Functional genomics aim to discover the biological function of particular genes and to uncover how sets of genes and their products work together. Transgenic plants are proving to be powerful tools to study various aspects of plant sciences. The emerging scientific revolution sparked by genomics based technologies is producing enormous amounts of DNA sequence information that, together with plant transformation methodology, is opening up new experimental opportunities for functional genomics analysis.
2. Plant functional genomics methods
The main methods of Plant Functional Genomics are as follows.
2.1. Functional annotations for genes
Gene function prediction is based on comparison of genomes and proteomes with searching homologies within different species to gene of interest with known functions from nucleotide and amino acid databases. Putative genes can be identified by scanning a genome for regions likely to encode proteins, based on characteristics such as long open reading frames, transcriptional initiation sequences, and polyadenylation sites. A sequence identified as a putative gene must be confirmed by further evidence, such as similarity to cDNA or EST sequences from the same organism, similarity of the predicted protein sequence to known proteins, association with promoter sequences, or evidence that mutating the sequence produces an observable phenotype.
2.2. Gene-targeted and site-directed mutagenesis. Reverse genetics methods (loss of function)
Using transgenic plant with insertion/deletion or site-specific mutations. Host gene is replaced with mutant allele. The most conventional approach to the analysis of gene function is loss-of-function mutagenesis by chemicals or fast neutrons that introduce random mutations or deletions in the genome (Ostergaard and Yanofsky 2004).
Transferred DNA (T-DNA) tagging or transposon tagging methods were developed to generate loss-of-function mutations because these tag sequences can be used to identify the genes disrupted by these elements (Sundaresan and Ramachandran 2001; Sussman et al. 1999). However, because many plant genes in
2.3. Overexpression of normal gene in transgenic plants (gain of function)
Gain-of-function approaches have been used as an alternative or complementary method to loss-of-function approaches as well as to confer new functions to plants. Gain-of-function is achieved by increasing gene expression levels through the random activation of endogenous genes by transcriptional enhancers or the expression of individual transgenes by transformation. Gain-of-function mutagenesis is based on the random insertion of transcriptional enhancers into the genome or the expression of transgenes under the control of a strong promoter (Matsui et al. 2006; Nakazawa et al. 2003; Weigel et al. 2000). In this approach, phenotypes of gain-of-function mutants that overexpress a member of a gene family can be observed without interference from other family members, which allows the characterization of functionally redundant genes(T. Ito and Meyerowitz 2000; Nakazawa et al. 2001).
Alternatively it is possible to overexpress mutant forms of a gene that interfere with the (wildtype) genes function. Over expression of a mutant gene may result in high levels of a non-functional protein resulting in a dominant negative interaction with the wild type protein. In this case the mutant version will out compete for the wild type proteins partners resulting in a mutant phenotype.
The advantages of gain-of function approaches in comparison to loss-of-function for the characterization of gene functions include the abilities to (
The first gain-of-function approach in plants was the activation-tagging system (Kakimoto 1996). In this system, T-DNA that harbors strong promoter or enhancer elements is randomly integrated into the plant genome. The introduced promoter or enhancer elements activate genes near the site of insertion.
Other recently developed gain-of-function approaches include cDNA overexpression and open reading frame (ORF) overexpression systems. In these approaches, cDNAs from Cdna libraries, representative full-length cDNAs (fl-cDNAs), or ORFs are strongly expressed when they were cloned downstream of a strong promoter.
The production of a large population of gain-of-function mutants can accelerate the high-throughput screening of desired mutants and the characterization of gene functions.
In the activation-tagging method, plant genes are randomly activated to produce gain-of function mutants. In this strategy, the promoter or enhancer elements from the
After the selection of mutants from the population of transformants, T-DNA insertion sites are determined to identify candidate genes.
Plasmid rescue, inverse PCR, or adapter PCR methods can be used to recover the genomic fragments near the T-DNA right and left border sequences (Spertini et al. 1999; Yamamoto et al. 2003). TAIL-PCR is also an efficient method to determine T-DNA insertion sites (Singer and Burke 2003)
Although many algorithms have been developed to predict the presence of transcriptional units within the genome, the accuracy of such predictions is still limited. Empirical information is required to correct annotation, and the main source of experimental information to achieve this is derived from RNA transcript analysis. Notable progress in
Progress in sequencing technology has revealed the genome sequences of many plant species that include
However, transgenic approaches for both forward and reverse genetic studies are not yet practical in many plants in which transformation methodology is inefficient or not available. A heterologous expression approach provides a solution for the high-throughput characterization of gene functions in these plant species.
One study used approximately 10,000 nonredundant fl-cDNA clones from the RIKEN
The introduced fl-cDNAs can be cloned easily using vector-specific primers after the isolation of mutants. Thus, the cDNA that caused the mutant phenotype can be directly linked to a function.
The full-length cDNA over-expressing gene (FOX) hunting system is an alternative gain of- function approach that uses fl-cDNAs. The FOX hunting system was applied for the high-throughput analysis of rice genes by heterologous expression in
These advantages have enabled researchers to express heterologous genes in
Whole genome sequencing makes it possible to predict the presence of genes in the genome. Of particular interest are the gene elements that encode proteins, called ORFs. Because ORFs can be distinguished from fl-cDNAs by their lack of 5_ and 3_ untranslated region (UTR) sequences, they can be considered a minimal unit of the gene that encodes information on the functional protein. The
2.4. Studying gene expression using DNA-RNA hybridization, gene silencing
Transgene expression in pair with reporter gene under control of inducible promoter allows to reveal temporal functional effects of gene expression and the compartmentalization of transgene products. The gene silencing techniques (also known as RNA-interference) allow to achieve temporary disrupting effects of gene expression (gene knockdown). This procedure offer the possibility to explore gene expression more precise.
Because transgene-induced RNAi has been effective at silencing one or more genes in a wide range of plants, this technology also bears potential as a powerful functional genomics tool across the plant kingdom.
RNA-induced gene silencing (RNAi), was originally observed as unusual expression patterns of a transgene designed to induce overexpression of chalcone synthase in petunia plants (Napoli et al. 1990).
In the years following this observation, experiments in many model systems contributed to rapid advancements in understanding the underlying mechanisms, and RNA-mediated gene silencing processes came to be collectively known as RNA interference (RNAi). It is known that the ‘triggers’ for RNAi were small RNAs, 21–25 nts in length, that were processed from longer, double-stranded (ds) RNAs by endonuclease proteins referred to as dicers (Fire et al. 1998; Hamilton and Baulcombe 1999; Mello et al. 2001; Zamore et al. 2000). These siRNAs cause direct degradation of mRNAs in a homology dependent manner and lead to post-transcriptional silencing of the silencing target. Other gene silencing methods are direct heterochromatin formation and DNA methylation at regulatory sequences for the target to be silenced, which alsoinduce transcriptional silencing of target loci in a homology dependent fashion (reviewed by ref. (Eamens et al. 2008). Now, it is understood that RNAi is an evolutionarily conserved mechanism for gene regulation that is critical for many examples of growth and development.
