The Dawn of the Age of Multi-Parent MAGIC Populations in Plant Breeding: Novel Powerful Next-Generation Resources for Genetic Analysis and Selection of Recombinant Elite Material

Growth and antioxidant responses to water stress in eggplant MAGIC population parents, F1 hybrids and a subset of recombinant inbred lines

BACKGROUND

The generation of new eggplant (Solanum melongena L.) cultivars with drought tolerance is a main challenge in the current context of climate change. In this study, the eight parents (seven of S. melongena and one of the wild relative S. incanum L.) of the first eggplant MAGIC (Multiparent Advanced Generation Intercrossing) population, together with four F1 hybrids amongst them, five S5 MAGIC recombinant inbred lines selected for their genetic diversity, and one commercial hybrid were evaluated in young plant stage under water stress conditions (30% field capacity; FC) and control conditions (100% FC). After a 21-day treatment period, growth and biomass traits, photosynthetic pigments, oxidative stress markers, antioxidant compounds, and proline content were evaluated.

RESULTS

Significant effects (p < 0.05) were observed for genotype, water treatments and their interaction in most of the traits analyzed. The eight MAGIC population parental genotypes displayed a wide variation in their responses to water stress, with some of them exhibiting enhanced root development and reduced foliar biomass. The commercial hybrid had greater aerial growth compared to root growth. The four F1 hybrids among MAGIC parents differed in their performance, with some having significant positive or negative heterosis in several traits. The subset of five MAGIC lines displayed a wide diversity in their response to water stress.

CONCLUSION

The results show that a large diversity for tolerance to drought is available among the eggplant MAGIC materials, which can contribute to developing drought-tolerant eggplant cultivars.

Omics-driven utilization of wild relatives for empowering pre-breeding in pearl millet

MAIN CONCLUSION

Pearl millet wild relatives harbour novel alleles which could be utilized to broaden genetic base of cultivated species. Genomics-informed pre-breeding is needed to speed up introgression from wild to cultivated gene pool in pearl millet. Rising episodes of intense biotic and abiotic stresses challenge pearl millet production globally. Wild relatives provide a wide spectrum of novel alleles which could address challenges posed by climate change. Pre-breeding holds potential to introgress novel diversity in genetically narrow cultivated Pennisetum glaucum from diverse gene pool. Practical utilization of gene pool diversity remained elusive due to genetic intricacies. Harnessing promising traits from wild pennisetum is limited by lack of information on underlying candidate genes/QTLs. Next-Generation Omics provide vast scope to speed up pre-breeding in pearl millet. Genomic resources generated out of draft genome sequence and improved genome assemblies can be employed to utilize gene bank accessions effectively. The article highlights genetic richness in pearl millet and its utilization with a focus on harnessing next-generation Omics to empower pre-breeding.

Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea

Terminal drought is one of the major constraints to crop production in chickpea (Cicer arietinum L.). In order to map drought tolerance related traits at high resolution, we sequenced multi-parent advanced generation intercross (MAGIC) population using whole genome resequencing approach and phenotyped it under drought stress environments for two consecutive years (2013-14 and 2014-15). A total of 52.02 billion clean reads containing 4.67 TB clean data were generated on the 1136 MAGIC lines and eight parental lines. Alignment of clean data on to the reference genome enabled identification of a total, 932,172 of SNPs, 35,973 insertions, and 35,726 deletions among the parental lines. A high-density genetic map was constructed using 57,180 SNPs spanning a map distance of 1606.69 cM. Using compressed mixed linear model, genome-wide association study (GWAS) enabled us to identify 737 markers significantly associated with days to 50% flowering, days to maturity, plant height, 100 seed weight, biomass, and harvest index. In addition to the GWAS approach, an identity-by-descent (IBD)-based mixed model approach was used to map quantitative trait loci (QTLs). The IBD-based mixed model approach detected major QTLs that were comparable to those from the GWAS analysis as well as some exclusive QTLs with smaller effects. The candidate genes like FRIGIDA and CaTIFY4b can be used for enhancing drought tolerance in chickpea. The genomic resources, genetic map, marker-trait associations, and QTLs identified in the study are valuable resources for the chickpea community for developing climate resilient chickpeas.

