Plant multi-parent advanced generation intercross (MAGIC) populations
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Whole-Genome Analysis of Multienvironment or Multitrait QTL in MAGIC

Whole-Genome Analysis of Multienvironment or Multitrait QTL in MAGIC | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it

Multiparent Advanced Generation Inter-Cross (MAGIC) populations are now being utilized to more accurately identify the underlying genetic basis of quantitative traits through quantitative trait loci (QTL) analyses and subsequent gene discovery. The expanded genetic diversity present in such populations and the amplified number of recombination events mean that QTL can be identified at a higher resolution. Most QTL analyses are conducted separately for each trait within a single environment. Separate analysis does not take advantage of the underlying correlation structure found in multienvironment or multitrait data. By using this information in a joint analysis—be it multienvironment or multitrait — it is possible to gain a greater understanding of genotype- or QTL-by-environment interactions or of pleiotropic effects across traits. Furthermore, this can result in improvements in accuracy for a range of traits or in a specific target environment and can influence selection decisions. Data derived from MAGIC populations allow for founder probabilities of all founder alleles to be calculated for each individual within the population. This presents an additional layer of complexity and information that can be utilized to identify QTL. A whole-genome approach is proposed for multienvironment and multitrait QTL analysis in MAGIC. The whole-genome approach simultaneously incorporates all founder probabilities at each marker for all individuals in the analysis, rather than using a genome scan. A dimension reduction technique is implemented, which allows for high-dimensional genetic data. For each QTL identified, sizes of effects for each founder allele, the percentage of genetic variance explained, and a score to reflect the strength of the QTL are found. The approach was demonstrated to perform well in a small simulation study and for two experiments, using a wheat MAGIC population.

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The Genetic Basis of Natural Variation in Seed Size and Seed Number and Their Trade-Off Using Arabidopsis thaliana MAGIC Lines

The Genetic Basis of Natural Variation in Seed Size and Seed Number and Their Trade-Off Using Arabidopsis thaliana MAGIC Lines | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it

Offspring number and size are key traits determining an individual's fitness and a crop's yield. Yet, extensive natural variation within species is observed for these traits. Such variation is typically explained by trade-offs between fecundity and quality, for which an optimal solution is environmentally dependent. Understanding the genetic basis of seed size and number, as well as any possible genetic constraints preventing the maximization of both, is crucial from both an evolutionary and applied perspective. We investigated the genetic basis of natural variation in seed size and number using a set of Arabidopsis thaliana Multiparent Advanced Generation Inter-Cross (MAGIC) lines. We also tested whether life-history affects seed size, number, and their trade-off. We found that both seed size and seed number are affected by a large number of mostly non-overlapping QTL; suggesting that seed size and seed number can evolve independently. The allele that increases seed size at most identified QTL is from the same natural accession, indicating past occurrence of directional selection for seed size. Although a significant trade-off between seed size and number is observed, its expression depends on life-history characteristics, and generally explains little variance. We conclude that the trade-off between seed size and number might have a minor role in explaining the maintenance of variation in seed size and number, and that seed size could be a valid target for selection.

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Whole-genome QTL analysis for MAGIC - Springer

Whole-genome QTL analysis for MAGIC - Springer | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it

Multi-parent advanced generation inter-cross (MAGIC) populations have been developed for mice and several plant species and are useful for the genetic dissection of complex traits. The analysis of quantitative trait loci (QTL) in these populations presents some additional challenges compared with traditional mapping approaches. In particular, pedigree and marker information need to be integrated and founder genetic data needs to be incorporated into the analysis. Here, we present a method for QTL analysis that utilizes the probability of inheriting founder alleles across the whole genome simultaneously, either for intervals or markers. The probabilities can be found using three-point or Hidden Markov Model (HMM) methods. This whole-genome approach is evaluated in a simulation study and it is shown to be a powerful method of analysis. The HMM probabilities lead to low rates of false positives and low bias of estimated QTL effect sizes. An implementation of the approach is available as an R package. In addition, we illustrate the approach using a bread wheat MAGIC population.