There are multiple pathways by which small RNA molecules can influence gene expression in plants, at both the transcriptional and post-transcriptional levels. These pathways vary in their sources of small RNAs and specific mechanisms of silencing (S. W. L. Chan 2008; Eamens et al. 2008; Verdel et al. 2009).
Because transgene-induced RNAi has been effective at silencing one or more genes in a wide range of plants, this technology also bears potential as a powerful functional genomics tool across the plant kingdom. A common strategy for functional genomics projects is to generate lines that are deficient for the activity of a subset of genes, and test the knock down lines for phenotypes to characterize the function of the knocked down gene.
In many cases, a single inverted repeat transgene can be designed to silence multiple, closely related genes (Springer et al. 2007).
To induce transcriptional silencing with a transgene, a typical strategy involves designing a construct such that a dsRNA is generated which bears homology to the promoter region of the intended silencing target (Mette et al. 2000). Herein, this method of silencing will be referred to as promoter directed RNA silencing.
To induce post-transcriptional silencing with a transgene, a portion of the coding region of the gene is typically introduced into an inverted repeat (IR) construct, and expression of that transgene will result in a dsRNA with homology to the coding region of the intended silencing target (McGinnis et al. 2005). This type of silencing is likely mediated by components of the trans-acting siRNA pathway in plants (reviewed by ref. Verdel et al. 2009). Herein, this method of silencing will be referred to as coding region directed RNA silencing.
2.5. Analysis of spatial and temporal expression of studied gene
Genomic studies tend to be done at the whole tissue/organ level due to the ease of collecting samples and/or the lack of tools necessary to isolate sufficient quantities of specific cell or tissue types. Recent studies, however, have shown that most transcriptional responses to environmental stimuli are cell-type specific (Dinneny 2008; Gifford et al. 2008). In addition, the many examples of ion-channels, hormone biosynthetic enzymes and signaling components with spatially complex expression patterns clearly illustrate the need to study all aspects of plant biology at high-spatial and temporal resolution to fully understand the plant–environment interaction.
The root of
Genetically-encoded fluorophores offer a vast tool kit to study
Transgene expression is usually driven by a constitutive promoter. Thus, high expression levels in inappropriate tissue or developmental contexts might occur. This misexpression can cause the ectopic expression of endogenous genes and might result in a phenotype that is not related to the authentic functions of the transgene. In some cases, this misexpression can lead to the incorrect functional annotation of genes. Tissue-specific expression can provide information on intracellular events in each tissue. Replacing the
Two component systems have been developed for conditional gene activation or silencing (Brand et al. 2006). They combine an activator locus that codes for an artificial transcription factor expressed in restricted tissues at precise developmental times.
The activation or the ectopic expression of developmentally controlled transcription factors sometimes causes an embryonic or seedling lethal phenotype, making it difficult to analyze the function of the gene. Thus, controlled gene expression by an inducible system might be an efficient approach to identify these genes (Zuo et al. 2002).
Microarrays allow the identification of candidate genes involved in a given process based on variation between transcript levels for different conditions and shared expression patterns with genes of known function. With appropriate controls and repeated experiments, significant data are obtained on gene expression profiles under various conditions (including stresses) or in various organs. Because of the large quantity of data produced by these techniques and the desire to find biologically meaningful patterns, bioinformatics is crucial to analyze functional genomics data. However, the DNA microarray and bioinformatics data are not sufficient for determining correct expression profiles due to limited accuracy of the obtained data. Next stage of investigations explores the properties and functions of selected genes. In this case, a transgenic plant construction is one of the most informative techniques.
2.7. Next generation sequencing
Previously, DNA sequencing was performed almost exclusively by the Sanger method, which has excellent accuracy and reasonable read length but very low throughput. Sanger sequencing was used to obtain the first sequence of the human genome in 2001 (Lander et al. 2001; Venter et al. 2001). Shortly thereafter, the second complete individual genome (James D. Watson) was sequenced using next-generation technology, which marked the first human genome sequenced with new Next Generation Sequencing (NGS) technology (Wheeler et al. 2008). A common strategy for NGS is to use DNA synthesis or ligation process to read through many different DNA templates in parallel (Fuller et al. 2009). Therefore, NGS reads DNA templates in a highly parallel manner to generate massive amounts of sequencing data but, as mentioned above, the read length for each DNA template is relatively short (35–500 bp) compared to traditional Sanger sequencing (1000–1200 bp). NGS technologies have increased the speed and throughput capacities of DNA sequencing and, as a result, dramatically reduced overall sequencing costs (Metzker 2010).
Current NGS approaches can be classified into three major categories:
DNA-Seq. Genome-based sequencing yielding genomic deletions and rearrangements, copy-number variations (CNV) of smaller regions or elements, and single-nucleotide polymorphisms (SNPs).
RNA-Seq. RNA-Sequencing, yielding genome-wide and quantitative information about transcribed regions (exons, and subsequently transcripts).
Chromatin-immunoprecipitation (ChIP)-Seq. a) transcription factor (TF)-based ChIP, yielding genome-wide information about the physical binding sites of individual TFs to within a few hundred base pairs. b) Epigenetic ChIP (DNA methylation and/or histone modifications), yielding information about modifications and the accessibility of genomic regions to TFs and other factors.
The inclusion of NGS-based transcriptome sequencing for ChIP of transcription factor binding and epigenetic analyses (usually based on DNA methylation or histone modification ChIP) completes the picture with unprecedented resolution enabling the detection of even subtle differences such as alternative splicing of individual exons.
Next-generation sequencing technologies have found broad applicability in functional genomics research. Their applications in the field have included gene expression profiling, genome annotation, small non-coding RNA (ncRNA) discovery and profiling, and detection of aberrant transcription, which are areas that have been previously dominated by microarrays. Thus, functional genomics and systems biology approaches will benefit from the enormous data density intrinsic to NGS applications, which will beyond doubt play an important role both in definition as well as verification of mathematical models of biological systems such as a cell or a tissue.
As mentioned above the inventory of methods used to study gene product functions
One of such models may be the approach that is developed in our laboratories that employ transgenic plants that constitutively express bacterial genes, which code enzymes that are functionally homologous to plant enzymes. Such an approach was proposed and used in our laboratory since mid-1980s (Piruzian et al. 1983; Piruzian and Andrianov 1986). It involves several stages: search a cloning of a gene of interest, sequencing, sequence modification (if needed, e.g. when codon usage in the gene is different from that in the model organism), gene transfer into the model organism, and studies of biochemical and phenotypic changes that entail expression of the foreign gene. Such an approach is feasible owing to the similarity of metabolic pathways and gene networks that regulate the activities of pro- and eukaryotic organisms under normal conditions and under exposure to various biotic and abiotic stresses. In addition, the use of bacterial genes helps to avoid many problems that arise during cloning, modifications and expression of eukaryotic genes in plants, whereas the constitutive nature of bacterial gene expression allows revealing “hot spots” of action of the homologous plant enzymes.
