**3. Cellular trafficking and toxicity of polycationic nanostructures**

For achievement of an efficient systemic delivery of gene-based nanomedicines, various factors appear to play crucial role, including: 1) the physicochemical characteristics of the gene-based therapies, 2) the effects of biological environment, 3) the functionality of membranes and barriers, and 4) the biological impacts of cellular microenvironment.

Toxicogenomics of Nonviral Cationic Gene Delivery Nanosystems 551

to cells by means of one or both of two types of cell binding interaction machineries, i.e. receptor and non-receptor mediated bindings (Medina-Kauwe et al., 2005). At cellular level, trafficking of the gene-based nanomedicines is basically performed through vesicular transportation pathways, in which they may engineer their own escape from demise in the lysosome. Endocytosis of macromolecular nanomedicines occurs through various cellular pathways, including clathrin coated pits, caveolae membranes and lipid rafts (Conner & Schmid, 2003; Spang, 2008). More likely, these complexes enter cells through nonspecific exploitation of these endocytic machineries, presumably mainly involving clathrin-mediated endocytic pathway. This route initiates and stabilizes membrane curvature formation, in which the adaptor proteins bind to clathrin pits and augment the inward pull of the

It has been evidenced that the N-1(-(2,3-dioleoyloxy)propyl)-N,N,Ntrimethylammoniummethylsulphate (DOTAP) lipoplexes are internalized by cells solely via clathrin-mediated endocytosis, however PEI polyplexes were shown to be internalized both by clathrin-mediated and caveolae-mediated endocytosis (Rejman et al., 2005). Once inside the cytoplasm, DNA is released from vesicular compartment upon physicochemical properties of the genomedicine. The endosomal escape of DNA at an early stage of endocytosis is deemed to be critical for cytosolic DNA delivery and determination of overall transfection efficiency. Among CPs and CLs, fusogenic lipid dioleoylphosphatidylethanolamine (DOPE) as a helper lipid for liposome-based DNA delivery were reported to induce membrane fusion between the endosome and the liposome and result in membrane destabilization and release of DNA into the cytoplasm (Farhood et al., 1995). Such destabilization of the vesicular membrane further highlights the interaction of cationic lipids with cellular compartments. This inadvertent nonspecific interaction may be exacerbated for *in vivo* systemic gene, which requires high and potentially toxic doses of nonviral vectors. Utilization of the cell-specific ligands or antibodies were reported to lower the cytotoxicity, while facilitating tissue targeting (Rawat et al., 2007), in which the ligand choice is largely dictated by whether or not the target receptor undergoes vesicular trafficking and the endocytic pathway used by the vector is dependent upon the targeting ligand as well as cell type. The structural architecture of the gene delivery nanosystems was shown to be important from gene expression changes viewpoints (Omidi et al., 2005b), which is also largely dependent upon cell type, in particular the membrane lipid composition and membrane phase state (Kabanov, 2006). Adsorption of polycations such as poly(N -ethyl-4-vinylpyridinium) salts (PEVP) in liposomic biomembranes was shown to induce flip-flop of negatively charged lipids (e.g., cardiolipin, phosphatidylserine, and phosphatidic acid) from the inner to the outer leaflet of the liquid liposomal membrane, but not in solid membranes (Yaroslavov et al., 1994; Yaroslavov et al., 2006). Among polycations, starburst PAMAM dendrimers and PEI appeared to elicit the most dramatic increase in membrane permeability by interacting the membranous biomolecules and forming holes in lipid membranes (Hong et al., 2006; Leroueil et al., 2007). Such structures could function as gates, through which the lipid molecules can be transported across the biomembranes (Kabanov, 2006). Fig. 2 represents cytotoxicity of linear and branched PEI in

Upon differences in cell types, the polyions can bind to the cellular compartments and accordingly induce compartmentalization within certain areas of the membranes and inadvertently trigger various signaling paths. Furthermore, nanoscaled defects were shown to be induced by PAMAM dendrimers through removing lipid from the fluid domains at a

membrane towards the cytoplasm leading to vesicle formation (Young, 2007).

A431 cells (Kafil & Omidi, 2011).

Fig. 1. Schematic representation of various polymer based gene delivery nanosystems. To prepare gene medicine nanosystems (NS) nucleic acids (e.g., antisense, siRNA, and aptamer) are generally entrapped, encapsulated or conjugated with polymers. Genes can be conjugated to magnetic nanoparticles (MNP) and quantum dots for concurrent detection and therapy.

