It’s already a protein-packed ancient grain beloved by foodies. Now scientists say they’ve mapped the genome of quinoa, potentially unlocking a way to mass produce at prices that could help feed the world’s hungry. 
 
 By tinkering with the genetic makeup of the plant, a team of researchers based out of King Abdullah University in Saudi Arabia say it’s possible to grow a strain of quinoa that’s easier to process. In doing so, scientists hope the cost of the grain could one day be comparable to wheat. 
 
 Most quinoa on the market is grown in South America—typically Peru, Bolivia, and Ecuador. For decades it was a quiet crop, the food of peasants around the Andean mountains. But that changed sometime around 2006, when its categorization as a superfood by some in the nutrition sphere sparked a craze in Europe and the US. In 2007, the US imported about 7 million pounds (3.2 million kg) of the grain—which had skyrocketed to 70 million pounds by 2013, according to the Agricultural Marketing Resource Center. 
 
 In that same period, the price of quinoa tripled. The prices fell slightly (paywall) in 2015, the result of a better supply-demand balance, but it still remains a nutritious food mostly cordoned of to the middle classes. 
 
 Eventually, researchers hope to discover ways to grow the grain with a stockier plant that won’t fall over as easily as it does currently and find ways to grow it in different climates. The grain naturally contains a toxic compound called saponins, a bitter component of quinoa seeds that’s used by the plant to ward off predators. 
 
 But by finding a way to grow the plant without its saponins, scientists say the seeds will taste sweeter and companies can spend less money and time removing the compound. ||||| By Shoshana Pritzker, R.D., C.D.N. 
 
 Every year a [not so] new quirky food product comes out of the woodwork to take over grocery stores and e-recipe pages. It’s interesting to see which ones make the grade, and which don’t quite live up to the hype. This year was no different: Quinoa emerged as the clear favorite in the kitchen and in good-for-you nutrients. What is it about quinoa that makes us forget about oldies (but goodies) like brown rice and sweet potatoes? 
 
 It seems like everybody is eating quinoa these days. People are serving it up as a hearty side dish, using it as an energy-boosting breakfast-grain alternative, or making it a main-dish attraction. Quinoa’s versatility and incredible nutrient profile is no doubt the reason it has become one of the hottest carb sources of 2013. If you still find yourself wondering what the heck quinoa is, you’re not alone: Most people think quinoa is a grain like rice or wheat, especially since it cooks up the same way rice would, with two cups of water for every cup of quinoa. Believe it or not, quinoa isn't a grain at all -- it’s actually a [super] seed or pseudo-grain. 
 
 So what’s the big hoopla about? Quinoa is one of the most nutrient-dense carbs available today. It’s got a whopping six grams of protein per cup and is the only carb source that contains all nine essential amino acids. Plus, this seed is a complete protein! On top of that, quinoa is high in lysine, the chief amino acid that’s responsible for healing sore muscles after an intense workout. 
 
 As if that’s not enough, quinoa has a handful of healing and healthy-living benefits. It's packed with minerals, including iron, phosphorous, manganese and copper. Both copper and manganese help fight free radicals and keep our bones strong, while iron and phosphorous are important for energy production and cancer prevention. Another positive health benefit of quinoa is that it’s loaded with fiber -- about 2.5 grams per serving. Among other things, fiber provides a feeling of fullness after a meal, helps maintain a healthy digestive tract and improves insulin control by slowing down the rate of sugar being released into your bloodstream. ||||| No statistical methods were used to predetermine sample size. The experiments were not randomized and the investigators were not blinded to allocation during experiments and outcome assessment. 
 
