Although the general effect of stored mRNA degradation on the initial protein synthesis in seed germination can be easily understood, it needs to be pointed out that it is still an open question regarding which stored mRNAs are required for seed germination. Addressing this question would require specific elimination of the stored mRNAs of a particular gene without affecting other stored mRNAs and processes, which is difficult to achieve technically.
Since all stored mRNAs showed degradation in seed aging, we used a short fragment e. This method should be applicable for studying seed stored mRNAs in different plants. The long and short fragments do not have to be the same in lengths as the ones used here. For a different application, it would be good to determine the quantitative relationship between the fragment length and aging time Figure 4 , based on which suitable long and short fragments could be selected.
We observed two fundamental characteristics of stored mRNA degradation during seed aging. This finding indicates that when the mRNA length increases by the same increment e. Second, when a given length e. Based on these two characteristics, we can estimate the relative amount of undamaged mRNAs at a given aging time and frequency of degradation at one nucleotide level. The percentages of estimated undamaged mRNAs, e.
We further developed a method to estimate the average rate of degradation at one nucleotide level. The rates of degradation for six different mRNAs were also very similar. To our knowledge, there has been no previous report on quantifying the degradation of stored mRNAs during seed aging. It should allow comparisons of different mRNAs, different regions of the same mRNA, and different aging conditions in plant seeds.
Our quantitative analyses of individual stored mRNAs showed that each stored mRNAs was degraded at a constant rate over the aging time, while among different stored mRNAs analyzed they showed similar rates of degradation. Since all stored mRNAs analyzed in this study showed similar trends of gradual decreases, these results suggest a scenario that majority of stored mRNAs are degraded with a similar pattern and at a constant rate during seed aging.
The scale of work prevented us from comparing the rate of degradation for a large number of individual stored mRNAs in this study.
The methods developed in this study should help to address this question through comparative and quantitative analyses of individual stored mRNAs, which had been difficult to determine previously. In assessing seed aging status, the classical methods such as seed germination percentage and seedling growth have a few major problems: little change during the asymptomatic phase and the lack of strictly linear relationship between in the parameter analyzed and aging time.
A better parameter should have a tight linear relationship with seed aging time and be able to detect changes during the asymptomatic phase Fu et al. However, analyzing one or a few mRNAs is technically much simpler and requires less effort, cost and time than sequencing entire cDNA libraries. The fragment size distribution in the resulting cDNA libraries may not truly represent the fragment size distribution in the initial RNA samples due to the differences in the binding efficiency of different DNA fragment sizes to the DNA purifying matrix, affecting the quantitative analysis based on the cDNA fragment lengths.
Since seeds age with different speeds under different conditions, seed storage time may not be a good indicator of the seed aging status. Stored mRNAs can serve as more reliable biomarkers. We observed that the AA and NA seeds with 0. Thus, one possible way of measuring the aging status of different NA seeds is to establish a reference aging timeline using AA seeds, and then map the NA seed samples to a point on the reference timeline, in a way similar to the use of a reference protein to determine the concentrations of protein samples.
Thus, stored mRNAs could provide a more reliable and precise yardstick for determining seed aging status and facilitate seed aging research.
On the other hand, this method requires molecular biology expertise and equipment, which is technically more challenging and costs more compared to the traditional seed germination assay. The traditional methods such as seed germination assay could still provide reasonable indication of seed aging.
Thus, these methods may still be preferred for seed quality analysis laboratories, as they cost much less and require no molecular biology expertise and equipment. However, with time, molecular techniques might become simpler and more streamlined making the analysis of stored mRNA degradation easier to perform. In this study, we developed new methods to quantify the changes in seed stored mRNAs and estimate the rate of mRNA breakdown at one nucleotide level.
These methods should facilitate the studies of seed stored mRNAs in plants. Furthermore, these methods should also be applicable for analyzing slow RNA degradation in other plants and non-plant systems. For accelerated aging treatments, a procedure described previously Sugliani et al. Dry seeds were placed in 2 ml tubes with the cap removed each tube having mg seeds. After 7 days, a seed was considered germinated if the radicle was equal or longer than the length of the seed.
For the fresh seedling weight, all seedlings from one plate were weighed together and the average seedling weight was calculated. For the root length, seeds were sown on the plates, which were placed vertically in the growth chamber. After 10 days, plate images were taken, the primary root length of each seedling was measured with the NIH ImageJ software Version 1. At least three plates were used for each seed sample. In brief, seeds were grounded in liquid nitrogen.
