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.

BackgroundSubstantial progress in high-throughput metagenomic sequencing methodologies has enabled the characterisation of bacteria from various origins (for example gut and skin). However, the recently-discovered bacterial microbiota present within animal internal tissues has remained unexplored due to technical difficulties associated with these challenging samples.ResultsWe have optimized a specific 16S rDNA-targeted metagenomics sequencing (16S metabarcoding) pipeline based on the Illumina MiSeq technology for the analysis of bacterial DNA in human and animal tissues. This was successfully achieved in various mouse tissues despite the high abundance of eukaryotic DNA and PCR inhibitors in these samples. We extensively tested this pipeline on mock communities, negative controls, positive controls and tissues and demonstrated the presence of novel tissue specific bacterial DNA profiles in a variety of organs (including brain, muscle, adipose tissue, liver and heart).ConclusionThe high throughput and excellent reproducibility of the method ensured exhaustive and precise coverage of the 16S rDNA bacterial variants present in mouse tissues. This optimized 16S metagenomic sequencing pipeline will allow the scientific community to catalogue the bacterial DNA profiles of different tissues and will provide a database to analyse host/bacterial interactions in relation to homeostasis and disease.

Leukemia inhibitory factor (LIF)/STAT3 signalling is a hallmark of naive pluripotency in rodent pluripotent stem cells (PSCs), whereas fibroblast growth factor (FGF)-2 and activin/nodal signalling is required to sustain self-renewal of human PSCs in a condition referred to as the primed state. It is unknown why LIF/STAT3 signalling alone fails to sustain pluripotency in human PSCs. Here we show that the forced expression of the hormone-dependent STAT3-ER (ER, ligand-binding domain of the human oestrogen receptor) in combination with 2i/LIF and tamoxifen allows human PSCs to escape from the primed state and enter a state characterized by the activation of STAT3 target genes and long-term self-renewal in FGF2- and feeder-free conditions. These cells acquire growth properties, a gene expression profile and an epigenetic landscape closer to those described in mouse naive PSCs. Together, these results show that temporarily increasing STAT3 activity is sufficient to reprogramme human PSCs to naive-like pluripotent cells.

De novo sequencing of complex genomes is one of the main challenges for researchers seeking high-quality reference sequences. Many de novo assemblies are based on short reads, producing fragmented genome sequences. Third-generation sequencing, with read lengths >10 kb, will improve the assembly of complex genomes, but these techniques require high-molecular-weight genomic DNA (gDNA), and gDNA extraction protocols used for obtaining smaller fragments for short-read sequencing are not suitable for this purpose. Methods of preparing gDNA for bacterial artificial chromosome (BAC) libraries could be adapted, but these approaches are time-consuming, and commercial kits for these methods are expensive. Here, we present a protocol for rapid, inexpensive extraction of high-molecular-weight gDNA from bacteria, plants, and animals. Our technique was validated using sunflower leaf samples, producing a mean read length of 12.6 kb and a maximum read length of 80 kb.