 Quinoa sequencing and assembly 
 
 We sequenced Chenopodium quinoa Willd. (quinoa) accession PI 614886 (BioSample accession code SAMN04338310; also known as NSL 106399 and QQ74). DNA was extracted from leaf and flower tissue of a single plant, as described in the “Preparing Arabidopsis Genomic DNA for Size-Selected ~20 kb SMRTbell Libraries” protocol (http://www.pacb.com/wp-content/uploads/2015/09/Shared-Protocol-Preparing-Arabidopsis-DNA-for-20-kb-SMRTbell-Libraries.pdf). DNA was purified twice with Beckman Coulter Genomics AMPure XP magnetic beads and assessed by standard agarose gel electrophoresis and Thermo Fisher Scientific Qubit Fluorometry. 100 Single-Molecule Real-Time (SMRT) cells were run on the PacBio RS II system with the P6-C4 chemistry by DNALink (Seoul). De novo assembly was conducted using the smrtmake assembly pipeline (https://github.com/PacificBiosciences/smrtmake) and the Celera Assembler, and the draft assembly was polished using the quiver algorithm. 
 
 DNA was also sequenced using an Illumina HiSeq 2000 machine. For this, DNA was extracted from leaf tissue of a single soil-grown plant using the Qiagen DNeasy Plant Mini Kit. 500-bp paired-end (PE) libraries were prepared using the NEBNext Ultra DNA Library Prep Kit for Illumina. Sequencing reads were processed with Trimmomatic (v0.33)42, and reads <75 nucleotides in length after trimming were removed from further analysis. The remaining high-quality reads were assembled with Velvet (v1.2.10)43 using a k-mer of 75. 
 
 Integrating BioNano optical maps with the PacBio assembly 
 
 High-molecular-weight DNA was isolated and labelled from leaf tissue of three-week old quinoa plants according to standard BioNano protocols, using the single-stranded nicking endonuclease Nt.BspQI. Labelled DNA was imaged automatically using the BioNano Irys system and de novo assembled into consensus physical maps using the BioNano IrysView analysis software. The final de novo assembly used only single molecules with a minimum length of 150 kb and eight labels per molecule. PacBio-BioNano hybrid scaffolds were identified using IrysView’s hybrid scaffold alignment subprogram. 
 
 Chicago library preparation and sequencing 
 
 Using the same DNA prepared for PacBio sequencing, a Chicago library was prepared as described previously10. The library was sequenced on an Illumina HiSeq 2500. 
 
 Scaffolding the PacBio and BioNano assemblies with HiRise 
 
 Chicago sequence data (in FASTQ format) was used to scaffold the PacBio-BioNano hybrid assembly using HiRise, a software pipeline designed specifically for using Chicago data to assemble genomes10. Chicago library sequences were aligned to the draft input assembly using a modified SNAP read mapper (http://snap.cs.berkeley.edu). The separations of Chicago read pairs mapped within draft scaffolds were analysed by HiRise to produce a likelihood model, and the resulting likelihood model was used to identify putative mis-joins and score prospective joins. 
 
 Kurmi × 0654 population mapping and genetic marker analysis 
 
 A population was developed by crossing Kurmi (green, sweet) and 0654 (red, bitter). Homozygous high- and low-saponin F 2 lines were identified by planting 12 F 3 seeds derived from each F 2 line, harvesting F 4 seed from these F 3 plants, and then performing foam tests on the F 4 seed. Phenotyping was validated using gas chromatography/mass spectrometry (GC/MS). RNA was extracted from inflorescences containing a mixture of flowers and seeds at various stages of development from the parents and 45 individual F 3 progeny. RNA extraction and Illumina sequencing were performed as described above. Sequencing reads from all lines were trimmed using Trimmomatic and mapped to the reference assembly using TopHat44, and SNPs were called using SAMtools mpileup (v1.1)45. 
 
 For linkage mapping, markers were assigned to linkage groups on the basis of the grouping by JoinMap v4.1. Using the maximum likelihood algorithm of JoinMap, the order of the markers was determined; using this as start order and fixed order, regression mapping in JoinMap was used to determine the cM distances. 
 