Within the circulation system, blood cells, proteins, enzymes and serum components may bind to the genomedicines and cause instability and lowered transfection efficiency (Konopka et al., 2005). In addition, the circulating gene therapies must circumvent the immune system clearance and cross the capillary endothelial cells to reach the target cells/tissue. Once inside the target cells (normally via receptor-mediated endocytosis pathway), the genomedicine must overcome the subcellular and/or biomolecular impacts. In fact, the amphipathic sheet like lipid bilayer architecture of the biological membranes along with the integrated proteins separate cells from their environment and form the boundaries of different organelles inside the cells, at which exchange of materials among the different parts of a cell is controlled (Omidi & Gumbleton, 2005). Nonviral vectors may bind

Fig. 1. Schematic representation of various polymer based gene delivery nanosystems. To prepare gene medicine nanosystems (NS) nucleic acids (e.g., antisense, siRNA, and aptamer)

Within the circulation system, blood cells, proteins, enzymes and serum components may bind to the genomedicines and cause instability and lowered transfection efficiency (Konopka et al., 2005). In addition, the circulating gene therapies must circumvent the immune system clearance and cross the capillary endothelial cells to reach the target cells/tissue. Once inside the target cells (normally via receptor-mediated endocytosis pathway), the genomedicine must overcome the subcellular and/or biomolecular impacts. In fact, the amphipathic sheet like lipid bilayer architecture of the biological membranes along with the integrated proteins separate cells from their environment and form the boundaries of different organelles inside the cells, at which exchange of materials among the different parts of a cell is controlled (Omidi & Gumbleton, 2005). Nonviral vectors may bind

are generally entrapped, encapsulated or conjugated with polymers. Genes can be conjugated to magnetic nanoparticles (MNP) and quantum dots for concurrent detection

and therapy.

to cells by means of one or both of two types of cell binding interaction machineries, i.e. receptor and non-receptor mediated bindings (Medina-Kauwe et al., 2005). At cellular level, trafficking of the gene-based nanomedicines is basically performed through vesicular transportation pathways, in which they may engineer their own escape from demise in the lysosome. Endocytosis of macromolecular nanomedicines occurs through various cellular pathways, including clathrin coated pits, caveolae membranes and lipid rafts (Conner & Schmid, 2003; Spang, 2008). More likely, these complexes enter cells through nonspecific exploitation of these endocytic machineries, presumably mainly involving clathrin-mediated endocytic pathway. This route initiates and stabilizes membrane curvature formation, in which the adaptor proteins bind to clathrin pits and augment the inward pull of the membrane towards the cytoplasm leading to vesicle formation (Young, 2007).

It has been evidenced that the N-1(-(2,3-dioleoyloxy)propyl)-N,N,Ntrimethylammoniummethylsulphate (DOTAP) lipoplexes are internalized by cells solely via clathrin-mediated endocytosis, however PEI polyplexes were shown to be internalized both by clathrin-mediated and caveolae-mediated endocytosis (Rejman et al., 2005). Once inside the cytoplasm, DNA is released from vesicular compartment upon physicochemical properties of the genomedicine. The endosomal escape of DNA at an early stage of endocytosis is deemed to be critical for cytosolic DNA delivery and determination of overall transfection efficiency. Among CPs and CLs, fusogenic lipid dioleoylphosphatidylethanolamine (DOPE) as a helper lipid for liposome-based DNA delivery were reported to induce membrane fusion between the endosome and the liposome and result in membrane destabilization and release of DNA into the cytoplasm (Farhood et al., 1995). Such destabilization of the vesicular membrane further highlights the interaction of cationic lipids with cellular compartments. This inadvertent nonspecific interaction may be exacerbated for *in vivo* systemic gene, which requires high and potentially toxic doses of nonviral vectors. Utilization of the cell-specific ligands or antibodies were reported to lower the cytotoxicity, while facilitating tissue targeting (Rawat et al., 2007), in which the ligand choice is largely dictated by whether or not the target receptor undergoes vesicular trafficking and the endocytic pathway used by the vector is dependent upon the targeting ligand as well as cell type. The structural architecture of the gene delivery nanosystems was shown to be important from gene expression changes viewpoints (Omidi et al., 2005b), which is also largely dependent upon cell type, in particular the membrane lipid composition and membrane phase state (Kabanov, 2006). Adsorption of polycations such as poly(N -ethyl-4-vinylpyridinium) salts (PEVP) in liposomic biomembranes was shown to induce flip-flop of negatively charged lipids (e.g., cardiolipin, phosphatidylserine, and phosphatidic acid) from the inner to the outer leaflet of the liquid liposomal membrane, but not in solid membranes (Yaroslavov et al., 1994; Yaroslavov et al., 2006). Among polycations, starburst PAMAM dendrimers and PEI appeared to elicit the most dramatic increase in membrane permeability by interacting the membranous biomolecules and forming holes in lipid membranes (Hong et al., 2006; Leroueil et al., 2007). Such structures could function as gates, through which the lipid molecules can be transported across the biomembranes (Kabanov, 2006). Fig. 2 represents cytotoxicity of linear and branched PEI in A431 cells (Kafil & Omidi, 2011).