3. Usage of the methods of functional genomics for studying fundamental and applied aspects of plant life
3.1. Biotic stress tolerance
Activation tagging has been used for the isolation of mutants with resistance to biotic stress. For example,
Recently we have proposed the model for studying the role of plant dioxygenases. Phenolic compounds serve as antioxidants and protect plants from active oxygen species. The content of phenolic compounds changes as plants grow and get mature and in response to biotic and abiotic influences, and these changes are achieved through modulation of enzymatic activities involved in their synthesis and degradation. Enzymes that take part in oxidation of aromatic compounds include dioxygenases (Tsoi et al. 1988). These enzymes oxidize phenolic compounds by breaking the aromatic ring, and thus enable subsequent biodegradation of phenols. There is evidence that plant dioxygenase (coded for by the
3.2. Abiotic stress tolerance
Environmental stresses are the major factors adversely affecting plant growth and development as well as productivity. Of the various abiotic stresses, drought and osmotic stress cause considerable agronomic problems by limiting crop yield and distribution world-wide (Chaves and Oliveira 2004).
Drought and osmotic stress induce a range of alterations at the molecular, biochemical, and cellular levels in plants, including stomatal closure, repression of photosynthesis, accumulation of osmolytes, and the inducible expression of genes involved in stress tolerance (Shinozaki and Yamaguchi-Shinozaki 2007).
The accumulation of proline by plants is a common physiological indicator and occurs under various abiotic stresses. There is an increasing body of evidence supporting the role of proline as a compatible osmolyte that maintains cellular osmotic adjustment and stabilizes the structure of proteins and membrane integrity (Verbruggen and Hermans 2008). Overexpression of different genes has been shown to significantly enhance proline levels in transgenic rice and improve their tolerance to environmental stresses ( Ito et al. 2006; Liu et al. 2007; Pasquali et al. 2008; Xiang et al. 2007; Xu et al. 2008; Chen et al. 2009).
The transference of a single gene encoding a specific stress protein does not always result in sufficient expression to produce useful tolerance, because multiple and complex pathways are involved in controlling plant drought responses (Bohnert et al. 1995) and because modification of a single enzyme in a biochemical pathway is usually contrasted by a tendency of plant cells to restore homeostasis (Djilianov et al. 2002). Targeting multiple steps in a pathway may often modify metabolite fluxes in a more predictable manner. Another promising approach is therefore to engineer the overexpression of genes encoding stress inducible transcription factors.
There is increasingly more experimental support for the manipulation of the expression of stress-related transcription factor genes as a powerful tool in the engineering of stress-tolerant transgenic crops. This would, in turn, lead to the up-regulation of a series of stress-related genes under their control in transgenic plants (P. K. Agarwal et al. 2006).For example, the overexpression of transcription factor genes, such as ZFP252, SNAC1, OsNAC6, OsDREB1A, and HvCBF4, could enhance rice tolerance to different environmental stresses (Nakashima et al. 2007; Oh et al. 2007; Xiong et al. 2006; Xu et al. 2008; Yamaguchi-Shinozaki et al. 2006).
Following the application of microarray technology, several hundred stress induced genes, mainly in the model plant
Mutants with abiotic stress tolerance have been isolated by activation tagging and include the
FOX lines that consist of 43 stress-inducible transcription factors were constructed to elucidate stress-related gene function (Fujita et al. 2007). The T1 generation was screened for salt-stress-resistant lines and led to the identification of salt-tolerant lines. Among them, four lines harbored the same transgene,
Transcription factors play an important role in plant development and stress responses. The
Weiste and colleagues (Weiste et al. 2007) generated an ORF collection composed of members of the ERF transcription factor family. They constructed a destination vector to enable ectopic expression driven by the
Typically a gene coding for a transcription factor in
In other cases a gene coding for a transcription factor is isolated and characterized in
A high-throughput gain-of-function approach has been applied to isolate salt stress tolerance genes using cDNAs of
By overexpressing a Athsp101 protein, Katiyar-Agarwal and associates ( 2003) generated a heat-tolerant transgenic rice (cv. Pusa basmati 1) line. This group showed that almost all the transgenic plants recovered after severe heat stress of 45–500C and exhibited vigorous growth during the subsequent recovery at 280C, while the untransformed plants could not recover to a similar extent.
In our experiments with salt stress tolerance, we have selected a mutant of
Koh and co-workers ( 2007) reported that knockout (KO) mutants of rice
Huang and co-workers (2008b) generated transgenic tobacco expressing rice A20/AN1- type zinc finger protein gene (
Major efforts have been made to identify genes that are associated with drought stress in a number of plant species (Gong et al. 2010; Huang et al. 2008a; Manavalan et al. 2009; Tran and Mochida 2010; Zheng et al. 2010). In rice, identification of drought-responsive genes has been carried out by means of expression profiling studies such as microarrays, expressed sequence tags (ESTs), RNA gel blot analyses and qRT-PCR (Rabbani et al. 2003; Rabello et al. 2008; Ramachandran et al. 2008; Reddy et al. 2007; Zhou et al. 2007). As a result, hundreds of genes that were induced or suppressed by drought stress have been identified. A number of these genes have been analyzed in detail, resulting in their characters as regulatory genes, such as transcription factor (TF) and protein kinase encoding genes, whose products regulate other stress-responsive genes. Some of the identified stress-responsive genes are functional genes which encode metabolic components, such as late embryogenesis abundant (LEA) proteins and osmoprotectant-synthesizing enzymes, important for stress tolerance (Yang et al. 2010).
Recently, Yang and associates (2010) classified drought-responsive genes into three groups based on their biological functions: transcriptional regulation, post-transcriptional RNA or protein phosphorylation, and osmoprotectant metabolism or molecular chaperons. However, among the genes that are affected by drought many genes have unknown functions. Efforts will be continued to determine the functions of the unknown drought-responsive genes.
Aquaporins, which are water channel proteins that translocate water across cell membranes, have been demonstrated for their roles in various physiological processes including stomatal closure (Li et al. 2008).
