Genome-wide association study in quinoa reveals selection pattern typical for crops with a short breeding history.

Quinoa germplasm preserves useful and substantial genetic variation, yet it remains untapped due to a lack of implementation of modern breeding tools. We have integrated field and sequence data to characterize a large diversity panel of quinoa. Whole-genome sequencing of 310 accessions revealed 2.9 million polymorphic high confidence single nucleotide polymorphism (SNP) loci. Highland and Lowland quinoa were clustered into two main groups, with FST divergence of 0.36 and linkage disequilibrium (LD) decay of 6.5 and 49.8 kb, respectively. A genome-wide association study using multi-year phenotyping trials uncovered 600 SNPs stably associated with 17 traits. Two candidate genes are associated with thousand seed weight, and a resistance gene analog is associated with downy mildew resistance. We also identified pleiotropically acting loci for four agronomic traits important for adaptation. This work demonstrates the use of re-sequencing data of an orphan crop, which is partially domesticated to rapidly identify marker-trait association and provides the underpinning elements for genomics-enabled quinoa breeding.

As human populations grow and climate change tightens its grip, developing nutritious crops which can thrive on poor soil and under difficult conditions will become a priority. Quinoa, a harvest currently overlooked by agricultural research, could be an interesting candidate in this effort. With its high nutritional value and its ability to tolerate drought, frost and high concentrations of salt in the soil, this hardy crop has been cultivated in the Andes for the last 5,000 to 7,000 years. Today its commercial production is mainly limited to Peru, Bolivia, and Ecuador. Pinpointing the genetic regions that control traits such as yields or flowering time would help agronomists to create new varieties better suited to life under northern latitudes and mechanical farming. To identify these genes, Patiranage et al. grew 310 varieties of quinoa from all over the world under the same conditions; the genomes of these plants were also examined in great detail. Analyses were then performed to link specific genetic variations with traits relevant to agriculture, helping to pinpoint changes in the genetic code linked to differences in how the plants grew, resisted disease, or produced seeds of varying quality. Candidate genes likely to control these traits were then put forward. The study by Patiranage et al. provides a genetic map where genes of agronomical importance have been precisely located and their effects measured. This resource will help to select genetic profiles which could be used to create new quinoa breeds better adapted to a changing world.

Genomic background selection to reduce the mutation load after random mutagenesis.

Random mutagenesis is a standard procedure to increase allelic variation in a crop species, especially in countries where the use of genetically modified crops is limited due to legal constraints. The chemical mutagen EMS is used in many species to induce random mutations throughout the genome with high mutation density. The major drawback for functional analysis is a high background mutation load in a single plant that must be eliminated by subsequent backcrossing, a time and resource-intensive activity. Here, we demonstrate that genomic background selection combined with marker-assisted selection is an efficient way to select individuals with reduced background mutations within a short period. We identified BC1 plants with a significantly higher share of the recurrent parent genome, thus saving one backcross generation. Furthermore, spring rapeseed as the recurrent parent in a backcrossing program could accelerate breeding by reducing the generation cycle. Our study depicts the potential for reducing the background mutation load while accelerating the generation cycle in EMS-induced winter oilseed rape populations by integrating genomic background selection.

Haplotype variations of major flowering time genes in quinoa unveil their role in the adaptation to different environmental conditions.

Response to photoperiod is of major importance in crop production. It defines the adaptation of plants to local environments. Quinoa is a short-day plant which had been domesticated in the Andeans regions. We wanted to understand the adaptation to long-day conditions by studying orthologues of two major flowering time regulators of Arabidopsis, FLOWERING LOCUS T (FT) and CONSTANS (CO) in quinoa accessions with contrasting photoperiod response. By searching the quinoa reference genome sequence, we identified 24 FT and six CO homologs. CqFT genes displayed remarkably different expression patterns between long- and short-day conditions, whereas the influence of the photoperiod on CqCOL expressions was moderate. Cultivation of 276 quinoa accessions under short- and long-day conditions revealed great differences in photoperiod sensitivity. After sequencing their genomes, we identified large sequence variations in 12 flowering time genes. We found non-random distribution of haplotypes across accessions from different geographical origins, highlighting the role of CqFT and CqCOL genes in the adaptation to different day-length conditions. We identified five haplotypes causing early flowering under long days. This study provides assets for quinoa breeding because superior haplotypes can be assembled in a predictive breeding approach to produce well-adapted early flowering lines under long-day photoperiods.