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DIVERSITY ARRAYS TECHNOLOGY(DArT) : A Novel Tool for Harnessing Genetic Potential of Orphan Crops. : 

DIVERSITY ARRAYS TECHNOLOGY(DArT) : A Novel Tool for Harnessing Genetic Potential of Orphan Crops. RANGANATHA S.C. PAK6216 Sr.M.Sc. (Plant Biotechnology)


INTRODUCTION Genetic diversity is the raw material available to Plant breeders. By productively recombining Genetic diversity, Plant breeders have been successfully producing, year after year, improved cultivars of the major domesticated species used in the world’s diverse agricultural systems. Molecular genetic markers offer a powerful tool to accelerate and refine this process.

Slide 4: 

Existing genetic marker (genotyping) technologies, mostly developed for applications in human health, have also been applied successfully to agricultural species, but their cost remains prohibitive for most agricultural applications. This is particularly true for species for which no molecular data and very limited resources are available.

Limitations of Existing Technologies : 

Limitations of Existing Technologies Current Molecular marker technologies include RFLP, AFLP, SSR (microsatellites), and SNP. All are having some of the limitations:


RFLP Genome coverage is slow because it is a Sequential process. It is based on Sequence information. The Cost of scoring the markers (“genotyping “) is high and the throughput low.


AFLP Scoring is done by electrophoresis on gels, therefore limited throughput. An allele is represented by the size of a band on the gel, which can be difficult to assess objectively. Typing of new varieties of a species can be done under the hypothesis that bands of identical size represent the same allele of the same locus, which is not always true. Cloning the polymorphic bands is a labor-intensive and Sequential procedure.

SSR : 

SSR The Marker discovery phase is expensive and involves DNA sequencing. A high-resolution gel equipment system is required for genotyping. Marker scoring usually requires one amplification reaction per marker; therefore the analysis is sequential not parallel. The Cost of producing SSR data point is more.

SNP : 

SNP Requires Marker-specific amplification reaction, or Marker specific primers, oligonucleotides, or probes. The initial investment required for Marker discovery (sequencing of allelic variants) and Assay development remains prohibitive for many agricultural species.

Slide 10: 

To overcome the limitations of existing marker technologies, Diversity Arrays Technology (DArT) has been developed.

Diversity Arrays Technology (DArT) : 

Diversity Arrays Technology (DArT) It is a novel method to discover and score Genetic polymorphic markers. DArT is a Sequence-independent, high-throughput method, able to discover hundreds of markers in a single experiment. DArT markers are typed in parallel, using high-throughput platforms, with a low cost per data point.

Slide 12: 

With DArT, Plant breeders, Plant ecologists, as well as the managers of the germplasm collections, will be able to perform genetic analysis in a cost-effective and high-throughput manner. DArT fingerprints will be useful for accelerating plant breeding, and for the characterization and management of genetic diversity in domesticated species as well as in their wild relatives. DArT, was invented by one of US Scientist A. Kilian.

Slide 13: 

DArT successfully developed for Rice, Barley, Wheat, and Cassava. Also produced a dedicated data management and analysis package. Work is in progress to establish DArT for other species of importance to tropical agriculture : Pigeonpea, Sorghum, and Chickpea.

Slide 14: 

DArT was developed to provide a practical and cost-effective whole-genome fingerprinting tool.

DArT has three key attributes of interest to Plant breeders and scientists studying and managing genetic diversity: : 

DArT has three key attributes of interest to Plant breeders and scientists studying and managing genetic diversity: (a) It is independent from DNA sequence. (b) The genetic scope of analysis is defined by the user and easily expandable. (c) The method provides for high throughput and low-cost data production.

Principle of DArT : 

Principle of DArT

Current Status of DArT Development : 

Current Status of DArT Development It is divided into 3 stages. 1.Current stage 2.Mature stage 3.Establishment stage

1. Current stage : 

1. Current stage More recently the proof of concept of DArT has been developed for a range of species (Jaccoud et al., 2001).

A list of species currently working, with the number of clones assayed from each species, to identify the best complexity reduction method for each species. : 

A list of species currently working, with the number of clones assayed from each species, to identify the best complexity reduction method for each species.

2. Mature stage : 

2. Mature stage Barley Work on Barley has resulted in the identification of approximately 1000 polymorphic markers from two different genomic representations. A DArT genetic map has been built for a population derived from a cross between cultivars Steptoe and Morex (Wenzl et al., 2004). It is now possible to deliver whole-genome profiles of Barley.

Slide 21: 

Wheat Several hundred DArT markers are identified in Wheat and are currently building genetic maps of wheat populations. It is now possible to deliver whole-genome profiles of Wheat. Rice Several hundred DArT markers and a genotyping tool have been developed in Rice.

3. Establishment stage : 

3. Establishment stage Currently establishing the technology on Cassava, Apple, Pigeonpea, Sorghum, Chickpea, Sugarcane and Qinoa. DArT established for the model species Arabidopsis thaliana (Wittenberg et al, 2004).