Revitalizing agriculture: next-generation genotyping and -omics technologies enabling molecular prediction of resilient traits in the Solanaceae family

This review highlights -omics research in Solanaceae family, with a particular focus on resilient traits. Extensive research has enriched our understanding of Solanaceae genomics and genetics, with historical varietal development mainly focusing on disease resistance and cultivar improvement but shifting the emphasis towards unveiling resilience mechanisms in genebank-preserved germplasm is nowadays crucial. Collecting such information, might help researchers and breeders developing new experimental design, providing an overview of the state of the art of the most advanced approaches for the identification of the genetic elements laying behind resilience. Building this starting point, we aim at providing a useful tool for tackling the global agricultural resilience goals in these crops.

Conventional and new genetic resources for an eggplant breeding revolution

Eggplant (Solanum melongena) is a major vegetable crop with great potential for genetic improvement owing to its large and mostly untapped genetic diversity. It is closely related to over 500 species of Solanum subgenus Leptostemonum that belong to its primary, secondary, and tertiary genepools and exhibit a wide range of characteristics useful for eggplant breeding, including traits adaptive to climate change. Germplasm banks worldwide hold more than 19 000 accessions of eggplant and related species, most of which have yet to be evaluated. Nonetheless, eggplant breeding using the cultivated S. melongena genepool has yielded significantly improved varieties. To overcome current breeding challenges and for adaptation to climate change, a qualitative leap forward in eggplant breeding is necessary. The initial findings from introgression breeding in eggplant indicate that unleashing the diversity present in its relatives can greatly contribute to eggplant breeding. The recent creation of new genetic resources such as mutant libraries, core collections, recombinant inbred lines, and sets of introgression lines will be another crucial element and will require the support of new genomics tools and biotechnological developments. The systematic utilization of eggplant genetic resources supported by international initiatives will be critical for a much-needed eggplant breeding revolution to address the challenges posed by climate change.

Development and evaluation of the utility of GenoBaits Peanut 40K for a peanut MAGIC population

Population and genotype data are essential for genetic mapping. The multi-parent advanced generation intercross (MAGIC) population is a permanent mapping population used for precisely mapping quantitative trait loci. Moreover, genotyping-by-target sequencing (GBTS) is a robust high-throughput genotyping technology characterized by its low cost, flexibility, and limited requirements for information management and support. In this study, an 8-way MAGIC population was constructed using eight elite founder lines. In addition, GenoBaits Peanut 40K was developed and utilized for the constructed MAGIC population. A subset (297 lines) of the MAGIC population at the S2 stage was genotyped using GenoBaits Peanut 40K. Furthermore, these lines and the eight parents were analyzed in terms of pod length, width, area, and perimeter. A total of 27 single nucleotide polymorphisms (SNPs) were revealed to be significantly associated with peanut pod size-related traits according to a genome-wide association study. The GenoBaits Peanut 40K provided herein and the constructed MAGIC population will be applicable for future research to identify the key genes responsible for important peanut traits.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01417-w.

Integrated Genomic Selection for Accelerating Breeding Programs of Climate-Smart Cereals

Rapidly rising population and climate changes are two critical issues that require immediate action to achieve sustainable development goals. The rising population is posing increased demand for food, thereby pushing for an acceleration in agricultural production. Furthermore, increased anthropogenic activities have resulted in environmental pollution such as water pollution and soil degradation as well as alterations in the composition and concentration of environmental gases. These changes are affecting not only biodiversity loss but also affecting the physio-biochemical processes of crop plants, resulting in a stress-induced decline in crop yield. To overcome such problems and ensure the supply of food material, consistent efforts are being made to develop strategies and techniques to increase crop yield and to enhance tolerance toward climate-induced stress. Plant breeding evolved after domestication and initially remained dependent on phenotype-based selection for crop improvement. But it has grown through cytological and biochemical methods, and the newer contemporary methods are based on DNA-marker-based strategies that help in the selection of agronomically useful traits. These are now supported by high-end molecular biology tools like PCR, high-throughput genotyping and phenotyping, data from crop morpho-physiology, statistical tools, bioinformatics, and machine learning. After establishing its worth in animal breeding, genomic selection (GS), an improved variant of marker-assisted selection (MAS), has made its way into crop-breeding programs as a powerful selection tool. To develop novel breeding programs as well as innovative marker-based models for genetic evaluation, GS makes use of molecular genetic markers. GS can amend complex traits like yield as well as shorten the breeding period, making it advantageous over pedigree breeding and marker-assisted selection (MAS). It reduces the time and resources that are required for plant breeding while allowing for an increased genetic gain of complex attributes. It has been taken to new heights by integrating innovative and advanced technologies such as speed breeding, machine learning, and environmental/weather data to further harness the GS potential, an approach known as integrated genomic selection (IGS). This review highlights the IGS strategies, procedures, integrated approaches, and associated emerging issues, with a special emphasis on cereal crops. In this domain, efforts have been taken to highlight the potential of this cutting-edge innovation to develop climate-smart crops that can endure abiotic stresses with the motive of keeping production and quality at par with the global food demand.

