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 ...

Summary Salt stress decreases plant growth prior to significant ion accumulation in the shoot. However, the processes underlying this rapid reduction in growth are still unknown. To understand the changes in salt stress responses through time and at multiple physiological levels, examining different plant processes within a single set‐up is required. Recent advances in phenotyping has allowed the image‐based estimation of plant growth, morphology, colour and photosynthetic activity. In this study, we examined the salt stress‐induced responses of 191 Arabidopsis accessions from 1 h to 7 days after treatment using high‐throughput phenotyping. Multivariate analyses and machine learning algorithms identified that quantum yield measured in the light‐adapted state (Fv′/Fm′) greatly affected growth maintenance in the early phase of salt stress, whereas the maximum quantum yield (QYmax) was crucial at a later stage. In addition, our genome‐wide association study (GWAS) identified 770 loci that were specific to salt stress, in which two loci associated with QYmax and Fv′/Fm′ were selected for validation using T‐DNA insertion lines. We characterized an unknown protein kinase found in the QYmax locus that reduced photosynthetic efficiency and growth maintenance under salt stress. Understanding the molecular context of the candidate genes identified will provide valuable insights into the early plant responses to salt stress. Furthermore, our work incorporates high‐throughput phenotyping, multivariate analyses and GWAS, uncovering details of temporal stress responses and identifying associations across different traits and time points, which are likely to constitute the genetic components of salinity tolerance.

No abstract

Salt stress decreases plant growth prior to significant ion accumulation in the shoot. However, the processes underlying this rapid reduction in growth are still unknown. To understand the changes in salt stress responses through time and at multiple physiological levels, examining different plant processes within a single setup is required. Recent advances in phenotyping has allowed the image-based estimation of plant growth, morphology, colour and photosynthetic activity. In this study, we examined the salt stress-induced responses of 191 Arabidopsis accessions from one hour to seven days after treatment using high-throughput phenotyping. Multivariate analyses and machine learning algorithms identified that quantum yield measured in the light-adapted state (Fv′/Fm′) greatly affected growth maintenance in the early phase of salt stress, while maximum quantum yield (QY max) was crucial at a later stage. In addition, our genome-wide association study (GWAS) identified 770 loci that were specific to salt stress, in which two loci associated with QY max and Fv′/Fm′ were selected for validation using T-DNA insertion lines. We characterised an unknown protein kinase found in the QY max locus, which reduced photosynthetic efficiency and growth maintenance under salt stress. Understanding the molecular context of the identified candidate genes will provide valuable insights into the early plant responses to salt stress. Furthermore, our work incorporates high-throughput phenotyping, multivariate analyses and GWAS, uncovering details of temporal stress responses, while identifying associations across different traits and time points, which likely constitute the genetic components of salinity tolerance.

No abstract