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A General Modeling Framework for Genome Ancestral Origins in Multiparental Populations

A General Modeling Framework for Genome Ancestral Origins in Multiparental Populations | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it

The next generation of QTL (quantitative trait loci) mapping populations have been designed with multiple founders, where one to a number of generations of intercrossing are introduced prior to the inbreeding phase to increase accumulated recombinations and thus mapping resolution. Examples of such populations are Collaborative Cross (CC) in mice and Multiparent Advanced Generation Inter-Cross (MAGIC) lines in Arabidopsis. The genomes of the produced inbred lines are fine-grained random mosaics of the founder genomes. In this article, we present a novel framework for modeling ancestral origin processes along two homologous autosomal chromosomes from mapping populations, which is a major component in the reconstruction of the ancestral origins of each line for QTL mapping. We construct a general continuous time Markov model for ancestral origin processes, where the rate matrix is deduced from the expected densities of various types of junctions (recombination breakpoints). The model can be applied to monoecious populations with or without self-fertilizations and to dioecious populations with two separate sexes. The analytic expressions for map expansions and expected junction densities are obtained for mapping populations that have stage-wise constant mating schemes, such as CC and MAGIC. Our studies on the breeding design of MAGIC populations show that the intercross mating schemes do not matter much for large population size and that the overall expected junction density, and thus map resolution, are approximately proportional to the inverse of the number of founders.

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Harvesting the Promising Fruits of Genomics: Applying Genome Sequencing Technologies to Crop Breeding

Harvesting the Promising Fruits of Genomics: Applying Genome Sequencing Technologies to Crop Breeding | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it

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.

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Efficiently Tracking Selection in a Multiparental Population: The Case of Earliness in Wheat

Efficiently Tracking Selection in a Multiparental Population: The Case of Earliness in Wheat | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it

Multiparental populations are innovative tools for fine mapping large numbers of loci. Here we explored the application of a wheat Multiparent Advanced Generation Inter-Cross (MAGIC) population for QTL mapping. This population was created by 12 generations of free recombination among 60 founder lines following modification of the mating system from strict selfing to strict outcrossing using the ms1b nuclear male sterility gene. Available parents and a subset of 380 SSD lines of the resulting MAGIC population were phenotyped for earliness and genotyped with the 9K i-Select SNP array and additional markers in candidate genes controlling heading date. We demonstrated that 12 generations of strict outcrossing rapidly and drastically reduced linkage disequilibrium to very low levels even at short map distances and also greatly reduced the population structure exhibited among the parents. We developed a Bayesian method, based on allelic frequency, to estimate the contribution of each parent in the evolved population. To detect loci under selection and estimate selective pressure, we also developed a new method comparing shifts in allelic frequency between the initial and the evolved populations due to both selection and genetic drift with expectations under drift only. This evolutionary approach allowed us to identify 26 genomic areas under selection. Using association tests between flowering time and polymorphisms, six of these genomic areas appeared to carry flowering time QTLs, one of which corresponds to Ppd-D1, a major gene involved in the photoperiod sensitivity. Frequency shifts at four out of six areas were consistent with earlier flowering of the evolved population relative to the initial population. The use of this new outcrossing wheat population, mixing numerous initial parental lines through multiple generations of panmixia, is discussed in terms of power to detect genes under selection and association mapping. Furthermore we provide new statistical methods for use in future analyses of multiparental populations.

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Usefulness of Multiparental Populations of Maize (Zea mays L.) for Genome-Based Prediction

The efficiency of marker-assisted prediction of phenotypes has been studied intensively for different types of plant breeding populations. However, one remaining question is how to incorporate and counterbalance information from biparental and multiparental populations into model training for genome-wide prediction. To address this question, we evaluated testcross performance of 1652 doubled-haploid maize (Zea mays L.) lines that were genotyped with 56,110 single nucleotide polymorphism markers and phenotyped for five agronomic traits in four to six European environments. The lines are arranged in two diverse half-sib panels representing two major European heterotic germplasm pools. The data set contains 10 related biparental dent families and 11 related biparental flint families generated from crosses of maize lines important for European maize breeding. With this new data set we analyzed genome-based best linear unbiased prediction in different validation schemes and compositions of estimation and test sets. Further, we theoretically and empirically investigated marker linkage phases across multiparental populations. In general, predictive abilities similar to or higher than those within biparental families could be achieved by combining several half-sib families in the estimation set. For the majority of families, 375 half-sib lines in the estimation set were sufficient to reach the same predictive performance of biomass yield as an estimation set of 50 full-sib lines. In contrast, prediction across heterotic pools was not possible for most cases. Our findings are important for experimental design in genome-based prediction as they provide guidelines for the genetic structure and required sample size of data sets used for model training.