The rice plasma membrane intrinsic proteins (OsPIP) proteins are subfamilies of aquaporins and are divided into two subgroups, OsPIP1 and OsPIP2. Several members of OsPIP1 and OsPIP2 subfamilies were responsive to drought and salt stresses. Transgenic
Transgenic rice overexpressing
In some cases however, constitutive expression of a gene normally only induced by stress, has negative effects – so-called pleiotropic effects (Chan et al. 2002; Kasuga et al. 1999; Nakashima et al. 2007) – on growth and development when stress is not present. One solution is to use inducible (rather than constitutive) promoters that allow expression of a transgene only when it is required, while it is silenced otherwise. For example constitutive expression in
An ideal stress-inducible promoter would be completely silenced under normal conditions, but induced by stress in a fairly short time (a few hours) after stress onset. The promoter of the
3.3. Increase of productivity
The development of unique transgenic plants provides an applied angle, in making available highly nutritious "speciality crops," and also adds to the genetic resources that can be used to develop insightful knowledge base about genetic, biochemical, and physiological regulation of various metabolic pathways and functional metabolites. The transgenic tomatoes that accumulate higher polyamines, Spd and Spm, during ripening are a kind of a "gain of function" genotype, and we are using them to address the questions on the role of polyamines in fruit metabolism, in particular, their crosstalks with other functional molecules to enable higher nutritional quality of vegetables and fruits.
In this case, a fruit ripening-specific promoter was used to drive the expression of yeast
An analysis of the principal, soluble constituents of wild-type and Spd/Spm-accumulating transgenic tomato, generated using high-resolution NMR spectroscopic methods, showed that the same metabolites were present in wild-type/azygous control tomatoes as in the transgenic tomato fruit. However, the latter conspicuously revealed differential metabolite content as compared to the controls (Mattoo et al. 2006). The red transgenic fruit were characterized by higher accumulation of the amino acids glutamine and asparagine; micronutrient choline; the organic acids citrate, fumarate, and malate; and an unidentified compound A. Compared to the control, wild-type fruit, the levels of valine, aspartic acid, sucrose, and glucose in the transgenic red fruit were reduced. These changes reflected specific alteration of metabolism, since the levels of isoleucine, glutamic acid, aminobutyric acid, phenylalanine, and fructose remained similar in the nontransgenic and transgenic fruits. Consequently, the transgenic red fruit have significantly higher fructose/glucose and acid [citrate+malate]/sugar [glucose+fructose+sucrose] ratios (Mattoo et al. 2006), consistent with higher fruit juice and nutritional quality reported in the 2 transgenics (Mehta et al. 2002), attributes favorably considered as higher quality in tomato breeding programs.
3.4. Xenobiotic tolerance
We have created transgenic plants expressing a mutant, glyphosate-resistant EPSP synthase from
3.5. Studying processes of plant physiology
One of the best examples of the use of the activation-tagging system to identify genes involved in plant development is the isolation of
LeClere and Bartel ( 2001) generated
Thus, the FOX hunting system is capable of the highthroughput characterization of gene functions.
A high-efficiency transformation method has been developed in rice. This makes rice an ideal host plant for the FOX hunting system (Ichikawa et al. 2007). More than 28,000 rice fl-cDNAs have been generated (Kikuchi et al. 2003). Approximately 12,000 rice lines have been generated in which 13,980 independent fl-cDNAs were overexpressed under the control of the ubiquitin promoter. Among several phenotypes in the T0 generation, three dwarf lines that carry the same novel
The ORF overexpression approach can also be used to investigate the function of putative genes identified by computer-based means. Small secreted peptides, less than 150 amino acids long, were predicted to identify genes involved in plant development in
The T-DNA vector pER16, which contains the estradiol-inducible promoter, was used for the conditional activation of nearby genes by the addition of estradiol. This system was used to identify the gene
Recently we have proposed a new strategy for creating experimental models for plant functional genomics. It is based on the expression in transgenic plants of genes from thermophilic bacteria encoding functional analogues of plant proteins with high specific activity and thermal stability. We have validated this strategy by comparing physiological, biochemical and molecular properties of control tobacco plants and transgenic plants expressing genes of β-glucanases with different substrate specificity. We demonstrate that the expression of bacterial β-1,3–1,4-glucanase gene exerts no significant influence on tobacco plant metabolism, while the expression of bacterial β-1,3-glucanase affects plant metabolism only at early stages of growth and development. By contrast, the expression of bacterial β-1,4-glucanase has a significant effect on transgenic tobacco plant metabolism, namely, it affects plant morphology, the thickness of the primary cell wall, phytohormonal status, and the relative sugar content. We propose a hypothesis of β-glucanase action as an important factor of genetic regulation of metabolic processes in plants.
It should also be mentioned that many plant enzymes have numerous isozymes, and for this reason the activity assays as well as functional studies of particular isozymes
The next our work was the construction of experimental models for studying the role of isopentyl transferases in phytohormone synthesis and plant differentiation.
It has been supposed that phytohormones, cytokinins in particular, are largely responsible for the viability of plants following exposure to abiotic stress and to pathogens. Therefore, an employment of genes whose expression alters the phytohormone balance for studying plant metabolism is deemed especially promising. One of such enzymes is isopentenyl transferase, a key enzyme of the cytokinin biosynthesis pathway. As a functional bacterial analogue of this enzyme, we have used isopentyl transferase (coded for by the T-
To study the role of enzymes related to hydrocarbon metabolism in plants we have chosen the gene
In plant functional genomics most approaches have introduced genes with a constitutive or inducible promoters, resulting in gene overexpression in transgenic plants. In some cases, however, it has been conferred by gene down-regulation by RNA interference, co-suppression or loss-of-function mutants. Each approach has advantages and disadvantages in different aspects of high-throughput characterization of gene functions. The first aspect is the basic construction strategy to produce a large population of mutant lines. The second aspect is whether mutants generated in each system can cover the vast numbers and wide variety of genes. Identification of all gene functions is the final goal of functional analysis at a genome level, and the production of mutants for this purpose. The final aspect is the enhancement of endogenous gene expression with tissue specificity. Highthroughput functional genomics is helping to shift the focus from the characterization of individual gene functions to a more systems-based holistic or synthetic approach to understand the genetic mechanisms that underlay gene regulation and complex signaling networks.
This work was supported by grant from Russian Academy of Sciences ("Biodiversity program"), and grant Russian Foundation for Basic Research (grant # 10-04-01195-Б).
Agarwal M. et al. 2003‘ Molecular characterization of rice hsp101: complementation of yeast hsp104 mutation by disaggregation of protein granules and differential expression in indica and japonica rice types’, 51 (4), 543 53.
Agarwal P. K. et al. 2006‘ Role of DREB transcription factors in abiotic and biotic stress tolerance in plants’, , 25 (12), 1263 1274
Ahad A. Nick P. 2007‘ Actin is bundled in activation-tagged tobacco mutants that tolerate aluminum’, , 225 (2), 451 468
Ahad A. Wolf J. Nick P. 2003‘ Activation-tagged tobacco mutants that are tolerant to antimicrotubular herbicides are cross-resistant to chilling stress’, , 12 (5), 615 29.
