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The goal of many breeding programmes is the combination of several improved traits to produce a cultivar that meets demands of farmer and consumer. For example, breeding aromatic rice varieties having both high quality and yield is an objective in Vietnam to satisfy domestic consumers and increase value in the export market. Genetic variation is the starting point for any breeding programme. In some cases sufficient variation exists and traditional hybridizations and introgressions are suitable for cultivar development. In other cases, new variation, such as that created through mutagenesis, is required for the development of new traits. Thus, a combinatorial approach using both hybridization and induced mutations can be considered when the goal is a new cultivar expressing several improved traits. We have taken this approach in rice breeding to generate lines with improved aroma and high iron content. Here we provide a protocol for mutation induction, hybridization and phenotypic analysis for the improvement of aroma and iron content in rice using a combined mutation and hybridization approach. Example data from this work is shown. This approach can be easily adapted for other traits of interest.

Phenotyping of large plant populations for genetic research or plant breeding is often time-consuming and expensive. Seed composition is a primary breeding objective as this determines quality for various markets, e.g food, fodder and industrial processing. Near-infrared reflectance spectroscopy (NIRS) is a fast developing analytical tool for seed composition screening. For example, it is utilised in plant breeding programmes to predict compositional concentrations in various samples. NIRS can be used to detect variation between seed lots and between individual seeds and can be used to identify and isolate new phenotypes including mutants based on spectroscopic sample properties. Spectral data of seed samples may be subjected to principal component analysis to separate groups and individuals with distinct compositional properties. Spectroscopic outliers such as mutants with novel seed quality alleles may then be selected based on principal component scores. Outliers represent a small subset of the entire population, and these may be subject to more rigorous analyses (chemical, physiological and genetic). In determining their potential exploitation, NIRS is a high-throughput phenotyping platform that can be used to reduce large sample sizes, e.g a mutant population to manageable numbers.

Plant proteomes are complex and therefore their analyses represent major technical challenges. In fact, proteome analyses depend on several crucial steps, such as the amount of proteins, extraction, separation, visualization, identification, quantification, and the interaction between proteins and other molecules in a plant tissue at a given time.

To date it is recognized, that there is no single method able to describe an entire plant proteome. Even though several alternatives exist, the most widely used methodology for proteome analysis includes two-dimensional gel electrophoresis (2-DE), mass spectrometry, and bioinformatics tools.

The proteome represents a valuable field of study related to gene functions since many biochemical pathways of fatty acids and secondary metabolites in this species provide an alternative potential source to fossil oil useful for production of biodiesel. Therefore, a detailed proteome analysis of using gel-based electrophoresis combined with identification by mass spectrometric analyses could help to understand its potentials as a source of biofuel.

Due to the low correlation between protein expression level and mRNA in plant tissues, it is not advisable to predict a final amount of protein from quantities of mRNA. However, it is generally accepted that protein analysis allows to identify so far unknown genes and to assign them a function.

This chapter provides a selection of methods, reproducible with the highest resolution and quality of results from sample preparation to proteins identification of .

Nucleotide variation, whether induced or natural, is responsible for a vast majority of heritable phenotypic variation. Evaluation of genomic DNA sequence is therefore fundamental for both functional genomics and marker-assisted breeding. The starting point for this is the extraction of high-quality DNA of a suitable quantity for planned downstream applications. A myriad of kits and techniques exists, but not all are suitable for laboratories with limiting infrastructure due to high costs and reliance on toxic chemicals. We describe here a protocol for extraction of high-quality genomic DNA from leaves of a variety of plant species that uses self-prepared buffers and reagents and obviates the need for toxic organic chemicals such as chloroform. We also provide a protocol for using free image analysis software to quantify isolated DNA.

Single-strand-specific nucleases are used to cleave mismatches in otherwise double-stranded DNA. Assays typically involve PCR amplification followed by a denaturing and annealing step to generate heteroduplexed DNA molecules from PCR products containing nucleotide polymorphisms. This is followed by digestion with nucleases that cleave at the site of the mismatch. The molecular weights of the cleavage products indicate the approximate position of nucleotide polymorphisms in PCR amplicons. Cleaved DNA products are observed by one of several readout platforms such as native gel electrophoresis, denaturing gel electrophoresis, capillary electrophoresis, or denaturing high-performance liquid chromatography (DHPLC). This approach is highly suitable for accurate discovery of natural and induced single-nucleotide polymorphisms (SNPs) and also small insertions and deletions (indels). The use of self-extracted single-strand-specific nucleases, typically prepared from crude extracts of celery (, is common for reverse-genetics (e.g. Targeting Induced Local Lesions IN Genomes (TILLING)) and studies of natural nucleotide polymorphisms (e.g. Ecotilling). While protocols have been published describing the preparation of single-strand-specific nuclease from plant tissues, many rely on toxic chemicals, dialysis and large-volume preparatory centrifuges and also require steps to be performed at 4 °C. We provide here a streamlined room temperature extraction protocol that uses standard microcentrifuges and eliminates toxic chemicals and traditional dialysis.