 Genes differentially expressed between bitter and sweet lines and between green and red lines were identified using default parameters of the Cuffdiff function of the Cufflinks program46. 
 
 Atlas × Carina Red population mapping and genetic marker analysis 
 
 A second mapping population was developed by crossing Atlas (sweet) and Carina Red (bitter). Bitter and sweet F 2 lines were identified by performing foam and taste tests on the F 3 seed. DNA sequencing was performed with DNA from the parents and 94 sweet F 2 lines, as described above, and sequencing reads were mapped to the reference assembly using BWA. SNPs were called in the parents and in a merged file containing all combined F 2 lines. 
 
 Genotype calls were generated for the 94 F 2 genotypes by summing up read counts over a sliding window of 500 variants, at all variant positions for which the parents were homozygous and polymorphic. Over each 500-variant stretch, all reads with Atlas alleles were summed, and all reads with the Carina Red allele were summed. Markers were assigned to linkage groups using JoinMap, with regression mapping used to obtain the genetic maps per linkage group. 
 
 Integrated linkage map 
 
 The Kurmi × 0654 and Atlas × Carina Red maps were integrated with the previously published quinoa linkage map13, with the Kurmi × 0654 map being used as the reference for the positions of anchor markers and scaling. We selected markers from the same scaffold that were in the same 10,000-bp bin in the assembly. The anchor markers on the alternative map received the position of the Kurmi × 0654 map anchor marker in the integrated map. This process was repeated with anchor markers at the 100,000-bp bin level. The assumption is that at the 100,000-bp bin level recombination should essentially be zero. On this level, a regression of cM position on both maps yielded R2 values >0.85 and often >0.9, so the regression line can easily be used for interpolating the positions of the alternative map towards the corresponding position on the Kurmi × 0654 map. All Kurmi × 0654 markers went into the integrated map on their original position. 
 
 Chromosome pseudomolecules 
 
 Pseudomolecules were assembled by concatenating scaffolds based on their order and orientation as determined from the integrated linkage map. An AGP (‘A Golden Path’) file was made that describes the positions of the scaffold-based assembly in coordinates of the pseudomolecule assembly, with 100 ‘N’s inserted between consecutive scaffolds. Based on these coordinates, custom scripts were used to generate the pseudomolecule assembly and to recoordinate the annotation file. 
 
 Sequencing and assembly of C. pallidicaule and C. suecicum 
 
 DNA was extracted from C. pallidicaule (PI 478407) and C. suecicum (BYU 1480) and was sent to the Beijing Genomic Institute (BGI, Hong Kong) where one 180-bp PE library and two mate-pair libraries with insert sizes of 3 and 6 kb were prepared and sequenced on the Illumina HiSeq platform to obtain 2 × 100-bp reads for each library. The generated reads were trimmed using the quality-based trimming tool Sickle (https://github.com/najoshi/sickle). The trimmed reads were then assembled using the ALLPATHS-LG assembler47, and GapCloser v1.1248 was used to resolve N spacers and gap lengths produced by the ALLPATHS-LG assembler. 
 
 Genome annotation 
 
 Repeat families found in the genome assemblies of quinoa, C. pallidicaule and C. suecicum (see Supplementary Information 3) were first independently identified de novo and classified using the software package RepeatModeler49. RepeatMasker50 was used to discover and identify repeats within the respective genomes. 
 
 AUGUSTUS51 was used for ab initio gene prediction, using model training based on coding sequences from Amaranthus hypochondriacus, Beta vulgaris, Spinacia oleracea and Arabidopsis thaliana. RNA-seq and isoform sequencing reads generated from RNA of different tissues were mapped onto the reference genome using Bowtie 2 (ref. 52) and GMAP53, respectively. Hints with locations of potential intron–exon boundaries were generated from the alignment files with the software package BAM2hints in the MAKER package54. MAKER with AUGUSTUS (intron–exon boundary hints provided from RNA-seq and isoform sequencing) was then used to predict genes in the repeat-masked reference genome. To help guide the prediction process, peptide sequences from B. vulgaris and the original quinoa full-length transcript (provided as EST evidence) were used by MAKER during the prediction. Genes were characterized for their putative function by performing a BLAST search of the peptide sequences against the UniProt database. PFAM domains and InterProScan ID were added to the gene models using the scripts provided in the MAKER package. 
 