Upon differences in cell types, the polyions can bind to the cellular compartments and accordingly induce compartmentalization within certain areas of the membranes and inadvertently trigger various signaling paths. Furthermore, nanoscaled defects were shown to be induced by PAMAM dendrimers through removing lipid from the fluid domains at a

Toxicogenomics of Nonviral Cationic Gene Delivery Nanosystems 553

Once complexed with nucleic acid (e.g., antisense oligonucleotide or plasmid vector), lipoplexes revealed marginally reduced toxicity towards macrophages (Filion & Phillips, 1997b). Furthermore, since cationic lipids display intrinsic anti-inflammatory activity, they should be cautiously utilized as a gene delivery system to transfer nucleic acids for

DNA microarray technology has advanced and accelerated the identification process for mechanistic toxicology to illuminate genomic aspects of toxicology that could consequently postulate early effect within targets cells/tissues upon exposure to the toxicants (de et al., 2004). Recently, an interesting study was performed to compare different commercially available cationic liposome–DNA lipoplexes (Masotti et al., 2009), and it was reported that the lipoplex size and cationic lipid to DNA ratio are the two main parameters affecting the transfection efficiency of lipoplexes. The lipofection efficiency was determined mainly by lipoplex size, but not by the extent of lipoplex–cell interactions including binding, uptake or fusion. In the presence or absence of serum, lipoplex size was found to be a major factor determining lipofection efficiency. These researchers concluded that, by controlling lipoplex size, an efficient lipid delivery system may be

Florea et al. (2002) evaluated PEIs with different molecular weights for their efficiency in transfecting undifferentiated COS-1 and well-differentiated human submucosal airway epithelial Calu-3 cells and showed that transfection efficiency was dependent upon the cell types, but not molecular weights. These researchers reported that gene transfer by PEI was 3 orders of magnitude more effective in COS-1 than in Calu-3 cells, perhaps because of secretion of mucins by Calu-3 cells (Florea et al., 2002). However, the larger molecular weights of PEI were also shown to yield the highest transfection efficiency in EA.hy 926 cell line derived from a fusion of the human A549 cell line with human umbilical vein endothelial cells, HUVEC (Godbey et al., 2001). Two types of cytotoxicities in process of PEI -mediated cell transfection have been reported: 1) an immediate toxicity associated with free PEI, 2) a delayed toxicity associated with cellular processing of PEI/DNA complexes (Godbey et al., 1999; Godbey et al., 2001). The immediate toxicity seems to occur upon interaction of the free PEIs with negatively charged serum proteins (e.g., albumin) and red blood cells (cytotoxic effects), while the delayed toxicity by PEI/DNA complex appeared to be closely related to the release of DNA (genomic effects). In cell culture, free PEI interacts with cellular components and inhibits normal cellular process. It causes several changes to cells, which include cell shrinking, reduced number of mitoses and vacuolization of the cytoplasm. We have observed significant genotoxicity impacts induced by PEI in A431 cells

Toxicity impacts of nanostructured materials have been recently reviewed (Nel et al., 2006), while many aspects of this issue (in particular at genomics/protemics levels) still remains unresolved. As a result, necessity of analysis of toxicogenomics of the nanoscaled advanced biomaterials is very clear. It will direct us towards development of safe pharmaceutical formulations with maximal efficiency and wide therapeutic index yet displaying minimal toxicity profiles since the conventional assessment of toxicity solely provide preliminary information with little devotion to the global genomic/proteomic impacts (Hollins et al., 2007; Kabanov et al., 2005; Kabanov, 2006; Omidi et al., 2005a). If this is the case, then the gene and drug delivery paradigms are going to stumble upon new era to deal with

gene therapy *in vivo*.

achieved for *in vitro* and *in vivo* gene therapy.