Evaluation of Inbred Maize (Zea mays L.) for Tolerance to Low Phosphorus at the Seedling Stage

In underdeveloped nations where low-input agriculture is practiced, low phosphorus (LP) in the soil reduces the production of maize. In the present study, a total of 550 inbred maize lines were assessed for seedling traits under LP (2.5 × 10^-6 mol L^-1 of KH₂PO₄) and NP (2.5 × 10^-4 mol L^-1 of KH₂PO₄) hydroponic conditions. The purpose of this study was to quantify the amount of variation present in the measured traits, estimate the genetic involvement of these characteristics, examine the phenotypic correlation coefficients between traits, and to integrate this information to prepare a multi-trait selection index for LP tolerance in maize. A great deal of variability in the maize genotype panel was confirmed by descriptive statistics and analysis of variance (ANOVA). Estimated broad-sense heritability (h²) ranged from 0.7 to 0.91, indicating intermediate to high heritability values for the measured traits. A substantial connection between MSL and other root traits suggested that the direct selection of MSL (maximum shoot length) could be beneficial for the enhancement of other traits. The principal component analysis (PCA) of the first two main component axes explained approximately 81.27% of the variation between lines for the eight maize seedling variables. TDM (total dry matter), SDW (shoot dry weight), RDW (root dry weight), SFW (shoot fresh weight), RFW (root fresh weight), MRL (maximum root length), and MSL measurements accounted for the majority of the first principal component (59.35%). The multi-trait indices were calculated based on PCA using all the measured traits, and 30 genotypes were selected. These selected lines might be considered as the potential source for the improvement of LP tolerance in maize.

The Era of Plant Breeding: Conventional Breeding to Genomics-assisted Breeding for Crop Improvement

Plant breeding has made a significant contribution to increasing agricultural production. Conventional breeding based on phenotypic selection is not effective for crop improvement. Because phenotype is considerably influenced by environmental factors, which will affect the selection of breeding materials for crop improvement. The past two decades have seen tremendous progress in plant breeding research. Especially the availability of high-throughput molecular markers followed by genomic-assisted approaches significantly contributed to advancing plant breeding. Integration of speed breeding with genomic and phenomic facilities allowed rapid quantitative trait loci (QTL)/gene identifications and ultimately accelerated crop improvement programs. The advances in sequencing technology helps to understand the genome organization of many crops and helped with genomic selection in crop breeding. Plant breeding has gradually changed from phenotype-to-genotype-based to genotype-to-phenotype-based selection. High-throughput phenomic platforms have played a significant role in the modern breeding program and are considered an essential part of precision breeding. In this review, we discuss the rapid advance in plant breeding technology for efficient crop improvements and provide details on various approaches/platforms that are helpful for crop improvement. This review will help researchers understand the recent developments in crop breeding and improvements.

Fast integration and accumulation of beneficial breeding alleles through an AB-NAMIC strategy in wheat

Wheat (Triticum aestivum) is among the most important staple crops for safeguarding the food security of the growing world population. To bridge the gap between genebank diversity and breeding programs, we developed an advanced backcross-nested association mapping plus inter-crossed population (AB-NAMIC) by crossing three popular wheat cultivars as recurrent founders to 20 germplasm lines from a mini core collection. Selective backcrossing combined with selection against undesirable traits and extensive crossing within and between sub-populations created new opportunities to detect unknown genes and increase the frequency of beneficial alleles in the AB-NAMIC population. We performed phenotyping of 590 AB-NAMIC lines and a natural panel of 476 cultivars for six consecutive growing seasons and genotyped these 1066 lines with a 660K SNP array. Genome-wide association studies of both panels for plant development and yield traits demonstrated improved power to detect rare alleles and loci with medium genetic effects in AB-NAMIC. Notably, genome-wide association studies in AB-NAMIC detected the candidate gene TaSWEET6-7B (TraesCS7B03G1216700), which has high homology to the rice SWEET6b gene and exerts strong effects on adaptation and yield traits. The commercial release of two derived AB-NAMIC lines attests to its direct applicability in wheat improvement. Valuable information on genome-wide association study mapping, candidate genes, and their haplotypes for breeding traits are available through WheatGAB. Our research provides an excellent framework for fast-tracking exploration and accumulation of beneficial alleles stored in genebanks.