 Re-sequencing 
 
 The following quinoa accessions were chosen for DNA re-sequencing: 0654, Ollague, Real, Pasankalla (BYU 1202), Kurmi, CICA-17, Regalona (BYU 947), Salcedo INIA, G-205-95DK, Cherry Vanilla (BYU 1439), Chucapaca, Ku-2, PI 634921 (Ames 22157), Atlas and Carina Red. The following accessions of C. berlandieri were sequenced: var. boscianum (BYU 937), var. macrocalycium (BYU 803), var. zschackei (BYU 1314), var. sinuatum (BYU 14108), and subsp. nuttaliae (‘Huauzontle’). Two accessions of C. hircinum (BYU 566 and BYU 1101) were also sequenced. All sequencing was performed with an Illumina HiSeq 2000 machine, using either 125-bp (Atlas and Carina Red) or 100-bp (all other accessions) paired-end libraries. Reads were trimmed using Trimmomatic and mapped to the reference assembly using BWA (v0.7.10)55. Read alignments were manipulated with SAMtools, and the mpileup function of SAMtools was used to call SNPs. 
 
 Identification of orthologous genes 
 
 Orthologous and paralogous gene clusters were identified using OrthoMCL28. Recommended settings were used for all-against-all BLASTP comparisons (Blast+ v2.3.056) and OrthoMCL analyses. Custom Perl scripts were used to process OrthoMCL outputs for visualization with InteractiVenn57. 
 
 Phylogenetic inference 
 
 Using OrthoMCL, orthologous gene sets containing two copies in quinoa and one copy each in C. pallidicaule, C. suecicum, and B. vulgaris were identified. In total, 7,433 gene sets were chosen, and their amino acid sequences were aligned individually for each set using MAFFT58. The 7,433 alignments were converted into PHYLIP format files by the seqret command in the EMBOSS package59. Individual gene trees were then constructed using the maximum likelihood method using proml in PHYLIP60. 
 
 In addition, the genomic variants of all 25 sequenced taxa (Supplementary Data 5) relative to the reference sequence were called based on the mapped Illumina reads in 25 BAM files using SAMtools. To call variants in the reference genome (PI 614886), Illumina sequencing reads were mapped to the reference assembly. Variants were then filtered using VCFtools61 and SAMtools, and the qualified SNPs were combined into a single VCF file which was used as an input into SNPhylo62 to construct the phylogenetic relationship using maximum likelihood and 1,000 bootstrap iterations. 
 
 To identify FT homologues, the protein sequence from the A. thaliana flowering time gene FT was used as a BLAST query. Filtering for hits with an E value <1 × e−3 and with RNA-seq evidence resulted in the identification of four quinoa proteins. One quinoa protein (AUR62013052) appeared to be comprised of two tandem repeats which were separated for the purposes of phylogenetic analysis. For the construction of the phylogenetic tree, protein sequences from these five quinoa FT homologues were aligned using Clustal Omega63 along with two B. vulgaris (gene models: BvFT1-miuf.t1, BvFT2-eewx.t1) and one A. thaliana (AT1G65480.1) homologue. Phylogenetic analysis was performed with MEGA64 (v6.06). The JTT model was selected as the best fitting model. The initial phylogenetic tree was estimated using the neighbour joining method (bootstrap value = 50, Gaps/ Missing Data Treatment = Partial Deletion, Cutoff 95%), and the final tree was estimated using the maximum likelihood method with a bootstrap value of 1,000 replicates. The syntenic relationships between the coding sequences of the chromosomal regions surrounding these FT genes were visualized using the CoGE65 GEvo tool and the Multi-Genome Synteny Viewer66. 
 