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MAGIC Wheat: multiparnet populations for the genetic dissection of agronomic traits

MAGIC Wheat: multiparnet populations for the genetic dissection of agronomic traits | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it
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Invited speaker talk on Wheat MAGIC at the 2014 EUCARPIA conference

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PhD vacancies at NIAB: MAGIC

PhD vacancies at NIAB: MAGIC | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it

Early-Stage Researcher (ESR) positions funded by the FP7 Marie Curie European Industrial Doctorate program: Max-CROP

 

 

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Multi-parent advanced generation inter-cross (MAGIC) populations in rice: progress and potential for genetics research and breeding

Multi-parent advanced generation inter-cross (MAGIC) populations in rice: progress and potential for genetics research and breeding | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it

The indica MAGIC population is the most advanced of the MAGIC populations developed thus far and comprises 1328 lines produced by single seed descent (SSD). At the S4 stage of SSD a subset (200 lines) of this population was genotyped using a genotyping-by-sequencing (GBS) approach and was phenotyped for multiple traits, including: blast and bacterial blight resistance, salinity and submergence tolerance, and grain quality. Genome-wide association mapping identified several known major genes and QTLs including Sub1 associated with submergence tolerance and Xa4 and xa5 associated with resistance to bacterial blight. Moreover, the genome-wide association study (GWAS) results also identified potentially novel loci associated with essential traits for rice improvement.


Via Elsa Ballini
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Methods for linkage disequilibrium mapping in crops

Linkage disequilibrium (LD) mapping in plants detectsand locates quantitative trait loci (QTL) by the strengthof the correlation between a trait and a marker. It offersgreater precision in QTL location than family-based link-age analysis and should therefore lead to more efficientmarker-assisted selection, facilitate gene discovery andhelp to meet the challenge of connecting sequencediversity with heritable phenotypic differences. Unlikefamily-based linkage analysis, LD mapping does notrequire family or pedigree information and can beappliedtoarangeofexperimentalandnon-experimentalpopulations. However, care must be taken duringanalysis to control for the increased rate of false positiveresults arising from population structure and varietyinterrelationships. In this review, we discuss how suit-able the recently developed alternative methods of LDmapping are for crops.

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where the term 'MAGIC' for multi-parent populations was first introduced to the literature

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Multiparent intercross populations in analysis of quantitative traits

Multiparent intercross populations in analysis of quantitative traits | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it

Plant MAGIC review 2012

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AlphaMPSim: flexible simulation of multi-parent crosses

AlphaMPSim: flexible simulation of multi-parent crosses | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it

Multi-parent crosses of recombinant inbred lines exist in many species for fine-scale analysis of genome structure and marker–trait association. These populations encompass a wide range of crossing designs with varying potential. AlphaMPSim is a flexible simulation program that is efficiently designed for comparison of alternative designs for traits with varying genetic architectures and biallelic markers with densities up to full sequence. A large pool of founder haplotypes can be supplied by the user, or generated via integration with external coalescent simulation programs such as MaCS. From these, diverse founders for multi-parent designs can be generated automatically, and users can compare designs generated from diverse pedigrees. Full tracking of identity by descent status of alleles within the pedigree is undertaken, and output files are compatible with commonly available analysis packages in R.

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Bayesian Modeling of Haplotype Effects in Multiparent Populations

Bayesian Modeling of Haplotype Effects in Multiparent Populations | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it
A general Bayesian model, Diploffect, is described for estimating the effects of founder haplotypes at quantitative trait loci(QTL) detected in multiparental genetic populations; such populations include the Collaborative Cross (CC), Heterogeneous Socks (HS),and many others for which local genetic variation is well described by an underlying, usually probabilistically inferred, haplotypemosaic. Our aim is to provide a framework for coherent estimation of haplotype and diplotype (haplotype pair) effects that takes intoaccount the following: uncertainty in haplotype composition for each individual; uncertainty arising from small sample sizes andinfrequently observed haplotype combinations; possible effects of dominance (for noninbred subjects); genetic background; and thatprovides a means to incorporate data that may be incomplete or has a hierarchical structure. Using the results of a probabilistichaplotype reconstruction as prior information, we obtain posterior distributions at the QTL for both haplotype effects and haplotypecomposition. Two alternative computational approaches are supplied: a Markov chain Monte Carlo sampler and a procedure based onimportance sampling of integrated nested Laplace approximations. Using simulations of QTL in the incipient CC (pre-CC) andNorthport HS populations, we compare the accuracy of Diploffect, approximations to it, and more commonly used approaches basedon Haley–Knott regression, describing trade-offs between these methods. We also estimate effects for three QTL previously identifiedin those populations, obtaining posterior intervals that describe how the phenotype might be affected by diplotype substitutions at themodeled locus.