Overview of DArT : 

Overview of DArT DArT consists of several steps: 1. Complexity reduction of the DNA of interest 2. Library creation 3. Microarraying libraries onto glass slides 4. Hybridization of fluoro-labelled DNA onto slides 5. Scanning of slides for hybridization signal 6. Data extraction and analysis

1. Complexity reduction : 

1. Complexity reduction DArT works by reducing the complexity of a DNA sample to obtain a 'representation' of that sample. Complexity reduction method relies on a combination of restriction enzyme digestion and adapter ligation, followed by amplification (Wenzl et al., 2004).

Slide 26: 

DArT operates on the principle that the genomic 'representation' contains two types of fragments: Constant fragments, found in any 'representation' prepared from a DNA sample from an individual belonging to a given species. Variable (polymorphic) fragments called molecular markers, only found in some but not all of the 'representations'. The variable fragments are informative because they reflect Sequence variation that determines the fraction of the original DNA sample that is included in the 'representation'. We call the variable fragments as DArT markers. Their presence Vs absence in a genomic 'representation' is assayed by hybridizing the 'representation' to a DArT array consisting of a library of that species.

2. Library creation : 

2. Library creation To create a library for any species, a mixture of genomic 'representations' from a pool of individuals covering the genetic diversity of the species is amplified. These fragments are cloned into a vector that is introduced into E. coli to form a library. Within the library, each colony contains one of the fragments from the genomic 'representation'.

3. Microarraying : 

3. Microarraying At present the high-throughput capability of DArT is based on a microarray platform. After library creation, a selection of clones from the library are arranged into a plate format (usually 384-well plates). The fragments within the library are amplified and spotted onto glass slides using a microarrayer to form a genotyping array.

4. Hybridization : 

4. Hybridization The genotyping arrays are hybridized with genomic 'representations' of individual DNA samples prepared using the same complexity reduction method. These individual 'representations' are labelled with one fluorescent label, while the vector fragment is labelled with another fluorescent label to act as a reference. Each individual 'representation' will only hybridize to matching fragments on the genotyping array, thereby displaying a unique hybridization pattern.

5. Scanning : 

5. Scanning The hybridized slides are first washed and processed to remove unbound labelled DNA. The slides are then scanned using a Scanner to detect fluorescent signal emitted from the hybridized fragments. The result from each fluorescent channel is recorded and the resulting images are stored in TIF format.

6. Data analysis : 

6. Data analysis The data from the scanned images is extracted and analyzed using the DArtsoft software and the information is managed by the DArtdb Laboratory Information Management System.

Slide 37: 

DArT involves a new use of microarrays that does not require sequence knowledge, and thus may become very useful to crop researchers. In DArT Preparing the Array and Genotyping a sample are very important.

DArT: Preparing the array : 

DArT: Preparing the array Restriction generated fragments representing the diversity of a gene pool are cloned. The outcome is called a 'representation' (typically 0.1% to 10% of the genome). Polymorphic clones in the library are identified by arraying inserts from a random set of clones and hybridizing the array to different samples. The inserts from polymorphic clones are immobilized on a chip.

DArT: Genotyping a sample : 

DArT: Genotyping a sample Label the representation (DNA) of the sample with fluorescence and hybridize against the array. Scan the array and measure, for each array spot, the amount of hybridisation signal. By using multiple labels, contrast a representation from one sample with a representation from another or with a control probe.

Advantages of DArT : 

Advantages of DArT Do not require Sequence information. High throughput and low-cost data production. Fast data acquisition and analysis. Detects single-base changes as well as insertions and or deletions. Detects differences in DNA methylation, depending on the enzyme used to generate the fragments.

Cont…d : 

Cont…d Sequence-ready clones are generated. Small DNA sample required. Good transferability of markers among breeding populations Full automation possible.

Disadvantages of DArT : 

Disadvantages of DArT Dominance of markers. Technically demanding.

Applications of DArT Markers : 

Applications of DArT Markers DArT markers can be used as any other genetic marker. With DArT, Comprehensive genome profiles are becoming affordable for virtually any crop, regardless of the level of molecular information available for the crop. DArT genome profiles will be used for the recognition and management of Biodiversity. Ex : Germplasm collections.

Cont…d : 

Cont…d Identification of duplicate accessions and a better understanding of the genetic relationships between the accessions could help to control the costs of maintaining these collections. DArT genome profiles will enable breeders to map QTL in one week, thereby allowing them to focus on the most crucial factor in plant breeding: reliable and precise phenotyping. Once many genomic regions of interest are identified in many different lines, DArT profiles accelerate the introgression of a selected genomic region into an elite genetic background. Ex : Marker Assisted Back Crossing

Cont…d : 

Cont…d DArT profiles can be used to guide the assembly of many different regions into improved varieties, for this purpose, dense genome cover is essential in order to follow many regions simultaneously. Because of the large number of lines to be typed, high throughput and affordability are critical factors in this method.


