PREFACE REPETITIVE DNA: AN IMPORTANT SOURCE OF VARIATION IN EUKARYOTIC GENOMES Categories of DNA Sequence Mutations Tandem-Repetitive DNA: The Biology of Mini- and Microsatellites Minisatellites Microsatellites Transposable Elements Class I Transposons Class II Transposons Unclassified Transposons Transposons and Genome Evolution Transposons as Molecular Markers DETECTING DNA VARIATION BY MOLECULAR MARKERS Properties of Molecular Markers Traditional Marker Systems Protein Markers and Allozymes DNA Sequencing Restriction Fragment Length Polymorphism (RFLP) Analysis The PCR Generation: Molecular Markers Based on In Vitro DNA Amplification Principle of the PCR Cleaved Amplified Polymorphic Sequences PCR with Arbitrary Primers: RAPD and Its Variants Microsatellites Inter-Repeat PCR DNA Profiling of Genic Regions: Resistance Gene Analog Polymorphism, Sequence-Related Amplified Polymorphism, and Target Region Amplification Polymorphism Hybridization of Microsatellites to RAPD and MP-PCR Products AFLP Analysis and Its Variants Single-Strand Conformation Polymorphism Analysis and Related Techniques Miscellaneous Techniques LABORATORY EQUIPMENT METHODOLOGY Safety Precautions Isolation, Purification, and Quantitation of Plant DNA Collection and Preservation of Plant Tissue in the Field Plant DNA Extraction: General Considerations CTAB Protocol I CTAB Protocol II SDS-Potassium Acetate Protocol DNA Preparation via Nuclei Quantitation of DNA Basic Molecular Techniques Restriction of DNA Polymerase Chain Reaction DNA Sequencing Agarose Gel Electrophoresis PAA Gel Electrophoresis Detection of DNA in Gels Gel Drying Southern Blotting Generation of Radiolabeled Probes, Primers, and PCR Products Blot Hybridization Signal Detection PCR with Arbitrary Primers Standard RAPD Protocol Influence of Reaction Conditions and Components Modifications Microsatellite-Primed PCR Standard Protocol of Microsatellite-Primed PCR Influence of Reaction Conditions and Components Modifications PCR and Hybridization: Combinatory Techniques Assessing the Genomic Copy Number of PCR Amplicons Testing the Homology of Comigrating Bands Random Amplified Polymorphic Microsatellites Amplified Fragment Length Polymorphism Standard AFLP Protocol Using Radioisotopes AFLP Protocol Using Fluorescence-Labeled Primers Selective Amplification of Microsatellite Polymorphic Loci and Microsatellite AFLP Protocols Technical Aspects and Modifications Robustness and Reproducibility Generation and Analysis of Microsatellite Markers Microsatellite Analysis Using Radioisotopes Microsatellite Analysis Using Fluorochromes Technical Aspects and Modifications Generating Microsatellite Markers Without Cloning Microsatellite Cloning CAPS Analysis of cpDNA and mtDNA Standard CAPS Protocol Choice of CAPS Primers EVALUATION OF MOLECULAR MARKER DATA Robustness and Reproducibility Reliability Band Homology Band Linkage and Neutrality Fragment Sizing and Matching General Precautions Equipment Multilocus vs. Single-Locus Approaches Multilocus Markers Single-Locus Markers and Polyploids Band Sharing and Genetic Distances Coefficients of Similarity Dissimilarity Coefficients and Genetic Distances Identity and Uniqueness Clonal Structure Ordination, Clustering, and Dendrograms Ordination Techniques Construction of Dendrograms Population Genetic Analysis Measures of Variation Genetic Differentiation between Populations Genetic Distances between Populations Inbreeding Coefficient and Mating Systems Estimation of Relatedness and Paternity Testing Migration and Hybridization Gene Flow, Isolation-by-Distance, and Spatial Structure Phylogeography and Nested Clade Analysis Statistical Testing of Hypotheses: Analytical and Computational Methods APPLICATIONS OF DNA FINGERPRINTING IN PLANT SCIENCES A Brief History of DNA Fingerprinting Minisatellite and Oligonucleotide DNA Probes Detect Genetic Variation PCR-Based Methods Enter the Stage Microsatellite DNA Analyses Yield Codominant Markers Universal Organellar DNA Primers Produce Uniparental Markers Genotype Identification Individual-Specific DNA Fingerprints Cultivar Identification In Vitro-Propagated Plant Material and Somaclonal Variation Sports and Other Mutants Genetic Diversity Variation and Relatedness among Cultivars Analysis of Population Genetic Diversity and Its Distribution Hybridization and Introgression Plant Conservation Germplasm Characterization and Preservation Plant Taxonomy and Systematics Taxonomic Relationships Revealed by Multilocus DNA Methods Microsatellite Markers in Taxonomic Studies Taxonomic Consequences from DNA Profiling Data Phylogeography Phylogeography Based on cpDNA Phylogeography Based on Nuclear Genes LINKAGE ANALYSIS AND GENETIC MAPS Generating High-Density Genetic Maps Selection of Parent Plants Mapping Population Linkage Analysis The Genetic Map Cytogenetic Maps Genetic vs. Physical Maps Synteny: The Comparative Analysis of Genomes Marker-Assisted Selection Molecular Markers and Positional Cloning WHICH MARKER FOR WHAT PURPOSE: A COMPARISON Morphological Characters and Allozymes vs. DNA Markers Different Kinds of DNA Markers Discriminatory Power Genetic Distances Within- and Among-Population Variation Gene Tagging and Genetic Linkage Mapping Costs Conclusions FUTURE PROSPECTS: SNIPS AND CHIPS FOR DNA AND RNA PROFILING Single-Nucleotide Polymorphisms What Is a SNiP SNP Discovery DNA Microarrays Expression Profiling and Expression Markers APPENDIX 1: PLANT DNA ISOLATION PROTOCOLS APPENDIX 2: SUPPLIERS AND SELLERS OF REAGENTS AND EQUIPMENT APPENDIX 3: COMPUTER PROGRAMS DEALING WITH THE EVALUATION OF DNA SEQUENCE VARIATION AND MOLECULAR MARKER DATA APPENDIX 4: WEB PAGES OF INTEREST REFERENCES INDEX