(Kafil & Omidi, 2011) and xenografted mice (our unpublished data).

"functionalized excipients".

significantly greater rate than for the gel domains (Erickson et al., 2008). This reinforces a possibility of compartmentalization of synthetic polymers within different membrane domains as well as a differential effect of polymers on functional systems in the membranes that consecutively provoke inadvertent cytoplasmic/nucleic consequences directly and indirectly via secondary messengers such as G proteins.

Fig. 2. Cytotoxicity of polyethylenimine (25 kDa) polymers in A431 cells evaluated by MTT assay. A) Cytotoxicity of B PEI with IC50=37 μg. B) Cytotoxicity of LPEI with IC50=74 μg. BPEI: Branched polyethylenimine; LPEI: linear polyethylenimine; adapted with permission from (Kafil & Omidi, 2011).

Fischer et al. (2003) monitored cytotoxicity of various polycationic gene delivery systems in L929 mouse fibroblasts using MTT assay and the release of the cytosolic enzyme lactate dehydrogenase (LDH). They showed a pattern for cellular toxicity as follow, poly(ethylenimine)=poly(L-lysine)>poly(diallyl-dimethyl-ammonium chloride)>diethylaminoethyl-dextran>poly(vinyl pyridinium bromide)>Starburst dendrimer>cationized albumin>native albumin. These researchers, interestingly, confirmed the molecular weight and the cationic charge density of the polycations as key parameters for the interaction with the cell membranes and accordingly the cell damage (Fischer et al., 2003). Besides, interaction of dendrimers with erythrocyte membrane proteins was shown to trigger echinocytosis (Domanski et al., 2004), while the cationic liposomes are less cytotoxic than dendrimers. The toxicity by CLs appeared to be dependent upon the type of cationic lipid macromolecule, concentration, molecular weight and the presence of DNA, where complexation of the polycations with DNA resulted in reduced tissue damage. However, Gebhart et al. (2001) showed increased cytotoxicity in the cos-7 cells upon complexation of various polymers with DNA (Gebhart & Kabanov, 2001).

Filion et al. (1997) have performed an important body of work by evaluating the toxicity of liposomes, formulated with various cationic lipids, towards murine macrophages and T lymphocytes and the human monocyte-like U937 cell line. They reported occurrence of pronounced toxicity by cationic liposomes formulated from DOPE and cationic lipids based on diacyltrimethylammonium propane (dioleoyl-, dimyristoyl-, dipalmitoyl-, disteroyl-: DOTAP, DMTAP, DPTAP, DSTAP) or dimethyldioctadecylammonium bromide (DDAB) in the phagocytic cells (macrophages and U937 cells), but not within non-phagocytic T lymphocytes. They also showed the rank order of toxicity as follows: DOPE/DDAB > DOPE/DOTAP > DOPE/DMTAP > DOPE/DPTAP > DOPE/DSTAP.

significantly greater rate than for the gel domains (Erickson et al., 2008). This reinforces a possibility of compartmentalization of synthetic polymers within different membrane domains as well as a differential effect of polymers on functional systems in the membranes that consecutively provoke inadvertent cytoplasmic/nucleic consequences directly and

Fig. 2. Cytotoxicity of polyethylenimine (25 kDa) polymers in A431 cells evaluated by MTT assay. A) Cytotoxicity of B PEI with IC50=37 μg. B) Cytotoxicity of LPEI with IC50=74 μg. BPEI: Branched polyethylenimine; LPEI: linear polyethylenimine; adapted with permission