Anonymous 2000‘Analysis of the genome sequence of the flowering plant Arabidopsis thaliana’, 408 (6814), 796-815.
Ashikari M. et al. 2009‘ The ethylene response factors SNORKEL1 and SNORKEL2 allow rice to adapt to deep water’, , 460 (7258), 1026 U116-U116.
Bechtold N. Pelletier G. 1998‘ In planta Agrobacterium-mediated transformation of adult Arabidopsis thaliana plants by vacuum infiltration’, 82 259 66.
Bhatnagar-Mathur P. Vadez V. Sharma K. K. 2008‘ Transgenic approaches for abiotic stress tolerance in plants: retrospect and prospects’, 27 (3), 411 424
Birnbaum K. et al. 2003‘ A gene expression map of the Arabidopsis root’, , 302 (5652), 1956 1960
Birnbaum K. et al. 2005‘ Cell type-specific expression profiling in plants via cell sorting of protoplasts from fluorescent reporter lines’, 2 (8), 615 9.
Boerjan W. et al. 1995‘ Superroot, a recessive mutation in Arabidopsis, confers auxin overproduction’, , 7 (9), 1405 19.
Bohnert H. J. Nelson D. E. Jensen R. G. 1995‘ Adaptations to Environmental Stresses’, , 7 (7), 1099 111.
Borevitz J. O. et al. 2000‘ Activation tagging identifies a conserved MYB regulator of phenylpropanoid biosynthesis’, 12 (12), 2383-94.
Brady S. M. et al. 2007‘ A high-resolution root spatiotemporal map reveals dominant expression patterns’, , 318 (5851), 801 806.
Brand L. et al. 2006‘ A versatile and reliable two-component system for tissue-specific gene induction in Arabidopsis’, 141 (4), 1194- 204.
Capell T. Bassie L. Christou P. 2004‘ Modulation of the polyamine biosynthetic pathway in transgenic rice confers tolerance to drought stress’, 101 (26), 9909-14.
Carninci P. et al. 1998‘ Thermostabilization and thermoactivation of thermolabile enzymes by trehalose and its application for the synthesis of full length cDNA’, 95 (2), 520- 4.
( Carninci P. et al. 1997), ‘High efficiency selection of full-length cDNA by improved biotinylated cap trapper’, DNA Res, 4 (1), 61-6.
Carninci P. et al. 1996‘High-efficiency full-length cDNA cloning by biotinylated CAP trapper’, 37 (3), 327-36.
Chan M. T. et al. 2002‘Tomato plants ectopically expressing Arabidopsis CBF1 show enhanced resistance to water deficit stress’, 130 (2), 618-26.
Chan S. W. L. 2008‘Inputs and outputs for chromatin-targeted RNAi’, 13 (7), 383-89.
Chaves M. M. Oliveira M. M. 2004‘Mechanisms underlying plant resilience to water deficits: prospects for water-saving agriculture’, 55 (407), 2365-84.
Chen J. B. et al. 2009‘Cloning the PvP5CS gene from common bean (Phaseolus vulgaris) and its expression patterns under abiotic stresses’, 166 (1), 12-9.
Chen X. Guo Z. 2008‘Tobacco OPBP1 enhances salt tolerance and disease resistance of transgenic rice’, 9 (12), 2601-13.
Cheng Y. Dai X. Zhao Y. 2006‘Auxin biosynthesis by the YUCCA flavin monooxygenases controls the formation of floral organs and vascular tissues in Arabidopsis’, 20 (13), 1790-9.
Chu C. C. et al. 2008‘Overexpression of a rice OsDREB1F gene increases salt, drought, and low temperature tolerance in both Arabidopsis and rice’, 67 (6), 589-602.
Collins J. E. et al. 2004‘A genome annotation-driven approach to cloning the human ORFeome’, 5 (10), R84.
Cominelli E. et al. 2008‘Over-expression of the Arabidopsis AtMYB41 gene alters cell expansion and leaf surface permeability’, 53 (1), 53-64.
del Campillo E. 1999‘Multiple endo- 1 4-beta-D-glucanase (cellulase) genes in Arabidopsis’, 46, 39-61.
Delarue M. et al. 1998‘Sur2 mutations of Arabidopsis thaliana define a new locus involved in the control of auxin homeostasis’, 14 (5), 603-11.
Dinneny J. R. 2008‘Cell identity mediates the response of Arabidopsis roots to abiotic stress ( 320pg 942, 2008)’, 322 (5898), 44-44.
Dinneny J. R. 2010‘Analysis of the salt-stress response at cell-type resolution’, 33 (4), 543-51.
Dinneny J. R. et al. 2008‘Cell identity mediates the response of Arabidopsis roots to abiotic stress’, 320 (5878), 942-5.
Djilianov D. et al. 2002‘Freezing tolerant tobacco, transformed to accumulate osmoprotectants’, 163 (1), 157-64.
Du J. et al. 2008‘Functional gene-mining for salt-tolerance genes with the power of Arabidopsis’, 56 (4), 653-64.
Eamens A. et al. 2008‘RNA silencing in plants: Yesterday, today, and tomorrow’, 147 (2), 456-68.
Feng L. et al. 2007‘Overexpression of SBPase enhances photosynthesis against high temperature stress in transgenic rice plants’, 26 (9), 1635-46.
Fire A. et al. 1998‘Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans’, 391 (6669), 806-11.
Foolad M. R. et al. 2007‘Heat tolerance in plants: An overview’, 61 (3), 199-223.
Frommer W. B. Davidson M. W. Campbell R. E. 2009‘Genetically encoded biosensors based on engineered fluorescent proteins’, 38 (10), 2833-41.
Fujita M. et al. 2007‘Identification of stress-tolerance-related transcription-factor genes via mini-scale Full-length cDNA Over-eXpressor (FOX) gene hunting system’, 364 (2), 250-7.
Fuller C. W. et al. 2009‘The challenges of sequencing by synthesis’, 27 (11), 1013-23.
Gifford M. L. et al. 2008‘Cell-specific nitrogen responses mediate developmental plasticity’, 105 (2), 803-8.
Goff S. A. et al. 2002‘A draft sequence of the rice genome (Oryza sativa L. ssp japonica)’, 296 (5565), 92-100.
Goldenkova I. V. et al. 2002‘The Expression of the Bacterial Gene for Xylose(Glucose) Isomerase in Transgenic Tobacco Plants Affects Plant Morphology and Phytohormonal Balance’, 49 (4), 524-29.
Gong P. et al. 2010‘Transcriptional profiles of drought-responsive genes in modulating transcription signal transduction, and biochemical pathways in tomato’, 61 (13), 3563-75.
Guo L. et al. 2006‘Expression and functional analysis of the rice plasma-membrane intrinsic protein gene family’, 16 (3), 277-86.
Gurley W. B. 2000‘HSP101: a key component for the acquisition of thermotolerance in plants’, 12 (4), 457-60.
