Quinoa (Chenopodium quinoa Willd., 2n = 4x = 36) is a highly nutritious crop that is adapted to thrive in a wide range of agroecosystems. It was presumably first domesticated more than 7,000 years ago by pre-Columbian cultures and was known as the 'mother grain' of the Incan Empire 1 . Quinoa has adapted to the high plains of the Andean Altiplano (> 3,500 m above sea level), where it has developed tolerance to several abiotic stresses [2][3][4] . Quinoa has gained international attention because of the nutritional value of its seeds, which are gluten-free, have a low glycaemic index 5 , and contain an excellent balance of essential amino acids, fibre, lipids, carbohydrates, vitamins, and minerals 6 . Quinoa has the potential to provide a highly nutritious food source that can be grown on marginal lands not currently suitable for other major crops. This potential was recognized when the United Nations declared 2013 as the International Year of Quinoa, this being one of only three times a plant has received such a designation.Despite its agronomic potential, quinoa is still an underutilized crop 7 , with relatively few active breeding programs 8 . Breeding efforts to improve the crop for important agronomic traits are needed to expand quinoa production worldwide. To accelerate the improvement of quinoa, we present here the allotetraploid quinoa genome. We demonstrate the utility of the genome sequence by identifying a gene that probably regulates the presence of seed triterpenoid saponin content. Moreover, we sequenced the genomes of additional diploid and tetraploid Chenopodium species to characterize genetic diversity within the primary germplasm pool for quinoa and to understand sub-genome evolution in quinoa. Together, these resources provide the foundation for accelerating the genetic improvement of the crop, with the objective of enhancing global food security for a growing world population. Sequencing, assembly and annotationWe sequenced and assembled the genome of the coastal Chilean quinoa accession PI 614886 (BioSample accession code SAMN04338310) using single-molecule real-time (SMRT) sequencing technology from Pacific Biosciences (PacBio) and optical and chromosome-contact maps from BioNano Genomics 9 and Dovetail Genomics 10 . The assembly contains 3,486 scaffolds, with a scaffold N50 of 3.84 Mb and 90% of the assembled genome contained in 439 scaffolds (Table 1). The total assembly size of 1.39 gigabases (Gb) is similar to the reported size estimates of the quinoa genome (1.45-1.50 Gb (refs 11,12)). To combine scaffolds into pseudomolecules, an existing linkage map from quinoa 13 was integrated with two new linkage maps. The resulting map (Extended Data Fig. 1) of 6,403 unique markers spans a total length of 2,034 centimorgans (cM) and consists of 18 linkage groups (Supplementary Table 7), corresponding to the haploid chromosome number of quinoa. Pseudomolecules (hereafter referred to as chromosomes, which are numbered according to a previously published single-nucleotide polymorphism (SNP) linkage ...

Association or linkage disequilibrium (LD)-based mapping strategies are receiving increased attention for the identification of quantitative trait loci (QTL) in plants as an alternative to more traditional, purely linkage-based approaches. An attractive property of association approaches is that they do not require specially designed crosses between inbred parents, but can be applied to collections of genotypes with arbitrary and often unknown relationships between the genotypes. A less obvious additional attractive property is that association approaches offer possibilities for QTL identification in crops with hard to model segregation patterns. The availability of candidate genes and targeted marker systems facilitates association approaches, as will appropriate methods of analysis. We propose an association mapping approach based on mixed models with attention to the incorporation of the relationships between genotypes, whether induced by pedigree, population substructure, or otherwise. Furthermore, we emphasize the need to pay attention to the environmental features of the data as well, i.e., adequate representation of the relations among multiple observations on the same genotypes. We illustrate our modeling approach using 25 years of Dutch national variety list data on late blight resistance in the genetically complex crop of potato. As markers, we used nucleotide binding-site markers, a specific type of marker that targets resistance or resistance-analog genes. To assess the consistency of QTL identified by our mixed-model approach, a second independent data set was analyzed. Two markers were identified that are potentially useful in selection for late blight resistance in potato.

Phosphorus (P) is often an important limiting factor for crop yields, but rock phosphate as fertilizer is a non-renewable resource and expected to become scarce in the future. High P input levels in agriculture have led to environmental problems. One of the ways to tackle these issues simultaneously is improving phosphorus use efficiency (PUE) of the crops through breeding. In this review, we describe plant architectural and physiological traits important for PUE. Subsequently, we discuss efficient methods of screening for PUE traits. We address targeted cultivation methods, including solid and hydroponic systems, as well as testing methods, such as image analysis systems, and biomass and photosynthesis measurements. Genetic variation for PUE traits has been assessed in many crops, and genetics of PUE has been studied by quantitative trait loci (QTL) analyses and genome-wide association study. A number of genes involved in the plant's response to low P have been characterized. These genes include transcription factors, and genes involved in signal transduction, hormonal pathways, sugar signalling, P saving metabolic pathways, and in P scavenging, including transporters and metabolites and/or ATP-ases mobilizing P in the soil. In addition, the role of microorganisms promoting PUE of plants, particularly arbuscular mycorrhizal fungi is discussed. An overview is given of methods for selecting for optimal combinations of plant and fungal genotypes, and their genetics, incl. QTLs and genes involved. In conclusion, significant progress has been made in selecting for traits for PUE, developing systems for the difficult but highly relevant root phenotyping, and in identifying QTLs and genes involved.

The conserved sequences in the nucleotide-binding sites of the nucleotide-binding site-leucine-rich repeat (NBS-LRR) class of disease resistance (R) genes have been used for PCR-based R-gene isolation and subsequent development of molecular markers. Here we present a PCR-based approach (NBS profiling) that efficiently targets R genes and R-gene analogs (RGAs) and, at the same time, produces polymorphic markers in these genes. In NBS profiling, genomic DNA is digested with a restriction enzyme, and an NBS-specific (degenerate) primer is used in a PCR reaction towards an adapter linked to the resulting DNA fragments. The NBS profiling protocol generates a reproducible polymorphic multilocus marker profile on a sequencing gel that is highly enriched for R genes and RGAs. NBS profiling was successfully used in potato with several restriction enzymes, and several primers targeted to different conserved motifs in the NBS. Across primers and enzymes, the NBS profiles contained 50-90% fragments that were significantly similar to known R-gene and RGA sequences. The protocol was similarly successful in other crops (including tomato, barley, and lettuce) without modifications. NBS profiling can thus be used to produce markers tightly linked to R genes and R-gene clusters for genomic mapping and positional cloning and to mine for new alleles and new sources of disease resistance in available germplasm.

A spring barley collection of 192 genotypes from a wide geographical range was used to identify quantitative trait loci (QTLs) for salt tolerance traits by means of an association mapping approach using a thousand SNP marker set. Linkage disequilibrium (LD) decay was found with marker distances spanning 2-8 cM depending on the methods used to account for population structure and genetic relatedness between genotypes. The association panel showed large variation for traits that were highly heritable under salt stress, including biomass production, chlorophyll content, plant height, tiller number, leaf senescence and shoot Na(+), shoot Cl(-) and shoot, root Na(+)/K(+) contents. The significant correlations between these traits and salt tolerance (defined as the biomass produced under salt stress relative to the biomass produced under control conditions) indicate that these traits contribute to (components of) salt tolerance. Association mapping was performed using several methods to account for population structure and minimize false-positive associations. This resulted in the identification of a number of genomic regions that strongly influenced salt tolerance and ion homeostasis, with a major QTL controlling salt tolerance on chromosome 6H, and a strong QTL for ion contents on chromosome 4H.