Crop breeding chips and genotyping platforms: progress, challenges and perspectives (original) (raw)
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The Fast and the Cheap: SNP and DArT-Based Whole Genome Profiling for Crop Improvement
In this paper we focus on two technologies that appear to be best suited for whole-genome profiling: SNP and DArT. Sequencing accomplishments in several model species have shown that the value of sequencing is limited without comprehensive information about genome diversity. In the sequenced genomes, large studies are fuelling the development of SNP typing techniques. These techniques will eventually replace DNA typing methods with lower throughput such as SSRs, AFLP, CAPs and RFLPs. The most popular SNP typing assays and the most promising SNP technology platforms are briefly reviewed here. The slow uptake of SNP markers in plants, especially those plants for which limited resources are invested, is caused partly by the small or nonexistent market demand and partly by the lack of sequence information. DArT is an upcoming technology that avoids most of the problems of lower-throughput typing technologies and does not require sequence information. Here we describe the principles of DArT and the current status of development of this technology. We also discuss the requirements for an effective application of whole-genome profiling to plant breeding.
PLoS biology, 2014
Next generation sequencing (NGS) technologies are being used to generate whole genome sequences for a wide range of crop species. When combined with precise phenotyping methods, these technologies provide a powerful and rapid tool for identifying the genetic basis of agriculturally important traits and for predicting the breeding value of individuals in a plant breeding population. Here we summarize current trends and future prospects for utilizing NGS-based technologies to develop crops with improved trait performance and increase the efficiency of modern plant breeding. It is our hope that the application of NGS technologies to plant breeding will help us to meet the challenge of feeding a growing world population.
Genomic Selection in the Era of Next Generation Sequencing for Complex Traits in Plant Breeding
Frontiers in genetics, 2016
Genomic selection (GS) is a promising approach exploiting molecular genetic markers to design novel breeding programs and to develop new markers-based models for genetic evaluation. In plant breeding, it provides opportunities to increase genetic gain of complex traits per unit time and cost. The cost-benefit balance was an important consideration for GS to work in crop plants. Availability of genome-wide high-throughput, cost-effective and flexible markers, having low ascertainment bias, suitable for large population size as well for both model and non-model crop species with or without the reference genome sequence was the most important factor for its successful and effective implementation in crop species. These factors were the major limitations to earlier marker systems viz., SSR and array-based, and was unimaginable before the availability of next-generation sequencing (NGS) technologies which have provided novel SNP genotyping platforms especially the genotyping by sequencin...
The molecularization of public sector crop breeding: Progress, problems, and prospects
Advances in Agronomy, Vol 95, 2007
Molecular markers and genetic maps are available for most important food crops. Marker-trait associations have been established for a diverse array of traits in these crops, and research on marker/quantitative trait loci (QTL) validation and refinement is increasingly common. Researchers are now routinely using candidate gene-based mapping and genome-wide linkage disequilibrium and association analysis in addition to classical QTL mapping to identify markers broadly applicable to breeding programs. Marker-assisted selection (MAS) is practiced for enhancing various host plant resistances, several quality traits, and a number of abiotic stress tolerances in many wellresearched crops. Markers are also increasingly used to transfer yield or quality-enhancing QTL alleles from wild relatives to elite cultivars. Largescale MAS-based breeding programs for crops such as rice, maize, wheat, barley, pearl millet, and common bean have already been initiated worldwide. Advances in ''omics'' technologies are now assisting researchers to address complex biological issues of significant agricultural importance: modeling genotype-by-environment interaction; fine-mapping, cloning, and pyramiding of QTL; gene expression analysis and gene function elucidation; dissecting the genetic structure of germplasm collections to mine novel alleles and develop genetically structured trait-based core collections; and understanding the molecular basis of heterosis. The challenge now is to translate and integrate this knowledge into appropriate tools and methodologies for plant breeding programs. The role of computational tools in achieving this is becoming increasingly important. It is expected that harnessing the outputs of genomics research will be an important component in successfully addressing the challenge of doubling world food production by 2050.
Single nucleotide polymorphisms (SNPs) are the most abundant DNA sequence variation in the genomes which can be used to associate genotypic variation to the phenotype. Therefore, availability of a high-density SNP array with uniform genome coverage can advance genetic studies and breeding applications. Here we report the development of a high-density SNP array 'Axiom_Arachis' with 58 K SNPs and its utility in groundnut genetic diversity study. In this context, from a total of 163,782 SNPs derived from DNA resequencing and RNA-sequencing of 41 groundnut accessions and wild diploid ancestors, a total of 58,233 unique and informative SNPs were selected for developing the array. In addition to cultivated groundnuts (Arachis hypogaea), fair representation was kept for other diploids (A. duranensis, A. stenosperma, A. cardenasii, A. magna and A. batizocoi). Genotyping of the groundnut 'Reference Set' containing 300 genotypes identified 44,424 polymorphic SNPs and genetic diversity analysis provided in-depth insights into the genetic architecture of this material. The availability of the high-density SNP array 'Axiom_Arachis' with 58 K SNPs will accelerate the process of high resolution trait genetics and molecular breeding in cultivated groundnut. Crop improvement programs in general are focused on enhancing productivity, improving quality and resilience to biotic and abiotic stress by creating and/or harnessing genetic diversity. Genomics-assisted breeding (GAB) has accelerated crop improvement programs for development of improved cultivars in several crops 1. Availability of high density genotyping platform with uniformly distributed genome-wide genetic markers is must have genomic resource in a crop for high resolution genetic dissection of complex traits and tracking the favorable alleles in a breeding population 2. Single nucleotide polymorphisms (SNPs) are the most abundant DNA sequence variations among various types of structural/genetic/sequence variations in the genome. Until recently, it has been a tedious, labor-intensive and expensive task to develop even a limited number of SNPs. In the last decade, next-generation sequencing (NGS) technologies have evolved very rapidly and have become the cheapest and fastest method of identification of genome-wide SNPs 1. The most commonly used NGS approach for identifying and assaying SNPs is genotyping-by-sequencing (GBS) 3. While GBS provides generation of high-density SNP data in less time and less cost, allelic data are not generated for all the SNPs detected among individuals/lines in a given population 4. Furthermore, though the imputation methods are available to infer missing data, these methods rely on prior extensive genotyping data.