 

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Potential of a tomato MAGIC population to decipher the genetic control of quantitative traits and detect causal variants in the resequencing era

Potential of a tomato MAGIC population to decipher the genetic control of quantitative traits and detect causal variants in the resequencing era | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it

Identification of the polymorphisms controlling quantitative traits remains a challenge for plant geneticists. Multiparent advanced generation intercross (MAGIC) populations offer an alternative to traditional linkage or association mapping populations by increasing the precision of quantitative trait loci (QTL) mapping. Here, we present the first tomato MAGIC population and highlight its potential for the valorization of intraspecific variation, QTL mapping and causal polymorphism identification. The population was developed by crossing eight founder lines, selected to include a wide range of genetic diversity, whose genomes have been previously resequenced. We selected 1536 SNPs among the 4 million available to enhance haplotype prediction and recombination detection in the population. The linkage map obtained showed an 87% increase in recombination frequencies compared to biparental populations. The prediction of the haplotype origin was possible for 89% of the MAGIC line genomes, allowing QTL detection at the haplotype level. We grew the population in two greenhouse trials and detected QTLs for fruit weight. We mapped three stable QTLs and six specific of a location. Finally, we showed the potential of the MAGIC population when coupled with whole genome sequencing of founder lines to detect candidate SNPs underlying the QTLs. For a previously cloned QTL on chromosome 3, we used the predicted allelic effect of each founder and their genome sequences to select putative causal polymorphisms in the supporting interval. The number of candidate polymorphisms was reduced from 12 284 (in 800 genes) to 96 (in 54 genes), including the actual causal polymorphism. This population represents a new permanent resource for the tomato genetics community.

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PDF: Effect of advanced intercrossing on genom structure and on the power to detect linke quantitative trait loci in a multi-parent population a simulation study in rice

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Multiparental Mapping of Plant Height and Flowering Time QTL in Partially Isogenic Sorghum Families

Sorghum varieties suitable for grain production at temperate latitudes show dwarfism andphotoperiod insensitivity, both of which are controlled by a small number of loci with large effects. Westudied the genetic control of plant height andflowering time infive sorghum families (A–E), each derivedfrom a cross between a tropical line and a partially isogenic line carrying introgressions derived froma common, temperate-adapted donor. A total of 724 F2:3lines were phenotyped in temperate and tropicalenvironments for plant height andflowering time and scored at 9139 SNPs using genotyping-by-sequencing.Biparental mapping was compared with multiparental mapping in different subsets of families (AB,ABC, ABCD, and ABCDE) using both a GWAS approach, whichfit each QTL as a single effect across allfamilies, and using a joint linkage approach, whichfit QTL effects as nested within families. GWAS using allfamilies (ABCDE) performed best at the clonedDw3locus, whereas joint linkage using all families per-formed best at the clonedMa1locus. Both multiparental approaches yielded apparently synthetic associ-ations due to genetic heterogeneity and were highly dependent on the subset of families used. Comparisonof all mapping approaches suggests that a GA2-oxidase underliesDw1, and that a mir172a gene underliesaDw1-linked flowering time QTL.

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Genetics and G3 special issue on: Multiparental Populations

he success of a recent workshop in Cambridge (http://mus.well.ox.ac.uk/19genomes/MAGIC-WORKSHOP/) discussing the results of experiments with Multiparental populations (MPP) and methods for analysis of MPPs underscores the strong community interest to share knowledge within a wide range of species and approaches. New MPPs are increasingly being created in crop and animal model species, making this an opportune time to begin an MPP focus in GENETICS and G3. We expect these articles to give rise to new theories and methods for the analysis of MPPs, as well as improved experimental design. This MPP focus for GENETICS and G3 encompasses experimental and methodological contributions in both plants and animals. We invite additional articles on this topic and encourage you to read the editorial for additional information.