Hamilton A. J. Baulcombe D. C. 1999‘A species of small antisense RNA in posttranscriptional gene silencing in plants’, 286 (5441), 950-2.
Hara K. et al. 2007‘The secretory peptide gene EPF1 enforces the stomatal one-cell-spacing rule’, 21 (14), 1720-5.
Heyman J. A. et al. 1999‘Genome-scale cloning and expression of individual open reading frames using topoisomerase I-mediated ligation’, 9 (4), 383-92.
Hong S. W. Vierling E. 2000‘Mutants of Arabidopsis thaliana defective in the acquisition of tolerance to high temperature stress’, 97 (8), 4392-7.
Huang D. et al. 2008a‘The relationship of drought-related gene expression in Arabidopsis thaliana to hormonal and environmental factors’, 59 (11), 2991-3007.
Huang J. et al. 2008b‘Expression analysis of rice A20/AN 1-type zinc finger genes and characterization of ZFP177 that contributes to temperature stress tolerance’, 420 (2), 135-44.
Ichikawa H. et al. 2007‘A genome-wide gain-of-function analysis of rice genes using the FOX-hunting system’, 65 (4), 357-71.
Ito T. Meyerowitz E. M. 2000‘Overexpression of a gene encoding a cytochrome 450CYP78A9, induces large and seedless fruit in arabidopsis’, 12 (9), 1541-50.
Ito Y. et al. 2006‘Functional analysis of rice DREB1/CBF-type transcription factors involved in cold-responsive gene expression in transgenic rice’, 47 (1), 141-53.
Iusibov V. M. et al. 1989‘[Transfer of the agrobacterial gene for cytokinin biosynthesis into tobacco plants]’, (7), 11-3.
Iyer-Pascuzzi A. et al. 2009‘Functional genomics of root growth and development in Arabidopsis’, 12 (2), 165-71.
Jaillon O. et al. 2007‘The grapevine genome sequence suggests ancestral hexaploidization in major angiosperm phyla’, 449 (7161), 463-7.
Kakimoto T. 1996‘CKI1, a histidine kinase homolog implicated in cytokinin signal transduction’, 274 (5289), 982-5.
Kasuga M. et al. 1999‘Improving plant drought, salt, and freezing tolerance by gene transfer of a single stress-inducible transcription factor’, 17 (3), 287-91.
Katiyar-Agarwal S. Agarwal M. Grover A. 2003‘Heat-tolerant basmati rice engineered by over-expression of hsp101’, 51 (5), 677-86.
Kaul S. et al. 2000‘Analysis of the genome sequence of the flowering plant Arabidopsis thaliana’, 408 (6814), 796-815.
Kikuchi S. et al. 2003‘Collection, mapping, and annotation of over 28,000 cDNA clones from japonica rice’, 301 (5631), 376-9.
Kitagawa M. et al. 2005‘Complete set of ORF clones of Escherichia coli ASKA library (a complete set of E. coli K-12 ORF archive): unique resources for biological research’, 12 (5), 291-9.
Koch M. et al. 2006‘A role for a flavin-containing mono-oxygenase in resistance against microbial pathogens in Arabidopsis’, 47 (4), 629-39.
Koh J. H. et al. 2007‘T-DNA tagged knockout mutation of rice OsGSK1, an orthologue of Arabidopsis BIN2, with enhanced tolerance to various abiotic stresses’, 65 (4), 453-66.
Lander E. S. et al. 2001‘Initial sequencing and analysis of the human genome’, 409 (6822), 860-921.
Lawton K. Maleck K. 1998‘Plant Strategies for Resistance to Pathogens ‘, 9 208 13.
Le Clere S. Bartel B. 2001‘A library of Arabidopsis 35S-cDNA lines for identifying novel mutants’, 46 (6), 695-703.
Lee J. T. et al. 2003‘Expression of Arabidopsis CBF1 regulated by an ABA/stress inducible promoter in transgenic tomato confers stress tolerance without affecting yield’, 26 (7), 1181-90.
Li G. W. et al. 2008‘Characterization of OsPIP2;7, a water channel protein in rice’, 49 (12), 1851-8.
Libertini E. Li Y. Mc Queen-Mason S. J. 2004‘Phylogenetic analysis of the plant endo-beta- 1 4-glucanase gene family’, 58 (5), 506-15.
Liu K. et al. 2007‘Overexpression of OsCOIN, a putative cold inducible zinc finger protein, increased tolerance to chilling, salt and drought, and enhanced proline level in rice’, 226 (4), 1007-16.
Makarova R. V. et al. 1997‘Phytohormone Production in Tobacco ipt-Regenerates in vitro’, 44 (5), 762-68.
Manavalan L. P. et al. 2009‘Physiological and molecular approaches to improve drought resistance in soybean’, 50 (7), 1260-76.
Mathews H. et al. 2003‘Activation tagging in tomato identifies a transcriptional regulator of anthocyanin biosynthesis, modification, and transport’, 15 (8), 1689-703.
Matsui M. et al. 2006‘The FOX hunting system: an alternative gain-of-function gene hunting technique’, 48 (6), 974-85.
Matsui M. et al. 2009‘Systematic approaches to using the FOX hunting system to identify useful rice genes’, 57 (5), 883-94.
Matsuyama A. et al. 2006‘ORFeome cloning and global analysis of protein localization in the fission yeast Schizosaccharomyces pombe ( 24pg 841, 2006)’, 24 (8), 1033-33.
Mattoo A. K. et al. 2006‘Nuclear magnetic resonance spectroscopy-based metabolite profiling of transgenic tomato fruit engineered to accumulate spermidine and spermine reveals enhanced anabolic and nitrogen-carbon interactions’, 142 (4), 1759-70.
Mayer K. F. et al. 1998‘Role of WUSCHEL in regulating stem cell fate in the Arabidopsis shoot meristem’, 95 (6), 805-15.
Mc Ginnis K. et al. 2005‘Transgene-induced RNA interference as a tool for plant functional genomics’, 392 1 24.
Mehta R. A. et al. 2002‘Engineered polyamine accumulation in tomato enhances phytonutrient content, juice quality, and vine life’, 20 (6), 613-8.
Mello C. C. et al. 2001‘Genes and mechanisms related to RNA interference regulate expression of the small temporal RNAs that control C-elegans developmental timing’, 106 (1), 23-34.
Mett V. L. et al. 1991‘Cloning and Expression of Mutant Gene for EPSP-Syntase Escherichia coli in Transgenic Plants.’, 3 19 22.
Mette M. F. et al. 2000‘Transcriptional silencing and promoter methylation triggered by double-stranded RNA’, 19 (19), 5194-201.
Metzker M. L. 2010‘Sequencing technologies- the next generation’, 11 (1), 31-46.
