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Faced with the current large-scale public health emergency, collecting, sorting, and analyzing biomedical information related to the “coronavirus” should be done as quickly as possible to gain a global perspective, which is a basic requirement for strengthening epidemic control capacity. However, for human researchers studying the viruses and the hosts, the vast amount of information available cannot be processed effectively and in a timely manner, particularly when the scientific understanding may be limited, which can further lower the information processing efficiency. We present TWIRLS, a method that can automatically acquire, organize, and classify information. Additionally, independent functional data sources can be added to build an inference system using a machine-based approach, which can provide relevant knowledge to help human researchers quickly establish subject cognition and to make more effective decisions. TWIRLS can automatically analyze more than three million words in more than 14,000 literature articles in only 4 hours. Combining with generalized gene interaction databases creates a data interface that can help researchers to further analyze the information. Using the TWIRLS system, we found that an important regulatory factor angiotensin-converting enzyme 2 (ACE2) may be involved in the host pathological changes on binding to the coronavirus after infection. After triggering functional changes in ACE2/AT2R, an imbalance in the steady-state cytokine regulatory axis involving the Renin-Angiotensin System and IP-10 leads to a cytokine storm.

The evolution of bread wheat (Triticum aestivum) is distinctive in that domestication, natural hybridization, and allopolyploid speciation have all had significant effects on the diversification of its genome. Wheat was spread around the world by humans and has been cultivated in China for ~4,600 years. Here, we report a comprehensive assessment of the evolution of wheat based on the genome-wide resequencing of 120 representative landraces and elite wheat accessions from China and other representative regions. We found substantially higher genetic diversity in the A and B subgenomes than in the D subgenome. Notably, the A and B subgenomes of the modern Chinese elite cultivars were mainly derived from European landraces, while Chinese landraces had a greater contribution to their D subgenomes. The duplicated copies of homoeologous genes from the A, B, and D subgenomes were commonly found to be under different levels of selection. Our genome-wide assessment of the genetic changes associated with wheat breeding in China provides new strategies and practical targets for future breeding.