Chaz Andre

Bio: Chaz Andre is an academic researcher from DuPont. The author has contributed to research in topics: Restriction fragment length polymorphism & Genetic marker. The author has an hindex of 3, co-authored 3 publications receiving 2881 citations.

The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis

Abstract: The utility of RFLP (restriction fragment length polymorphism), RAPD (random-amplified polymorphic DNA), AFLP (amplified fragment length polymorphism) and SSR (simple sequence repeat, microsatellite) markers in soybean germplasm analysis was determined by evaluating information content (expected heterozygosity), number of loci simultaneously analyzed per experiment (multiplex ratio) and effectiveness in assessing relationships between accessions. SSR markers have the highest expected heterozygosity (0.60), while AFLP markers have the highest effective multiplex ratio (19). A single parameter, defined as the marker index, which is the product of expected heterozygosity and multiplex ratio, may be used to evaluate overall utility of a marker system. A comparison of genetic similarity matrices revealed that, if the comparison involved both cultivated (Glycine max) and wild soybean (Glycine soja) accessions, estimates based on RFLPs, AFLPs and SSRs are highly correlated, indicating congruence between these assays. However, correlations of RAPD marker data with those obtained using other marker systems were lower. This is because RAPDs produce higher estimates of interspecific similarities. If the comparisons involvedG. max only, then overall correlations between marker systems are significantly lower. WithinG. max, RAPD and AFLP similarity estimates are more closely correlated than those involving other marker systems.

4 – Generating and Using DNA Markers in Plants

Abstract: This chapter presents description and comparison of different DNA marker systems. DNA markers are being applied to a wide variety of problems central to plant genome analysis. Each marker system is characterized by a unique combination of advantages and disadvantages and the choice of a marker system is dictated to a significant extent by the application. Factors to consider in choosing a marker system include the amount of available plant material, the quality of the DNA, and the availability of public collections of DNA markers for the species being examined. Restriction fragment length polymorphism (RFLP) markers are generally codominant, allowing detection and characterization of multiple alleles at a given RELP locus among individuals in a population. Several types of polymorphism can be detected, including single base substitutions, insertions, and deletions. One clear disadvantage to using RFLP markers is the large amount of high-quality genomic DNA required from each individual. It is suggested that once the mapping parents have been chosen and low-copy RFLP probes obtained, those probes that detect useful polymorphisms in the segregating population must be identified. The polymerase chain reaction analysis and identification of polymorphisms are also elaborated.

Linkage disequilibrium and fingerprinting in sugar beet

Abstract: It has been suggested that map information for molecular markers can be used to strengthen finterprinting analyses. The success of this strategy depends on the distribution of linkage disequilibrium over the genome. Using 451 mapped AFLP markers, we investigated the occurrence of linkage disequilibrium in nine sugar beet breeding lines. A low but significant level of linkage disequilibrium was found for unlinked markers. Only for very tigthly linked (<3 cM) markers was this level substantially higher. This implies that little is gained in utilising the map position of the markers in fingerprinting applications.

The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis

Abstract: The utility of RFLP (restriction fragment length polymorphism), RAPD (random-amplified polymorphic DNA), AFLP (amplified fragment length polymorphism) and SSR (simple sequence repeat, microsatellite) markers in soybean germplasm analysis was determined by evaluating information content (expected heterozygosity), number of loci simultaneously analyzed per experiment (multiplex ratio) and effectiveness in assessing relationships between accessions. SSR markers have the highest expected heterozygosity (0.60), while AFLP markers have the highest effective multiplex ratio (19). A single parameter, defined as the marker index, which is the product of expected heterozygosity and multiplex ratio, may be used to evaluate overall utility of a marker system. A comparison of genetic similarity matrices revealed that, if the comparison involved both cultivated (Glycine max) and wild soybean (Glycine soja) accessions, estimates based on RFLPs, AFLPs and SSRs are highly correlated, indicating congruence between these assays. However, correlations of RAPD marker data with those obtained using other marker systems were lower. This is because RAPDs produce higher estimates of interspecific similarities. If the comparisons involvedG. max only, then overall correlations between marker systems are significantly lower. WithinG. max, RAPD and AFLP similarity estimates are more closely correlated than those involving other marker systems.

Comparison of different nuclear DNA markers for estimating intraspecific genetic diversity in plants.

Abstract: A compilation was made of 307 studies using nuclear DNA markers for evaluating among- and within-population diversity in wild angiosperms and gymnosperms. Estimates derived by the dominantly inherited markers (RAPD, AFLP, ISSR) are very similar and may be directly comparable. STMS analysis yields almost three times higher values for within-population diversity whereas among-population diversity estimates are similar to those derived by the dominantly inherited markers. Number of sampled plants per population and number of scored microsatellite DNA alleles are correlated with some of the population genetics parameters. In addition, maximum geographical distance between sampled populations has a strong positive effect on among-population diversity. As previously verified with allozyme data, RAPD- and STMS-based analyses show that long-lived, outcrossing, late successional taxa retain most of their genetic variability within populations. By contrast, annual, selfing and/or early successional taxa allocate most of the genetic variability among populations. Estimates for among- and within-population diversity, respectively, were negatively correlated. The only major discrepancy between allozymes and STMS on the one hand, and RAPD on the other hand, concerns geographical range; within-population diversity was strongly affected when the former methods were used but not so in the RAPD-based studies. Direct comparisons between the different methods, when applied to the same plant material, indicate large similarities between the dominant markers and somewhat lower similarity with the STMS-based data, presumably due to insufficient number of analysed microsatellite DNA loci in many studies.

Analysis of Genetic Diversity in Crop Plants—Salient Statistical Tools and Considerations

Abstract: Knowledge about germplasm diversity and genetic relationships among breeding materials could be an invaluable aid in crop improvement strategies. A number of methods are currently available for analysis of genetic diversity in germplasm accessions, breeding lines, and populations. These methods have relied on pedigree data, morphological data, agronomic performance data, biochemical data, and more recently molecular (DNA-based) data. For reasonably accurate and unbiased estimates of genetic diversity, adequate attention has to be devoted to (i) sampling strategies; (ii) utilization of various data sets on the basis of the understanding of their strengths and constraints; (iii) choice of genetic distance measure(s), clustering procedures, and other multivariate methods in analyses of data; and (iv) objective determination of genetic relationships. Judicious combination and utilization of statistical tools and techniques, such as bootstrapping, is vital for addressing complex issues related to data analysis and interpretation of results from different types of data sets, particularly through clustering procedures. This review focuses on application of statistical tools and techniques in analysis of genetic diversity at the intraspecific level in crop plants.