The genome of the mesopolyploid crop species Brassica rapaThe Brassica rapa Genome Sequencing Project Consortium 1 Abstract:The Brassicaceae family which includes Arabidopsis thaliana, is a natural priority for reaching beyond botanical models to more deeply sample angiosperm genomic and functional diversity. Here we report the draft genome sequence and its annoation of Brassica rapa, one of the two ancestral species of oilseed rape. We modeled 41,174 protein-coding genes in the B. rapa genome. B. rapa has experienced only the second genome triplication reported to date, with its close relationship to A. thaliana providing a useful outgroup for investigating many consequences of triplication for its structural and functional evolution. The extent of gene loss (fractionation) among triplicated genome segments varies, with one copy containing a greater proportion of genes expected to have been present in its ancestor (70%) than the remaining two (46% and 36%). Both a generally rapid evolutionary rate, and specific copy number amplifications of particular gene families, may contribute to the remarkable propensity of Brassica species for the development of new morphological variants. The B. rapa genome provides a new resource for comparative and evolutionary analysis of the Brassicaceae genomes and also a platform for genetic improvement of Brassica oil and vegetable crops.2

Background: The coronavirus disease 2019 (COVID-19) outbreak originating in Wuhan, Hubei province, China, coincided with chunyun, the period of mass migration for the annual Spring Festival. To contain its spread, China adopted unprecedented nationwide interventions on January 23 2020. These policies included large-scale quarantine, strict controls on travel and extensive monitoring of suspected cases. However, it is unknown whether these policies have had an impact on the epidemic. We sought to show how these control measures impacted the containment of the epidemic. Methods: We integrated population migration data before and after January 23 and most updated COVID-19 epidemiological data into the Susceptible-Exposed-Infectious-Removed (SEIR) model to derive the epidemic curve. We also used an artificial intelligence (AI) approach, trained on the 2003 SARS data, to predict the epidemic. Results: We found that the epidemic of China should peak by late February, showing gradual decline by end of April. A five-day delay in implementation would have increased epidemic size in mainland China three-fold. Lifting the Hubei quarantine would lead to a second epidemic peak in Hubei province in mid-March and extend the epidemic to late April, a result corroborated by the machine learning prediction. Conclusions: Our dynamic SEIR model was effective in predicting the COVID-19 epidemic peaks and sizes. The implementation of control measures on January 23 2020 was indispensable in reducing the eventual COVID-19 epidemic size.

The gut microbiota has been linked to cardiovascular diseases. However, the composition and functional capacity of the gut microbiome in relation to cardiovascular diseases have not been systematically examined. Here, we perform a metagenome-wide association study on stools from 218 individuals with atherosclerotic cardiovascular disease (ACVD) and 187 healthy controls. The ACVD gut microbiome deviates from the healthy status by increased abundance of Enterobacteriaceae and Streptococcus spp. and, functionally, in the potential for metabolism or transport of several molecules important for cardiovascular health. Although drug treatment represents a confounding factor, ACVD status, and not current drug use, is the major distinguishing feature in this cohort. We identify common themes by comparison with gut microbiome data associated with other cardiometabolic diseases (obesity and type 2 diabetes), with liver cirrhosis, and rheumatoid arthritis. Our data represent a comprehensive resource for further investigations on the role of the gut microbiome in promoting or preventing ACVD as well as other related diseases.