The content was well mixed with handshaking. The supernatant was discarded and the pellet was further treated with DNase. In this protocol, all centrifugations were performed at 22, g. The gel images were obtained with a BioDoc-It imaging document system and used without any modifications except for cropping to show the DNA band. The mastermix For the unaged control sample, the copy number of amplified DNA C c for a specific fragment of mRNA at the threshold cycle can be estimated as:.
Similarly for the aged sample, the copy number of amplified DNA C a at the threshold cycle can be estimate as:. Our results suggested that the lesions to stored mRNAs occurred likely randomly. We derived an estimator for the probability of stored mRNA degradation at one nucleotide level. P 0 can be defined as the probability that no nucleotide is broken within the given mRNA template, and thus we have:. Ten mg seeds were soaked in 1. HW and Y-BF initiated the project. LZ performed most of the experimental work.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. LZ was partially supported by a devolved scholarship from the University of Saskatchewan. Almoguera, C. BMC Plant Biol. Ayala-Torres, S. Analysis of gene-specific DNA damage and repair using quantitative polymerase chain reaction.
Methods 22, — Bray, C. Lesions in the ribosomes of non-viable pea Pisum arvense embryonic axis tissue. Biochim Biophys. Acta , 14— Brocklehurst, P. Ribosomal RNA integrity and rate of seed germination. Planta , — Bueso, E. Plant Physiol. Callis, J. Chen, H. Comai, L. Coordinate expression of transcriptionally regulated isocitrate lyase and malate synthase genes in Brassica napus L.
Plant Cell 1, — Dure, L. Long-lived messenger Rna - evidence from cotton seed germination. FAO Google Scholar. Fernandez-Marin, B. Evidence for the absence of enzymatic reactions in the glassy state. A case study of xanthophyll cycle pigments in the desiccation-tolerant moss Syntrichia ruralis. Finch-Savage, W. Seed dormancy and the control of germination. New Phytol.
Fleming, M. Decline in RNA integrity of dry-stored soybean seeds correlates with loss of germination potential. The kinetics of ageing in dry-stored seeds: a comparison of viability loss and RNA degradation in unique legacy seed collections. Exploring the fate of mRNA in aging seeds: protection, destruction, or slow decay? Fragkostefanakis, S. Prospects of engineering thermotolerance in crops through modulation of heat stress transcription factor and heat shock protein networks.
Fu, Y. Towards a better monitoring of seed ageing under ex situ seed conservation. Crop Evol. Gadaleta, M. Reduced transcription of mitochondrial DNA in the senescent rat. Garza-Caligaris, L. At3g transcript: a molecular marker of seed ageing. Gupta, A. Held, P. An introduction to reactive oxygen species. Resources-App Guides , 5—9. Holdsworth, M. Therefore, proper watering and optimum temperature is necessary for a happily growing Arabidopsis plant.
It is also important to protect the plants from insects, so we hang pest-traps in the growth chamber to catch fungus gnats.
A Five-six old day plants. B day old plants. C 1 month old plants. Flowering: — At approximately four-five weeks, plants start flowering and are ready for transformation to produce transgenic lines Fig-4C. This means it is time to switch them from top to mid shelves. Only healthy looking flowering plants are used for transformation. Transformation and separation of lines: — Tranformation is achieved by infecting seeds with Agrobacterium, which transfers the DNA of interest to the the developing ovule and produces transgenic seeds.
Arabidopsis seeds are contained within siliques seed capsules , so before every transformation I make sure to cut all the already-formed siliques to increase the efficiency of getting transgenic seeds. After transformation, I lay the plants down in a flat Fig-5A for two days, after which they are placed upright and watered with nutrient solution.
One week after transformation the plants need to be stacked and tied Fig-5B , both to support them and to avoid any contact or entanglement with other plants. Contamination is the main issue while maintaining a transgenic line, so I use aricons Fig-5C , which provide proper air to the plants and help avoiding the mixing of seeds to other lines. A Plant after transformation. B Tied plants after transformation.
