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Manual Genomics and Breeding for Climate-Resilient Crops: Vol. 1 Concepts and Strategies

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It is independent from DNA sequence; that is, the discovery of polymorphic DArT markers and their scoring in subsequent analysis does not require any DNA sequence data. The detail of methodology for DArT is described by Jaccoud et al. To identify the polymorphic markers, a complexity reduction method is applied on the metagenome, a pool of genomes representing the germplasm of interest.

Polymorphic clones DArT markers show variable hybridization signal intensities for different individuals. DArT is one of the recently developed molecular techniques and it has been used in rice [ 66 ], wheat [ 38 , 67 , 68 ], barley [ 69 ], eucalyptus [ 70 ], Arabidopsis [ 71 ], cassava [ 72 ], pigeon-pea [ 73 ], and so forth.

DArT markers can be used as any other genetic marker. With DArT, comprehensive genome profiles are becoming affordable regardless of the molecular information available for the crop.

DArT genome profiles are very useful for characterization of germplasm collections, QTL mapping, reliable and precise phenotyping, and so forth. However, DArT technique involves several steps, including preparation of genomic representation for the target species, cloning, data management, and analysis, requiring dedicated software such as DArTsoft and DArTdb. DArT markers are primarily dominant present or absent or differences in intensity, which limits its value in some application [ 38 ]. DNA sequencing technology has played a pivotal role in the advancement of molecular biology [ 74 ].

Next generation sequencing NGS or second generation sequencing technologies are revolutionizing the study of variation among individuals in a population. Most NGS technologies reduce the cost and time required for sequencing than Sanger-style sequencing machines first generation sequencing. These techniques have made it possible to conduct robust population-genetic studies based on complete genomes rather than just short sequences of a single gene.

The Solexa sequencing platform was commercialized in The working principle is sequencing-by-synthesis chemistry. This platform has its origins in the system described by Shendure et al. Helicos offers the first universal genetic analysis platform that does not require amplification. Pursuing a single molecule sequencing strategy simplifies the DNA sample preparation process, avoids PCR-induced bias and errors, simplifies data analysis, and tolerates degraded samples.

Helicos single-molecule sequencing is often referred to as third generation sequencing. The detailed methodology, advantages, and disadvantages of each NGS technology were reviewed by many authors [ 78 — 81 ]. It is essential to know the different ways that the data generated by molecular techniques can be analyzed before their application to diversity studies. Two main types of analysis are generally followed: i analysis of genetic relationships among samples and ii calculation of population genetics parameters in particular diversity and its partitioning at different levels.

The advent and explorations of molecular genetics led to a better definition of Euclidean distance to mean a quantitative measure of genetic difference calculated between individuals, populations, or species at DNA sequence level or allele frequency level. Readers are requested to read Mohammadi and Prasanna [ 85 ] review paper for more details about different GD measures.

There are two main ways of analyzing the resulting distance or similarity matrix, namely, principal coordinate analysis PCA and dendrogram or clustering, tree diagram. PCA is used to produce a 2 or 3 dimensional scatter plot of the samples such that the distances among the samples in the plot reflect the genetic distances among them with a minimum of distortion. Another approach is to produce a dendrogram or tree diagram , that is, grouping of samples together in clusters that are more genetically similar to each other than to samples in other clusters.

However, because these techniques are based on the incorporation of genomic elements in the primer sets or else target specific regions in the genome, biases affecting the evaluation process can occur. Although many recently developed targeting methods detect large numbers of polymorphisms, not many studies to date have utilized them, largely due to their unfamiliarity. In many cases the drawbacks are unknown. These mainly affect the analysis of the banding patterns produced, largely depending on the nature of the methods and whether they generate dominant or codominant markers.

These are self-explanatory; therefore, the features and method of calculations were not much discussed separately in our text. Many software programs are available for assessing genetic diversity; however, most of them are freely available through source link to internet and corresponding institute web links are given in Table 2. In this section, we described some of the programs available which are mostly used in molecular diversity analyses in the postgenomic era Table 2.