Ming R. et al. 2008‘The draft genome of the transgenic tropical fruit tree papaya (Carica papaya Linnaeus)’, 452 (7190), 991-6.
Mittler R. Feng X. Cohen M. 1998‘Post-transcriptional suppression of cytosolic ascorbate peroxidase expression during pathogen-induced programmed cell death in tobacco’, 10 (3), 461-73.
Nakashima K. et al. 2007‘Functional analysis of a NAC-type transcription factor OsNAC6 involved in abiotic and biotic stress-responsive gene expression in rice’, 51 (4), 617-30.
Nakazawa M. et al. 2001‘DFL1, an auxin-responsive GH3 gene homologue, negatively regulates shoot cell elongation and lateral root formation, and positively regulates the light response of hypocotyl length’, 25 (2), 213-21.
Nakazawa M. et al. 2003‘Activation tagging, a novel tool to dissect the functions of a gene family’, 34 (5), 741-50.
Nanjo T. et al. 2007‘Functional annotation of 19,841 Populus nigra full-length enriched cDNA clones’, 8, 448.
Napoli C. Lemieux C. Jorgensen R. 1990‘Introduction of a Chimeric Chalcone Synthase Gene into Petunia Results in Reversible Co-Suppression of Homologous Genes in Trans’, 2 (4), 279-89.
Nelson D. E. et al. 2007‘Plant nuclear factor Y (NF-Y) B subunits confer drought tolerance and lead to improved corn yields on water-limited acres’, 104 (42), 16450-55.
Neumyvakin L. V. Kobets N. S. Piruzian E. S. 1990‘Cultivation of an Escherichia coli Mutant Superproducing Proline and Resistant to Increased Concentration of NaCl. ‘, 26 (8), 1370-79.
Neumyvakin L. V. Kobets N. S. Piruzian E. S. 1991‘Obtaining and Cloning Mutant proBosm Gene from Escherichia coli Providing the Resistant to Increased Concentration of NaCl. ‘, 33, 122.
Nishiyama T. et al. 2003‘Comparative genomics of Physcomitrella patens gametophytic transcriptome and Arabidopsis thaliana: implication for land plant evolution’, 100 (13), 8007-12.
Odell J. T. Nagy F. Chua N. H. 1985‘Identification of DNA sequences required for activity of the cauliflower mosaic virus 35S promoter’, 313 (6005), 810-2.
Ogihara Y. et al. 2004‘Construction of a full-length cDNA library from young spikelets of hexaploid wheat and its characterization by large-scale sequencing of expressed sequence tags’, 79 (4), 227-32.
Oh S. J. et al. 2007‘Expression of barley HvCBF4 enhances tolerance to abiotic stress in transgenic rice’, 5 (5), 646-56.
Okazaki K. et al. 2009‘The PLASTID DIVISION1 and 2 components of the chloroplast division machinery determine the rate of chloroplast division in land plant cell differentiation’, 21 (6), 1769-80.
Ostergaard L. Yanofsky M. F. 2004‘Establishing gene function by mutagenesis in Arabidopsis thaliana’, 39 (5), 682-96.
Pasquali G. et al. 2008‘Osmyb4 expression improves adaptive responses to drought and cold stress in transgenic apples’, 27 (10), 1677-86.
Paterson A. H. et al. 2009‘The Sorghum bicolor genome and the diversification of grasses’, 457 (7229), 551-6.
Paz-Ares J. et al. 1998‘More than 80R2R 3-MYB regulatory genes in the genome of Arabidopsis thaliana’, 14 (3), 273-84.
Pereira A. et al. 2002‘Activation tagging using the En-I maize transposon system in Arabidopsis’, 129 (4), 1544-56.
Pereira A. et al. 2004‘The SHINE clade of AP2 domain transcription factors activates wax biosynthesis, alters cuticle properties, and confers drought tolerance when overexpressed in Arabidopsis’, 16 (9), 2463-80.
Pereira A. et al. 2007‘Improvement of water use efficiency in rice by expression of HARDY, an Arabidopsis drought and salt tolerance gene’, 104 (39), 15270-75.
Piano F. et al. 2005‘New genes with roles in the C-elegans embryo revealed using RNAi of ovary-enriched ORFeome clones’, 15 (2), 250-59.
Piruzian E. S. Andrianov V. M. 1986‘Cloning and analysis of replication region of the C58 nopaline Ti plasmid and its application for foreign gene transfer into plants’, Genetika (Russian), 22 2674 83.
Piruzian E. S. Stekhin I. N. Andrianov V. M. 1983‘[Cloning of the Ti-plasmid DNA fragments of Agrobacterium tumefaciens in Escherichia coli and the identification of the site of origin of Ti-plasmid replication]’, 273 (5), 1249-51.
Piruzian E. S. et al. 1988‘The use of bacterial genes encoding herbicide tolerance in constructing transgenic plants’, 5 (8), 242-8.
Piruzian E. S. et al. 1989‘[Expression of the Escherichia coli glucose isomerase gene in transgenic plants]’, 305 (3), 729-31.
Piruzian E. S. et al. 2002‘Physiological and Biochemical Characteristics of Tobacco Transgenic Plants Expressing Bacterial Dioxygenase ‘, 49 817 22.
Piruzian E. S. et al. 2000‘Transgenic Plants Expressing Foreign Genes as a Model for Studying Plant Stress Responses and a Source for Resistant Plant Forms’, 47 (3), 327-36.
Qi Y. et al. 2011‘Over-expression of mitochondrial heat shock protein 70 suppresses programmed cell death in rice’, 585 (1), 231-9.
Rabbani M. A. et al. 2003‘Monitoring expression profiles of rice genes under cold, drought, and high-salinity stresses and abscisic acid application using cDNA microarray and RNA gel-blot analyses’, 133 (4), 1755-67.
Rabello A. R. et al. 2008‘Identification of drought-responsive genes in roots of upland rice (Oryza sativa L)’, 9, 485.
Ralph S. G. et al. 2008‘A conifer genomics resource of 200,000 spruce (Picea spp.) ESTs and 6,464 high-quality, sequence-finished full-length cDNAs for Sitka spruce (Picea sitchensis)’, 9, 484.
Ramachandran S. et al. 2008‘A comprehensive transcriptional profiling of the WRKY gene family in rice under various abiotic and phytohormone treatments’, 49 (6), 865-79.
Reddy A. R. et al. 2007‘Identification of stress-responsive genes in an indica rice (Oryza sativa L.) using ESTs generated from drought-stressed seedlings’, 58 (2), 253-65.
Ronald P. C. et al. 2006‘Sub1A is an ethylene-response-factor-like gene that confers submergence tolerance to rice’, 442 (7103), 705-08.
Rual J. F. et al. 2004‘Human ORFeome version 1.1: a platform for reverse proteomics’, 14 (10B), 2128 35.