C Plants in Aricons. Harvesting and store seeds: — After 3 or 4 weeks of transformation, plants become brown and dried, indicating that they are ready for harvesting Fig-5B. Using scissors I carefully cut the plant from the pot, rub them with my fingers and strain the seeds to remove pods and plant debris Fig One plant can give thousands of seeds.
I always collect seeds in tubes containing 1 or 2 desiccant pellets. For long-term use, we store seeds in a desiccator at c. If seeds are not properly dry, over time their germination efficiency decreases. Transgenic plants: — After collecting the transgenic seeds I and sow them in a big black tray not in pots. Transgenic plants are resistant to the herbicide glufosinate-ammonium, so I spray the plants with this herbicide to select for successful transformants.
A Seeds are planted for selection. B Transgenic plants after selection. Advantages and disadvantages : — There is no need to be present around the clock, but the growth chamber has to be monitored frequently.
There is no fear of any infection, blood or need for surgery, and it is a very clean and friendly model organism. With proper care, seeds will remain viable for years, so it is possible to return to old projects easily. The only major disadvantage is the chance of cross-contamination between seed lines. One line can be contaminated easily when other groups or two researchers are working on different project in the same area. Also, the generation time of six to eight weeks is a bit slower than other systems.
But in the meantime, there are always molecular experiments to do. Known seed size mutants can be detected. B Three measurements of seeds from a wild-type left and a fis mutant silique right were normalized and plotted on a histogram, respectively.
To identify novel genes with effects on seed size and demonstrate the effectiveness of the scanner in a high-throughput application we performed a mutant screen. The identification of a novel mutant as part of a high-throughput screen demonstrates the effectiveness of this method in performing large-scale analysis of seed size phenotypes.
A large amount of genetic diversity is present between different accessions of Arabidopsis. This genetic diversity can be used in a QTL analysis to discover new loci that regulate seed size. Accessions with the greatest difference in seed size are most informative in a QTL analysis as they are more likely to contain alleles with large and easily detectable effects on seed size.
We aimed to detect differences in seed sizes between different accessions of Arabidopsis with a view of performing a QTL analysis. Significant differences in average seed size between accessions were observed Figure 5.
The average seed weight showed a strong correlation with average seed area See additional file 3 : Figure S2. Seeds of the Bur accession were clearly the largest, while Bay-0, L er , Eil and Sha accessions had the smallest seeds. Although we attempted to reduce biological variation by vernalization and trimming of the auxiliary buds, it is likely that maternal resource allocation still had some influence on the differences we observed.
We also examined the seed size of 80 different Arabidopsis accessions from the genomes project [ 19 ]. These results provide a basis for analyzing the natural variation in seed size found between accessions.
Variation between accessions can be detected. Seeds obtained from the stock center were measured directly using the scanner. To better define and identify putative QTLs, interval mapping was carried out using the EM algorithm. Similar results were obtained using Haley-Knott [ 21 ] and the extended Haley-Knott analysis [ 22 ] data not shown.
Given that multiple QTL were identified further analysis was used that could better identify and model the effects of multiple QTL segregating in the population. Therefore a 2 QTL analysis scantwo was used to compare each chromosome for likely additive effect and or interacting the full model QTL.
The significance of the association was determined using permutations. Linkage maps are shown for each chromosome with CC on the left and BC on the right. This was followed by an interaction of QTL on chromosomes 2 and 4 9. There was some evidence of a QTL on 5 with a significant result for the full model 5. Given this evidence and the results from the linkage mapping a chromosome 5 QTL was also included in the subsequent multiple QTL modeling.
This was used to determine the amount of variation in seed size explained for both the individual and combined QTL. Various models were tested including all of the QTL identified for the CvixCol and BurxCol crosses, including the two possible QTL on chromosome 4 as shown by the multiple peaks in Figure 6 from the interval mapping results , individually modeling each of the different positions for the QTL on chromosome 4, and possible interactions identified from the 2 QTL analysis.
The variance explained by each of the QTL varied from 3. Boxplots of the average seed size for each QTL marker genotype. Seed size is a trait of considerable importance. However, the small size of seeds and high levels of biological variation hinder its study in Arabidopsis. Here, we describe a rapid method of measuring seed size that is capable of detect subtle differences.
This method offers advantages over weighing large numbers of seeds to determine seed size, as it avoids the need to count individual seeds and, as every seed is measured individually, alterations in the distribution of seed sizes is easily identified. We demonstrate the utility of this method by successfully using it to identify a seed size mutant and seed size QTL. One important determinant of seed size is the rate and duration of endosperm proliferation during the early stages of seed development.