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PhD Available: Exploring diversity for crop improvement in multiparent populations — Department of Plant Sciences, Cambridge University/NIAB

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An Eight-Parent Multiparent Advanced Generation Inter-Cross Population for Winter-Sown Wheat: Creation, Properties, and Validation

An Eight-Parent Multiparent Advanced Generation Inter-Cross Population for Winter-Sown Wheat: Creation, Properties, and Validation | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it

MAGIC populations represent one of a new generation of crop genetic mapping resources combining high genetic recombination and diversity. We describe the creation and validation of an eight-parent MAGIC population consisting of 1091 F7 lines of winter-sown wheat (Triticum aestivum L.). Analyses based on genotypes from a 90,000-single nucleotide polymorphism (SNP) array find the population to be well-suited as a platform for fine-mapping quantitative trait loci (QTL) and gene isolation. Patterns of linkage disequilibrium (LD) show the population to be highly recombined; genetic marker diversity among the founders was 74% of that captured in a larger set of 64 wheat varieties, and 54% of SNPs segregating among the 64 lines also segregated among the eight founder lines. In contrast, a commonly used reference bi-parental population had only 54% of the diversity of the 64 varieties with 27% of SNPs segregating. We demonstrate the potential of this MAGIC resource by identifying a highly diagnostic marker for the morphological character "awn presence/absence" and independently validate it in an association-mapping panel. These analyses show this large, diverse, and highly recombined MAGIC population to be a powerful resource for the genetic dissection of target traits in wheat, and it is well-placed to efficiently exploit ongoing advances in phenomics and genomics. Genetic marker and trait data, together with instructions for access to seed, are available at http://www.niab.com/MAGIC/.

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Use of a large multiparent wheat mapping population in genomic dissection of coleoptile and seedling growth

Use of a large multiparent wheat mapping population in genomic dissection of coleoptile and seedling growth | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it

Identification of alleles towards the selection for improved seedling vigour is a key objective of many wheat breeding programmes. A multiparent advanced generation intercross (MAGIC) population developed from four commercial spring wheat cultivars (cvv. Baxter, Chara, Westonia and Yitpi) and containing ca. 1000 F2-derived, F6:7 RILs was assessed at two contrasting soil temperatures (12 and 20 °C) for shoot length and coleoptile characteristics length and thickness. Narrow-sense heritabilities were high for coleoptile and shoot length (h2 = 0.68–0.70), indicating a strong genetic basis for the differences among progeny. Genotypic variation was large, and distributions of genotype means were approximately Gaussian with evidence for transgressive segregation for all traits. A number of significant QTL were identified for all early growth traits, and these were commonly repeatable across the different soil temperatures. The largest negative effects on coleoptile lengths were associated with Rht-B1b (−8.2%) and Rht-D1b (−10.9%) dwarfing genes varying in the population. Reduction in coleoptile length with either gene was particularly large at the warmer soil temperature. Other large QTL for coleoptile length were identified on chromosomes 1A, 2B, 4A, 5A and 6B, but these were relatively smaller than allelic effects at the Rht-B1 and Rht-D1 loci. A large coleoptile length effect allele (a = 5.3 mm at 12 °C) was identified on chromosome 1AS despite the relatively shorter coleoptile length of the donor Yitpi. Strong, positive genetic correlations for coleoptile and shoot lengths (rg = 0.85–0.90) support the co-location of QTL for these traits and suggest a common physiological basis for both. The multiparent population has enabled the identification of promising shoot and coleoptile QTL despite the potential for the confounding of large effect dwarfing gene alleles present in the commercial parents. The incidence of these alleles in commercial wheat breeding programmes should facilitate their ready implementation in selection of varieties with improved establishment and early growth.

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QTL detection power of multi-parental RIL populations in Arabidopsis thaliana

QTL detection power of multi-parental RIL populations in Arabidopsis thaliana | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it

Arabidopsis multiparent RIL

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Abstract: Fine Mapping a QTL for Dormancy in a Multi-Parent RIL Population Utilising the IWGSC Wheat Survey Sequence (PAG Asia 2013)

Abstract: Fine Mapping a QTL for Dormancy in a Multi-Parent RIL Population Utilising the IWGSC Wheat Survey Sequence (PAG Asia 2013) | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it
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From mutations to MAGIC: resources for gene discovery, validation and delivery in crop plants

From mutations to MAGIC: resources for gene discovery, validation and delivery in crop plants | Plant multi-parent advanced generation intercross (MAGIC) populations | Scoop.it

Plant MAGIC review 2008

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