A genomic analysis of the Wuhan coronavirus has led a research team from Chinese Academy of Science to identify bats as the likely source of the ongoing outbreak. As reported in Nature this week, the investigators studied bronchoalveolar lavage fluid samples from seven patients with severe pneumonia, six of whom were seafood workers at the market in Wuhan where the outbreak began, and obtained full-length genome sequences from five of the individuals. They find that the sequences are almost identical to each other, share nearly 80 percent sequence identity with SARS coronaviruses. Further, the scientists find that the Wuhan coronavirus sequence is 96 percent identical at the whole-genome level to a bat coronavirus. They also discover that the Wuhan coronavirus infects cells through the same route as SARS coronaviruses, provide details on how the virus is transmitted between people, and suggest that drugs used to combat SARS may be effective against the Wuhan virus.
New single-cell genomic technologies hold great potential for developing next-generation immunotherapies and will likely become an essential tool for drug development in the near future, a trio of Weizmann Institute of Science researchers write in this week's Nature Medicine. In their Perspective piece, the group provides an overview of emerging single-cell technologies and the impact they can have on target identification and immunotherapy development, particularly in cancer. "Single-cell genomic technologies have transformed the ability to examine heterogeneous tissues and complex processes," they write. "Utilization of these technologies in drug-development pipelines for immunotherapies will dramatically enhance the ability to discover new target molecules, characterize the cells and pathways targeted by these agents, and facilitate rational design of the most effective agents."
A new bioinformatic method that uses nucleotide count to identify cancer driver genes is reported in Nature Genetics this week. Developed by a Harvard Medical School-led team, the approach uses mutations in unusual nucleotide contexts in combination with established sources for driver gene discovery. By applying it to whole-exome sequencing data from 11,873 tumor-normal pairs, the team was able to identify 460 driver genes that clustered into 21 cancer-related pathways. "Our study," the team says, "provides a resource of driver genes across 28 tumor types with additional driver genes identified according to mutations in unusual nucleotide contexts."