The domesticated sunflower, Helianthus annuus L., is a global oil crop that has promise for climate change adaptation, because it can maintain stable yields across a wide variety of environmental conditions, including drought 1 . Even greater resilience is achievable through the mining of resistance alleles from compatible wild sunflower relatives 2,3 , including numerous extremophile species 4 . Here we report a high-quality reference for the sunflower genome (3.6 gigabases), together with extensive transcriptomic data from vegetative and floral organs. The genome mostly consists of highly similar, related sequences 5 and required single-molecule realtime sequencing technologies for successful assembly. Genome analyses enabled the reconstruction of the evolutionary history of the Asterids, further establishing the existence of a whole-genome triplication at the base of the Asterids II clade 6 and a sunflowerspecific whole-genome duplication around 29 million years ago 7 . An integrative approach combining quantitative genetics, expression and diversity data permitted development of comprehensive gene networks for two major breeding traits, flowering time and oil metabolism, and revealed new candidate genes in these networks. We found that the genomic architecture of flowering time has been shaped by the most recent whole-genome duplication, which suggests that ancient paralogues can remain in the same regulatory networks for dozens of millions of years. This genome represents a cornerstone for future research programs aiming to exploit genetic diversity to improve biotic and abiotic stress resistance and oil production, while also considering agricultural constraints and human nutritional needs 8,9 .As the only major crop domesticated in North America, with its sunlike inflorescence that inspired artists, the sunflower is both a social icon and a major research focus for scientists. In evolutionary biology, the Helianthus genus is a long-time model for hybrid speciation and adaptive introgression 10 . In plant science, the sunflower is a model for understanding solar tracking 11 and inflorescence development 12 .Despite this large interest, assembling its genome has been extremely difficult as it mainly consists of long and highly similar repeats. This complexity has challenged leading-edge assembly protocols for close to a decade 13 .To finally overcome this challenge, we generated a 102× sequencing coverage of the genome of the inbred line XRQ using 407 singlemolecule real-time (SMRT) cells on the PacBio RS II platform. Production of 32 million very long reads allowed us to generate a genome assembly that captures 3 gigabases (Gb) (80% of the estimated genome size) in 13,957 sequence contigs. Four high-density genetic maps were combined with a sequence-based physical map to build the sequences of the 17 pseudo-chromosomes that anchor 97% of the gene content (Fig.
Available upon request (http://moulon/~bioinfo/BioMercator/). Free of charge for academic use.
Quantitative trait loci (QTL) detection experiments have often been restricted to large biallelic populations. Use of connected multiparental crosses has been proposed to increase the genetic variability addressed and to test for epistatic interactions between QTL and the genetic background. We present here the results of a QTL detection performed on six connected F(2) populations of 150 F(2:3) families each, derived from four maize inbreds and evaluated for three traits of agronomic interest. The QTL detection was carried out by composite interval mapping on each population separately, then on the global design either by taking into account the connections between populations or not. Epistatic interactions between loci and with the genetic background were tested. Taking into account the connections between populations increased the number of QTL detected and the accuracy of QTL position estimates. We detected many epistatic interactions, particularly for grain yield QTL (R(2) increase of 9.6%). Use of connections for the QTL detection also allowed a global ranking of alleles at each QTL. Allelic relationships and epistasis both contribute to the lack of consistency for QTL positions observed among populations, in addition to the limited power of the tests. The potential benefit of assembling favorable alleles by marker-assisted selection are discussed.
Among the several linkage disequilibrium measures known to capture different features of the non-independence between alleles at different loci, the most commonly used for diallelic loci is the r 2 measure. In the present study, we tackled the problem of the bias of r 2 estimate, which results from the sample structure and/or the relatedness between genotyped individuals. We derived two novel linkage disequilibrium measures for diallelic loci that are both extensions of the usual r 2 measure. The first one, r S 2 , uses the population structure matrix, which consists of information about the origins of each individual and the admixture proportions of each individual genome. The second one, r V 2 , includes the kinship matrix into the calculation. These two corrections can be applied together in order to correct for both biases and are defined either on phased or unphased genotypes. We proved that these novel measures are linked to the power of association tests under the mixed linear model including structure and kinship corrections. We validated them on simulated data and applied them to real data sets collected on Vitis vinifera plants. Our results clearly showed the usefulness of the two corrected r 2 measures, which actually captured 'true' linkage disequilibrium unlike the usual r 2 measure.
The last two authors contributed equally to this work. SummaryBacterial wilt, one of the most devastating bacterial diseases of plants worldwide, is caused by Ralstonia solanacearum and affects many important crop species. We show that several strains isolated from solanaceous crops in Europe are pathogenic in different accessions of Arabidopsis thaliana. One of these strains, 14.25, causes wilting symptoms in A. thaliana accession Landsberg erecta (Ler) and no apparent symptoms in accession Columbia (Col-0). Disease development and bacterial multiplication in the susceptible Ler accession depend on functional hypersensitive response and pathogenicity (hrp) genes, key elements for bacterial pathogenicity. Genetic analysis using Ler  Col-0 recombinant inbred lines showed that resistance is governed by at least three loci: QRS1 (Quantitative Resistance to R. solanacearum) and QRS2 on chromosome 2, and QRS3 on chromosome 5. These loci explain about 90% of the resistance carried by the Col-0 accession. The ERECTA gene, which encodes a leucine-rich repeat receptor-like kinase (LRR-RLK) and affects development of aerial organs, is dimorphic in our population and lies close to QRS1. Susceptible Ler plants transformed with a wild-type ERECTA gene, and the LER line showed increased disease resistance to R. solanacearum as indicated by reduced wilt symptoms and impaired bacterial growth, suggesting unexpected cross-talk between resistance and developmental pathways.
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