Many of these perform similar tasks, with the main differences being in the user interface, type of data input and output, and platform. Thus, choosing which to use depends heavily on individual preferences. Agriculturist has been realized that diverse plant genetic resources are priceless assets for humankind which cannot be lost. Presence of genetic variability in crops is essential for its further improvement by providing options for the breeders to develop new varieties and hybrids. This can be achieved through phenotypic and molecular characterization of PGR.

Sometimes, large size of germplasm may limit their use in breeding. This may be overcome by developing and using subsets like core and minicore collection representing the diversity of the entire collection of the species. Molecular markers are indispensable tools for measuring the diversity of plant species. Low assay cost, affordable hardware, throughput, convenience, and ease of assay development and automation are important factors when choosing a technology.

Now with the high throughput molecular marker technologies ensuring speed and quality of data generated, it is possible to characterize the larger number of germplasm with limited time and resources. Next generation sequencing reduced the cost and time required for sequencing the whole genome. Many software packages are available for assessing phenotypic and molecular diversity parameters that increased the efficiency of germplasm curators and, plant breeders to speed up the crop improvement.

Therefore, we believe that this paper provides useful and contemporary information at one place; thus, it improves the understanding of tools for graduate students and also practical applicability to the researchers. The authors declare that there is no conflict of interests regarding the publication of this paper. Genetics Research International. Indexed in Web of Science. Journal Menu. Special Issues Menu. Subscribe to Table of Contents Alerts. Table of Contents Alerts. Srinivasan 3. Abstract The importance of plant genetic diversity PGD is now being recognized as a specific area since exploding population with urbanization and decreasing cultivable lands are the critical factors contributing to food insecurity in developing world.

Introduction Diversity in plant genetic resources PGR provides opportunity for plant breeders to develop new and improved cultivars with desirable characteristics, which include both farmer-preferred traits yield potential and large seed, etc. Table 1: Some basic statistical concept on genomic data for genetic diversity assessment.

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Genomics and Breeding for Climate-Resilient Crops

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Publications - Sustainable Seed Systems Lab

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Irina S. Biodiversity, Biofuels, Agroforestry and Conservation Agriculture. Temperature and Plant Development. Keara Franklin. Molecular Techniques in Crop Improvement. The Algae World. Dinabandhu Sahoo. Transgenic Plants and Beyond. Marcel Kuntz. Sustainability of Organic Farming in Nepal. Mrinila Singh. Genetics, Biofuels and Local Farming Systems. Sustainable Agriculture towards Food Security. Arulbalachandran Dhanarajan.

Plant Responses to Environmental Stimuli. Michel Thellier. Crop Production for Agricultural Improvement. Muhammad Ashraf. Drought Stress in Maize Zea mays L. Muhammad Aslam.

NEED TO ADAPT CROPS TO NEW AND CHANGING ENVIRONMENTS AND THE ROLE OF GENOMICS

Fernando Ramirez. Achieving sustainable cultivation of sugarcane Volume 2. Philippe Rott. Ryozo Imai. Arthropod-Plant Interactions. Guy Smagghe.

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Combating Desertification and Land Degradation. Victor Castillo. Biotechnology of Neglected and Underutilized Crops. Shri Mohan Jain. Abiotic Stress Biology in Horticultural Plants. Yoshinori Kanayama. Parasitic Orobanchaceae. Lytton J. Abiotic Stress Physiology of Horticultural Crops. Srinivasa Rao. The Castor Bean Genome. Chittaranjan Kole. Genomics of Plant-Associated Bacteria. Dennis C. Ralph A. Transgenic Crop Plants. Genome Mapping and Genomics in Laboratory Animals. Paul Denny. Plant Nanotechnology. The Brassica rapa Genome. Genomics and Breeding for Climate-Resilient Crops.

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