Sunday, October 12, 2014

Novel Approaches for Understanding Germination Control



QTL Analyses

Dormancy is a quantitative trait, involving many genes and is influenced substantially by environmental factors. Within a given plant species, different accessions of wild plants and different varieties of cultivated plants exhibit genetic variation in seed dormancy. Quantitative traits are becoming more amenable to genetic analysis because the position of quantitative trait loci (QTL) and the relative contribution of these loci can now be determined (reviewed in Koornneef et al., 2002). 


Recombinant inbred lines are best for QTL analysis of dormancy and allow the testing of a large number of genetically identical seeds in different environmental conditions. This type of analysis has been reported for Arabidopsis thaliana (Van Der Schaar, et al., 1997), barley (Han et al., 1996), rice (Lin et al., 1998) and wheat (Kato et al., 2001). Many of the QTL of wheat co-locate with those of barley, but not with those of rice (Kato et al., 2001). Crosses between wild and cultivated genotypes are useful for QTL analysis because of the deeper dormancy associated with the former (Cai and Morishma, 2000; Fennimore et al., 1999). This type of analysis in barley and Arabidopsis is being followed by the study of individual genes (or chromosome regions) containing specific dormancy QTL and by fine mapping (Koornneef et al., 2002). Ultimately these approaches may allow the molecular identification of genes that affect dormancy in these species by mapped-based cloning.
Metabolite Profiling

Metabolites are the end products of cellular regulatory processes, and their levels can be regarded as the ultimate response of biological systems to genetic or environmental changes. Thus, metabolomics is the link between genotype and phenotype (Fiehn, 2002) and this functional genomics approach will contribute to the understanding of complex developmental processes in plants, especially the regulation of metabolic networks and its perturbation by genetic or environmental means. The term ‘metabolomics’ encompasses many approaches including: (1) an unbiased identification and quantification of all metabolites in a given biological sample from an organism grown under defined conditions; (2) quantification of several pre-defined targets e.g. of all metabolites of a specific pathway or a set of metabolites typical for different pathways; (3) metabolic fingerprinting—the collection and analysis of crude metabolite mixtures to rapidly classify samples without separation of individual metabolites; and (4) metabolite target analysis—involving the development of specialised protocols for the analysis of a specific set of metabolites (e.g. hormones and hormone metabolites that can be present at low quantities and hence represent ‘difficult analytes’) (Fiehn, 2002). 

The number of metabolites present in plant kingdom is estimated to exceed 200 000 and a fundamental lack of biochemical and physiological knowledge about network organization in plants, may impede progress on some metabolomic initiatives (reviewed in Fiehn, 2002). However, regarding metabolite target analysis, a liquid chromatography electrospray tandem mass spectrometry method has been developed to quantify simultaneously all of the major plant hormone classes and hormone metabolites in seeds. Further, the technology has been applied to characterise hormone flux associated with secondary dormancy and germination of lettuce seeds (Chiwocha et al., 2003). Hormones and hormones metabolites targeted in this study included ABA and its metabolites (ABA-GE, 7′-OHABA, PA and DPA), indole-3-acetic acid (IAA), indole-3-aspartate (IAAsp), zeatin, zeatin riboside, isopentenyladenine, isopentenyladenosine, and gibberellins 1, 3, 4 and 7. 

Thermodormancy was achieved by incubating imbibed seeds at a non-optimal temperature for germination (33°C instead of 23°C). The state of secondary dormancy induced in this manner was associated with surprisingly active hormone flux. Moreover, the hormone and hormone metabolite profiles of germinating and thermodormant lettuce seeds were distinct. This was particularly true for ABA and its metabolites, in which thermodormant seeds accumulated high levels of DPA, while germinating seeds accumulated high amounts of ABA glucose ester. Thermodormant seeds were further distinguished from germinating seeds by exhibiting major accumulations of IAA and zeatin which were not accompanied by any significant increases in the levels of their conjugates IAAsp and zeatin riboside, respectively. The most striking changes potentially reflective of hormonal cross-talk included a marked accumulation of auxin (IAA) levels in thermodormant seeds, that was coincident with a major increase in the level of DPA (Chiwocha et al., 2003). Whether there is a key interaction between auxin biosynthesis and ABA catabolism remains to be determined.

Targeted metabolic profiling of plant hormones can be expanded to include a greater number of signalling compounds to give a more comprehensive view of hormone levels, hormone metabolism and changes in intracellular mediators (secondary messengers). Although these studies have not been performed yet on the seeds of a range of species, understanding metabolic flux during dormancy maintenance, termination of dormancy, germination and early post-germinative growth will generate information about how hormone-induced signalling networks control these complex processes in seeds. It will in essence provide a ‘snapshot’ of the hormone signalling status of the seed during key stages and transitions.

Transcriptomics and Proteomics

Genes and proteins whose patterns of expression/synthesis coincide with dormancy maintenance and its termination need to be functionally characterised. Further, the lack of sensitive screens for mutants and the high degree of gene redundancy in plant genomes has contributed to a reduced effectiveness of ‘forward genetic’ approaches to identifying the genes that play regulatory roles in the dormancy-to-germination and germination-to-growth transitions.