The GCP molecular marker toolkit, an instrument for use in breeding food security crops
Molecular Breeding, 2011
Crop genetic resources carry variation useful for overcoming the challenges of modern agriculture. Molecular markers can facilitate the selection of agronomically important traits. The pervasiveness of genomics research has led to an overwhelming number of publications and databases, which are, nevertheless, scattered and hence often difficult for plant breeders to access, particularly those in developing countries. This situation separates them from developed countries, which have better endowed programs for developing varieties. To close this growing knowledge gap, we conducted an intensive literature review and consulted with more than 150 crop experts on the use of molecular markers in the breeding program of 19 food security crops. The result was a list of effectively used and highly reproducible sequence tagged site (STS), simple sequence repeat (SSR), single nucleotide polymorphism (SNP), and sequence characterized amplified region (SCAR) markers. However, only 12 food crops had molecular markers suitable for improvement. That is, markerassisted selection is not yet used for Musa spp., coconut, lentils, millets, pigeonpea, sweet potato, and yam. For the other 12 crops, 214 molecular markers were found to be effectively used in association with 74 different traits. Results were compiled as the GCP Molecular Marker Toolkit, a free online tool that aims to promote the adoption of molecular approaches in breeding activities.
Molecular Genetics, Genomics, and Biotechnology in Crop Plant Breeding
Agronomy
A diverse set of molecular markers techniques have been developed over the last almost 40 years and used with success for breeding a number of major crops. These have been narrowed down to a few preferred DNA based marker types, and emphasis is now on adapting the technologies to a wide range of crop plants and trees. In this Special Issue, the strength of molecular breeding is revealed through research and review papers that use a combination of molecular markers with other classic breeding techniques to obtain quality improvement of the crop. The constant improvement and maintenance of quality by breeding is crucial and challenged by a changing climate and molecular markers can support the direct introgression of traits into elite breeding lines. All the papers in this Special Issue “Molecular genetics, Genomics, and Biotechnology in Crop Plant Breeding” have attracted significant attention, as can be witnessed by the graphs for each paper on the Journal’s homepage. It is the hope...
SNP Markers and Their Impact on Plant Breeding
The Role of Bioinformatics in Agriculture, 2014
The use of molecular markers has revolutionized the pace and precision of plant genetic analysis which in turn facilitated the implementation of molecular breeding of crops. The last three decades have seen tremendous advances in the evolution of marker systems and the respective detection platforms. Markers based on single nucleotide polymorphisms (SNPs) have rapidly gained the center stage of molecular genetics during the recent years due to their abundance in the genomes and their amenability for high-throughput detection formats and platforms. Computational approaches dominate SNP discovery methods due to the everincreasing sequence information in public databases; however, complex genomes pose special challenges in the identification of informative SNPs warranting alternative strategies in those crops. Many genotyping platforms and chemistries have become available making the use of SNPs even more attractive and efficient. This paper provides a review of historical and current efforts in the development, validation, and application of SNP markers in QTL/gene discovery and plant breeding by discussing key experimental strategies and cases exemplifying their impact.
Array-based high-throughput DNA markers for crop improvement
2008
The last two decades have witnessed a remarkable activity in the development and use of molecular markers both in animal and plant systems. This activity started with lowthroughput restriction fragment length polymorphisms and culminated in recent years with single nucleotide polymorphisms (SNPs), which are abundant and uniformly distributed. Although the latter became the markers of choice for many, their discovery needed previous sequence information. However, with the availability of microarrays, SNP platforms have been developed, which allow genotyping of thousands of markers in parallel. Besides SNPs, some other novel marker systems, including single feature polymorphisms, diversity array technology and restriction site-associated DNA markers, have also been developed, where array-based assays have been utilized to provide for the desired ultra-high throughput and low cost. These microarray-based markers are the markers of choice for the future and are already being used for construction of high-density maps, quantitative trait loci (QTL) mapping (including expression QTLs) and genetic diversity analysis with a limited expense in terms of time and money. In this study, we briefly describe the characteristics of these array-based marker systems and review the work that has already been done involving development and use of these markers, not only in simple eukaryotes like yeast, but also in a variety of seed plants with simple or complex genomes.
Advances in Plant Genotyping: Where the Future Will Take Us
Methods in Molecular Biology, 2014
Genetic diversity between individuals can be tracked and monitored using a range of molecular markers. These markers can detect variation ranging in scale from a single base pair up to duplications and translocations of entire chromosomal regions. The genotyping of individuals allows the detection of this variation and it has been successfully applied in plant science for many years. The increasing amounts of sequence data able to be generated using next-generation sequencing (NGS) technologies have produced a vast expansion in the rate of discovery of polymorphisms, with single nucleotide polymorphisms (SNPs) predominating as the marker of choice. This increase in polymorphic marker resources through effi cient discovery, coupled with the utility of SNPs, has enabled the shift to high-throughput genotyping assays and these methods are reviewed and discussed here, alongside the recent innovations allowing increased throughput.