CASE STUDY Diversity arrays technology (DArT) for high throughput profiling of the hexaploid wheat genome ( Mona Akbari et al., 2006 )

Objective of the Study : 

Objective of the Study Is DArT performs well for the hexaploid genome of Bread Wheat (Triticum aestivum L.) ???

Materials and Methods : 

Materials and Methods Plant material This study is based on a collection of 62 Wheat cultivars and the double haploid (DH) population derived from a cross between cultivars Cranbrook and Halberd (Kammholz et al., 2001).

Slide 52: 

DNA extraction The DNA was extracted from leaves of 2-week-old Wheat seedlings using a modified cetyltrimethylammoniumbromide method (Doyle and Doyle, 1987). Some samples were extracted from root tissue using a Proprietary DNA extraction procedure.

DArT procedure : 

DArT procedure Preparation of DArT arrays Several DArT arrays were built in this study. For each of these arrays, a genomic representation was generated from a mixture of Wheat cultivars using the PstI-based complexity reduction method (Wenzl et al.,2004).

Slide 54: 

Genotyping of DNA samples Genomic representations of individual Wheat cultivars were generated with the same complexity reduction method used to prepare the library spotted on the array. Image analysis and Polymorphism scoring Groups of two or three TIF images of individual slides were analyzed using DArTsoft (Version 7).

Slide 55: 

The programme computed several quality parameters for each marker: (a) the between-allelic-states variance of the relative target hybridization intensity as a percentage of the total variance (P-value), (b) the percentage of DNA samples with defined ‘0’ or ‘1’ allele calls (call rate) and (c) the fraction of Concordant calls for replicate assays.

Slide 56: 

Complexity reduction testing Polymorphic clones were identified with DArTsoft Version 6, using P > 85% and call rate > 80% as quality thresholds. Development and quality evaluation of a PstI/TaqI array These arrays were used to genotype 411 wheat lines to select high-quality polymorphic clones and to identify germplasm that was not sufficiently represented on the array (excess of ‘0’ scores). Clones with a P-value greater than 70% and not more than a single discordant call across the nine replicate assays were selected as markers.

Slide 57: 

Cultivar diversity analysis A group of 62 Bread wheat cultivars was genotyped on the Version 2.0 array. For quality control, 10 cultivars were genotyped twice. Clones with P > 77%, call rate > 85% and 100% allele-calling consistency across the 10 replicated assays were selected as markers. The marker scores were subjected to Principal coordinate analysis to visualize the Genetic relationships among the cultivars (Anderson, 2003).

Slide 58: 

Genetic mapping Clones with P > 80% and Call rate of at least 80% were initially selected for mapping. Clones with P between 75 and 80% were later incorporated into the map allowing for a single double-crossover event per marker.


RESULTS & DISCUSSION Evaluation of Complexity reduction methods Table 1: Polymorphism levels obtained with four different complexity reduction methods

Test of PstI/TaqI array performance : 

Test of PstI/TaqI array performance Fig. 1 Relationships among different quality parameters for DArT markers.

Genetic relationship between Wheat cultivars revealed by DArT : 

Genetic relationship between Wheat cultivars revealed by DArT Fig. 2: Principal Coordinate analysis of 62 wheat cultivars based on 411 DArT markers.

Genetic mapping of DArT markers : 

Genetic mapping of DArT markers Table 2 : Mapping quality features of different sets of markers

Slide 63: 

Fig. 3 Genetic map for a cross between wheat cultivars Cranbrook and Halberd.

Segregation distortion : 

Segregation distortion There was no significant difference between DArT and non-DArT markers in the distribution of parental alleles. Only in two areas of the map was segregation distortion significant at the P < 0.01 level (chromosome regions 4AL and 1DS). These two regions contained both DArT and non-DArT markers.

Marker distribution among chromosomes and genomes : 

Marker distribution among chromosomes and genomes Fig. 4: Relationship between the number of DArT markers and the number of other markers across the 21 chromosomes.

Centromeric clustering : 

Centromeric clustering Selected 10 chromosomes with the largest numbers of markers (1A, 3A, 4A, 6A, 7A, 2B, 3B, 5B, 7B, 1D) to compare the degree of centromeric clustering between DArT and non-DArT markers by calculating for each dataset and chromosome, the percentage of markers located in ‘centromeric regions’ (the central one-third of the genetic length of a chromosome). On average there were few DArT markers (24 ± 17%) than non-DArT markers (39 ± 16%) in centromeric regions. This difference was significant at the P < 0.03 level as deduced from a one-tailed t-test based on the expectation that PstI-based DArT markers should show a bias towards non-centromeric, hypomethylated regions (Peter Wenzl et al. submitted).

Uniqueness of segregation patterns : 

Uniqueness of segregation patterns


CONCLUSIONS DArT can be effectively used to genotype polyploid species with large genomes such as Wheat. The Data quality for Wheat was similar to the quality of DArT data previously generated for Barley and several other species. A single DArT assay, which takes a maximum of three working days to complete from DNA to data, generates a reproducible medium-density scan of the hexaploid wheat genome that is useful for a range of molecular breeding and genomic applications.

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