Biofortification to avoid malnutrition in humans in a changing climate: Enhancing micronutrient bioavailability in seed, tuber, and storage roots

Malnutrition results in enormous socio-economic costs to the individual, their community, and the nation's economy. The evidence suggests an overall negative impact of climate change on the agricultural productivity and nutritional quality of food crops. Producing more food with better nutritional quality, which is feasible, should be prioritized in crop improvement programs. Biofortification refers to developing micronutrient -dense cultivars through crossbreeding or genetic engineering. This review provides updates on nutrient acquisition, transport, and storage in plant organs; the cross-talk between macro- and micronutrients transport and signaling; nutrient profiling and spatial and temporal distribution; the putative and functionally characterized genes/single-nucleotide polymorphisms associated with Fe, Zn, and β-carotene; and global efforts to breed nutrient-dense crops and map adoption of such crops globally. This article also includes an overview on the bioavailability, bioaccessibility, and bioactivity of nutrients as well as the molecular basis of nutrient transport and absorption in human. Over 400 minerals (Fe, Zn) and provitamin A-rich cultivars have been released in the Global South. Approximately 4.6 million households currently cultivate Zn-rich rice and wheat, while ~3 million households in sub-Saharan Africa and Latin America benefit from Fe-rich beans, and 2.6 million people in sub-Saharan Africa and Brazil eat provitamin A-rich cassava. Furthermore, nutrient profiles can be improved through genetic engineering in an agronomically acceptable genetic background. The development of "Golden Rice" and provitamin A-rich dessert bananas and subsequent transfer of this trait into locally adapted cultivars are evident, with no significant change in nutritional profile, except for the trait incorporated. A greater understanding of nutrient transport and absorption may lead to the development of diet therapy for the betterment of human health.

Development of a MAGIC population and high-resolution quantitative trait mapping for nicotine content in tobacco

Multiparent Advanced Generation Inter-Cross (MAGIC) population is an ideal genetic and breeding material for quantitative trait locus (QTL) mapping and molecular breeding. In this study, a MAGIC population derived from eight tobacco parents was developed. Eight parents and 560 homozygous lines were genotyped by a 430K single-nucleotide polymorphism (SNP) chip assay and phenotyped for nicotine content under different conditions. Four QTLs associated with nicotine content were detected by genome-wide association mapping (GWAS), and one major QTL, named qNIC7-1, was mapped repeatedly under different conditions. Furthermore, by combining forward mapping, bioinformatics analysis and gene editing, we identified an ethylene response factor (ERF) transcription factor as a candidate gene underlying the major QTL qNIC7-1 for nicotine content in tobacco. A presence/absence variation (PAV) at qNIC7-1 confers changes in nicotine content. Overall, the large size of this MAGIC population, diverse genetic composition, balanced parental contributions and high levels of recombination all contribute to its value as a genetic and breeding resource. The application of the tobacco MAGIC population for QTL mapping and detecting rare allelic variation was demonstrated using nicotine content as a proof of principle.

Mutations in the SmAPRR2 transcription factor suppressing chlorophyll pigmentation in the eggplant fruit peel are key drivers of a diversified colour palette

Understanding the mechanisms by which chlorophylls are synthesized in the eggplant (Solanum melongena) fruit peel is of great relevance for eggplant breeding. A multi-parent advanced generation inter-cross (MAGIC) population and a germplasm collection have been screened for green pigmentation in the fruit peel and used to identify candidate genes for this trait. A genome-wide association study (GWAS) performed with 420 MAGIC individuals revealed a major association on chromosome 8 close to a gene similar to APRR2. Two variants in SmAPRR2, predicted as having a high impact effect, were associated with the absence of fruit chlorophyll pigmentation in the MAGIC population, and a large deletion of 5.27 kb was found in two reference genomes of accessions without chlorophyll in the fruit peel. The validation of the candidate gene SmAPRR2 was performed by its sequencing in a set of MAGIC individuals and through its de novo assembly in 277 accessions from the G2P-SOL eggplant core collection. Two additional mutations in SmAPRR2 associated with the lack of chlorophyll were identified in the core collection set. The phylogenetic analysis of APRR2 reveals orthology within Solanaceae and suggests that specialization of APRR2-like genes occurred independently in Cucurbitaceae and Solanaceae. A strong geographical differentiation was observed in the frequency of predominant mutations in SmAPRR2, resulting in a lack of fruit chlorophyll pigmentation and suggesting that this phenotype may have arisen and been selected independently several times. This study represents the first identification of a major gene for fruit chlorophyll pigmentation in the eggplant fruit.

statgenMPP: an R package implementing an IBD-based mixed model approach for QTL mapping in a wide range of multi-parent populations

MOTIVATION

Multi-parent populations (MPPs) are popular for QTL mapping because they combine wide genetic diversity in parents with easy control of population structure, but a limited number of software tools for QTL mapping are specifically developed for general MPP designs.