DNA fingerprinting in plants: principles, methods, and applications

Motivation: Core sets are necessary to ensure that access to useful alleles or characteristics retained in genebanks is guaranteed. We have successfully developed a computational tool named ‘PowerCore’ that aims to support the development of core sets by reducing the redundancy of useful alleles and thus enhancing their richness. Results: The program, using a new approach completely different from any other previous methodologies, selects entries of core sets by the advanced M (Maximization) strategy implemented through a modified heuristic algorithm. The developed core set has been validated to retain all characteristics for qualitative traits and all classes for quantitative ones. PowerCore effectively selected the accessions with higher diversity representing the entire coverage of variables and gave a 100% reproducible list of entries whenever repeated. Availability: PowerCore software uses the .NET Framework Version 1.1 environment which is freely available for the MS Windows platform. The files can be downloaded from http://genebank.rda.go.kr/powercore/.The distribution of the package includes executable programs, sample data and a user manual.

PowerCore: a program applying the advanced M strategy with a heuristic search for establishing core sets

Molecular markers (SSR, SNP and DArT) and agronomical traits have been used in the world’s largest olive (Olea europaea L.) germplasm collection (IFAPA, Centre Alameda del Obispo, Cordoba, Spain) to study the patterns of genetic diversity and underlying genetic structure among 361 olive accessions. In addition the marker data were used to construct a set of core collections by means of two different algorithms (MSTRAT and PowerCore) based on M (maximization) strategy. Our results confirm that the germplasm collection is a useful source of genetically diverse material. We also found that geographical origin is an important factor structuring genetic diversity in olive. Subsets of 18, 27, 36, 45 and 68 olive accessions, representing respectively 5%, 7.5%, 10%, 12.5% and 19% of the whole germplasm collection, were selected based on the information obtained by all the data set as well as each marker type considered individually. According to our results, the core collections that represent between 19% and 10% of the total collection size could be considered as optimal to retain the bulk of the genetic diversity found in this collection. Due to its high efficiency at capturing all the alleles/traits states found in the whole collection, the core size of 68 accessions could be of special interest for genetic conservation applications in olive. The high average genetic distance and diversity and the almost equal representation of accessions from different geographical regions indicate that the core size of 36 accessions, could be the working collection for olive breeders.

Developing a core collection of olive ( Olea europaea L.) based on molecular markers (DArTs, SSRs, SNPs) and agronomic traits