 The alignment of bHLH domains was performed with Clustal Omega63, using sequences from Mertens et al.39. The phylogeny was inferred using the maximum likelihood method based on the JTT matrix-based model67. Initial trees for the heuristic search were obtained automatically by applying Neighbour-Join and BioNJ algorithms to a matrix of pairwise distances estimated using a JTT model, and then selecting the topology with superior log likelihood value. All positions containing gaps and missing data were eliminated. 
 
 Distinguishing and analysing the quinoa sub-genomes 
 
 Trimmed PE Illumina sequencing reads that were used for the de novo assembly of C. suecicum and C. pallidicaule were mapped onto the reference quinoa genome using the default settings of BWA. For every base in the quinoa genome, the depth coverage of properly paired reads from the C. suecicum and C. pallidicaule mapping was calculated using the program GenomeCoverage in the BEDtools package68. A custom Perl script was used to calculate the percentage of each scaffold with more than 5× coverage from both diploids. Scaffolds were assigned to the A or B sub-genome if >65% of the bases were covered by reads from one diploid and <25% of the bases were covered by reads from the other diploid. The relationship between the quinoa sub-genomes and the diploid species C. pallidicaule and C. suecicum was presented in a circle proportional to their sizes using Circos69. Orthologous regions in the three species were identified using BLASTN searches of the quinoa genome against each diploid genome individually. Single top BLASTN hits longer than 8 kb were selected and presented as links between the quinoa genome assembly (arranged in chromosomes, see Supplementary Information 7.3) and the two diploid genome assemblies on the Circos plot (Fig. 2a). 
 
 Sub-genome synteny was analysed by plotting the positions of homoeologous pairs of A- and B-sub-genome pairs within the context of the 18 chromosomes using Circos. Synteny between the sub-genomes and B. vulgaris was assessed by first creating pseudomolecules by concatenating scaffolds which were known to be ordered and oriented within each of the nine chromosomes. Syntenic regions between these B. vulgaris chromosomes and those of quinoa were then identified using the recommended settings of the CoGe SynMap tool70 and visualized using MCScanX71 and VGSC72. For the purposes of visualization, quinoa chromosomes CqB05, CqA08, CqB11, CqA15 and CqB16 were inverted. 
 
 Saponin analyses 
 
 Quinoa seeds were embedded in a 2% carboxymethylcellulose solution and frozen above liquid nitrogen. Sections of 50 μm thickness were obtained using a Reichert-Jung Frigocut 2800N, modified to use a Feather C35 blade holder and blades at −20 °C using a modified Kawamoto method73. A 2,5-dihydroxybenzoic acid (Sigma-Aldrich) matrix (40 mg ml−1 in 70% methanol) was applied using a HTX TM-Sprayer (HTX Technologies LLC) with attached LC20-AD HPLC pump (Shimadzu Scientific Instruments). Sections were vacuum dried in a desiccator before analysis. The optical image was generated using an Epson 4400 Flatbed Scanner at 4,800 d.p.i. For mass spectrometric analyses, a Bruker SolariX XR with 7T magnet was used. Images were generated using Bruker Compass FlexImaging 4.1. Data were normalized to the TIC, and brightness optimization was employed to enhance visualization of the distribution of selected compounds. Individual spectra were recalibrated using Bruker Compass DataAnalysis 4.4 to internally lock masses of known DHB clusters: C 14 H 9 O 6 = 273.039364 and C 21 H 13 O 9 = 409.055408 m/z. Accurate mass measurements for individual saponins and identified compounds were run using continuous accumulation of selected ions (CASI) using mass windows of 50–100 m/z and a transient of 4 megaword generating a transient of 2.93 s providing a mass resolving power of approximately 390,000 at 400 m/z. Lipids were putatively assigned by searching the LipidMaps database74 (http://www.lipidmaps.org) and lipid class confirmed by collision-induced dissociation using a 10 m/z window centred around the monoisotopic peak with collision energy of between 15–20 V. 
 