RESULTS

We developed an R package called statgenMPP, adopting a unified identity-by-descent (IBD)-based mixed model approach for QTL analysis in MPPs. The package offers easy-to-use functionalities of IBD calculations, mixed model solutions and visualizations for QTL mapping in a wide range of MPP designs, including diallele, nested-association mapping populations, multi-parent advanced genetic inter-cross populations and other complicated MPPs with known crossing schemes.

AVAILABILITY AND IMPLEMENTATION

The R package statgenMPP is open-source and freely available on CRAN at https://CRAN.R-project.org/package=statgenMPP.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Overexpression of the WAPO-A1 gene increases the number of spikelets per spike in bread wheat

Two homoeologous QTLs for number of spikelets per spike (SPS) were mapped on chromosomes 7AL and 7BL using two wheat MAGIC populations. Sets of lines contrasting for the QTL on 7AL were developed which allowed for the validation and fine mapping of the 7AL QTL and for the identification of a previously described candidate gene, WHEAT ORTHOLOG OF APO1 (WAPO1). Using transgenic overexpression in both a low and a high SPS line, we provide a functional validation for the role of this gene in determining SPS also in hexaploid wheat. We show that the expression levels of this gene positively correlate with SPS in multiple MAGIC founder lines under field conditions as well as in transgenic lines grown in the greenhouse. This work highlights the potential use of WAPO1 in hexaploid wheat for further yield increases. The impact of WAPO1 and SPS on yield depends on other genetic and environmental factors, hence, will require a finely balanced expression level to avoid the development of detrimental pleiotropic phenotypes.

Genetic Augmentation of Legume Crops Using Genomic Resources and Genotyping Platforms for Nutritional Food Security

Recent advances in next generation sequencing (NGS) technologies have led the surge of genomic resources for the improvement legume crops. Advances in high throughput genotyping (HTG) and high throughput phenotyping (HTP) enable legume breeders to improve legume crops more precisely and efficiently. Now, the legume breeder can reshuffle the natural gene combinations of their choice to enhance the genetic potential of crops. These genomic resources are efficiently deployed through molecular breeding approaches for genetic augmentation of important legume crops, such as chickpea, cowpea, pigeonpea, groundnut, common bean, lentil, pea, as well as other underutilized legume crops. In the future, advances in NGS, HTG, and HTP technologies will help in the identification and assembly of superior haplotypes to tailor the legume crop varieties through haplotype-based breeding. This review article focuses on the recent development of genomic resource databases and their deployment in legume molecular breeding programmes to secure global food security.

The root system architecture of wheat establishing in soil is associated with varying elongation rates of seminal roots: quantification using 4D magnetic resonance imaging

Seedling establishment is the first stage of crop productivity, and root phenotypes at seed emergence are critical to a successful start of shoot growth as well as for water and nutrient uptake. In this study, we investigate seedling establishment in winter wheat utilizing a newly developed workflow based on magnetic resonance imaging (MRI). Using the eight parents of the MAGIC (multi-parent advanced generation inter-cross) population we analysed the 4D root architecture of 288 individual seedlings grown in natural soils with plant neighbors over 3 d of development. Time of root and shoot emergence, total length, angle, and depth of the axile roots varied significantly among these genotypes. The temporal data resolved rates of elongation of primary roots and first and second seminal root pairs. Genotypes with slowly elongating primary roots had rapidly elongating first and second seminal root pairs and vice versa, resulting in variation in root system architecture mediated not only by root angle but also by initiation and relative elongation of axile roots. We demonstrated that our novel MRI workflow with a unique planting design and automated measurements allowed medium throughput phenotyping of wheat roots in 4D and could give new insights into regulation of root system architecture.