This has been demonstrated in crosses between Arabidopsis plants of different ploidies [ 12 ]. Seed development in these crosses is characterized by an increase in the rate and duration of division in peripheral endosperm, delayed endosperm cellularization and an increase in the size of chalazal endosperm [ 12 ].
Parental genome dosage effects, including the dosage of imprinted genes, have been implicated in seed viability of interploidy crosses [ 24 ]; however, it is known that the TTG2 gene, expressed in the maternal sporophytic tissues, plays a role in seed viability of these crosses and that the Col allele of TTG2 has a negative impact on seed viability in interploidy crosses [ 23 ].
The small seed size of these mutants is the result of reduced growth and early cellularization of the endosperm. As a first step to identify additional genes involved in endosperm development, we obtained the endosperm transcriptome from laser dissected proliferating endosperm tissue [ 18 ]. We identified genes that were preferentially expressed during early endosperm development.
To investigate if any of these genes affect endosperm proliferation, and therefore final seed size, we screened through homozygous SALK T-DNA insertion lines in these genes [ 17 ]. Using the scanner and image software allowed us to rapidly measure the seed size of T-DNA lines. However, these lines did not show any effect on seed size See additional file 2 : Table S1. Further analysis of this mutant indicated a chromosomal translocation had occurred which may be causing the phenotype data not shown , so a map-based cloning approach will be needed to isolate the mutation.
Nonetheless, the discovery of this seed size mutant demonstrates that our method is effective way of screening for novel mutants. Another approach for identifying genes involved in determining seed size is to utilize the considerable natural variation in the size of seeds from different Arabidopsis accessions. We grew 11 accessions under controlled conditions and measured the seed size, identifying the Bur accession as having the largest seeds Figure 5.
An additional 80 accessions with genome sequences available from the genomes project [ 19 ] were measured directly using seeds obtained from the stock center See additional file 4 : Figure S3.
The results obtained in our study are similar to those reported by de Jong et al. Accessions with large differences in seed size offer an ideal resource for identifying the underlying genetics. To determine if our method for measuring seed size could be used to identify QTL, we obtained two RIL populations generated using Col and the large seed size accessions Cvi and Bur. As we were interested in discovering QTL with a major affect on seed size, we limited our analysis to the core populations of RIL lines, described in Simon et al.
We are currently backcrossing a number of the RILs with Col to generate near isogenic lines to facilitate the cloning of the major QTL using a map-based approach.
The fact that the only the chromosome 4 QTL mapped to similar region in the two RIL populations, highlights the importance of using multiple parents to identify different alleles capable of affecting seed size. With an increasing number of RIL populations becoming available [ 20 , 26 , 27 ], our method for rapidly and accurately determining the seed size of the individual RILs should help facilitate the discovery of novel QTL. We have developed a simple, inexpensive and rapid method for measuring seed size that offers significant advantages over measuring seed weight.
Using this method, we identified a mutant with smaller seeds and discovered a number of seed size QTL, thus proving its utility in high-throughput and large scale applications. Siliques were harvested once they had turned completely brown but before they had dropped seeds. Siliques were allowed to dry in open microcentrifuge tubes for at least three days before measurement.
Dried silique material was removed using forceps and the seeds were spread onto the scanner bed Microtek Scanmaker i ensuring that no seeds were touching. Images were taken of each individual silique at a resolution of dpi using transmitted light.
ImageJ particle analysis software was used to measure seed area [ 28 ]. Flowers were emasculated using fine-tipped forceps taking care not to damage the ovary. Two days after emasculation, pollen from the appropriate male parent was applied to the tip of the stigma. Linkage maps were reconstructed for both populations using marker and recombination data from VNAT [ 29 ]. The linkage maps were initially assessed for associations with average seed size using single marker analysis and by then interval mapping using the EM algorithm.
A two-QTL genome scan using scantwo analysis was then used to identify QTL with additive or interactive effects referred to as the full model and significance thresholds were determined using permutations. The results from these analyses were used to develop multiple QTL models that were compared using the makeqtl and fitqtl functions. This model was then used to determine improved estimates of the QTL locations using refineqtl.
The 1. Plant Physiol. Plant Cell. Plant J.
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