 Quinoa flowers were marked at anthesis, and seeds were sampled at 12, 16, 20 and 24 days after anthesis. A pool of five seeds from each time point was analysed using GC/MS. 
 
 Quantification of saponins was performed indirectly by quantifying oleanolic acid (OA) derived from the hydrolysis of saponins extracted from quinoa seeds. Derivatized solution was analysed using single quadrupole GC/MS system (Agilent 7890 GC/5975C MSD) equipped with EI source at ionisation energy of 70 eV. Chromatography separation was performed using DB-5MS fused silica capillary column (30m × 0.25 mm I.D., 0.25 μm film thickness; Agilent J&W Scientific), chemically bonded with 5% phenyl 95% methylpolysiloxane cross-linked stationary phase. Helium was used as the carrier gas with constant flow rate of 1.0 ml min−1. The quantification of OA in each sample was performed using a standard curve based on standards of OA. 
 
 Specific, individual saponins were identified in quinoa using a preparation of 20 mg of seeds performed according a modified protocol from Giavalisco et al.75. Samples were measured with a Waters ACQUITY Reversed Phase Ultra Performance Liquid Chromatography (RP-UPLC) coupled to a Thermo-Fisher Exactive mass spectrometer, which consists of an electrospray ionisation source and an Orbitrap mass analyser. A C18 column was used for the hydrophilic measurements. Chromatograms were recorded in full-scan MS mode (mass range, 100 −1,500). Extraction of the LC/MS data was accomplished with the software REFINER MS 7.5 (GeneData). 
 
 SwissModel76 was used to produce homology models for the bHLH region of AUR62017204, AUR62017206 and AUR62010677. RaptorX77 was used for prediction of secondary structure and disorder. QUARK78 was used for ab initio modelling of the C-terminal domain, and the DALI server79 was used for 3D homology searches of this region. Models were manually inspected and evaluated using the PyMOL program (http://pymol.org). 
 
 Data availability statement 
 
 The genome assemblies and sequence data for C. quinoa, C. pallidicaule and C. suecicum were deposited at NCBI under BioProject codes PRJNA306026, PRJNA326220 and PRJNA326219, respectively. Additional accessions numbers for deposited data can be found in Supplementary Data 9. The quinoa genome can also be accessed at http://www.cbrc.kaust.edu.sa/chenopodiumdb/ and on the Phytozome database (http://www.phytozome.net/). ||||| Image copyright Huw Evans picture agency Image caption Demand for the gluten free grain has soared in recent years, particularly in the US and Europe 
 
 Scientists have successfully decoded the genome of quinoa, one of the world's most nutritious but underutilised crops. 
 
 The South American grain is a hugely popular "super-food" because it is well balanced and gluten-free. 
 
 However, prices for quinoa have rocketed in recent years as demand exceeded supply. 
 
 Researchers believe the genetic code will rapidly lead to more productive varieties that will push down costs. 
 
 'Mother grain' 
 
 Experts say that quinoa was first domesticated more than 7,000 years ago around Lake Titicaca in the Andean highlands and centuries later became known as the "mother grain" of the Inca empire. 
 
 After the arrival of the Spanish, the crop was marginalised and never fully domesticated or bred to its full potential. 
 
 The crop grows at high altitudes and in cool temperatures, factors which have limited its production outside of Peru, Bolivia and Ecuador, although many countries grow small amounts. 
 
 However the nutritional composition and the fact that quinoa is gluten-free, high in protein and moderate in carbohydrate has seen international demand for the foodstuff soar. 
 