Bread wheat (Triticum aestivum), one of the world's major crops, is genetically very diverse. In order to select a representative sample of the worldwide wheat diversity, 3,942 accessions originating from 73 countries were analysed with a set of 38 genomic simple sequence repeat (SSR) markers. The number of alleles at each locus ranged from 7 to 45 with an average of 23.9 alleles per locus. The 908 alleles detected were used together with passport data to select increasingly large sub-samples that maximised both the number of observed alleles at SSR loci and the number of geographical origins. A final core of 372 accessions (372CC) was selected with this M strategy. All the different geographical areas and more than 98% of the allelic diversity at the 38 polymorphic loci were represented in this core. The method used to build the core was validated, by using a second set of independent markers [44 expressed sequence tag (EST)-SSR markers] on a larger sample of 744 accessions: 96.74% of the alleles observed at these loci had already been captured in the 372CC. So maximizing the diversity with a first set of markers also maximised the diversity at a second independent set of locus. To relate the genetic structure of wheat germplasm to its geographical origins, the two sets of markers were used to compute a dissimilarity matrix between geographical groups. Current worldwide wheat diversity is clearly divided according to wheat's European and Asian origins, whereas the diversity within each geographical group might be the result of the combined effects of adaptation of an initial germplasm to different environmental conditions and specific breeding practices. Seeds from each accession of the 372CC were multiplied and are now available to the scientific community. The genomic DNA of the 372CC, which can be entirely contained in a 384-deep-well storage plate, will be a useful tool for future studies of wheat genetic diversity.

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A worldwide bread wheat core collection arrayed in a 384-well plate

Microsatellites or simple sequence repeats are highly variable DNA sequences that can be used as informative markers for the genetic analysis of plants and animals. For the development of microsatellite markers in Capsicum, microsatellites were isolated from two small-insert genomic libraries and the GenBank database. Using five types of oligonucleotides, (AT)15, (GA)15, (GT)15, (ATT)10 and (TTG)10, as probes, positive clones were isolated from the genomic libraries, and sequenced. Out of 130 positive clones, 77 clones showed microsatellite motifs, out of which 40 reliable microsatellite markers were developed. (GA)n and (GT)n sequences were found to occur most frequently in the pepper genome, followed by (TTG)n and (AT)n. Additional 36 microsatellite primers were also developed from GenBank and other published data. To measure the information content of these markers, the polymorphism information contents (PICs) were calculated. Capsicum microsatellite markers from the genomic libraries have shown a high level of PIC value, 0.76, twice the value for markers from GenBank data. Forty six microsatellite loci were placed on the SNU-RFLP linkage map, which had been derived from the interspecific cross between Capsicum annuum “TF68” and Capsicum chinense “Habanero”. The current “SNU2” pepper map with 333 markers in 15 linkage groups contains 46 SSR and 287 RFLP markers covering 1,761.5 cM with an average distance of 5.3 cM between markers.

Characterization and molecular genetic mapping of microsatellite loci in pepper

Germplasm characterization is an important link between the conservation and utilization of plant genetic resources. A total of 134 accessions from six Capsicumspecies maintained at the Asian Vegetable Research and Development Center were characterized using 110 randomly amplified polymorphic DNA (RAPD) markers. Ten pairs of potentially duplicated accessions were identified. Multidimensional scaling analysis of the genetic distances among accessions resulted in clustering corresponding to a previous species assignment except for six accessions. Diagnostic RAPDs were identified which discriminate among the Capsicumspecies. The diagnostic markers were employed for improved taxonomic identification of accessions since many morphological traits used in the identification of Capsicumare difficult to score. Three Capsicumaccessions, misclassified based on morphological traits, were reassigned species status based on diagnostic RAPDs. Three accessions, not previously classified, were assigned to a species based on diagnostic RAPDs. Definitive conclusions about the species assignment of three other accessions were not possible. The level of diversity between Capsicum annuumaccessions from the genebank and the breeding program were compared and no differences were observed either for RAPD variation or diversity. The utilization of genetic resources as a source of variance for useful traits in the breeding program may be the reason for the similarity of these two groups.

Variation among and within Capsicum species revealed by RAPD markers

The development of a core collection, one which represents the genetic diversity of a crop with minimal redundancy and increases utility of the collection as a whole, is especially important as the funding for germplasm collections decreases. With limited resources, it is difficult to manage large germplasm collections and disperse genetically diverse germplasm to plant breeders. An algorithm was developed to assist in selection of core collections based on estimates of genetic distance. The criteria for selection of the maximum genetically diverse set were based on rankings of genetic distance between an accession with respect to all other accessions. Depending on the size core which a user wished, a zone around each selected accession was determined and no other accession within these limits was selected. The premise for the algorithm was that the genetic variability represented in the core must be representative of the distribution of genetic distances within the population of interest. In the present study, the algorithm was used with RAPD-marker-based estimates of genetic distance for 270 Theobroma cacao L. accessions and 134 Capsicum accessions that chose a set representing 18.5% of the population and representing the breadth of RAPD-based variation.

Julie M. Rodriguez

Papers

Variation among and within Capsicum species revealed by RAPD markers

Development of an algorithm identifying maximally diverse core collections.