Forward genetics refers to the identification and characterization of the gene that is responsible for the mutant phenotype, the goal of reverse genetics is to examine the effect of induced mutationor altered expression of a particular gene and to understand the gene function (Ahringer, 2006). Forward and reverse genetics approaches are used to determine the function of genes.
Schematic diagram depicting forward and reverse genetic approaches
Both approaches begin with the development of a suitably mutagenized population .Mutagen choice and dosage affect the spectrum and density of induced genomic mutations. Mutagenesis of multi-cellular tissues such as seed result in the first generation being a genetic mosaic because each cell carries unique mutations. Self-fertilization, when available, is used to make plants non-chimeric .Traditional or forward genetics involves phenotypic evaluation and selection of novel plant phenotypes. Plants with interesting characteristics can be incorporated immediately into breeding programs and, when desired, the mutation causing the phenotype can be cloned to understand the function of genes and to produce a perfect genetic marker .Reverse genetic strategies begin with genotypic screening of the mutant population to identify novel induced mutations in candidate genes. This is followed by phenotypic evaluation of those individuals harboring putative deleterious mutations
The aim of forward genetics is to determine the genetic basis of observed phenotypic variation. To generate random mutations in an organism, various approaches are exploited for example Xrays, ultraviolet irradiation and chemical treatment. These gene disruptions are followed by selection of aberrant phenotypes, associated with various traits, such as high-yield, early maturity, lodging resistance, disease resistance, drought tolerance, cold tolerance, toxic metal resistance, etc. After mutants are identified, they need to be classified. The aim is to gather mutants into complementation multiple independent mutant alleles can efficiently be used to validate a candidate gene. One example of such collection is the Scandinavian barley mutant collection. The generation of this collection has started in 1928 bythe Swedish geneticists Hermann Nilsson-Ehle andÅke Gustafsson. In the mid 1930-ies, the firstviable mutations were observed and notable amongthem arehigh-yielding, early maturity, dense spike,tillering capacity, straw-stiffness, seed-size andmutants useful for understanding basic agronomically important traits such as photosynthetic capacity and protective outer barrierformation(Lundqvist, 2005).In this way the barleymutants became very important for breeding improvedvarieties and for subsequent genetic studies.
The goal of genetic mapping is to identify the locus of the gene responsible for the trait of interest. The first step in all mapping studies is to find markers that are linked with the trait. Physical linkage will lead to co-inheritance of markers, while recombination events will break these associations. The next steps are to develop appropriate mapping populations; screen parents for marker polymorphism and genotype mapping population. Afterwards a linkage analysis is performed to find out recombination frequencies between markers which in turn lead to the fine mapping of the location of the gene of interest. If the genome of the plant of interest is not fully sequenced, the synteny between physical and genetic maps of closely related plants, with sequenced genome enables the assessment of the gene content at the fine mapped locus.
The following databases and their online genome browsers and blast search capabilities are essential for these syntenic studies:
Phytozome: comparative genomics of plants
PlantGDB: plant genome database
Expression analyses with microarray
DNA microarray is one of the most efficient methods for gene expression analysis (Gregory et al., 2008; Morohashi et al., 2009;Park et al., 2004; Petersen et al., 2005; Schena et al., 1995;Zhu et al., 2012). It was further shown that microarray is a very promising technology for identification of genes in transcription deficient mutants (Zakhrabekova S, 2002; Zakhrabekova et al., 2007). The approach of using phenotypically similar mutants minimizes the number of candidate genes for sequencing, due to the reduction of genes which are secondarily affected by the mutation. Both cDNA and Affymetrix microarray platforms are able to successfully pinpoint the gene which is down- or up-regulated due to induced or naturally occurred mutation events. It was also shown that nonsense-mediated mRNA decay in barley mutants expands the number of mutants that can be used for gene identification by the microarray approach(Gadjieva et al., 2004).
Useful data base for gene expression studies;
PLEXdb (Plant Expression Database) is a unified gene expression resource for plants and plant pathogens
Planet is a gene expression database for the plants: barley, rice, wheat, Arabidopsis, Medicago, poplar and soybean based on Affymetrix contigs
Different microarrays technologies:
Candidate gene approach
This approach is appropriate for plants where mutant collections, represented by multiple independent mutant alleles are available. The major difficulty with this approach is that in order to choose a potential candidate gene for the mutation, researchers must already have an understanding of the mechanisms underlying the phenotypic disorder. Very good “educated guesses” can be done if a study of similar mutants has been performed in another related plant and the corresponding orthologous gene has been identified. Then this gene can be a potential candidate for the mutation in the investigated plant and the principle proof that this candidate gene is responsible for the observed phenotype is coming from comparative sequence analysis of all available mutant alleles in the particular locus (Zakhrabekova et al., 2012). Alternative methods which can be used to hunt a gene responsible for a mutant phenotype. The RNA-seq method is also called ” Whole Transcriptome Shotgun Sequencing” (“WTSS”) (Morin et al., 2008). This is a high-throughput order to get information about the RNA content in the cells. Since converting RNA into cDNA by using reverse transcriptase might introduce mutations, single-molecule direct RNA sequencing technology has been developed. The sequences of all RNA in the mutant are then compared with the wild-type indicate mutant candidates. This method also requires a number of different mutant alleles to give a reliable answer (Ozsolak and Milos, 2011).
It is a powerful method to selectively sequence the coding regions of the genome as a less costly alternative to whole genome sequencing (Ng et al. 2009). This method can be combined with target-enrichment strategies, which give possibility to selectively capture genomic regions of interest from a DNA sample prior to sequencing (Basiardes et al., 2005). Identification of mutations by this method requires as well as in RNA-seq a number of different mutant alleles to give a trust worthy answer.
Some examples of mutant varieties derived from forward genetic screens with published