Doubled haploidy is an important tool for plant breeders. It provides a rapid means of developing recombinant populations consisting of individuals that are homozygous and therefore genetically fixed. Homozygosity is also important in plant mutation breeding where many induced mutations are predicted to be recessive and mutant alleles need to be in a homozygous state before new traits are expressed. While production of doubled haploids has been described for many plant species, efficient means to validate that produced materials are indeed homozygous are needed. Polymorphism discovery methods utilizing enzymatic mismatch cleavage are ideally suited for validation of doubled haploid plants. We describe here a low-cost protocol that utilizes self-extracted single-strand-specific nucleases, standard PCR reactions and agarose gel electrophoresis that can be applied to most plant species.

The bioinformatics resources provide a wide range of tools that can be applied in different areas of mutation screening. The enormous and constantly increasing amount of genomic data obtained in plant-oriented molecular studies requires the development of efficient techniques for its processing. There is a wide range of bioinformatics tools which can aid in the course of mutation discovery. The following chapter focuses mainly on the application of different tools and resources to facilitate a Targeting-Induced Local Lesions in Genomes (TILLING) analysis. TILLING is a technique of reverse genetics that applies a traditional mutagenesis to create DNA libraries of mutagenised individuals that are then subjected to high-throughput screening for the identification of mutations. The bioinformatics tools have shown to be useful in supporting the process of candidate gene selection for mutation screening. The availability of bioinformatics software and experimental data repositories provides a powerful tool which enables a process of multi-database mining. The existing raw experimental data (genomics-related information, expression data, annotated ontologies) can be interpreted in terms of a new biological context. This may help in selecting the proper candidate gene for mutation discovery that is controlling the target phenotype. The mutation screening using a TILLING strategy requires a former knowledge of the full genomic sequence of the gene which is of interest. Depending on whether a fully sequenced genome of a particular species is available, different bioinformatics tools can facilitate this process. Specific tools can be also useful for the identification of possible gene paralogs which may mask the effect of mutated gene. Bioinformatics resources can also support the selection of gene fragments most prone to acquire a deleterious nucleotide change. Finally, there are available tools enabling a proper design of oligonucleotide primers for the amplification of a gene fragment for the purpose of mutation screening.

In the beginning of mutation research, mutations could only be detected indirectly through the analysis of the phenotypic alterations that they caused. The detection of mutations at the DNA level became possible with the development of sequencing methods. Nowadays, there are many different methods and strategies that have been created for mutation detection, both in natural and mutagenised populations. The strategies differ in accuracy and sensitivity, as well as in the laboratory facilities, time, costs and efforts that are required. The majority of them involve the pooling of DNA samples and the amplification of a gene (fragment) of interest followed by heteroduplex formation. One of the popular strategies for mutation identification takes advantage of the specific endonuclease (e.g. CEL I) that recognises and cuts heteroduplexes precisely at the 3′ position of the mismatch site. The cleaved fragments are usually visualised through electrophoresis in a polyacrylamide gel using LI-COR sequencers, but agarose electrophoresis may also be used for this purpose, although with less sensitivity. A different mutation identification strategy, which is based on the high-resolution melting (HRM) technique, may be the method of choice when working with a short gene or a gene fragment whose length optimally does not exceed 400 bp.

The average mutation density of a mutant population is a major consideration when developing resources for the efficient, cost-effective implementation of reverse genetics methods such as Targeting Induced Local Lesions in Genomes (TILLING). Reliable estimates of mutation density can be achieved by the analysis of several selected loci from hundreds of individuals via mismatch cleavage of heteroduplexes or sequencing. A more rapid and less expensive alternative involves reduced representation sequencing of the genomes of a few individuals. Here we present a detailed protocol for the construction of restriction enzyme sequence comparative analysis (RESCAN) sequencing libraries using a combination of single restriction enzyme digestion and solid phase reversible immobilization-based size selection of restriction fragments. Indexing of the libraries using barcoded adapters enables cost-saving multiplexing prior to sequencing on an Illumina platform. Mutation density can be determined from the resulting sequence data with or without a reference genome.

Advances in DNA sequencing (i.e., next-generation sequencing, NGS) have greatly increased the power and efficiency of detecting rare mutations in large mutant populations. Targeting Induced Local Lesions in Genomes (TILLING) is a reverse genetics approach for identifying gene mutations resulting from chemical mutagenesis. In traditional TILLING, mutation discovery is accomplished through mismatch cleavage of mutant and wild-type DNA heteroduplexes using endonucleases. This is followed by Sanger sequencing to determine the specific sequence changes. TILLING by sequencing (TBS) uses NGS to facilitate the concurrent detection and sequence characterization of mutations, which allows researchers to prioritize mutants for further analyses. NGS increases the sensitivity of mutation detection and thus improves screening efficiency by allowing the pooling of more DNAs. Here we describe a protocol for TBS using rice as an example. First, DNA from a mutant population is quantified and combined in an overlapping pool design. Then, target genes are amplified from DNA pools and amplicons are combined to maximize throughput and increase likelihood of mutation detection during sequencing. Once sequence data is obtained, mutations are called using statistical approaches that weigh likelihood of rare mutations versus the probability of PCR and sequencing error.