Fischer et al. (2003) monitored cytotoxicity of various polycationic gene delivery systems in L929 mouse fibroblasts using MTT assay and the release of the cytosolic enzyme lactate dehydrogenase (LDH). They showed a pattern for cellular toxicity as follow,

chloride)>diethylaminoethyl-dextran>poly(vinyl pyridinium bromide)>Starburst dendrimer>cationized albumin>native albumin. These researchers, interestingly, confirmed the molecular weight and the cationic charge density of the polycations as key parameters for the interaction with the cell membranes and accordingly the cell damage (Fischer et al., 2003). Besides, interaction of dendrimers with erythrocyte membrane proteins was shown to trigger echinocytosis (Domanski et al., 2004), while the cationic liposomes are less cytotoxic than dendrimers. The toxicity by CLs appeared to be dependent upon the type of cationic lipid macromolecule, concentration, molecular weight and the presence of DNA, where complexation of the polycations with DNA resulted in reduced tissue damage. However, Gebhart et al. (2001) showed increased cytotoxicity in the cos-7 cells upon complexation of

Filion et al. (1997) have performed an important body of work by evaluating the toxicity of liposomes, formulated with various cationic lipids, towards murine macrophages and T lymphocytes and the human monocyte-like U937 cell line. They reported occurrence of pronounced toxicity by cationic liposomes formulated from DOPE and cationic lipids based on diacyltrimethylammonium propane (dioleoyl-, dimyristoyl-, dipalmitoyl-, disteroyl-: DOTAP, DMTAP, DPTAP, DSTAP) or dimethyldioctadecylammonium bromide (DDAB) in the phagocytic cells (macrophages and U937 cells), but not within non-phagocytic T lymphocytes. They also showed the rank order of toxicity as follows: DOPE/DDAB > DOPE/DOTAP > DOPE/DMTAP > DOPE/DPTAP > DOPE/DSTAP.

poly(ethylenimine)=poly(L-lysine)>poly(diallyl-dimethyl-ammonium

various polymers with DNA (Gebhart & Kabanov, 2001).

indirectly via secondary messengers such as G proteins.

from (Kafil & Omidi, 2011).

Once complexed with nucleic acid (e.g., antisense oligonucleotide or plasmid vector), lipoplexes revealed marginally reduced toxicity towards macrophages (Filion & Phillips, 1997b). Furthermore, since cationic lipids display intrinsic anti-inflammatory activity, they should be cautiously utilized as a gene delivery system to transfer nucleic acids for gene therapy *in vivo*.

DNA microarray technology has advanced and accelerated the identification process for mechanistic toxicology to illuminate genomic aspects of toxicology that could consequently postulate early effect within targets cells/tissues upon exposure to the toxicants (de et al., 2004). Recently, an interesting study was performed to compare different commercially available cationic liposome–DNA lipoplexes (Masotti et al., 2009), and it was reported that the lipoplex size and cationic lipid to DNA ratio are the two main parameters affecting the transfection efficiency of lipoplexes. The lipofection efficiency was determined mainly by lipoplex size, but not by the extent of lipoplex–cell interactions including binding, uptake or fusion. In the presence or absence of serum, lipoplex size was found to be a major factor determining lipofection efficiency. These researchers concluded that, by controlling lipoplex size, an efficient lipid delivery system may be achieved for *in vitro* and *in vivo* gene therapy.

Florea et al. (2002) evaluated PEIs with different molecular weights for their efficiency in transfecting undifferentiated COS-1 and well-differentiated human submucosal airway epithelial Calu-3 cells and showed that transfection efficiency was dependent upon the cell types, but not molecular weights. These researchers reported that gene transfer by PEI was 3 orders of magnitude more effective in COS-1 than in Calu-3 cells, perhaps because of secretion of mucins by Calu-3 cells (Florea et al., 2002). However, the larger molecular weights of PEI were also shown to yield the highest transfection efficiency in EA.hy 926 cell line derived from a fusion of the human A549 cell line with human umbilical vein endothelial cells, HUVEC (Godbey et al., 2001). Two types of cytotoxicities in process of PEI -mediated cell transfection have been reported: 1) an immediate toxicity associated with free PEI, 2) a delayed toxicity associated with cellular processing of PEI/DNA complexes (Godbey et al., 1999; Godbey et al., 2001). The immediate toxicity seems to occur upon interaction of the free PEIs with negatively charged serum proteins (e.g., albumin) and red blood cells (cytotoxic effects), while the delayed toxicity by PEI/DNA complex appeared to be closely related to the release of DNA (genomic effects). In cell culture, free PEI interacts with cellular components and inhibits normal cellular process. It causes several changes to cells, which include cell shrinking, reduced number of mitoses and vacuolization of the cytoplasm. We have observed significant genotoxicity impacts induced by PEI in A431 cells (Kafil & Omidi, 2011) and xenografted mice (our unpublished data).

