Background Ginkgo biloba L. (Ginkgoaceae) is one of the most distinctive plants. It possesses a suite of fascinating characteristics including a large genome, outstanding resistance/tolerance to abiotic and biotic stresses, and dioecious reproduction, making it an ideal model species for biological studies. However, the lack of a high-quality genome sequence has been an impediment to our understanding of its biology and evolution.FindingsThe 10.61 Gb genome sequence containing 41,840 annotated genes was assembled in the present study. Repetitive sequences account for 76.58% of the assembled sequence, and long terminal repeat retrotransposons (LTR-RTs) are particularly prevalent. The diversity and abundance of LTR-RTs is due to their gradual accumulation and a remarkable amplification between 16 and 24 million years ago, and they contribute to the long introns and large genome. Whole genome duplication (WGD) may have occurred twice, with an ancient WGD consistent with that shown to occur in other seed plants, and a more recent event specific to ginkgo. Abundant gene clusters from tandem duplication were also evident, and enrichment of expanded gene families indicates a remarkable array of chemical and antibacterial defense pathways.ConclusionsThe ginkgo genome consists mainly of LTR-RTs resulting from ancient gradual accumulation and two WGD events. The multiple defense mechanisms underlying the characteristic resilience of ginkgo are fostered by a remarkable enrichment in ancient duplicated and ginkgo-specific gene clusters. The present study sheds light on sequencing large genomes, and opens an avenue for further genetic and evolutionary research.Electronic supplementary materialThe online version of this article (doi:10.1186/s13742-016-0154-1) contains supplementary material, which is available to authorized users.

A full-scale adaptive ocean sampling network was deployed throughout the month-long 2006 Adaptive Sampling and Prediction (ASAP) field experiment in Monterey Bay, California. One of the central goals of the field experiment was to test and demonstrate newly developed techniques for coordinated motion control of autonomous vehicles carrying environmental sensors to efficiently sample the ocean. We describe the field results for the heterogeneous fleet of autonomous underwater gliders that collected data continuously throughout the month-long experiment. Six of these gliders were coordinated autonomously for 24 days straight using feedback laws that scale with the number of vehicles. These feedback laws were systematically computed using recently developed methodology to produce desired collective motion patterns, tuned to the spatial and temporal scales in the sampled fields for the purpose of reducing statistical uncertainty in field estimates. The implementation was designed to allow for adaptation of coordinated sampling patterns using human-in-theloop decision making, guided by optimization and prediction tools. The results demonstrate an innovative tool for ocean sampling and provide a proof of concept for an important field robotics endeavor that integrates coordinated motion control with adaptive sampling. C

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Autonomous mobile sensor networks are employed to measure large-scale environmental fields.Yet an optimal strategy for mission design addressing both the cooperative motion control and the cooperative sensing is still an open problem. We develop strategies for multiple sensor platforms to explore a noisy scalar field in the plane. Our method consists of three parts. First, we design provably convergent cooperative Kalman filters that apply to general cooperative exploration missions. Second, a novel method is established to determine the shape of the platform formation to minimize error in the estimates and a cooperative formation control law is designed to asymptotically achieve the optimal formation shape. Third, we use the cooperative filter estimates in a provably convergent motion control law that drives the center of the platform formation to move along level curves of the field. This control law can be replaced by control laws enabling other cooperative exploration motion, such as gradient climbing, without changing the cooperative filters and the cooperative formation control laws.Performance is demonstrated on simulated underwater platforms in simulated ocean fields.