Newly Developed MAGIC Population Allows Identification of Strong Associations and Candidate Genes for Anthocyanin Pigmentation in Eggplant

Multi-parent advanced generation inter-cross (MAGIC) populations facilitate the genetic dissection of complex quantitative traits in plants and are valuable breeding materials. We report the development of the first eggplant MAGIC population (S3 Magic EGGplant InCanum, S3MEGGIC; 8-way), constituted by the 420 S3 individuals developed from the intercrossing of seven cultivated eggplant (Solanum melongena) and one wild relative (S. incanum) parents. The S3MEGGIC recombinant population was genotyped with the eggplant 5k probes SPET platform and phenotyped for anthocyanin presence in vegetative plant tissues (PA) and fruit epidermis (FA), and for the light-insensitive anthocyanic pigmentation under the calyx (PUC). The 7,724 filtered high-confidence single-nucleotide polymorphisms (SNPs) confirmed a low residual heterozygosity (6.87%), a lack of genetic structure in the S3MEGGIC population, and no differentiation among subpopulations carrying a cultivated or wild cytoplasm. Inference of haplotype blocks of the nuclear genome revealed an unbalanced representation of the founder genomes, suggesting a cryptic selection in favour or against specific parental genomes. Genome-wide association study (GWAS) analysis for PA, FA, and PUC detected strong associations with two myeloblastosis (MYB) genes similar to MYB113 involved in the anthocyanin biosynthesis pathway, and with a COP1 gene which encodes for a photo-regulatory protein and may be responsible for the PUC trait. Evidence was found of a duplication of an ancestral MYB113 gene with a translocation from chromosome 10 to chromosome 1 compared with the tomato genome. Parental genotypes for the three genes were in agreement with the identification of the candidate genes performed in the S3MEGGIC population. Our new eggplant MAGIC population is the largest recombinant population in eggplant and is a powerful tool for eggplant genetics and breeding studies.

New genomic regions associated with white mold resistance in dry bean using a MAGIC population

Dry bean (Phaseolus vulgaris L.) production in many regions is threatened by white mold (WM) [Sclerotinia sclerotiorum (Lib.) de Bary]. Seed yield losses can be up to 100% under conditions favorable for the pathogen. The low heritability, polygenic inheritance, and cumbersome screening protocols make it difficult to breed for improved genetic resistance. Some progress in understanding genetic resistance and germplasm improvement has been accomplished, but cultivars with high levels of resistance are yet to be released. A WM multiparent advanced generation inter-cross (MAGIC) population (n = 1060) was developed to facilitate mapping and breeding efforts. A seedling straw test screening method provided a quick assay to phenotype the population for response to WM isolate 1980. Nineteen MAGIC lines were identified with improved resistance. For genome-wide association studies (GWAS), the data was transformed into three phenotypic distributions-quantitative, polynomial, and binomial-and coupled with ∼52,000 single-nucleotide polymorphisms (SNPs). The three phenotypic distributions identified 30 significant genomic intervals [-log₁₀ (P value) ≥ 3.0]. However, across distributions, four new genomic regions as well as two regions previously reported were found to be associated with resistance. Cumulative R² values were 57% for binomial distribution using 13 genomic intervals, 41% for polynomial using eight intervals, and 40% for quantitative using 11 intervals. New resistant germplasm as well as new genomic regions associated with resistance are now available for further investigation.

Crafting for a better MAGIC: systematic design and test for Multiparental Advanced Generation Inter-Cross population

Multiparental Advanced Generation Inter-Cross (MAGIC) populations are valuable crop resources with a wide array of research uses including genetic mapping of complex traits, management of genetic resources and breeding of new varieties. Multiple founders are crossed to create a rich mosaic of highly recombined founder genomes in the MAGIC recombinant inbred lines (RILs). Many variations of MAGIC population designs exist; however, a large proportion of the currently available populations have been created empirically and based on similar designs. In our evaluations of five MAGIC populations, we found that the choice of designs has a large impact on the recombination landscape in the RILs. The most popular design used in many MAGIC populations has been shown to have a bias in recombinant haplotypes and low level of unique recombinant haplotypes, and therefore is not recommended. To address this problem and provide a remedy for the future, we have developed the “magicdesign” R package for creating and testing any MAGIC population design via simulation. A Shiny app version of the package is available as well. Our “magicdesign” package provides a unifying tool and a framework for creativity and innovation in MAGIC population designs. For example, using this package, we demonstrate that MAGIC population designs can be found which are very effective in creating haplotype diversity without the requirement for very large crossing programs. Furthermore, we show that interspersing cycles of crossing with cycles of selfing is effective in increasing haplotype diversity. These approaches are applicable in species that are hard to cross or in which resources are limited.