Sakurai T. et al. 2005‘RARGE: a large-scale database of RIKEN Arabidopsis resources ranging from transcriptome to phenome’, 33 (Database D647-50 647 50.
Sakurai T. et al. 2007‘Sequencing analysis of 20,000 full-length cDNA clones from cassava reveals lineage specific expansions in gene families related to stress response’, 7, 66.
Sasaki T. et al. 2002‘The genome sequence and structure of rice chromosome 1’, 420 (6913), 312-6.
Sato K. et al. 2009‘Development of 5006 full-length CDNAs in barley: a tool for accessing cereal genomics resources’, 16 (2), 81-9.
Sato Y. et al. 2004‘Over-expression of a small heat shock protein, sHSP17.7, confers both heat tolerance and UV-B resistance to rice plants’, 13 (2), 165-75.
Seki M. et al. 2002‘Functional annotation of a full-length Arabidopsis cDNA collection’, 296 (5565), 141-5.
Shinozaki K. Yamaguchi-Shinozaki K. 2007‘Gene networks involved in drought stress response and tolerance’, 58 (2), 221-7.
Singer T. Burke E. 2003‘High-throughput TAIL-PCR as a tool to identify DNA flanking insertions’, 236 241 72.
Slakeski N. et al. 1990‘Structure and tissue-specific regulation of genes encoding barley (1----3, 1----4)-beta-glucan endohydrolases’, 224 (3), 437-49.
Sokhansandzh A. et al. 1997‘[Transfer of bacterial genes for proline synthesis in plants and their expression by various plant promotors]’, 33 (7), 906-13.
Spertini D. Beliveau C. Bellemare G. 1999‘Screening of transgenic plants by amplification of unknown genomic DNA flanking T-DNA’, 27 (2), 308-14.
Springer N. M. et al. 2007‘Assessing the efficiency of RNA interference for maize functional genomics’, 143 (4), 1441-51.
Sundaresan V. Ramachandran S. 2001‘Transposons as tools for functional genomics’, 39 (3-4), 243-52.
Sussman M. R. Krysan P. J. Young J. C. 1999‘T-DNA as an insertional mutagen in Arabidopsis’, 11 (12), 2283-90.
Taji T. et al. 2008‘Large-scale collection and annotation of full-length enriched cDNAs from a model halophyte, Thellungiella halophila’, 8, 115.
Toyoda T. Shinozaki K. 2005‘Tiling array-driven elucidation of transcriptional structures based on maximum-likelihood and Markov models’, 43 (4), 611-21.
Tran L. S. Mochida K. 2010‘Functional genomics of soybean for improvement of productivity in adverse conditions’, 10 (4), 447-62.
Tsoi T. V. et al. 1988‘[Cloning and expression of Pseudomonas putida gene controlling the catechol- 2 3-oxygenase activity in Escherichia coli cells]’, 24 (9), 1550-61.
Tuskan G. A. et al. 2006‘The genome of black cottonwood, Populus trichocarpa (Torr. & Gray)’, 313 (5793), 1596-604.
Umezawa T. et al. 2008‘Sequencing and analysis of approximately 40,000 soybean cDNA clones from a full-length-enriched cDNA library’, 15 (6), 333-46.
Venter J. C. et al. 2001‘The sequence of the human genome’, 291 (5507), 1304-51.
Verbruggen N. Hermans C. 2008‘Proline accumulation in plants: a review’, 35 (4), 753-9.
Verdel A. et al. 2009‘Common themes in siRNA-mediated epigenetic silencing pathways’, 53 (2-3), 245-57.
Weigel D. et al. 2000‘Activation tagging in Arabidopsis’, 122 (4), 1003-13.
Weisshaar B. et al. 1998‘Towards functional characterisation of the members of the R2R 3-MYB gene family from Arabidopsis thaliana’, 16 (2), 263-76.
Weiste C. et al. 2007‘In planta ORFeome analysis by large-scale over-expression of GATEWAY-compatible cDNA clones: screening of ERF transcription factors involved in abiotic stress defense’, 52 (2), 382-90.
Wheeler D. A. et al. 2008‘The complete genome of an individual by massively parallel DNA sequencing’, 452 (7189), 872-6.
Xia Y. et al. 2004‘An extracellular aspartic protease functions in Arabidopsis disease resistance signaling’, 23 (4), 980-8.
Xiang Y. Huang Y. Xiong L. 2007‘Characterization of stress-responsive CIPK genes in rice for stress tolerance improvement’, 144 (3), 1416-28.
Xiong L. Z. et al. 2006‘Overexpressing a NAM, ATAF, and CUC (NAC) transcription factor enhances drought resistance and salt tolerance in rice’, 103 (35), 12987-92.
Xu D. Q. et al. 2008‘Overexpression of a TFIIIA-type zinc finger protein gene ZFP252 enhances drought and salt tolerance in rice (Oryza sativa L.)’, 582 (7), 1037-43.
Yamaguchi-Shinozaki K. et al. 2006‘Functional analysis of rice DREB1/CBF-type transcription factors involved in cold-responsive gene expression in transgenic rice’, 47 (1), 141-53.
Yamamoto Y. Y. et al. 2003‘Gene trapping of the Arabidopsis genome with a firefly luciferase reporter’, 35 (2), 273-83.
Yang S. et al. 2010‘Narrowing down the targets: towards successful genetic engineering of drought-tolerant crops’, 3 (3), 469-90.
Yu H. et al. 2008‘Activated expression of an Arabidopsis HD-START protein confers drought tolerance with improved root system and reduced stomatal density’, 20 (4), 1134-51.
Yusibov V. M. et al. 1991‘Phenotypically normal transgenic T-cyt tobacco plants as a model for the investigation of plant gene expression in response to phytohormonal stress’, 17 (4), 825-36.
Zamore P. D. et al. 2000‘RNAi: double-stranded RNA directs the ATP-dependent cleavage of mRNA at 21 to 23 nucleotide intervals’, 101 (1), 25-33.
Zhang J. Z. 2003‘Overexpression analysis of plant transcription factors’, 6 (5), 430-40.
Zhang X. D. et al. 1996‘Expression of the isopentenyl transferase gene is regulated by auxin in transgenic tobacco tissues’, 5 (1), 57-65.
Zhao Y. et al. 2001‘A role for flavin monooxygenase-like enzymes in auxin biosynthesis’, 291 (5502), 306-9.
Zheng J. et al. 2010‘Genome-wide transcriptome analysis of two maize inbred lines under drought stress’, 72 (4-5), 407-21.
Zhou J. et al. 2007‘Global genome expression analysis of rice in response to drought and high-salinity stresses in shoot, flag leaf, and panicle’, 63 (5), 591-608.
Zuo J. et al. 2002‘The WUSCHEL gene promotes vegetative-to-embryonic transition in Arabidopsis’, 30 (3), 349-59.