Proteomics approaches are being conducted to enhance our understanding of germination (Gallardo et al., 2001, 2002; reviewed in Bove et al., 2001). This type of analysis has been undertaken in Arabidopsis (ecotype Landsberg erecta). The basic approach involved two-dimensional gel electrophoresis separation of proteins derived from seeds at different stages (mature-dry, and mature seeds imbibed for 1, 2 and 3 days); about 1,300 proteins were resolved on the 2D gels and were classified with respect to their accumulation patterns. Several of the separated proteins were identified by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) spectrometry (Gallardo et al., 2001; reviewed in Bove et al., 2001). 

Germination sensu stricto (1 day imbibed seed) was characterised by changes in the abundance of ~40 proteins. Correlating with the resumption of cell elongation and cell-cycle activity, was the accumulation of an actin 7 (potentially required for germination and/or hypocotyl elongation), tubulin subunits and a WD-40-repeat protein (containing a repetitive segment of 40 amino acids ending in Trp-Asp). This latter protein resembles receptors of activated protein kinase C (having ~80% homology) and it may play a role in signal transduction and hormone-controlled cell division. Confirming several earlier studies (reviewed in Bewley, 1997), many of the proteins accumulated during very early hydration were derived from components of the mature dry seed (e.g. conserved mRNAs or proteins). The post-germinative phase was characterised by changes in the abundance of 35 proteins. Many were linked to the establishment of photosynthesis, the mobilisation of reserves or protective mechanisms (i.e. pathogen and herbivore-defence-related) (Gallardo et al., 2001). Unfortunately many of the changes in abundance of proteins were likely undetectable using these methods, in part due to the higher abundance of seed storage proteins and limitations associated with 2D gel techniques (e.g. hydrophobic proteins do not separate well). The ecotype of Arabidopsis used in the above-noted study exhibits little or no dormancy and it is likely that these studies will be followed up using the far more dormant Arabidopsis ecotype, Cape Verde Island (cvi) (Bove et al., 2001).

‘Phenomic’ approaches (functional genomic analyses of entire mutant collections) will aid in the unequivocal assignment of functions to unknown plant genes. Some of these studies have been initiated on mutants that are disrupted in hormone biosynthesis/response (Gallardo et al., 2002; Hoth et al., 2002). For example, a proteomics analysis to compare wild-type Arabidopsis seeds with seeds of the GA-deficient mutant (in which radicle emergence is completely dependent on exogenous GA) was undertaken (Gallardo et al., 2002). This study revealed that of the 40 or so proteins whose abundance changes during germination, only one, the cytoskeleton component αα-2,4 tubulin, appeared to require GA. The abundance of several proteins associated with later stages including metabolic control of seedling establishment was dependent on GA, and this included an increase in S-adenosyl-methionine synthetase, a housekeeping enzyme that catalyses the formation of S-adenosyl-methionine from ATP and methionone. Notably, GAs also appeared to control the abundance of the cell wall hydrolase, ββ-glucosidase, that possibly mediates embryo cell wall loosening involved in cell elongation and radicle extension (Gallardo et al., 2002).

Using a transcriptional profiling approach (massively parallel signature sequencing, or MPSS), Hoth et al. (2002) analysed gene regulation in seedlings of the abi1 mutant of Arabidopsis. Of the 1,354 genes that are responsive to exogenous ABA in wild-type seedlings, only ~9% of these ABA-responsive genes show a wild-type pattern of expression in the abi1 mutant seedlings; most exhibited reduced or strongly diminished expression. What is particularly interesting about the study is that several novel gene families were uncovered whose expression is ABA-regulated (Hoth et al., 2002). These included (1) About 100 genes encoding transcription factors or DNA-binding proteins; (2) Genes encoding ribosomal proteins that stabilise the tertiary structure of ribosomes and control the dynamics of protein synthesis; the majority of these (15 out of 21 identified) were down-regulated by ABA. (3) Genes encoding several proteins involved in regulated proteolysis. Most of these were up-regulated (~75%), and, in some cases, greater than 10-fold. Some of the encoded proteins had sequences that would predict RING finger motifs, F-boxes, or U-boxes; thus they may interact with target proteins of the ubiquitin-proteosome pathway (Hoth et al., 2002 and references therein). The ABA-repression of some the genes encoding these proteins further strengthens evidence from other studies showing that ABA blocks the degradation of certain proteins in seedlings (e.g. ABI5) (Lopez-Molina et al., 2001). (4) Genes encoding kinases and phosphatases, illustrating the importance of reversible protein phosphorylation as a key element of ABA signalling. About an equal number of genes encoding kinases (~40 in each case) were up- or down-regulated by ABA. However, the genes encoding phosphatases (most of which were type 2C phosphatases) were almost exclusively up-regulated by ABA. In the presence of ABA, dephosphorylation events may directly activate or inhibit transcription factors; alternatively, these may mediate oscillations in cytosolic Ca2+ concentrations that in turn regulate gene transcription (Hoth et al., 2002). Although the study did not focus on seed dormancy or germination, it illustrates the wealth of information regarding signal transduction pathways that can be derived from targeted functional genomics approaches.

Related Posts by Categories :



0 komentar:

Post a Comment