Genes: Journey Towards Genetic Improvement of Rice Via Functional Genomics.

Authors:  Ananda Mustafiz; Sumita Kumari; Ratna Karan
Journal:  Curr Genomics       Date:  2016-06       Impact factor: 2.236

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