Toxicity impacts of nanostructured materials have been recently reviewed (Nel et al., 2006), while many aspects of this issue (in particular at genomics/protemics levels) still remains unresolved. As a result, necessity of analysis of toxicogenomics of the nanoscaled advanced biomaterials is very clear. It will direct us towards development of safe pharmaceutical formulations with maximal efficiency and wide therapeutic index yet displaying minimal toxicity profiles since the conventional assessment of toxicity solely provide preliminary information with little devotion to the global genomic/proteomic impacts (Hollins et al., 2007; Kabanov et al., 2005; Kabanov, 2006; Omidi et al., 2005a). If this is the case, then the gene and drug delivery paradigms are going to stumble upon new era to deal with "functionalized excipients".

Toxicogenomics of Nonviral Cationic Gene Delivery Nanosystems 555

microarray technology. However, for accomplishment of a significant correlation between the gene expression profiles and their functionality expression, it is important to implement substantial complementary investigations to verify the results at the molecular level and as a result extend our understanding of gene expression patterns and molecular pathways. Microarray technology can be exploited to attain a wealth of data that can be used to develop a more complete understanding of gene expression, which can be used for transcriptional regulation and interactions as well as functional genomics. Despite its successful *in vitro* cell-based implementation, application of this technology for *in vivo*  investigations is deemed to be more sophisticated because of complexity of cytotoxicity and genotoxicity studies, which can be confounded by a number of variables such as type of target organ, effect of pharmacokinetics and/or pharmacodynamics parameters (Lobenhofer et al., 2001). Since its advent and application in life sciences, microarray has been widely applied for molecular/biological studies. In fact, a large number of indexed articles in various data banks (e.g., MEDLINE/PubMed) highlight the importance of microarray

Fig. 3 shows a schematic illustration of step-wise processes of the DNA microarray

Technically, DNA microarray can be generated in two different types including printing pre-synthesized cDNAs (500–2000 bp) or synthesizing short oligonucleotides (20–50 bases) onto glass microscope slides, in which gene spots include either fully sequenced genes of known function or collections of partially sequenced cDNA derived from expressed sequence tags (ESTs) corresponding to the messenger RNAs of unknown genes. For example in practice, one may compare two different cells/tissues from untreated (UT) versus treated (T). For gene expression profiling, normally total RNA is extracted from the untreated and treated samples. Using an indirect labeling methodology, they are converted to labeled cDNA (e.g., with aminoallyle-dUTP). The aminoallyle-dUTP-cDNA is then labeled with cyanine dye (e.g., Cy3 or Cy5). The Cy3 and Cy5 labeled aminoallyle-dUTPcDNA from UT and T samples are hybridized on a single glass array, which is subjected to several washing steps, scanning with an appropriate scanner (e.g., using RS Reloaded™, TECAN, Switzerland) and data mining (e.g., using GeneMath™ software; Applied Maths, Sint-Martens-Lathem, Belgium); for detailed information reader is directed to see (Hegde et

For microarray analysis, significantly upregulated and/or downregulated genes can be identified using traditional method (gene expression changes with a fixed cutoff threshold usually in 2 fold) to infer significance differences (i.e., the so called "fold change method"). The resultant data are normally presented as scatter plots of treated (T) versus untreated (UT) control. To reach this stage, data need to undergo a number of processes called as "transformation" and "normalization" to minimize the experimental erroneousness (i.e., the so called "data mining"). Since a scatter plot of T versus UT genes would cluster along a straight line, normalization of this type of data is equivalent to calculating the best-fit slope using regression techniques and adjusting the intensities so that the calculated slope is one. In many experiments, the intensities are nonlinear, and local regression techniques are more suitable, such as Locally WEighted Scatterplot Smoothing (LOWESS) regression (Berger et

In our studies, we have successfully exploited both approaches to study the impacts of the nonviral vectors (CPs and CLs based formulation) on global gene expression experiments. To get the significant alterations in gene expression, we rejected the arrays showing non-

technology in post-genomics era.

al., 2000; Omidi et al., 2005b; Omidi et al., 2008).

al., 2004; Chen et al., 2003).

technology.