 Prices tripled between 2006 and 2013 principally because quinoa's adoption as a "super-food" in Europe and the US. 
 
 Although fears were expressed that such rapid rises would hurt poorer people in South America who depend on quinoa, research showed that the increase in price actually benefitted people in the region. 
 
 Image copyright Getty Images Image caption Quinoa has not benefitted from breeding programmes and is still a relatively wild crop 
 
 Now an international team of scientists say that they have taken a major step forward in understanding the genetic makeup of the crop. 
 
 Using a combination of techniques, the researchers have produced the highest quality quinoa gene sequence to date. 
 
 "By sequencing the genome we have provided the foundation to enable breeders to work much faster and more powerfully," project leader Prof Mark Tester, from King Abdullah University of Science and Technology (KAUST), told BBC News. 
 
 "Especially the seeds, they will be able to develop a lot more varieties for different conditions, they will help us make a designer plant." 
 
 Image copyright Gabi Fiene Image caption The research has been carried out in Saudi Arabia where scientists wanted to understand the crop's potential to grow in salty conditions 
 
 The researchers say they have already make a key discovery because of the genome. 
 
 Quinoa seeds contain saponins, bitter and toxic compounds that protects the plant from predators. Removing the saponins for human consumption drives up the costs of processing. 
 
 "We've pinpointed one of the genes that we believe controls the production of saponins in quinoa which would facilitate the breeding of plants without saponins to make the seeds taste sweeter," said Prof Tester. 
 
 "For the saponins, that benefit can now be delivered to farmers through conventional breeding. We are putting the breeding into turbo charge, we are putting the breeding on steroids." 
 
 The researchers at KAUST were drawn to quinoa because of its ability to tolerate salt. The Saudi institute was interested in the crop because they believe it has great potential to grow in poorer soils, such as those in the Middle East, including those with a high salt level. 
 
 Image copyright Linda Polik Image caption The researchers have already discovered the genes that make quinoa seeds bitter 
 
 The scientists believe that the genetic understanding now gained will allow them to breed shorter, stockier plants that don't fall over as easily, and these benefits could be gained without the use of genetic modification. 
 
 They believe that these new breeds will see quinoa grown in more parts of the world - and that greater supply will push down the price. 
 
 "We need the price of quinoa to go down by a factor of five," said Prof Tester. 
 
 "If we get to a similar price to wheat it can be used in processing and in bread making and in many other foods and products. It has the chance to truly add to current world food production." 
 
 Other scientists in this field have welcome the news that the quinoa genome has been sequenced. 
 
 "The quinoa DNA sequence information is extremely valuable for identifying key genes controlling important agronomic traits and for identifying genetic variability among the cultivars," said Dr Sven-Erik Jacobsen from the University of Copenhagen. 
 
 "Now breeders can go into quinoa genomic library for the information that will help speed up the breeding process." 
 
 Researchers believe that genetic sequence of the grain will boost the production and popularity of the grain and it may no longer be the preserve of middle class foodies in richer countries. 
 
 "They can keep enjoying it," said Prof Tester. 
 
 "But they just might get a little bit annoyed that what they're eating is not so unusual and everyone else is eating it too!" 
 
 The study has been published in the journal Nature. 
 
 Follow Matt on Twitter and on Facebook ||||| Some strains can tolerate 38-degree days, salty soils and high altitudes, say researchers 
 
 The near-complete genome of quinoa was unveiled on Wednesday by scientists who say the grain cultivated centuries ago by Incas in the Andes could help feed a hungry world. 
 
 “Quinoa is incredibly resilient, and can grow in poor or salty soils,” said Mark Tester, a professor at King Abdullah University of Science and Technology in Saudi Arabia and leader of the consortium of scholars that decoded the plant’s genome. 
 
 “It could provide a healthy, nutritious food source for the world using land and water that currently cannot be used.” 
 
 Other major crop plants have been bred for centuries or, more recently, genetically modified to combine optimal traits to boost yield and bolster resistance to pests and climate change. Now, scientists can delve into the quinoa genome as well. 
 
 “Quinoa has great potential to enhance global food security,” Tester said. 
 
 The grain thrives at any altitude up to 4,000 metres (13,000 feet) above sea level, in conditions that would leave most food plants struggling. Some strains grow well at temperatures up to 38 degrees. 
 
 Best known outside its native region as a health food, quinoa is gluten-free and contains essential amino acids, fibre, vitamins and minerals. 
 
 Quinoa isn't a threat to food security. It's improving Peruvian farmers' lives Read more 
 
 It also scores lower than other crops on the glycaemic index, a measure of how quickly foods raise blood sugar levels – a major concern for those with diabetes. 
 
 Yet global consumption remains incidental compared with wheat, rice, barley or corn – less than 100,000 tonnes a year compared with hundreds of millions of tonnes for each of the other major grains and cereals. 
 
 
 
 One problem with quinoa is that the plant naturally produces bitter-tasting seeds, Tester explained. The bitterness – a natural defence against birds and other pests – comes from chemical compounds called saponins. The process for removing these chemicals is labour-intensive and costly, and requires ample use of water. 
 
 Another constraint is that quinoa plants tends to have small seed heads and long stalks that can collapse in strong wind or heavy rain. 
 
 “Despite its agronomic potential, quinoa is still an underutilised crop, with relatively few active breeding programmes,” Tester and three dozen colleagues wrote in the journal Nature. 
 
 First grown by humans thousands of years ago in the high plateau around Lake Titicaca in the Andes, quinoa is still barely domesticated, the researchers said. 
 
 
 
 Tester’s team has already pinpointed genes, including one that controls the production of saponins, that could be altered – through breeding or gene editing – to enhance quality and yields. 
 
 
 
 “With this new knowledge of quinoa DNA, we can quickly and easily select plants that do not produce bitter substances in the breeding process,” said co-author Robert van Loo, a scientist at Wageningen University and Research Centre in the Netherlands. South American varieties could probably be made sweeter with a single gene change, he added. 
 
 Most quinoa is grown in three Andean countries: Peru, Ecuador and Bolivia. 
 
 The United States and Canada account for nearly 70% of exports, followed by France, the Netherlands and Germany. The price of quinoa has nearly tripled in recent years due to increased demand. 
 
 If printed, the sequence of letters corresponding to the quinoa genome – comprised of 1.3bn molecular building blocks – would take up 500,000 pages.
– It has been hailed as a super food, a nutrient-packed, gluten-free dish that even carb counters can get behind. But could quinoa feed a hungry planet? That's the hope behind a new effort by scientists who've unlocked the humble grain's genome. "Quinoa has great potential to enhance global food security," lead researcher Mark Tester tells the Guardian. Because the plant has a high tolerance for salt, the BBC notes it can be grown in lower-quality soil such as that in Saudi Arabia, where the team is based. The problem with mass-producing quinoa is that the ancient staple—grown mostly in a few countries high in the Andes mountains—is time-consuming to get from the field to the table. Plus, the fragile plant's small heads and long stalks make it vulnerable to high winds and rain. Writing in the journal Nature, researchers identified genes that could be tweaked, such as those that control the production of saponins, which give quinoa a bitter, toxic coating unless washed away—a tedious process. The discovery is "an important first step" to producing a heartier form of quinoa, they write. Tester tells the BBC that new varieties of seeds adapted to various conditions will help make quinoa "a designer plant." A favorite of foodies, the price of quinoa has skyrocketed in recent years as demand has increased. The US imported 70 million pounds in 2013, up from 7 million six years earlier, per Quartz. But production has remained mostly flat. Increased production would drive down the price, which Tester said needs to drop by five times to make quinoa a contender to boost the world's food supply. (A food trend to watch in 2017: quinoa pasta.)